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",isbn:"978-1-83962-547-3",printIsbn:"978-1-83962-546-6",pdfIsbn:"978-1-83962-548-0",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"e5ba02fedd7c87f0ab66414f3b07de0c",bookSignature:"Dr. John P. Tiefenbacher",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10765.jpg",keywords:"Managing Urbanization, Managing Development, Managing Resource Use, Drought Management, Flood Management, Water Quality Monitoring, Air Quality Monitoring, Ecological Monitoring, Modeling Extreme Natural Events, Ecological Restoration, Restoring Environmental Flows, Environmental Management Perspectives",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 12th 2021",dateEndSecondStepPublish:"February 9th 2021",dateEndThirdStepPublish:"April 10th 2021",dateEndFourthStepPublish:"June 29th 2021",dateEndFifthStepPublish:"August 28th 2021",remainingDaysToSecondStep:"a month",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"A geospatial scholar working at the interface of natural and human systems, collaborating internationally on innovative studies about hazards and environmental challenges. Dr. Tiefenbacher has published more than 200 papers on a diverse array of topics that examine perception and behaviors with regards to the application of pesticides, releases of toxic chemicals, environments of the U.S.-Mexico borderlands, wildlife hazards, and the geography of wine.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"73876",title:"Dr.",name:"John P.",middleName:null,surname:"Tiefenbacher",slug:"john-p.-tiefenbacher",fullName:"John P. Tiefenbacher",profilePictureURL:"https://mts.intechopen.com/storage/users/73876/images/system/73876.jfif",biography:"Dr. John P. Tiefenbacher (Ph.D., Rutgers, 1992) is a professor of Geography at Texas State University. His research has focused on various aspects of hazards and environmental management. Dr. Tiefenbacher has published on a diverse array of topics that examine perception and behaviors with regards to the application of pesticides, releases of toxic chemicals, environments of the U.S.-Mexico borderlands, wildlife hazards, and the geography of wine. More recently his work pertains to spatial adaptation to climate change, spatial responses in wine growing regions to climate change, the geographies of viticulture and wine, artificial intelligence and machine learning to predict patterns of natural processes and hazards, historical ethnic enclaves in American cities and regions, and environmental adaptations of 19th century European immigrants to North America's landscapes.",institutionString:"Texas State University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"6",institution:{name:"Texas State University",institutionURL:null,country:{name:"United States of America"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"12",title:"Environmental Sciences",slug:"environmental-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"194667",firstName:"Marijana",lastName:"Francetic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/194667/images/4752_n.jpg",email:"marijana@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Evidence-based treatments are available for many mental health disorders. However, not all individuals benefit from every treatment. Psychiatric research has begun to focus on the neurobiological factors that predict who will benefit from an intervention by experiencing symptom improvement. This application of neuroimaging is still very much in development, but it has the potential to facilitate a major advance in psychiatry, namely that of personalized care. Personalization of treatment for mental health disorders has been identified as a public health priority [1]. The idea is to select the best therapy for a patient at the beginning of treatment based on a set of patient characteristics that have been shown to be associated with positive outcomes with a given intervention. Those who are well matched for a particular treatment are more likely to stay engaged in the treatment, which will lead to better outcomes [2]. Given the scarcity and expense of available mental health resources, treatment should be conserved so that sufficient resources are available for those who would benefit from a specific type of treatment [3]. Optimally, these efforts will serve to guide treatment development and planning, improve overall response rates, decrease treatment costs, and eventually improve the prognosis of those who suffer from mental illness. In this chapter we review recent advances in application of neuroimaging tools to predict treatment response in patients with internalizing psychological disorders. Following the core themes of Brain Mapping, this chapter focuses on describing the brain structures and functions that have been associated with clinically significant response to psychological and pharmacological treatments in internalizing disorders in addition to the underling research methodology used to investigate such relationships.
It is critically important to direct attention towards the study of internalizing problems. Internalizing disorders are associated with significant impairment and distress and they often lead to the development and reoccurrence of debilitating psychiatric illness [4,5]. Based on empirically derived classification models, internalizing disorders are characterized by maladjustment primarily expressed inwardly, as compared to externalizing patterns of behavior where maladjustment is expressed outwardly [6,7]. Although internalizing behavior is increasingly conceptualized as a dimensional construct, treatment research has typically focused on extreme conditions, tending to examine questions regarding internalizing behavior through the lens of discrete psychiatric disorders. Some internalizing disorders, such as Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD), involve negative affect characterized by anxious misery and distress. Other internalizing disorders, including Social Phobia, Specific Phobia, Agoraphobia, and Panic Disorder, involve negative affect associated with activation of the fear system. Obsessive Compulsive Disorder (OCD) has also been characterized as an internalizing disorder [8]. Grouping mental illnesses more broadly along an internalizing dimension is advantageous in a number of ways. Namely, this approach accounts for the high rates of comorbidity between internalizing disorders and it groups problems that share commonalities in pathophysiology and genetic variance [7]. For example, internalizing problems are centrally implicated in the threat response system and involve abnormalities in fronto-limbic brain circuitry. This chapter focuses on the most commonly exhibited internalized disorders, namely MDD and Anxiety Disorders [9].
The past two decades have shown significant advances in the development and refinement of treatments available to those who suffer from internalizing problems. Validated, evidence-based treatments (EBTs) are now available for treating the classes of internalizing problems discussed here, including specific mood and anxiety disorders. The commonalities in the EBTs for these classes of problems are considerable. Validated treatments include medication and/or psychotherapy [10-12].
In MDD, first-line treatments that are currently offered include antidepressant medications and psychotherapy. Regarding antidepressants, the first options are typically those that impact the monoamine neurotransmitters, such as the selective serotonin reuptake inhibitors (SSRIs). Second-line medication treatments impact other neurotransmitters such as dopamine or norepinephrine, and some impact serotonin by alternate mechanisms. Regarding psychotherapies, empirically validated interventions include cognitive behavioral therapy (CBT) and interpersonal therapy (IPT). For patients that do not respond to either or a combination of these treatments, additional options are considered including electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS).
Similarly for anxiety disorders, antidepressant medications and behavioral therapies, including CBT, are frequently the treatments of choice. While CBT in MDD primarily aims to change behavior by altering distorted cognitions, forms of CBT in the context of anxiety disorders employ the use of exposure techniques, where individuals face feared stimuli until their fear response naturally declines. Anxiolytics (e.g., benzodiazepines) are also used to mitigate acute symptoms of anxiety and are employed for short-term treatment of anxiety in more extreme cases [13].
Unfortunately, even when treatments are delivered under ideal circumstances, 30-60% patients with depressive and anxiety disorders who are treated are not likely to achieve remission with their first treatment [14-17]. Therefore, there is a great need for the identification of biological markers that predict which interventions would work and for whom, thus helping guide clinicians in selecting a treatment with the greatest potential to provide effective symptom management.
Several different types of neuroimaging techniques have been developed and increasingly employed in the context of psychiatric research. Research studies that have investigated neurobiological predictors of treatment response have relied on the use of structural and functional brain imaging technologies. In structural magnetic resonance imaging (MRI), a non-invasive imaging technique, both whole brain and individual structure volumes are examined. Researchers use this methodology to examine anatomical detail, localize individual brain regions and to identify brain pathology. Functional MRI (fMRI) methodology provides useful temporal information about brain function by measuring the blood-oxygen-level-dependent (BOLD) contrast, where changes in energy between oxygenated and deoxygenated blood within the brain across time are examined to assess neural functioning within specific task constraints. Additional functional imaging methods employed in the context of treatment prediction research include positron emission tomography (PET) and single-photon emission computed tomography (SPECT). These procedures are considered invasive procedures in that they use radioactive substances in order to generate contrasts that assess brain blood flow, blood perfusion, and glucose metabolism as an indirect measure of neural activity. This wide array of brain imaging techniques has been used to assess which brain structures and functions prior to treatment predict treatment response in individuals diagnosed with Major Depressive Disorder and Anxiety Disorders.
Major Depressive Disorder is a prevalent and debilitating disorder that is a leading cause of disability worldwide [18]. MDD often starts in adolescence and places youth at risk for morbidity and mortality across the lifespan. The negative outcomes associated with MDD affect all aspects of life: personal, social, and academic functioning, and may result in chronic suffering and early death. The prognosis for depression is particularly poor when the problems are evident early on in development [19-21]. While a broader array of mood disorders (e.g., Dsythymic Disorder) may be relevant to include here, this chapter focuses on MDD because most of the predictive literature has focused on adults diagnosed with this disorder. fMRI, PET, SPECT and volumetric imaging have been used to examine predictive biomarkers of treatment response in MDD. Since a majority of findings have implicated subregions of the anterior cingulate cortex (ACC), we begin by reviewing these regions and then extend to other parts of the brain that have been implicated through various modalities as predictive of treatment response.
Many imaging studies have now implicated the pregenual ACC as a key area differentiating responders from nonresponders for a variety of psychiatric treatments. For the most part, as suggested in a meta-analysis of 23 studies of adults with MDD using various modalities and treatments [22], elevated activity or metabolism in the pregenual ACC at baseline is generally predictive of a positive response to treatment. For example, Fu and colleagues [23] reported that at baseline, increased activity in the ACC was associated with a positive treatment response to CBT. Similarly, elevated resting activity of the pregenual ACC “confers better treatment outcomes by fostering adaptive self-referential processing and by helping to recalibrate cingulate regions implicated in cognitive control” [22].
Careful attention should be paid to the problem of inconsistencies across studies. For instance, as Pizagalli [22] noted, four of the studies in his meta-analysis showed that pregenual ACC predicted non-response to paroxetine [24], venlafaxine, CBT [25], and ECT [26] as measured by PET and non-response to repetitive transcranial magnetic stimulation (rTMS) as measured by SPECT [27]. Part of the inconsistency may be due to error in the assessment. Specifically, low resolution in fMRI acquisition may interfere with the ability to pinpoint exactly which areas predict treatment response versus non-response. For example, a PET study showed that pretreatment hypermetabolism at the interface between pregenual and subgenual ACC was notable in non-responders in comparison to responders [25]. Indeed, in contrast to pregenual ACC findings, it appears that the subgenual region of the ACC is associated with the opposite pattern, where some studies have suggested that increased resting metabolism or activation predicts treatment resistance [25,28,29]. In an fMRI study, hyperactivity of the subgenual ACC in response to emotional stimuli was associated with poor response to 16 sessions of CBT in 14 adults with MDD [28]. This group replicated their finding in a second, larger sample of 49 patients with MDD, finding that individuals with the lowest pretreatment sustained subgenual ACC reactivity in response to negative words displayed the most improvement after cognitive therapy [29]. Such work focusing on the subgenual ACC has contributed to current models in which this region has become one of the targets of deep-brain stimulation for patients with treatment-refractory MDD [30]. Figure 1 provides an illustration of various divisions within the ACC, including pregenual and subgenual regions.
This figure illustrates the anatomical locations of divisions within the anterior cingulate cortex (ACC). A reconstructed MRI of the medial surface of the right hemisphere of the brain depicts the ACC (sulcus and gyrus) in relation to the underlying corpus callosum (upper right). Cytoarchitecture and functional differences have distinguished cognitive (red) and affective (blue) divisions of the ACC (left; 31). Better treatment response to pharmacological and psychological therapies in MDD has been associated with activity within the affective division of the ACC, namely increased pre-treatment activity in the pregenual ACC (includes Brodmann Area BA32 and inferior portions of BA24] and decreased activity in the subgenual ACC (BA25 and caudal portions of BA32 and BA 24). The subgenual ACC has been identified as a target for deep-brain stimulation in patients with treatment resistant MDD [30]. Reprinted and adapted from Trends in Cognitive Sciences, volume 4[6], Bush, G., Luu, P., & Posner, M.I., Cognitive and emotional influences in anterior cingulate cortex, pages 215-222, Copyright (2000), with permission from Elsevier [32].
Not all imaging studies have pointed only to the pregenual and subgenual ACC as an important predictor of treatment response in MDD. Using a variety of methodological approaches, a growing number of studies have implicated a range of brain regions that are broadly associated with fronto-limbic circuitry. One fMRI study using an emotion-processing task before treatment with antidepressant medications (mirtazapine or venlafaxine) showed that at baseline, patients had higher activation in the dorsal/medial prefrontal cortex (PFC), posterior cingulate cortex and superior frontal gyrus. Furthermore, pre-treatment activations in caudate and insula were associated with successful treatment [33]. In an fMRI study that focused on anhedonia [34], patients with lower ventral/lateral PFC activation during cognitive reappraisal (suppression) of positive emotion at baseline had greater rates of improvement in anhedonia after 8 weeks of treatment with an antidepressant, specifically venlafaxine extended release or fluoxetine. Another study employing fMRI reported that with treatment using various antidepressants, greater right visual cortex and right subgenual ACC responses to sad stimuli, but not happy stimuli, were associated with a good clinical outcome in the early stages of treatment [35]. Similar to the findings reported by Light and colleagues [34], greater ventral/lateral PFC responses to either happy or sad faces were associated with a relatively poor outcome [35]. A recent rTMS study found that greater symptom improvement was significantly correlated with smaller deactivations at baseline in the ACC, the left medial orbitofrontal and the right middle frontal cortices, but larger activations in the putamen [36]. Using SPECT, responders to rTMS had greater perfusions in the left medial and bilateral superior frontal cortices (BA10), the left uncus/parahippocampal cortex (BA20/BA35] and the right thalamus [37]. In a PET study in adults with late-onset MDD, 34 patients remitted and 13 did not after treatment with antidepressants for 12 weeks. Left anterior fronto-cerebellar perfusion ratio had a global predictive power of 87% [38]. Analyzing this variable together with the baseline variables age of onset and duration of index episode, the predictive power of the model rose to 94% [38].
A few studies have reported on anatomical differences that have predicted MDD treatment response in broader front-limbic brain regions. Chen and colleagues [39] found that increased grey matter volumes in ACC, insula, and right tempro-parietal cortex was associated with faster rates of symptom improvement with fluoxetine. A recent study found that smaller left hippocampal volumes predicted better treatment response to six weeks of daily rTMS in adults with treatment-refractory depression; however, the significance for this prediction was only a trend [40]. If volumetric predictors could be established, these would be useful in comparison to other imaging techniques (e.g., PET, SPECT), as this type of imaging acquisition is relatively easy, safe and is consistent in analysis across sites. Like other modalities, however, the extant data are from cross-sectional studies, so it is unclear whether any differences relate to pre-existing processes or to scarring from disease exposure.
Since most medication treatments focus on serotonin, a reasonable approach is to examine how either serotonin binding or brain regions associated with serotonin production might be relevant to treatment response. A SPECT study that examined serotonin binding availability found that higher pretreatment diencephalic serotonin availability significantly predicted better treatment response to 4 weeks of paroxetine [41]. Miller and colleagues [42] used PET to assess serotonin transporter (5-HTT) binding in 19 currently depressed subjects with MDD who received naturalistic antidepressant treatment for one year. They found that non-remitters had lower 5-HTT binding than controls in midbrain, amygdala, and ACC (sub-region not specified). Remitters did not differ significantly from controls or non-remitters in 5-HTT binding. Assessment of baseline 5-HTT binding as a predictor of remission status was suggestive but not significant. In a PET study of adults with MDD who received community-based monoaminergic anti-depressant treatments by their physician, Milak and colleagues [43] reported that treatment remitters had lower activity in the region of the midbrain where monoaminergic nuclei are located prior to treatment, and that degree of improvement correlated with pretreatment midbrain activity.
Studies investigating neurobiological predictors of treatment response in MDD have primarily focused on adults with the illness. The most replicated findings implicate regions within the ACC as being particularly salient indicators of treatment outcome. Specifically, increased activity in areas within the ACC, namely the pregenual ACC, may be particularly predictive of improved outcome following both psychological and pharmacological intervention whereas hyperactivity in the subgenual ACC may be associated with poorer treatment response. In addition, pre-treatment serotonergic binding appears predict response to antidepressant therapy in adults with MDD. Other studies have linked structural and functional differences to pharmacological and psychological treatment response, but findings differ significantly as a function of the type of imaging modality employed (e.g., fMRI task based paradigm, PET). See Figure 2.
Summary of pre-treatment neuroimaging findings that have been associated with positive responses to Cognitive-Behavioral Therapy (CBT), repetitive transcranial magnetic stimulation (rTMS), and various anti-depressant medication treatments in MDD.
Several distinct types of anxiety disorders have been recognized in the field of psychiatry and delineated within the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR). Three will be discussed here, namely Obsessive Compulsive Disorder (OCD), General Anxiety Disorder (GAD), and Social Anxiety Disorder (SAD). Some initial headway is being made using neuroimaging to attempt to identify who will respond to which type of intervention for these disorders.
OCD is a significantly impairing mental illness associated with debilitating cycles of persistent anxiety-provoking thoughts, impulses or images that are accompanied by repetitive behaviors aimed at counteracting anxiety [44]. For example, an individual may have constant and intrusive thoughts that surfaces that he or she comes in contact with are dirty or have germs. These thoughts are experienced as extremely distressing to the individual, who as a result, engages in compulsive behavior (e.g., repetitive hand washing) to prevent or alleviate fear associated with the content of obsessive thoughts (e.g., contamination).
Top: Loci of significant correlations between pretreatment gray matter volume and subsequent response to Fluoxetine (top left) and CBT (top right). Bottom left: negative statistically significant correlation between pretreatment gray matter volume within the right middle lateral orbitofrontal cortex and improvements in OCD severity (measured by the Yale-Brown Obsessive Compulsive Scale: Y–BOCS) following treatment with fluoxetine. Bottom right: positive statistically significant correlation between pretreatment gray matter volume within the right medial prefrontal cortex, (subgenual anterior cingulate cortex) and Y–BOCS improvement following treatment with CBT. Reprinted and adapted from European Neuropsychopharmacology, published online, Hoexter et al., Differential prefrontal gray matter correlates of treatment response to fluoxetine or cognitive-behavioral therapy in obsessive–compulsive disorder, pages 1-12, Copyright (2012), with permission from Elsevier [45].
One study to date has investigated structural predictors of treatment response in OCD. Hoexter and colleagues [45] recruited thirty-eight treatment naive individuals with a primary diagnosis of OCD and randomized them to receive either 12 weeks of treatment with fluoxetine or 12 weekly sessions of group CBT. Specifically interested in structural prognostic indicators of treatment response, Hoexter et al. [45] found that smaller grey matter volumes prior to treatment initiation in the right middle lateral orbital frontal cortex (OFC) predicted a decrease in OCD symptoms following pharmacological intervention whereas greater grey matter volumes in the medial prefrontal cortex predicted better response following CBT (Figure 3). This study suggests that improvement via pharmacologic and psychological approaches in OCD may occur via different mechanisms.
Numerous functional imaging studies, primarily using PET imaging, have also investigated biological prognostic indicators in OCD. Brody and colleagues [46] showed that decreased metabolic activity in the orbitofrontal cortex (OFC) was associated with better outcomes with fluoxetine treatment whereas as increased metabolism in the same region predicted improvement following cognitive behavioral therapy (CBT). However, it is important to note that, unlike the Hoexter et al. [45] study above, treatment designation in this study was not randomized. Similar to Brody et al. [46], Saxena et al. [47] found an inverse relationship between OFC glucose metabolism using PET and response to 8-12 weeks of SSRI (paroxetine) treatment in 20 OCD outpatients. These negative correlations between regional OFC glucose metabolism and treatment response appear to be present in adults with childhood onset OCD [48]. In a symptoms provocation study, where individuals with contamination-related OCD were exposed to neutral and contamination specific stimuli, lower regional cerebral flood flow (rCBF) measured by PET in the OFC and higher pre-treatment rCBF in the bilateral posterior cinglate cortex (PCC) predicted better symptom reduction after a 12-week open trial of fluvoxamine [49]. The relationship between rCBF and treatment outcome was present in response to both OCD-related and neutral stimuli, suggesting that activity in the OFC and PCC exist independent of OCD-salient cues. Using a functional MRI paradigm that evoked OCD symptoms by displaying salient illness-related words, BOLD response in the right cerebellum and left superior temporal gyrus (STG) positively correlated with improvements in OCD symptoms following 12 weeks of SSRI (fluvoxamine) pharmacotherapy [50].
Given that SSRI medications have been shown to be effective in both OCD and MDD, Saxena et al. [47] examined whether pretreatment brain activity would differentially predict response to pharmacotherapy in these two different patient groups. 27 individuals with OCD and 27 with MDD underwent PET to measure cerebral glucose metabolism prior to paroxetine treatment. These researchers concluded that OCD symptom improvement was related to increased pretreatment metabolism in the right caudate nucleus whereas decreased depression symptoms were predicted by low amygdala and thalamus but increased medial prefrontal and ACC metabolism prior to treatment. This study, in particular, suggests that treatment with SRIs may improve OCD and MDD pathology by its impact at different brain sites.
Using SPECT imaging, investigators have examined neurochemical transporters as predictors of response to medication treatments in OCD. Specifically, Zitteral et al. [51] found that serotonin transporter (SERT) availability in thalamic and hypothalamic brain regions predicted better treatment outcomes following 14 weeks of sertraline (an SSRI) administration in a homogenous sample of OCD patients with behavioral checking compulsions. It is important to note that SERT availability has been associated with OCD symptom severity in previous studies [51,52], suggesting that individuals with higher transporter availability may be more likely to respond favorably to SSRIs as their serotonin system is less impaired prior to beginning intervention. Another SPECT study prior to 12 weeks of treatment with Inositol, a chemical precursor of second messengers in critical brain signaling pathways, found that higher blood perfusion in the left medial prefrontal regions differentiated OCD responders from nonresponders [53] and regional cerebral blood flow (rCBF) in cerebellar regions in addition to whole brain tracer uptake has also been shown to be elevated in OCD responders compared to nonresponders prior to beginning an open label trial of fluvoxamine [54].
GAD is a chronic and prevalent disorder characterized by frequent and excessive worry that is difficult to control [55]. This worry lasts for a minimum of six months and is associated with somatic and cognitive difficulties (e.g., fatigue, concentration problems), significant role impairment [44] and suicide [56].
To date, two known studies have investigated predictors of treatment response and non-response in GAD, both involving the use of fMRI methodology. Nitschke et al. [57] looked at brain reactivity to anticipatory cues of neutral and adverse stimuli (e.g., attack scenes vs. household items) in adults with GAD and examined how individual responses to these cues predicted outcome following an 8-week open label trial of venlafaxine, a type of selective serotonin and norepinephrine reuptake inhibitor (SNRI). Reminiscent of what has been found in the depression literature as discussed above, Nitschke et al. [57] found that activity in the pregenual ACC in response to anticipatory aversive and neutral cues predicted better outcomes. Specifically, individuals with hyperresponsivity in the pregenual ACC showed greater response to treatment measured by decreases in self-reported anxiety symptoms. The pregenual ACC is thought to play a role in the detection and resolution of emotional conflict [58] and thus Nitschke et al. [57] have proposed that individuals with greater pretreatment activity in this area may be better able to engage top-down control and regulate emotions when given treatment.
In the same participant pool, Whalen et al. [59] examined whether response to an emotional faces task could predict response following venlafaxine treatment in GAD. They specifically examined reactivity in the amygdala and rostral region of the ACC, as these areas have been found to be functionally related and relevant to the study of visually presented expressions of emotions [60]. Results from this study showed that increased reactivity in the rostral ACC and decreased reactivity in the amygdala when viewing fearful faces was related to improved outcomes after the 8-week medication trial (similarly measured by self-reported anxiety symptoms).
Since all participants were free from comorbid diagnoses, findings in these two studies cannot be accounted for by any other axis I disorder. In addition, results persisted after controlling for current depressive symptoms, further strengthening the conclusion that activity in these brain areas specifically predict GAD treatment outcome. However, the overlap in findings observed between studies in GAD and MDD, where activity in the pregenual ACC is implicated as a predictor of treatment response, may highlight the commonality in the underlying mechanisms of these disorders, which are commonly co-morbid. Future studies employing randomized, placebo controlled designs will need to be conducted in order to ensure that findings described above predict improvement with venlafaxine, not simply improvement in general.
SAD is characterized by intense fear of being in social situations in which judgment or embarrassment may occur. Age of onset in SAD is typically during mid-teen years, where symptoms tend to follow a long, protracted course of illness that often goes untreated [61].
Two known studies have investigated neuroimaging predictors of treatment outcome in SAD following psychotherapy interventions. Nine patients diagnosed with SAD underwent PET imaging using dopamine agonist ligands to examine dopamine function prior to 15 weeks of CBT [62]. The study found that reduced dopamine D2 receptor binding in the medial prefrontal cortex and the hippocampus prior to treatment predicted greater changes in self-reported social anxiety symptoms after CBT.
Employing fMRI methodology, Doehrmann et al. [63] investigated functional brain activity in response to emotional faces and scenes. Using whole-brain regression analyses, Doehrmann and colleagues found that BOLD response to angry vs. neutral faces in right occiptotemporal brain areas predicted better response to CBT, especially in initially more severe patients. This was true even when accounting for possible confounding effects of depressive co-morbidity. Researchers purport that predictive activity to faces over emotional non-face scenes is consistent with the social nature of SAD. While connectivity between higher-order visual and emotion processing areas has been shown to be altered in SAD, the authors note that further research is needed to elucidate the how the relationship between pretreatment activity in occiptotemporal brains relates to altered activity in limbic brain regions identified in other areas of research.
Within the class of anxiety disorders, neuroimaging outcome prediction studies have, thus far, focused mostly on OCD. Findings implicate the OFC as being especially important in regards to predicting outcomes following pharmacological and psychological interventions in this disorder; however, areas of the PFC, ACC, caudate, cerebellum and STG in addition to serotonin system functioning may be salient predictors of treatment response in OCD as well. Research in GAD and SAD is still in its infancy; however, initial studies suggest that activity in the ACC may differentiate individual response to medication treatment in GAD whereas D2 receptor binding in the prefrontal cortex and hippocampus can be used to predict better social anxiety outcomes following psychological intervention. (Figure 4).
Summary of pre-treatment neuroimaging findings that have been associated with positive responses to either Cognitive-Behavioral Therapy or anti-depressant medication treatments in anxiety disorders. (PFC=prefrontal cortex, OFC=orbital frontal cortex, SERT=serotonin transporter, STG=superior temporal gyrus, ACC=anterior cingulate cortex).
Internalizing disorders are serious and often debilitating problems associated with significant impairment and individual suffering. While pharmacological and psychological interventions show some efficacy in the treatment of MDD and anxiety disorders, more precise personalized care is needed in order to improve overall treatment outcomes and to reduce the cost of psychiatric interventions. While this avenue of research is in its infancy, the use of imaging methods to identify neurobiological markers that predict treatment outcome holds the potential to further advance the field of personalized psychiatry and may eventually help guide clinicians towards the selection of treatments that have the highest likelihood of improving individuals patients’ symptoms.
Advanced technologies have greatly facilitated efforts to examine anomalies in neural structure and function over the past decade. The findings in MDD show that regions of the anterior cingulate cortex have most reliably been identified as areas differentiating treatment responders from non-responders. Studies aimed at examining predictors of treatment outcome in anxiety disorders have primarily focused on OCD, most frequently implicating the orbital frontal cortex. Treatment predication research in other anxiety disorders, such as GAD and SAD is beginning to receive more attention.
While the research reviewed above provides an initial foundation for future research to advance personalized psychiatric care, several points need to be highlighted when considering these treatment studies. Most of the studies to date have reported results on small samples with uncontrolled treatment delivery, assessing imaging in the context of either a naturalistic and community-based treatment, or in the setting of a trial that compared different treatments but then examined effects after treatment arms were collapsed. While the field is currently limited in that large-scale treatment studies that involve comprehensive neurobiological assessments are highly labor intensive and are rarely feasible (for a noted exception see Dunlop et al. [64], next steps will require larger, more diverse samples and controlled treatment delivery to more accurately and reliably assess prediction across interventions.
Most research to date has been conducted in adult samples with little research examining biological predictors of treatment response in younger populations. It will be particularly important for future research to identify predictors of treatment response for children and adolescents suffering from anxiety and depression given that neurobiological factors associated with treatment outcomes may differ across development, early onset is a negative prognostic indicator of future problems and plasticity in key neural networks may be amenable to alteration during this period in development [20,65]. Furthermore, with the exception of symptom severity [20,66,67], younger age [67] and positive family history [68], few psychosocial indexes have consistently identified who responds favorably to an intervention [69], and very little is known as to which variables differentially predict response across types of interventions. Recent work has taken initial steps towards using brain imaging methods to identify biological markers for use in tailoring treatment for adolescent depression. In the only study to date that has published data on predictive imaging for adolescent depression, Forbes et al. [70] examined reward-related brain functioning in adolescent MDD before treatment with either CBT (n=7) or CBT plus a selective serotonin reuptake inhibitor (n=6). Due to the small number, the treatment arms were combined. Greater striatal activity during reward outcome predicted higher general severity after treatment, whereas greater striatal activation during reward anticipation predicted lower anxiety after treatment.
Inclusion of broader populations characterized as suffering from internalizing disorders may provide additional insights into relevant brain mechanisms for prevention. As previously mentioned, internalizing disorders have high rates of co-morbidity with one another, and although research to date has focused on depression and anxiety disorders, future research may be needed to delineate the biological underpinnings that account for such overlap. This work may help us refine particular psychological and pharmacological treatments. Similarly, expanding prediction studies to include internalizing problems outside of those classified as mood or anxiety disorders are also needed. Particularly, Eating Disorders have been characterized as belonging to the internalizing construct [71]; however, while imaging research has begun to characterize the neurobiological underpinnings of Eating Disorders [72-75], research has yet to examine neurobiological predictors of treatment response in this population.
While research reviewed above employed the use of fMRI, PET, and SPECT imaging techniques, the study of predictive biomarkers of treatment outcome should be expanded with the use of other neuroimaging methods. For example, the use of spectroscopy would provide evidence of pretreatment chemical and metabolite profiles predictive of treatment outcome. Similarly, resting state fMRI methods might be particularly useful, potentially elucidating our understanding of how different patterns of functional connectivity within and between neural circuits relate to treatment outcome or treatment resistance. In addition, it is expected that future research will increasingly employ the use of multi-modal approaches in predictive treatment research, helping to identify other biological markers not capable of being assessed via neuroimaging techniques. For example, current efforts are underway to more definitively assess biological markers for treatment response across treatments in adults with MDD (CBT, duloxetine, escitalopram) using multi-modal techniques including resting fMRI, neuroendocrine assessments, immune markers and measures of gene expression [64]. Additionally, neurobiological predictors of treatment response that have been identified thus far are not sufficiently strong enough nor have they been sufficiently replicated to warrant changes in clinical decision making at this juncture. Perhaps and understanding of broader brain networks will be enhanced by profiling numerous brain functions and structures that, in compilation, will more aptly predict treatment response.
An exciting advance that has the potential to improve personalized care is recent work incorporating machine-learning approaches to classify groups—disease versus no disease, or responders versus non-responders. Machine learning approaches are “brain reading” or “brain decoding” methods. Instead of analyzing the brain voxel by voxel, data from groups of voxels are used to train a computer program to distinguish different classes of data (e.g., treatment responders from treatment non-responders) and provide maps which indicate the levels by which different brain regions are accurately involved in the classification [76]. In a study that analyzed grey and white matter volumes, using a support vector machine (SVM) approach, Gong and colleagues [77] showed they were able to predict response versus non-response based on gray matter with 70% accuracy and based on white matter with 65% accuracy. Another study that used SVM measured responses to sad faces with fMRI before CBT in 16 unmedicated depressed adults. Brain regions implicated in clinical remission included ACC, superior and middle frontal cortices, paracentral cortex, superior parietal cortex, precuneus, and cerebellum, with 71% sensitivity and 86% specificity of response prediction [78]. A third SVM study found that the pattern of brain activity during sad facial processing correctly classified patients\' clinical response at baseline, prior to the initiation of treatment, at trend levels of significance [23]. SVM approaches are still new in the field and the value of such non-traditional statistical approaches still needs to be weighed.
Practical constraints must be considered as future efforts aim to translate knowledge of neurobiological predictors of treatment response into clinical practice. In addition to providing reliable data with high sensitivity and specificity, ideally a biomarker would be low in cost, easy to collect and simple to analyze [79]. It is possible that these approaches could be mechanized sufficiently to reduce costs and increase feasibility so that one day, routine clinical assessment will include the collection of data via neuroimaging technology [80]. For example, if activity in the ACC remains a robust predictor of treatment response in larger controlled studies, one potential implication of this type of research could be that individual patients presenting with MDD may undergo an MRI to measure pregenual and subgenual ACC activity, which could in turn be used to guide whether the individual is referred for Cognitive Behavioral Therapy or pharmacotherapy. Currently, such an approach is likely cost prohibitive and may not be sufficiently feasible given the constraints of data acquisition, preprocessing and analysis. Alternatively, once neuroimaging markers that predict treatment outcome are well established, neuroimaging technology used to identify brain regions and functions associated with treatment outcome may be used to aid in the development or refinement of proxy biomarkers, such as neuropsychological functioning or serum markers, that could feasibly measure prediction and be disseminated for wide-spread application of personalized psychiatric care.
Here we have focused on neurobiological factors that can be measured at baseline to predict treatment. However, increased understanding of what aspects of neurobiological factors change over the course of treatment may also serve to enhance our understanding of the pathophysiology of internalizing problems and aid in identifying neurobiological factors that are likely to predict treatment outcomes. A recent review of the literature on changes with treatment concludes that a functional normalization of the fear network occurs with recovery across treatments [81]. Specifically, evidence suggests that both psychotherapy and psychopharmacology each in specific ways result in normalization of activity in the target structures (respectively, “top-down” and “bottom-up” effects). Methodologies that capitalize on considering both prediction of and change associated with treatment outcomes are needed.
Advanced techniques, such as those used in neuroimaging research, offer tremendous benefit to our society in that they provide the capability to improve our understanding of the pathophysiology underlying internalizing problems and may eventually offer guidance in regards to treatment selection, allowing providers to choose only those treatments that are most likely to be maximally effective for a given individual. This area of research is still developing. The concept of neural network medicine envisions a time to come when treatments will be used to target a neural network rather than simply components within the network. While personalized medicine in psychiatry is still at an early stage, “it has a very promising future” (Costa e Silva, in press).
Different fermented foods could be categorized according to fermentation products just like organic acids which consisting of acetic acid and lactic acid (dairy and vegetables); and peptides and amino acids resulted from protein (fish and other fermentations); CO2 (bread); and alcohol (wine and beer) [1, 2]. Food fermentation is one of an early the most precise innovations created and developed by people.
\nIn Asia, coastal foragers during the age of primitive pottery (8000 to 3000 b.c.) were thought to have fermented vegetables before developing of crop-based agriculture [3]. It is possible that dairy fermentations in Middle East came after cattle domestication, alcohol was the first discovered fermented product from fruit fermentation. Many advanced fermentation procedures to produce alcohol by using the cereals were created nearly 4000 b.c., just like producing wine from rice in Asia and beer in Egypt [1]. In Asia, many composed references regarding fermentation innovation were found in historic poems Shijing Chinese book (1100 to 600 b.c.), that celebrates “the thousand wines of Yao,” in referring to a kingdom in China from 2300 b.c. Cucumber thought were first fermented nearly 2000b.c. in Middle East. Old composed records came from the remains of papers of a play (The Taxiarchs) by Eupolis a writer from Greece (429–412 b.c.), also in Christian Bible, pickles were repeated many times. The fermented cabbage and kimchi on the Korean style, is expected to have established in the primitive pottery age from the wizened vegetables ordinary fermentation stored in seawater [1].
\nSauerkraut on European style is thought was established in China, while the technique might be transferred to Europe at the invasion time of Mongol to central Europe in the 13th century. Nowadays, the vegetable fermentation industry is conducting on an enormous scale. Companies in United States that working on cucumber pickles fermentations may have 1000 fermentation tanks of forty-thousand-liter capacity at one site.
\nThroughout the ages, it was believed that cucumber pickle as the fairly fermented cucumber to which spices, vinegar, salt, and sometimes sugar has been added. While the preservation was not required by using the heat. Recently, fresh packed pickles, manufactured by adding of spices, salt, and vinegar to the fresh cucumbers under pasteurized preservation, are representing a huge portion of pickle industry.
\nIndustrial treatments tentatively preserve around 40% of crop through the fermentation in NaCI brines that contain fermentable carbohydrates which converting into acetic acids, ethanol, lactic acid, CO2, and other compounds by naturally existence lactic acid bacteria and yeast. This procedure uses to expand the using equipment packing line and workers to throughout the year operation in manufacturing of the final product.
\nTraditionally, fiberglass, wood, and polyethylene tanks are used for the fermentation that might require 10–21 days (period of storage in the same tanks is generally less than 1 year) and sometimes longer. Tanks are put outdoors to give the opportunity for sunlight ultraviolet irradiation to hit the surface of the brine and subsequently inhibiting yeasts and molds growing, and other microorganisms on the surface of the brine.
\nDuring the fermentation of cucumber pickles, brine storage and processing operations are liable to the reactions of oxidation which affect adversely on the quality properties. In spite of pickles are flooded in brine during fermentation and bulk-storage, while the containers are opening, which encourage the exposure to air and sunlight.
\nAdditionally, pickle tanks’ brines are usually spread with air in order to mix the components and to release CO2, and at the time of transferring to processing operations, pickles are removed from brine and subsequently exposes to light and oxygen. Also, the brines and pickles content of traces prooxidant metals just like copper, zinc and iron which act together with oxygen and light to be in charge of pigments oxidation and developing undesirable flavors sometimes, and this may lead to considerable economic loss of the market value.
\nCucumber (Cucumis sativus) fermentation in United States is conducted in 30,000–40,000 liter, fiberglass tanks with open top and placed outdoors to allowing the surface to exposure to sunlight. Sunlight UV radiation is dependent to suppression the surface aerobic yeasts that have the ability to utilize lactic acid that resulted from fermentation. Cucumbers are submerged totally with salt brine and kept under the brine surface with wooden headboards. Fermentation is usually conducted in 6% NaCl. Calcium chloride typically added the cover brine in order to keep the fragile texture, and firm of the fermented cucumber throughout fermentation and storage [4]. The fermentations of cucumber usually subject a homolactic acid fermentation, that is not resulting CO2 from sugars. Although CO2 could be produced via cucumbers respiration and via malate decarboxylation over the beginning of fermentation [4]. Some of lactic acid bacteria have an analytical malolactic enzyme that converting malate to lactate and CO2. The reaction of malolactic enzyme takes place intracellularly resulting in proton absorption, subsequently increasing the internal pH of the cell. Although it is a recommendable reaction in winemaking (applied to removing the acidity of wines), the fermentation of malolactic in cucumbers may lead to formation of “bloaters,” or undesirable pockets of internal gas, resulting in decreasing the yield of the production [5]. In order to prevent the formation of bloater, the fermentation of cucumber is clean with air to get rid the surplus CO2 from the tank [6]. In order to restrict the growing of aerobic microorganisms in air-purged cucumber fermentations, especially molds and yeasts, acetic acid (0.16%) or potassium sorbate (~0.04%) could be used as aids in processing [7].
\nAir purging may be stopped each day several hours to control aerobic microorganisms’ excessive growth. Usually, cucumber is fermented with Lactobacillus. plantarum and other LAB and may store for year in fermentation tanks in degrees under than 0 °C while NaCl concentration commonly increase to 10–15% during the storage to reduce freezing damage and keeping the required fermented cucumber texture. Cucumber should be washed before selling in order to remove the excess salt and then using different packages (jars, pouches, plastic pails) with suitable covers in packaging. The covers usually contain spices, acetic acid, and lactic acid residues. Pasteurization sometimes is used for fermented pickles while heat treatment is not used for big containers. Excessive growth of microorganisms is eliminated by low pH, organic acids, and absence of fermentable sugars. Cucumber fermentations depend on the growing of LAB that existence naturally on cucumbers surface. Although, some starter cultures are added to cucumber fermentation to get a consistent product, adding Lactobacillus plantarum does not decarboxylate malic acid (subsequently does not form bloaters) [9], and this approach has been created, developed, and tasted to identify culture growing capability in cucumber fermentations [10]. A procedure for starter culture preparation that suitable for the requirements of kosher is applicable to producers [11]. The brined cucumbers’ primary pH is nearly 6.5. Recycled brine could be used in commercial fermentations, or adding acetic acid to brine solutions. This acid addition may help in removing the excess CO2 and encouraging LAB growth, so the commercial fermentations’ primary pH could vary basically. Some of the metabolites could have an inhibitory effect on the other bacteria just like peroxides, bacteriocins, and peptides [12]. There might be 1.5% lactic acid, pH (3.1–3.5), few or no sugar at the end of fermentation. In such an environment that is acidic, anaerobic, high salty, and lacks sugar, there are a low number of microorganisms that have the ability to grow and survive to preserve cucumbers. Sometimes during storage, fermented cucumbers expose secondary undesired fermentation which is identified by pH increasing, lactic acid vanishing, propionic and butyric acid formation. Deterioration of fermented cucumber happening at the spring season beginning when increasing the surrounding temperature. Increasing propionic and butyric acid concentrations lead to smelly spoilage [13]. The microbial environment of this spoilage presently is not closely defined but may attribute to the growth of bacteria that form spores such as clostridia when increasing the pH above 4.6. The salt concentration of the fermented cucumbers is about (6% or more) and this is very high for consumption directly by humans. Therefore, the salt concentration is reduced to around 2% by water washing directly before packing and distribution. This treatment lead to high salt concentrations of the waste stream in addition to a high BOD resulting from the organic ingredients that are existed in the brine and that spread out of cucumbers over the process of desalting. Hence, cucumber brine of the desalting process is commonly recycled and might be utilized another fermentation [14]. The brines fermentation could be treated in order to expel the softening enzymes (mostly polygalacturonases) before the recycling [15], which acts on degrading cucumber cell’s pectic substances and softening the fruits.
\nFermentation is influenced by variables due to cucumbers, environmental conditions under which they are kept during fermentation, and microorganisms that are naturally present or intentionally added. Since it is so important to maintain the structural integrity of cucumbers, both physical and chemical factors are involved. The interactions between these factors lead to an extremely interesting and complex fermentation process [16]. A lot of research on the fermentation of cucumbers and other fruits and vegetables has been done. However, there is an incomplete understanding of the interactions between the microbiological, chemical, and physical factors involved.
\nBefore the cucumber fermentation industry can take full advantage of the biotechnology revolution that looms for many fermentation industries, more understanding of these interactions is needed [17].
\nThe production of CO2 in the cover brine of fermenting vegetables by heterofermentative LAB and fermentative species of yeasts has been linked with gas pockets formation inside the cucumber, which called formation of bloater (Figure 1). Homofermentative LAB capable of decarboxylating malic acid, as example L. plantarum, might cause bloating by producing a sufficient CO2 when combined with the CO2 formed from the respiring vegetable tissues [9, 18]. Prevention of bloater formation was effective in fermented cucumber brines by using nitrogen or air [6, 19]. Air purging has to be carefully controlled as it may result in fruit softening due to mold growth [20, 21] reduced brine acidity due to yeast growth and off-colors and flavors. The addition of potassium sorbate to fermentation brines, including the application of spray to brine surfaces, is widely used to minimize the growth of yeast and the development of CO2.
\nSteps brine fermentation of cucumber [8].
Oxidative yeasts may cause malodorous spoilage of fermented cucumbers to develop. The lactic acid generated during fermentation can be consumed by these microorganisms, with a subsequent increase in pH that facilitates the development of spoilage microorganisms [22, 23]. In cucumbers, lactic acid produced during primary fermentation can be catabolized by yeasts of the genera Pichia and Issatchenkia, causing an increase in pH.
\nPectinolytic enzymes derived from plant material or microbes can cause the softening of brined vegetables (Figure 2).
\n\nLactobacillus plantarum cells colonizing the cucumber tissue [24].
Mold growth accompanying film-forming yeast growth on the brine surface can cause softening of cucumbers. In the absence of sunlight and the presence of minimal amounts of oxygen, heavy scum yeast and/or mold growth is generally the result of neglecting brine material during extended storage. [25]. In order to maintain anaerobic conditions and to limit the growth of surface yeasts and molds, Pickled cucumber tanks are usually held indoors, with a seated plastic cover weighted down with water or brine. Mold polygalacturonases associated with cucumber flowers can also result in the softening of brined cucumbers. [26] By draining and rebrining the tank with calcium chloride, this problem can be reduced. 36 hours after the initial brining procedure. However, this solution is not about salt disposal. Recycled brines are instead treated to inactivate the softening enzymes, if necessary. [15] The addition of calcium chloride may slow down the rate of fermenting cucumbers’ enzymatic softening. This should not, however, be relied upon to eliminate problems with enzymatic softening. Care must be taken to minimize the contamination of flowers and plant debris by cucumbers, especially small fruits, which may be a source of contamination by pectinolytic molds. Due to the reduced amount of brine surface in contact with air compared to the total volume, softening is not a very serious problem in bulk Spanish-style cucumber fermentation. Yeasts and/or molds on the plastic drums used during the conditioning operations (sizing, grading, pitting, stuffing, etc.) can, however, cause softening. [22]. Desalting is used to prepare non-pasteurized fermented cucumbers, followed by the addition of cover liquor, often containing acetic acid and preservatives. Sugar is added to sweet pickles at concentrations of up to 40 percent. The main spoilage organisms in such products are osmotolerant yeasts, and a preservation prediction chart, based on the concentration of acid and sugar required for shelf stability, has been developed. On the surface of the liquid, aerobic molds and film yeasts may grow, mainly as a result of defective jar closure. Spoilage microorganisms in sweet pickles include yeasts [27] and lactobacilli, particularly the heterofermentative Lactobacillus fructivorans. In order to prevent the growth of LAB and yeast, non-fermented pickle products in which acetic acid is added to fresh cucumbers (known as fresh-pack pickles) are pasteurized. Recommended procedures include 165 °F (74 °C) for 15 minutes, as described by [28]. Spoilage usually occurs due to improper processing (insufficient heat to pasteurize) and/or improper acidification of pasteurized pickle products, so that a balanced brine product of pH 3.8 to 4.0 is not achieved. Molds and film yeasts are factors in cases of poor jar closure, where oxygen is introduced into the container, as with sweet pickles.
\nThis can lead to a potentially dangerous situation triggered by an increase in pH as the spoilage microorganisms consume organic acids. Germination of Clostridium botulinum spores can occur if the pH rises above 4.6. Non-acidified refrigerated products are sold commercially under a variety of names, including half-sour dills, real kosher dills, new kosher dills, sour overnight dills, garlic pickles, new half-sour pickles, new half-sour pickles, new half-sours, new home-style pickles, etc. [29]. These cucumbers may be kept at room temperature in barrels for a few days or longer and then refrigerated at 2–5 ° C to allow fermentation to occur. Microbial growth, enzymatic activity, and the curing process continue at a slow rate under cooling conditions. [29] The gaseous spoilage of the product is caused primarily by the previously mentioned microbial groups that form gas. Due to the much lower concentrations of salt added to these product types, softening issues in refrigerated-fermented products may develop. To such products, fresh, whole garlic cloves and other spices are normally added. It is possible that these spices contain softening enzymes. Whether the half-sour products are manufactured in bulk or in the retail jar, for more than a few weeks, the very nature of the product makes it difficult to maintain good quality. The barreled product achieves the Good Manufacturing Practices (GMP)-recommended brine pH of 4.6 or lowers for acidified foods typically before or shortly after refrigeration, and then slowly begins to produce acid. For a product made in a retail jar, this recommended condition for brine-product pH cannot be ensured because there is no uniform process adopted by the packers in which the product is initially acidified or intentionally incubated for the development of natural fermentation with lactic acid.
\nThe refrigerated fresh-pack (non-fermented) products contain 2–3 percent NaCl and sometimes sodium benzoate or other preservatives and are acidified with vinegar at a balanced pH of around 3.7. [29] The cucumbers are not heated, like the half-sour pickles, either before or after packing. The products will maintain an acceptable quality for several months if properly acidified, refrigerated, and preserved. However, recipes containing no vinegar or other acid in the initial cover liquor should be considered with caution. Quality assurance of cucumber products begins with the removal of the cucumber’s outer leaves and woody core. In addition to its undesirable texture, the existing sucrose in the core could be utilized by Lactobacillus mesenteroides resulting in formation of dextran which lead to a stringy and slimy texture. Cucumbers marketed under refrigerated conditions are preserved by the addition of sodium benzoate and metabisulfite [30]. Chemical changes that can result in discoloration (browning) and the formation of objectionable flavors influence the shelf life of such products. The growth of naturally occurring yeasts in cucumbers may result from uneven salting during cucumber preparation and may induce pink coloring and vegetable softening. Spanish-style olives were formerly preserved in cover solutions containing relatively high salt concentrations through fermentation. However, it has been demonstrated that an appropriate combination of low pH (3.5), combined acidity (0.025) mill equivalents (mEq)/L) and moderate proportions of acid (>20.4%) and salt (>25.0%) is also able to preserve well-cured cucumbers [31]. Incompletely cured cucumbers or those with characteristics outside the ranges necessary for complete stabilization without heat treatment have been gradually used to allow pasteurization to be commercialized. [22] In some cases, particularly when pasteurization is not recommended (plastic bags, seasoned olives, etc.), producers used authorized preservatives such as potassium sorbate or sodium benzoate [31].
\nUsually, fermentation is defined as an anaerobic process. Within the cucumber fermentation process, LAB and yeast convert glucose and fructose into lactic acid, ethanol, acetic acid, and CO2. The homofermentative LAB main pathway is breaking down of one six-carbon sugar (glucose) to produce two molecules of three-carbon lactic acid. More complex metabolism is used by Heterofermentative organisms. At the beginning, glucose is converted into CO2 five-carbon sugar phosphate, and furthermore degraded into lactic acid and a two-carbon compound, acetic acid or ethanol [32]. We shall concentrate here on vegetable fermentation biochemical features that link to quality of the product. So far, many researches are paying more attention in vegetables fermentation and storage, especially cucumbers, with reduced salt. Vegetable fermentations’ chloride waste can be extremely reduced in case of reducing the required salt for fermentation and storage in order to exclude the desalting step before the conversion to final products. Many research studied the relationship between concentration and type of the salt [33]. Replacing of NaCl with various cations and anions on fermentation of sugar in cucumber juice. The most interesting thing, fructose was the most preferred fermentable sugar to Lactobacillus plantarum more than glucose in most of experiments. Along with addition of different salts, the utilization of sugar was decreasing as anion or cation concentrations increasing. [33, 34] have identified various volatile ingredients in cucumbers that fermented with Lactobacillus plantarum (2% NaCl). About 37 volatile ingredients were determined, and as a result of fermentation, there was a little change in most of them. Inhibition of (E, Z)-2,6-nonadienal and 2-nonenal production was the most outstanding fermentation effect on cucumber volatiles. [35] Characterized trans- and cis-4-hexenoic acid as the strongest odors that specify the brine aroma properties of commercially fermented cucumbers in nearly 6% NaCl. [36] Illustrated that exposing the slurries (2% NaCl) of fermented cucumber to oxygen resulting in formation of nonenzymatic hexanal plus a series of trans unsaturated aldehydes with 5–8 carbon atoms that linked with oxidized odor intensity development the tissue of fermented cucumber. In the existence of light, about 100 μg/ml concentration of calcium disodium EDTA preserve nonfermented pickles against bleaching of pigments and lipid oxidation [15]. Although, when using this compound, there was a little reduction in pickles’ firmness retention. Firmness retention in cucumbers fermentation and storage is a key quality issue. It is difficult to assure the firmness retention (in reduced salt fermented cucumbers) equal to what can be accomplished by fermenting and storage in 6% NaCl or more. Nevertheless, over many previous years there was a wide understanding for softening of cucumber tissue.
\n[21] Showed the importance of calcium in keeping fermented cucumbers’ firmness. It was found that first-order kinetics is followed by the nonenzymatic softening of acidified, blanched cucumber tissue [37]. The mentioned kinetic manner made it reasonable to identify the activation of entropy and enthalpy of cucumbers’ nonenzymatic softening, although that the chemical reactions in charge of softening were not known. At 1.5 M NaCl, both activation of entropy and enthalpy were high. Cucumber softening was inhibited by calcium because it reduced activation entropy too much into a limit that activation overall free energy was reduced [38]. This behavior of thermodynamic is resembled to that which occurs when changing conformation of polymers, just like in denaturation of protein. It is totally differed from the observed properties of pectin acid hydrolysis. [39] Figured out that pectin’s acid hydrolysis rate was inefficient to be the reason for non-enzymatic softening the tissue of the cucumber. [40] Identified salt, temperature, and calcium concentrations combined effects on fermented cucumber tissue’s softening rate. The softening kinetics of fermented cucumbers did not follow the first-order simple reaction. Just like the tissues of many other plants, cucumber possesses enzymes that have the ability to degrade the ingredients of plant cell walls, which may lead to changing in the texture.
\nIn cucumbers, many activities of enzymes have been found such as exopolygalacturonase, pectinesterase, and endopolygalacturonase [41]. When fermenting or acidifying of cucumber, methyl groups are removed from pectin by pectinesterase [42]. Nevertheless, pectin’s’ enzymatic hydrolysis by polygalacturonases from cucumber has not been identified if it is a significant factor in fermented cucumbers’ softening. Adding of fungal polygalacturonases into the tanks of fermentation, especially on the flowers attached to small cucumbers has been linked to the commercially importance of fermented cucumbers’ enzymatic softening. [43] developed a sensitive new method of diffusion plate to determine the activity of polygalacturonase in the brines of fermentation and found that alumino-silicate clay has the ability of adsorbing and removing the activity of polygalacturonase from the brines of fermentation that are recycled. Enzymes which could hydrolyze polysaccharides of the cucumbers cell wall have not studied widely comparing with the enzymes that degrade pectin. [45] Showed that the activity of endo-β-1,4- gluconase in cucumber is inhibited under pH of 4.8 while endoglucomannan-splitting enzyme retains its activity under pH of 4.0 but is inhibited within the fermentation. In fresh cucumbers, they characterized 6 enzymes which hydrolyze p-nitrophenylglycosides of β-d-glucose, β-d-galactose, α-d-galactose, β-d-xylose, α-d-mannose, and α-l-arabinose, which were inhibited throughout the fermentation. The enzymes that have the ability to hydrolyze the synthetic substrates are widespread in plants. Resemble enzymatic activities were found in olives, pears, and Semillon grapes.
\n[44, 45] Discovered the same p-nitrophenyl glycosidases detected by [44] in cucumbers. She reported undetectable levels in 2% NaCl brines throughout the first week of fermentation [46, 47]. Gathered calcium addition, fresh cucumbers’ blanching relatively to enzyme inactivation, and a quick fermentation using a malolactic-negative Lactobacillus plantarum culture for cucumbers’ fermentation and keeping a required texture in reduced (4%) sodium chloride concentration. [48] Found notable degradation products of glucosinolate in cucumbers fermented with Lactobacillus sakei compared to cucumbers manufactured with lactic acid bacteria starter cultures. [49] Reported that ascorbigen, a compound resulted from a degradation product reaction of indole glucosinolate (glucobrassicin) and ascorbic acid, is the cucumbers’ dominant glucosinolate degradation product. Glucoraphinin existed in fresh cucumbers was converted over the fermentation into sulforphorane, however, sulforphorane was a relatively small glucosinolate degradation product in fermented cucumbers. There are many concerns about the biogenic amines’ formation in cucumbers. [50] Reported that storing cucumbers up to 12 months led to the formation of tyramine. While very trace amounts of tryptamine, histamine, and spermine were determined. These findings were assured in a study on vegetable products which concluded that tyramine concentration was about 4.9 mg/100 g in canned cucumbers [51], and the same finding and the concentration reported by [50]. No health risk existed referring to these mentioned biogenic amine levels, with the possible exception that individuals taking medications possessing monoamine oxidase inhibitors.
\nCompared to the fermentation of liquids such as beer, wine, and milk, unique problems are involved in the fermentation of whole vegetables. Structural integrity has to be preserved in whole vegetables, which is not a factor with liquids [52]. Tissue softening is also a serious defect that can be caused by pectinolytic enzymes of either microbial (primarily fungal) source [53] or of the cucumber fruit itself. Off-flavors and off-colors may result from improper methods of fermentation and handling.
\nThe cucumber pickle industry is faced with waste disposal, in addition to spoilage problems. These wastes consist of the salt used to prevent softening during fermentation and storage, and the organic wastes. Salt concentrations used greatly exceed the 2–3 percent desired in the final product [54].
\nThus, after storing the brine, the excess salt must be leached from the cucumbers before they are processed into finished products. Disposal of this non-biodegradable waste salt is a source of serious environmental concern. As the salt is extracted during leaching, soluble cucumbers, including desirable nutrients and flavor compounds, are also removed. These desirable components are not only lost, they must be degraded before being discharged into waterways. Discharge of salt and organic materials into municipal disposal systems typically entails an extra expense for pickle companies, since municipalities must charge for recovering the cost of handling such waste. [55] (Figure 3).
\nCucumber bloater defect caused by carbon dioxide microbiologically produced during fermentation by either yeasts or LAB [56].
Purge-and-trap analysis of cucumber slurries’ volatile ingredients in 2 percent reduced-salt salt brine before and after cucumber fermentation. Volatile components’ comparison before and after fermentation led to the derivation that the main influence of fermentation on volatile flavors was to prohibit the enzymatic production of E, Z-2,6-nonadienal and 2-nonenal enzymes in cucumbers [34]. These aldehydes are the major ingredients in charge of cucumbers’ fresh flavor [57]. Although, after a few days of cucumber fermentation, when tearing the tissue of cucumber, the pH descends low enough to deactivate the enzymes that forming these compounds. In fresh cucumber slurries, just benzaldehyde, ethyl benzene, and o-xylene were not found within the volatile ingredients characterized in the fermented cucumbers. Recently, the absence of flavor influence of volatile aldehydes is the main effect of the fermentation on flavor [35]. In fermented pickled cucumber brines, a low influence of volatility flavor compound was characterized. Adding of saturated salt to brine samples and heating to 50 °C, SPME (solid-phase microextraction) fiber sampling followed by GC-olfactometry resulted in the identification of a component with an odor close to that of the fermentation brine. The component with a fermentation brine odor was characterized as trans-4-hexenoic acid. The existence of cis-4-hexenoic acid was also tentatively characterized. A solution containing 25 ppm trans-4-hexenoic acid, 10 ppm phenyl ethyl alcohol, 0.65 percent lactic acid, 0.05 percent acetic acid, and 8 percent sodium chloride in a reconstitute experiment had an odor very similar to that of fermented cucumber brine. Lactic acid, acetic acid, and sodium chloride concentrations are acceptable for commercial brines after completing the fermentation. Adding of phenyl ethyl alcohol resulted in in a few enhancements in the matching odor. For that, the key component in the simulated brine solution was trans-4-hexenoic acid. The source of trans-4-hexenoic acid in fermentation brines is, unfortunately, not recognized.
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