BACKGROUND:Zebrafish larvae are translucent, allowing in vivo analysis of gut development and physiology, including gut motility. While recent progress has been made in measuring gut motility in larvae, challenges remain which can influence results, such as how data are interpreted, opportunities for technical user error, and inconsistencies in methods. METHODS:To overcome these challenges, we noninvasively introduced Nile Red fluorescent dye to fill the intraluminal gut space in zebrafish larvae and collected serial confocal microscopic images of gut fluorescence. We automated the detection of fluorescent-contrasted contraction events against the median-subtracted signal and compared it to manually annotated gut contraction events across anatomically defined gut regions. Supervised machine learning (multiple logistic regression) was then used to discriminate between true contraction events and noise. To demonstrate, we analyzed motility in larvae under control and reserpine-treated conditions. We also used automated event detection analysis to compare unfed and fed larvae. KEY RESULTS:Automated analysis retained event features for proximal midgut-originating retrograde and anterograde contractions and anorectal-originating retrograde contractions. While manual annotation showed reserpine disrupted gut motility, machine learning only achieved equivalent contraction discrimination in controls and failed to accurately identify contractions after reserpine due to insufficient intraluminal fluorescence. Automated analysis also showed feeding had no effect on the frequency of anorectal-originating contractions. CONCLUSIONS & INFERENCES:Automated event detection analysis rapidly and accurately annotated contraction events, including the previously neglected phenomenon of anorectal contractions. However, challenges remain to discriminate contraction events based on intraluminal fluorescence under treatment conditions that disrupt functional motility.

Neuropathic pain in rodents can be driven by ectopic spontaneous activity (SA) generated by sensory neurons in dorsal root ganglia (DRG). The recent demonstration that SA in dissociated human DRG neurons is associated with reported neuropathic pain in patients enables a detailed comparison of pain-linked electrophysiological alterations driving SA in human DRG neurons to alterations that distinguish SA in nociceptors from SA in low-threshold mechanoreceptors (LTMRs) in rodent neuropathy models. Analysis of recordings from dissociated somata of patient-derived DRG neurons showed that SA and corresponding pain in both sexes were significantly associated with the three functional electrophysiological alterations sufficient to generate SA in the absence of extrinsic depolarizing inputs. These include enhancement of depolarizing spontaneous fluctuations of membrane potential (DSFs), which were analyzed quantitatively for the first time in human DRG neurons. The functional alterations were indistinguishable from SA-driving alterations reported for nociceptors in rodent chronic pain models. Irregular, low-frequency DSFs in human DRG neurons closely resemble DSFs described in rodent nociceptors while differing substantially from the high-frequency sinusoidal oscillations described in rodent LTMRs. These findings suggest that conserved physiological mechanisms of SA in human nociceptor somata can drive neuropathic pain despite documented cellular differences between human and rodent DRG neurons. PERSPECTIVE: Electrophysiological alterations in human sensory neurons associated with patient-reported neuropathic pain include all three of the functional alterations that logically can promote spontaneous activity. The similarity of distinctively altered spontaneous depolarizations in human DRG neurons and rodent nociceptors suggests that spontaneously active human nociceptors can persistently promote neuropathic pain in patients.

Brain-derived neurotrophic factor (BDNF) is critically involved in the pathophysiology of chronic pain. However, the mechanisms of BDNF action on specific neuronal populations in the spinal superficial dorsal horn (SDH) requires further study. We used chronic BDNF treatment (200 ng/ml, 5–6 days) of defined-medium, serum-free spinal organotypic cultures to study intracellular calcium ([Ca2+]i) fluctuations. A detailed quantitative analysis of these fluctuations using the Frequency-independent biological signal identification (FIBSI) program revealed that BDNF simultaneously depressed activity in some SDH neurons while it unmasked a particular subpopulation of ‘silent’ neurons causing them to become spontaneously active. Blockade of gap junctions disinhibited a subpopulation of SDH neurons and reduced BDNF-induced synchrony in BDNF-treated cultures. BDNF reduced neuronal excitability assessed by measuring spontaneous excitatory postsynaptic currents. This was similar to the depressive effect of BDNF on the [Ca2+]i fluctuations. This study reveals novel regulatory mechanisms of SDH neuronal excitability in response to BDNF.

Body weight is maintained by balanced energy intake and expenditure; and more energy intake than expenditure results in obesity. The current obesity epidemic and lack of efficient therapeutics demand a clear understanding of the mechanism underlying the imbalance between food intake and energy expenditure. As both food intake and energy expenditure are controlled by neurons in the brain, elucidation of key body weight regulating neurons and their defects in obesity pathogenesis represents an important direction in order to reverse the obesity epidemic. Upon integrating information from both hormonal and synaptic inputs from a neural network, brain neurons release neurotransmitters, broadly including classical neurotransmitters and peptides, to relay the signal. Emerging evidence demonstrates that, in contrast to the canonical view on one neurotransmitter for a given neuron, many neurons release more than one neurotransmitter. Moreover, the recent availability of novel neuroscience technologies, including optogenetics and chemogenetics, combined with mouse genetics, has paved the way to dissecting the role of co-transmission. This chapter summarizes recent developments in the field regarding the role of co-transmission by key brain neurons that regulate body weight homeostasis. Unraveling the functional relationship between co-released neurotransmitters may help us to better harness the function of neurotransmitters to achieve more specific and effective targeting against obesity.

Introduction: Neuroprogression has been proposed as the pathological rewiring of the brain that takes place in parallel with clinical and neurocognitive deterioration in the course of psychiatric disorders. This study aims to review the biological underpinnings and clinical outcomes related to neuroprogression in post-traumatic stress disorder (PTSD). Methods: We performed a systematic review by searching PubMed, Embase, and Web of Science for articles published between January 1, 1960, and January 6, 2020. Inclusion criteria were met when articles assessed brain changes, neurocognition, functioning, inflammation, oxidative stress, and neurotrophins in patients with PTSD. Narrative review articles, case reports, and preclinical studies were excluded. Results: A total of 965 abstracts were identified and 15 articles were included in our systematic review. It seems that for a subset of patients whose symptoms worsen or are maintained at a high intensity there is a progressive change in the frontal lobe, especially the prefrontal cortex, and worsening of both neurocognition (verbal memory and facial recognition) and functioning (physical, psychological, social and environmental). Conclusion: Although current findings associate progressive reduction in frontal lobe size with neurocognitive impairment, further research is needed to characterize PTSD as a neuroprogressive disorder.

AbstractExtracting biological signals from non-linear, dynamic and stochastic experimental data can be challenging, especially when the signal is non-stationary. Many currently available methods make assumptions about the data structure (e.g., signal is periodic, sufficient recording time) and modify the raw data in pre-processing using filters and/or transformations. With an agnostic approach to biological data analysis as a goal, we implemented a signal detection algorithm in Python that quantifies the dimensional properties of waveform deviations from baseline via a running fit function. We call the resulting free program frequency-independent biological signal identification (FIBSI). We demonstrate the utility of FIBSI on two disparate types of experimental data:in vitrowhole-cell current-clamp electrophysiological recordings of rodent sensory neurons (i.e., nociceptors) andin vivofluorescence image time-lapse movies capturing gastrointestinal motility in larval zebrafish. In rodent nociceptors, depolarizing fluctuations in membrane potential are irregular in shape and difficult to distinguish from noise. Using FIBSI, we determined that nociceptors from naïve mice generate larger, more frequent fluctuations compared to naïve rats, suggesting species-specific specializations in rodent nociceptors. In zebrafish, measuring gut motility is a useful tool for addressing developmental and disease-related mechanisms associated with gut function. However, available methods are laborious, technically complex, and/or not cost-effective. We developed and tested a novel assay that can characterize intestinal peristalsis using imaging time series datasets. We used FIBSI to identify muscle contractions in the fluorescence signals and compared their frequencies in unfed and fed larvae. Additionally, FIBSI allowed us to discriminate between peristalsis and oscillatory sphincter-like movements in functionally distinct gut segments (foregut, midgut, and cloaca). We conclude that FIBSI, which is freely available via GitHub, is widely useful for the unbiased analysis of non-stationary signals and extraction of biologically meaningful information from experimental time series data and can be employed for both descriptive and hypothesis-driven investigations.Author SummaryBiologists increasingly work with large, complex experimental datasets. Those datasets often encode biologically meaningful signals along with background noise that is recorded along with the biological data during experiments. Background noise masks the real signal but originates from other sources, for example from the equipment used to perform the measurements or environmental disturbances. When it comes to analyzing the data, distinguishing between the real biological signals and the background noise can be very challenging. Many existing programs designed to help scientists with this problem are either difficult to use, not freely available, or only appropriate to use on very specific types of datasets. The research presented here embodies our goal of helping others to analyze their data by employing a powerful but novice-friendly program that describes multiple features of biological activity in its raw form without abstract transformations. We show the program’s applicability using two different kinds of biological activity measured in our labs. It is our hope that this will help others to analyze complex datasets more easily, thoroughly, and rigorously.

Diabetes is one of the most common comorbid diseases in patients with schizophrenia. The present study examined the prevalence of diabetes and its clinical correlates in a large sample of Chinese patients with schizophrenia, which has not been examined systemically. In this cross-sectional study, a total of 1189 patients (males/females = 938/251; average age: 48.51 ± 10.09 years) were recruited. Fasting blood samples were collected to diagnose diabetes. Psychiatric symptoms were measured with the Positive and Negative Syndrome Scale (PANSS). The prevalence of diabetes was 12.53% with a significant gender difference (males: 10.87% versus females: 18.73%). Compared to patients without diabetes, those with diabetes were older, had a later age of onset, had a higher BMI, had higher positive symptom scores and had higher level of metabolic indices, including triglyceride, cholesterol and HDL cholesterol. After stepwise binary logistic regression analysis, age, BMI, and triglyceride level remained significantly associated with diabetes. This study suggests that diabetes occur with high prevalence in Chinese schizophrenia patients. In addition, age, BMI, and triglyceride level possibly are useful markers predicting an increased risk for diabetes.

The current obesity epidemic mainly results from high-fat high-caloric diet (HFD) feeding and may also be contributed by chronic stress; however, the neural basis underlying stress-related diet-induced obesity remains unknown. Corticotropin-releasing hormone (CRH) neurons in the paraventricular hypothalamus (PVH), a known body weight-regulating region, represent one key group of stress-responsive neurons. Here, we found thatHFDfeeding bluntedPVH CRHneuron response to nutritional challenges as well as stress stimuli and dexamethesone, which normally produce rapid activation and inhibition on these neurons, respectively. We generated mouse models with the activity of these neurons clamped at high or low levels, both of which showedHFD-mimicking, bluntedPVH CRHneuron responsiveness. Strikingly, both models developed rapidHFD-induced obesity, associated withHFD-mimicking, reduced diurnal rhythmicity in feeding and energy expenditure. Thus, blunted responsiveness ofPVH CRHneurons, but not their absolute activity levels, underliesHFD-induced obesity and may also contribute to stress-induced obesity.

There is evidence that obesity or higher body mass index is correlated with cognitive impairment in schizophrenia. Recent studies have demonstrated that genetic risk factors, such as the NRG3, are correlated with both elevated BMI and reduced cognitive function. In present study, we aimed to determine whether possession of the NRG3 rs10748842 influences the correlation between elevated BMI and reduced cognitive ability in schizophrenia. To our knowledge, this has never been examined before. A total of 625 inpatients with schizophrenia and 400 controls were recruited. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was performed to assess cognitive function. We used multiple analysis of covariance (MANCOVA), analyses of covariance (ANCOVA), Pearson correlations, partial correlations, and multivariate regression analysis to test the influence of NRG3 rs10748842 on the aforementioned variables. All RBANS five sub-scores and total score were lower in patients than those in controls (all p < 0.001). Patients carrying NRG3 rs10748842 TC + CC heterozygous genotype had lower attention score compared to TT homozygous genotype (adjusted F = 4.77, p = 0.029). BMI was positively associated with language score in patients (β = 0.387, t = 2.59, p = 0.01). Interestingly, we further found positive association between BMI and language score in TT carriers (partial correlations: r = 0.13, adjusted p = 0.004; multivariate regression: β = 0.42, t = 2.66, p = 0.008), but not in CT + CC carrier (p > 0.05). Our study demonstrated that NRG3 rs10748842 was associated with cognitive impairments, especially attention performance in schizophrenia. Moreover, NRG3 rs10748842 altered the effect of BMI on cognitive impairments as measured by the RBANS language score in chronic patients with schizophrenia.

Defective rhythmic metabolism is associated with high-fat high-caloric diet (HFD) feeding, ageing and obesity; however, the neural basis underlying HFD effects on diurnal metabolism remains elusive. Here we show that deletion of BMAL1, a core clock gene, in paraventricular hypothalamic (PVH) neurons reduces diurnal rhythmicity in metabolism, causes obesity and diminishes PVH neuron activation in response to fast-refeeding. Animal models mimicking deficiency in PVH neuron responsiveness, achieved through clamping PVH neuron activity at high or low levels, both show obesity and reduced diurnal rhythmicity in metabolism. Interestingly, the PVH exhibits BMAL1-controlled rhythmic expression of GABA-A receptor γ2 subunit, and dampening rhythmicity of GABAergic input to the PVH reduces diurnal rhythmicity in metabolism and causes obesity. Finally, BMAL1 deletion blunts PVH neuron responses to external stressors, an effect mimicked by HFD feeding. Thus, BMAL1-driven PVH neuron responsiveness in dynamic activity changes involving rhythmic GABAergic neurotransmission mediates diurnal rhythmicity in metabolism and is implicated in diet-induced obesity.

BACKGROUND:Subjects with panic disorder are nearly 4 times as likely to attempt suicide as compared to subjects without this condition. METHODS:We searched the literature from Jan 1, 1960 to May, 4, 2019. Articles that reported a dichotomous sample of patients with panic disorder with and without suicidal behavior were included. OUTCOMES:Twelve studies with 1958 participants were included. Comorbid depression (k = 3, ES = 4.47 [2.63; 7.60]), depressive symptoms (k = 2, ES = 1.98 [1.26; 3.11]), older age (k = 3, ES = 1.66 [1.32; 2.10]), younger age of panic disorder onset (k = 2, ES = 0.65 [0.45; 0.94]), and history of alcohol dependence (k = 2, ES = 8.70 [1.20; 63.04]) were associated with suicide attempt in panic disorder. Depressive symptoms (k = 2, ES = 2.29 (1.60; 3.37]), anxiety symptoms (k = 2, ES = 1.90 [1.33; 2.69]), longer illness duration (k = 2, ES = 3.31 [1.90; 5.74]), comorbid depressive disorder (k = 4, ES = 3.88 [2.03; 7.41]), agoraphobia (k = 2, ES = 4.60 [1.47; 14.42]) and younger age of onset (k = 2, ES = 0.60 [0.38; 0.96]) were associated with suicidal ideation in panic disorder. INTERPRETATION:Our findings provide a framework for the development of suicide prevention strategies in this population.

OBJECTIVE Although a reduction in brain-derived neurotrophic factor (BDNF) has been implicated as a cause of cognitive impairment in type 2 diabetes mellitus (T2DM), the role of sex in moderating this effect has not been explored. METHODS We compared the difference in serum BDNF and performance on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) between 96 men and 134 women with T2DM. We compared this to the difference in serum BDNF and performance in the control group (104 men, 144 women). RESULTS Patients with T2DM performed worse on most RBANS indices (Eta=0.372; all p<0.05); within T2DM patients, men performed worse than women on the delayed memory score (74.1±12.1 vs. 79.9±11.5; p=0.002) and on the total score (71.4±11.5 vs. 76.5±10.8, p=0.025). Serum BDNF was lower in patients with T2DM vs. controls (7.5±2.7 ng/ml vs. 11.5±2.7 ng/ml: p<.001), and in males compared to females (6.9±2.4 vs. 7.9±2.8; p=0.024). Serum BDNF levels positively correlated with delayed memory score in patients with T2DM (β=0.19; p=0.007). However, this association was only observed in women, not in men (p interaction=0.04). Among healthy controls, no sex differences were noted in either RBANS or BDNF levels (Eta=0.04; Cohen's d<0.163; all p>0.05). CONCLUSIONS Our results show sex differences in poorer cognitive performance, lower BDNF concentration and their relationship in T2DM patients, suggesting that female sex may be a protective factor for cognitive decline in T2DM patients. However, the findings could only be regarded preliminary because of the cross-sectional design and chronicity of the diabetes.

Post-traumatic stress disorder (PTSD) has a lifetime prevalence of 10–12% in women and 5–6% in men. Patients with PTSD are at greater risk for obesity, type 2 diabetes mellitus, atherosclerosis, and myocardial infarction. In addition, a subset of these patients develops cognitive impairments unattributable to age or disease comorbidity alone, with hippocampal and prefrontal cortex atrophy. This chapter aims to review the evidence for neuroprogression in PTSD. This concept has been proposed as the pathological rewiring of the brain that takes place in parallel with the clinical and neurocognitive deterioration in the course of some psychiatric disorders. We will also review the biological pathways underlying neuroprogression in PTSD, including changes in inflammatory cytokines, corticosteroids, neurotrophins, and oxidative stress markers.

The paraventricular hypothalamus (PVH) regulates stress, feeding behaviors and other homeostatic processes, but whether PVH also drives defensive states remains unknown. Here we showed that photostimulation of PVH neurons in mice elicited escape jumping, a typical defensive behavior. We mapped PVH outputs that densely terminate in the ventral midbrain area, and found that activation of the PVH -> ventral midbrain (vMB) circuit produced profound defensive behavioral changes, including escape jumping, hiding, hyperlocomotion, and learned aversion. Electrophysiological recordings showed excitatory post-synaptic input onto ventral midbrain neurons via PVH fiber activation, and in vivo studies demonstrated that glutamate transmission from PVH -> vMB was required for the evoked behavioral responses. Photostimulation of PVH -> vMB fibers induced cFos expression mainly in non-dopaminergic neurons. Using a dual optogenetic-chemogenetic strategy, we further revealed that escape jumping and hiding were partially contributed by the activation of midbrain glutamatergic neurons. Taken together, our work unveils a hypothalamic-vMB circuit that encodes defensive properties, which may be implicated in normal stress-induced defensive responses.

ObjectiveTo identify factors associated with a history of suicide attempt in medical students.MethodsA Web‐based survey was sent out to a sample of medical students. A multi‐predictor Poisson regression was performed to identify factors associated with a history of suicide attempt. In addition, an elastic net regularization was used to build a risk calculator to identify students at risk for attempted suicide.ResultsA total of 4,840 participants were included in the study. Prevalence of suicide attempts in the sample was 8.94%. Risk factors associated with past suicide attempt in the multi‐predictor Poisson regression were as follows: female gender (P < 0.001); homosexuality (P < 0.001); low income (P = 0.026); bullying by university peers (P = 0.006); childhood (P = 0.001) or adult (P = 0.001) trauma; family history of suicide (P = 0.005); suicidal ideation within the last month (P < 0.001); daily tobacco use (P = 0.037); and being at severe risk for alcohol abuse (P = 0.023). Our elastic net model performed well with an AUC of 0.83.ConclusionsThis study identifies a number of key factors associated with a history of suicide attempts among medical students. Future longitudinal studies should assess the causal relationship between these factors and suicide attempts. Additionally, these results demonstrate that current available data on suicide attempts among medical students can be used to develop an accurate risk algorithm.

Animals must consider competing information before deciding to eat: internal signals indicating the desirability of food and external signals indicating the risk involved in eating within a particular environment. The behaviors driven by the former are manifestations of hunger, and the latter, anxiety. The connection between pathologic anxiety and reduced eating in conditions like typical depression and anorexia is well known. Conversely, anti-anxiety drugs such as benzodiazepines increase appetite. Here, we show that GABAergic neurons in the diagonal band of Broca (DBBGABA) are responsive to indications of risk and receive monosynaptic inhibitory input from lateral hypothalamus GABAergic neurons (LHGABA). Activation of this circuit reduces anxiety and causes indiscriminate feeding. We also found that diazepam rapidly reduces DBBGABA activity while inducing indiscriminate feeding. Our study reveals that the LHGABA→DBBGABA neurocircuit overrides anxiogenic environmental cues to allow feeding and that this pathway may underlie the link between eating and anxiety-related disorders.

Feeding is known to be profoundly affected by stress-related emotional states and eating disorders are comorbid with psychiatric symptoms and altered emotional responses. The neural basis underlying feeding regulation by stress-related emotional changes is poorly understood. Here, we identify a novel projection from the paraventricular hypothalamus (PVH) to the ventral lateral septum (LSv) that shows a scalable regulation on feeding and behavioral changes related to emotion. Weak photostimulation of glutamatergic PVH→LSv terminals elicits stress-related self-grooming and strong photostimulation causes fear-related escape jumping associated with respective weak and strong inhibition on feeding. In contrast, inhibition of glutamatergic inputs to LSv increases feeding with signs of reduced anxiety. LSv-projecting neurons are concentrated in rostral PVH. LSv and LSv-projecting PVH neurons are activated by stressors in vivo, whereas feeding bouts were associated with reduced activity of these neurons. Thus, PVH→LSv neurotransmission underlies dynamic feeding by orchestrating emotional states, providing a novel neural circuit substrate underlying comorbidity between eating abnormalities and psychiatric disorders.

Recent compelling research has demonstrated a pathophysiologic role for proinflammatory cytokines of microglial origin in decreasing neurocognitive function. Psychiatric diseases are already known to have reduced cognitive function and are also associated with increased inflammation. To elaborate on these data, our study aims to investigate how a particular polymorphism of the tumor necrosis factor gene, TNF-α -1031T/C, affects neurocognitive performance in patients with schizophrenia. We recruited 905 patients with schizophrenia and 571 healthy control subjects. We employed the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) to test for neurocognitive function and the positive and negative syndrome scale to evaluate schizophrenia severity. The -1031T/C polymorphism was genotyped in both healthy controls and schizophrenic patients. Our results demonstrate that patients with the C allele (either T/C or C/C) possessed increased immediate memory index, visuospatial/constructional index, and RBANS total scores as compared to patients without it (p < .05). In healthy controls, there was no significant difference across genotypes (p > .05). Our findings demonstrate that the TNF-α -1031T/C polymorphism may not play a role in the susceptibility of schizophrenia itself, but may be involved in the cognitive deficits of schizophrenia. This suggests an important role for cytokine signaling in mediating the severity of cognitive dysfunction in schizophrenia.

The lifetime risk of suicide and suicide attempt in patients with schizophrenia are 5% and 25%-50%, respectively. The current meta-analysis aims to determine risk factors associated with suicidality in subjects with schizophrenia. We searched Pubmed, Web of Science, EMBASE, and the reference lists of included studies. Inclusion criteria were met if an article reported a dichotomous sample of patients with schizophrenia with suicidal ideation, attempted suicide, or suicide compared to patients without. We also performed a cohort study meta-analysis as a supplemental analysis. A total of 96 studies with 80 488 participants were included in our analysis. Depressive symptoms (P<.0001), Positive and Negative Symptom Scale (PANSS) general score (P<.0001) and number of psychiatric hospitalizations (P<.0001) were higher in patients with suicide ideation. History of alcohol use (P=.0001), family history of psychiatric illness (P<.0001), physical comorbidity (P<.0001), history of depression (P<.0001), family history of suicide (P<.0001), history of drug use (P=.0024), history of tobacco use (P=.0034), being white (P=.0022), and depressive symptoms (P<.0001) were the most consistent variables associated with suicide attempts. The first two were also significant in the cohort meta-analysis. Being male (P=.0005), history of attempted suicide (P<.0001), younger age (P=.0266), higher intelligence quotient (P<.0001), poor adherence to treatment (P<.0001), and hopelessness (P<.0001) were the most consistently associated with suicide. The first three were also significant in the cohort meta-analysis. Our findings may help with future development of preventive strategies to combat suicide. Future studies may combine the above-mentioned variables by using multivariate predictive analysis techniques to objectively stratify suicidality in schizophrenia.