Effect of γ-tACS on prefrontal hemodynamics in bipolar disorder: A functional near-infrared study.

OBJECTIVES: Transcranial alternating current stimulation (tACS) is a potential therapeutic psychiatric tool that has been shown to modulate clinical symptoms and brain function by inducing brain oscillations. However, direct evidence on the effects of gamma-tACS (γ-tACS) on Bipolar I Disorder (BD-I) is limited. In the present study we used functional near-infrared spectroscopy to explore prefrontal hemodynamic changes in BD-I patients receiving combined γ-tACS intervention in addition to pharmacological treatment. METHODS: Only 39 male patients with BD-I in the acute manic phase were included, and they were randomly divided into an intervention group (n = 18) and a control group (n = 21). The intervention group received γ-tACS treatment on a weekday for a total of 10 sessions in the right prefrontal cortex and left prefrontal cortex. All participants were pretested (baseline) and posttested (2 weeks after) with questionnaires to assess clinical symptoms and cognitive abilities, and with functional near infrared spectroscopy (fNIRS) to assess spontaneous cortical hemodynamic activities. RESULTS: Compared to the control group, the intervention group had greater increases in Montreal Cognitive Assessment (MoCA) scores, and greater decreases in Bech-Rafaelsen Mania Rating Scale (BRMS) scores. In the intervention group, functional connectivity (FC) was significantly greater in the left hemisphere. γ-tACS treatment resulted in a left hemispheric lateralization effect of resting state FC in BD-I patients, increasing the hemodynamic activity of the patient's left prefrontal cortex. CONCLUSIONS: γ-tACS can improve cognitive impairment and mood symptoms with BD-I patients in an acute manic episode by enhancing FC in the patients' left prefrontal cortex.

Relationship between Cholesterol-Related Lipids and Severe Acute Pancreatitis: From Bench to Bedside.

It is well known that hypercholesterolemia in the body has pro-inflammatory effects through the formation of inflammasomes and augmentation of TLR (Toll-like receptor) signaling, which gives rise to cardiovascular disease and neurodegenerative diseases. However, the interaction between cholesterol-related lipids and acute pancreatitis (AP) has not yet been summarized before. This hinders the consensus on the existence and clinical importance of cholesterol-associated AP. This review focuses on the possible interaction between AP and cholesterol-related lipids, which include total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein (Apo) A1, from the bench to the bedside. With a higher serum level of total cholesterol, LDL-C is associated with the severity of AP, while the persistent inflammation of AP is allied with a decrease in serum levels of cholesterol-related lipids. Therefore, an interaction between cholesterol-related lipids and AP is postulated. Cholesterol-related lipids should be recommended as risk factors and early predictors for measuring the severity of AP. Cholesterol-lowering drugs may play a role in the treatment and prevention of AP with hypercholesterolemia.

Damage associated molecular patterns and neutrophil extracellular traps in acute pancreatitis.

Previous researches have emphasized a trypsin-centered theory of acute pancreatitis (AP) for more than a century. With additional studies into the pathogenesis of AP, new mechanisms have been explored. Among them, the role of immune response bears great importance. Pro-inflammatory substances, especially damage-associated molecular patterns (DAMPs), play an essential role in activating, signaling, and steering inflammation. Meanwhile, activated neutrophils attach great importance to the immune defense by forming neutrophil extracellular traps (NETs), which cause ductal obstruction, premature trypsinogen activation, and modulate inflammation. In this review, we discuss the latest advances in understanding the pathological role of DAMPs and NETs in AP and shed light on the flexible crosstalk between these vital inflammatory mediators. We, then highlight the potentially promising treatment for AP targeting DAMPs and NETs, with a focus on novel insights into the mechanism, diagnosis, and management of AP.

Usefulness of Random Forest Algorithm in Predicting Severe Acute Pancreatitis.

Background and Aims: This study aimed to develop an interpretable random forest model for predicting severe acute pancreatitis (SAP). Methods: Clinical and laboratory data of 648 patients with acute pancreatitis were retrospectively reviewed and randomly assigned to the training set and test set in a 3:1 ratio. Univariate analysis was used to select candidate predictors for the SAP. Random forest (RF) and logistic regression (LR) models were developed on the training sample. The prediction models were then applied to the test sample. The performance of the risk models was measured by calculating the area under the receiver operating characteristic (ROC) curves (AUC) and area under precision recall curve. We provide visualized interpretation by using local interpretable model-agnostic explanations (LIME). Results: The LR model was developed to predict SAP as the following function: -1.10-0.13×albumin (g/L) + 0.016 × serum creatinine (µmol/L) + 0.14 × glucose (mmol/L) + 1.63 × pleural effusion (0/1)(No/Yes). The coefficients of this formula were utilized to build a nomogram. The RF model consists of 16 variables identified by univariate analysis. It was developed and validated by a tenfold cross-validation on the training sample. Variables importance analysis suggested that blood urea nitrogen, serum creatinine, albumin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, calcium, and glucose were the most important seven predictors of SAP. The AUCs of RF model in tenfold cross-validation of the training set and the test set was 0.89 and 0.96, respectively. Both the area under precision recall curve and the diagnostic accuracy of the RF model were higher than that of both the LR model and the BISAP score. LIME plots were used to explain individualized prediction of the RF model. Conclusions: An interpretable RF model exhibited the highest discriminatory performance in predicting SAP. Interpretation with LIME plots could be useful for individualized prediction in a clinical setting. A nomogram consisting of albumin, serum creatinine, glucose, and pleural effusion was useful for prediction of SAP.

A Comparison of XGBoost, Random Forest, and Nomograph for the Prediction of Disease Severity in Patients With COVID-19 Pneumonia: Implications of Cytokine and Immune Cell Profile.

Background and Aims: The aim of this study was to apply machine learning models and a nomogram to differentiate critically ill from non-critically ill COVID-19 pneumonia patients. Methods: Clinical symptoms and signs, laboratory parameters, cytokine profile, and immune cellular data of 63 COVID-19 pneumonia patients were retrospectively reviewed. Outcomes were followed up until Mar 12, 2020. A logistic regression function (LR model), Random Forest, and XGBoost models were developed. The performance of these models was measured by area under receiver operating characteristic curve (AUC) analysis. Results: Univariate analysis revealed that there was a difference between critically and non-critically ill patients with respect to levels of interleukin-6, interleukin-10, T cells, CD4+ T, and CD8+ T cells. Interleukin-10 with an AUC of 0.86 was most useful predictor of critically ill patients with COVID-19 pneumonia. Ten variables (respiratory rate, neutrophil counts, aspartate transaminase, albumin, serum procalcitonin, D-dimer and B-type natriuretic peptide, CD4+ T cells, interleukin-6 and interleukin-10) were used as candidate predictors for LR model, Random Forest (RF) and XGBoost model application. The coefficients from LR model were utilized to build a nomogram. RF and XGBoost methods suggested that Interleukin-10 and interleukin-6 were the most important variables for severity of illness prediction. The mean AUC for LR, RF, and XGBoost model were 0.91, 0.89, and 0.93 respectively (in two-fold cross-validation). Individualized prediction by XGBoost model was explained by local interpretable model-agnostic explanations (LIME) plot. Conclusions: XGBoost exhibited the highest discriminatory performance for prediction of critically ill patients with COVID-19 pneumonia. It is inferred that the nomogram and visualized interpretation with LIME plot could be useful in the clinical setting. Additionally, interleukin-10 could serve as a useful predictor of critically ill patients with COVID-19 pneumonia.

Functional and structural alterations in the pain-related circuit in major depressive disorder induced by electroconvulsive therapy.

Approximately two-thirds of major depressive disorder (MDD) patients have pain, which exacerbates the severity of depression. Electroconvulsive therapy (ECT) is an efficacious treatment that can alleviate depressive symptoms; however, treatment for pain and the underlying neural substrate is elusive. We enrolled 34 patients with MDD and 33 matched healthy controls to complete clinical assessments and neuroimaging scans. MDD patients underwent second assessments and scans after ECT. We defined a pain-related network with a published meta-analysis and calculated topological patterns to reveal topologic alterations induced by ECT. Using the amplitude of low-frequency fluctuations (ALFFs), we probed local function aberrations of pain-related circuits in MDD patients. Subsequently, we applied gray matter volume (GMV) to reveal structural alterations of ECT relieving pain. The relationships between functional and structural aberrations and pain were determined. ECT significantly alleviated pain. The neural mechanism based on pain-related circuits indicated that ECT weakened the circuit function (ALFF: left amygdala and right supplementary motor area), while augmenting the structure (GMV: bilateral amygdala/insula/hippocampus and anterior cingulate cortex). The topologic patterns became less efficient after ECT. Correlation analysis between the change in pain and GMV had negative results in bilateral amygdala/insula/hippocampus. Similarity, there was a positive correlation between a change in ALFF in the left amygdala and improved clinical symptoms. ECT improved pain by decreasing brain local function and global network patterns, while increasing structure in pain-related circuits. Functional and structural alterations were associated with improvement in pain.

Increased delayed reward during intertemporal decision-making in schizophrenic patients and their unaffected siblings.

Intertemporal choices are decisions with consequences in multiple time periods and constitute a significant part of social cognition. The shared neuropathological characteristics of patients with schizophrenia and their siblings might express intermediate phenotypes in behavior that could be used to further characterize the illness. Schizophrenic patients, unaffected siblings, and healthy controls underwent a computerized version of the "Intertemporal Choice Task". All participants could choose between sooner-smaller (SS) and later-larger (LL) options in now-trials and in not-now-trials. Subjects also underwent a battery of cognitive neuropsychological assessment. Our results indicated that schizophrenic patients and unaffected siblings both had a tendency to choose LL options in now-trials or not-now-trials compared to healthy controls. Schizophrenic patients had significantly lower scores in several cognitive tasks, including MoCA, attention, executive functions, and information processing when compared with the other two groups. Moreover, within the schizophrenic patient group, significant correlations were found between intertemporal decision-making performance and executive function. The present study showed that both schizophrenic patients and unaffected siblings preferred to choose larger-delayed rewards during intertemporal decision-making, which may result from frontal-striatal and frontal-parietal network dysfunction. Their intertemporal decision-making performance was associated with executive function performance.

Deficit of supramodal executive control of attention in schizophrenia.

Although a deficit in executive control of attention is one of the hallmarks in schizophrenia that has significant impact on everyday functioning due to its relationship with thought processing, whether this deficit occurs across modalities, i.e., is supramodal, remains unclear. To investigate the supramodal mechanism in SZ, we examined cross-modal correlations between visual and auditory executive control of attention in a group of patients with schizophrenia (SZ, n = 55) compared to neurotypical controls (NC, n = 55). While the executive control effects were significantly correlated between the two modalities in the NC group, these effects were not correlated in the SZ group, with a significant group difference in the correlation. Further, the inconsistency and magnitude of the cross-modal executive control effects were significantly larger in the SZ group compared to the NC group. Together, these results suggest that there is a disruption of a common supramodal executive control mechanism in patients with schizophrenia, which may be related to the thought processing disorder characterizing the disorder.

Dissociation between visual line bisection and mental number line bisection in schizophrenia.

Many studies of hemispatial neglect patients have indicated that spatial attention processes operate similarly in visual space and number space. However, some studies have indicated a dissociation of processing between visual line bisection and mental number bisection. A number of investigations have suggested that schizophrenic patients show a mild right pseudo-neglect on visual line bisection tasks. The present study was designed to determine if a functional link exists between performance of visual line and number line bisection in schizophrenic patients. Groups of 40 schizophrenic patients and 40 controls performed each bisection task. In the visual line bisection task, schizophrenic patients showed a significant leftward bias relative to the healthy controls for 9 different line lengths. No significant difference in bias was found between the 2 groups on the mental line bisection task. These results indicated that schizophrenic patients may exhibit attention deficit with respect to visual space but not number space, suggestive of the dissociation of processing between visual line bisection and mental number line bisection. These results provide more insight into the correlation between the visual line and number bisection tasks in schizophrenic patients.