Application of machine learning for risky sexual behavior interventions among factory workers in China.

Introduction: Assessing the likelihood of engaging in high-risk sexual behavior can assist in delivering tailored educational interventions. The objective of this study was to identify the most effective algorithm and assess high-risk sexual behaviors within the last six months through the utilization of machine-learning models. Methods: The survey conducted in the Longhua District CDC, Shenzhen, involved 2023 participants who were employees of 16 different factories. The data was collected through questionnaires administered between October 2019 and November 2019. We evaluated the model's overall predictive classification performance using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. All analyses were performed using the open-source Python version 3.9.12. Results: About a quarter of the factory workers had engaged in risky sexual behavior in the past 6 months. Most of them were Han Chinese (84.53%), hukou in foreign provinces (85.12%), or rural areas (83.19%), with junior high school education (55.37%), personal monthly income between RMB3,000 (US$417.54) and RMB4,999 (US$695.76; 64.71%), and were workers (80.67%). The random forest model (RF) outperformed all other models in assessing risky sexual behavior in the past 6 months and provided acceptable performance (accuracy 78%; sensitivity 11%; specificity 98%; PPV 63%; ROC 84%). Discussion: Machine learning has aided in evaluating risky sexual behavior within the last six months. Our assessment models can be integrated into government or public health departments to guide sexual health promotion and follow-up services.

The Western and Chinese exercise training for blood pressure reduction among hypertensive patients: An overview of systematic reviews.

Hypertension remains the world's leading cause of premature death. Interventions such as exercise, diet modification, and pharmacological therapy remain the mainstay of hypertension treatment. Numerous systematic reviews and meta-analyses demonstrated the effectiveness of western exercises, such as aerobic exercise and resistance exercise, in reducing blood pressure in hypertensive patients. There is recently emerging evidence of blood pressure reduction with Chinese exercises, such as Tai Chi, Baduanjin, and Qigong. The current overview of systematic reviews aims to evaluate the quality and descriptively summarize the evidence for the effectiveness of western and Chinese exercises for hypertension management. Thirty-nine systematic reviews were included in this overview, with 15 of those being on Chinese exercise. Evidence suggests that exercise training, regardless of Western or Chinese exercise, generally reduced both systolic and diastolic blood pressure. High-intensity intermittent training did not further reduce blood pressure when compared to moderate-intensity continuous training. Conflicting results on the effectiveness of blood pressure reduction when comparing Chinese and Western exercise training were observed. This suggests the comparable effectiveness of Chinese exercise training, in particularly Tai Chi, to general or aerobic exercise training in terms of blood pressure reduction. The Chinese exercise modality and intensity may be more suitable for the middle-aged and elderly population.

Pain avoidance and functional connectivity between insula and amygdala identifies suicidal attempters in patients with major depressive disorder using machine learning.

Pain avoidance can effectively classify suicide attempters from non-attempters among patients with major depressive disorder (MDD). However, the neural circuits underlying pain processing in suicide attempters have not been described comprehensively. In Study 1, we recruited MDD patients with a history of suicide attempts (MDD-SA), and those without (MDD-NSA) to examine the patterns of psychological pain using the latent profile analysis. Further, in Study 2, participants including the MDD-SA, MDD-NSA, and healthy controls underwent resting-state functional magnetic resonance imaging. We used machine learning that included features of gray matter volume (GMV), the functional connectivity (FC) brain patterns of the region of interest, and behavioral data to identify suicide attempters. The results identified three latent classes of psychological pain in MDD patients: the low pain class (18.9%), the painful feeling class (37.2%), and the pain avoidance class (43.9%). Furthermore, the proportion of suicide attempters with high pain avoidance was the highest. The accuracy of multimodality classifiers (63%-92%) was significantly higher than that of brain-only classifiers (56%-85%) and behavior-only classifiers (64%-73%). Pain avoidance ranked first in the optimal feature set of the suicide attempt classification model. The crucial brain imaging features were FC between the left amygdala and right insula, right orbitofrontal and left thalamus, left anterior cingulate cortex and left insula, right orbitofrontal, amygdala, and the GMV of right thalamus. Additionally, the optimal feature set, including pain avoidance and crucial brain patterns of psychological pain neural circuits, was provided for the identification of suicide attempters.

The characterization of static and dynamic brain functional networks in suicide attempters with major depressive disorder and its relation to psychological pain.

Psychological pain is a robust predictor of suicide attempts in patients with major depressive disorder (MDD). However, whether suicide and psychological pain share a common neural basis remains unclear. Patients with MDD (n = 64) and healthy controls (HC) (n = 35) were recruited and patients were allocated to two groups: those with a history of suicide attempts (MDD-SA) (n = 25) and those without such a history (MDD-NSA) (n = 39). All participants completed the measurements and underwent functional magnetic resonance imaging to investigate the resting-state static and dynamic brain functional networks in default mode (DMN), central executive (CEN), salience (SN), and basal ganglia (BGN) networks. The MDD-SA group scored higher in pain avoidance than the MDD-NSA and HC groups. Functional connectivity within the dorsal DMN in the MDD-SA group was greater than that in the MDD-NSA and HC groups, and was significantly correlated with pain avoidance and suicide attempts. Dynamic functional connectivity analysis revealed that the proportion of State I in the fraction windows in the MDD-SA group was higher than those in the MDD-NSA and HC groups. Therefore, the increased functional connectivity within the dorsal DMN and segregation of networks may represent potential biological markers for suicide attempts related to psychological pain processing.

Biomineralization and biotechnological applications of bacterial magnetosomes.

Magnetosomes intracellularly biomineralized by Magnetotactic bacteria (MTB) are membrane-enveloped nanoparticles of the magnetic minerals magnetite (Fe3O4) or greigite (Fe3S4). MTB thrive in oxic-anoxic interface and exhibit magnetotaxis due to the presence of magnetosomes. Because of the unique characteristic and bionavigation inspiration of magnetosomes, MTB has been a subject of study focused on by biologists, medical pharmacologists, geologists, and physicists since the discovery. We herein first briefly review the features of MTB and magnetosomes. The recent insights into the process and mechanism for magnetosome biomineralization including iron uptake, magnetosome membrane invagination, iron mineralization and magnetosome chain assembly are summarized in detail. Additionally, the current research progress in biotechnological applications of magnetosomes is also elucidated, such as drug delivery, MRI image contrast, magnetic hyperthermia, wastewater treatment, and cell separation. This review would expand our understanding of biomineralization and biotechnological applications of bacterial magnetosomes.

Nitric Oxide Synthase Type 1 Methylation Is Associated With White Matter Microstructure in the Corpus Callosum and Greater Panic Disorder Severity Among Panic Disorder Patients.

Objectives: Methylation of the neuronal nitric oxide synthase (NOS1/nNOS) gene has recently been identified as a promising biomarker of psychiatric disorders. NOS1 plays an essential role in neurite outgrowth and may thus affect the microstructure development of white matter (WM) in the corpus callosum (CC), which is known to be altered in panic disorder (PD). We examined the relationship between NOS1 methylation, WM tracts in the CC, and symptoms based on this finding. Methods: Thirty-two patients with PD and 22 healthy controls (HCs) were recruited after age, gender, and the education level were matched. The cell type used was whole-blood DNA, and DNA methylation of NOS1 was measured at 20 CpG sites in the promoter region. Although 25 patients with PD were assessed with the Panic Disorder Severity Scale (PDSS), diffusion tensor imaging (DTI) scans were only collected from 16 participants with PD. Results: We observed that the PD group showed lower methylation than did the HCs group and positive correlations between the symptom severity of PD and methylation at CpG4 and CpG9. In addition, CpG9 methylation was significantly correlated with the fractional anisotropy (FA) and mean diffusivity (MD) values of the CC and its major components (the genu and the splenium) in the PD group. Furthermore, path analyses showed that CpG9 methylation offers a mediating effect for the association between the MD values of the genu of the CC and PD symptom severity (95% CI = -1.731 to -0.034). Conclusions: The results suggest that CpG9 methylation leads to atypical development of the genu of the CC, resulting in higher PD symptom severity, adding support for the methylation of NOS1 as a future prognostic indicator of PD.

Resting-state causal connectivity of the bed nucleus of the stria terminalis in panic disorder.

Panic disorder (PD) is associated with anticipatory anxiety, a sustained threat response that appears to be related to the bed nucleus of the stria terminalis (BNST). Individuals with panic disorder may demonstrate significant differences in causal connectivity of the BNST in comparison to healthy controls. To test this hypothesis, resting-state functional magnetic resonance imaging (fMRI) was used to identify aberrant causal connectivity of the BNST in PD patients. 19 PD patients and 18 healthy controls (HC) matched for gender, age and education were included. Granger causality analysis (GCA) utilizing the BNST as a seed region was used to investigate changes in directional connectivity. Relative to healthy controls, PD patients displayed abnormal directional connectivity of the BNST including enhanced causal connectivity between the left parahippocampal gyrus and left BNST, the right insula and the right BNST, the left BNST and the right dorsolateral prefrontal cortex (dlPFC) and right BNST to the left and right dlPFC. Furthermore, PD patients displayed weakened causal connectivity between the right dlPFC and the left BNST, the left dlPFC and the right BNST, the left BNST and the left dorsomedial prefrontal cortex (dmPFC), right insula, right fusiform, and right BNST to the right insula. The results suggest that PD strongly correlates with increased causal connectivity between emotional processing regions and the BNST and enhanced causal connectivity between the BNST and cognitive control regions.

The alteration of cognitive function networks in remitted patients with major depressive disorder: an independent component analysis.

INTRODUCTION: Dysfunctional connectivity of resting-state functional networks has been observed in patients with major depressive disorder (MDD), particularly in cognitive function networks including the central executive network (CEN), default mode network (DMN) and salience network (SN). Findings from studies examining how aberrant functional connectivity (FC) changed after antidepressant treatment, however, have been inconsistent. Thus, the purpose of the present study was to explore potential mechanisms of altered cognitive function networks during resting-state between remitted major depressive disorder (rMDD) patients and healthy controls (HCs) and furthermore, the relationship between dysfunctional connectivity patterns in rMDD and clinical symptoms. METHODOLOGY: In this study, 19 HCs and 19 rMDD patients were recruited for resting-state functional magnetic resonance imaging (fMRI) scanning. FC was evaluated with independent component analysis for CEN, DMN and SN. Two sample t tests were conducted to compare differences between rMDD and HCs. A Pearson correlation analysis was also performed to examine the relationship between connectivity of networks and cognitive function scores and clinical symptoms. RESULTS: Compared to healthy controls, remitted patients showed lower connectivity in CEN, mostly in the superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior parietal lobule (IPL) and part of the supramarginal gyrus (SMG). Conversely, the bilateral insula, part of the SMG (a key node of the CEN) and dorsal anterior cingulate cortex (dACC) of the DMN showed higher connectivity in rMDD patients. Pearson correlation results demonstrated that connectivity of the right IPL in CEN was positively correlated with cognitive function scores, and connectivity of the left insula was negatively correlated with BDI scores. CONCLUSIONS: Though rMDD patients reached the standard of clinal remission, unique impairments of FC in cognitive function networks remained. Aberrant FC between cognitive function networks responsible for executive control was observed in rMDD and may be associated with residual clinical symptoms.