Identification of RNA­dependent liquid­liquid phase separation proteins using an artificial intelligence strategy.

RNA-dependent liquid-liquid phase separation (LLPS) proteins play critical roles in cellular processes such as stress granule formation, DNA repair, RNA metabolism, germ cell development, and protein translation regulation. The abnormal behavior of these proteins is associated with various diseases, particularly neurodegenerative disorders like amyotrophic lateral sclerosis and frontotemporal dementia, making their identification crucial. However, conventional biochemistry-based methods for identifying these proteins are time-consuming and costly. Addressing this challenge, our study developed a robust computational model for their identification. We constructed a comprehensive dataset containing 137 RNA-dependent and 606 non-RNA-dependent LLPS protein sequences, which were then encoded using amino acid composition, composition of K-spaced amino acid pairs, Geary autocorrelation, and conjoined triad methods. Through a combination of correlation analysis, mutual information scoring, and incremental feature selection, we identified an optimal feature subset. This subset was used to train a random forest model, which achieved an accuracy of 90% when tested against an independent dataset. This study demonstrates the potential of computational methods as efficient alternatives for the identification of RNA-dependent LLPS proteins. To enhance the accessibility of the model, a user-centric web server has been established and can be accessed via the link: http://rpp.lin-group.cn.

Network Analysis of Depressive Symptoms in Chinese Sexual Minority Women During the COVID-19 Pandemic: An Intra-Group Perspective.

The prevalence of depression among sexual minority women is a significant concern, yet no prior research has conducted a network analysis of depressive symptoms in this population. This is the first study to address this gap by examining the network structure of depressive symptoms in Chinese sexual minority women during the COVID-19 pandemic, considering both sexual orientation and gender expression as part of an intra-group perspective. 1420 Chinese sexual minority women completed the Center for Epidemiologic Studies Depressive Symptoms (CES-D). Network analysis was employed to calculate edge and centrality measures, and the network structures of lesbians and bisexual women were compared based on sexual orientation and of femme, androgyny, and butch based on gender expression. Network analysis revealed that the core depressive symptoms of Chinese sexual minority women are "Felt depressed," "Fatigue," "Sad," and "Failure." Although no significant differences were found in the network structure and global strength of depressive symptoms between different sexual orientations and gender expressions, there were significant differences in the core symptoms. This study suggests the unique associations between depressive symptoms and social and historical contexts among sexual minority women and emphasizes the importance of considering these differences when providing targeted mental health interventions.

Small Intestinal Endocrine Cell Derived Exosomal ACE2 Protects Islet ß-Cell Function by Inhibiting the Activation of NLRP3 Inflammasome and Reducing ß-Cell Pyroptosis.

Background: The "gut-islets axis" is an important endocrine signaling axis that regulates islets function by modulating the gut microbiota and endocrine metabolism within the gut. However, the specific mechanisms and roles of the intestine in islets regulation remain unclear. Recent studies investigated that exosomes derived from gut microbiota can transport signals to remotely regulate islets ß-cell function, suggesting the possibility of novel signaling pathways mediated by gut exosomes in the regulation of the "gut-islet axis.". Methods: The exosomes were isolated from the intestinal enteroendocrine cell-line STC-1cells culture supernatants treated with palmitate acid (PA) or BSA. Metabolic stress models were established by separately subjecting MIN6 cells to PA stimulation and feeding mice with a high-fat diet. Intervention with exosomes in vitro and in vivo to assess the biological effects of exosomes on islets ß cells under metabolic stress. The Mas receptor antagonist A779 and ACE2ko mice were used to evaluate the role of exosomal ACE2. Results: We found ACE2, a molecule that plays a crucial role in the regulation of islets function, is abundantly expressed in exosomes derived from STC-1 under physiological normal condition (NCEO). These exosomes cannot only be taken up by ß-cells in vitro but also selectively transported to the islets in vivo. Following intervention with NCEXO, both Min6 cells in a lipotoxic environment and mice on a high-fat diet exhibited significant improvements in islets ß-cell function and ß-cell mass. Further investigations demonstrated that these protective effects are attributed to exosomal ACE2, as ACE2 inhibits NLRP3 inflammasome activation and reduces ß-cell pyroptosis. Conclusion: ACE2-enriched exosomes from the gut can selectively target islets, subsequently inhibiting NLRP3 inflammasome activation and ß cell pyroptosis, thereby restoring islets ß cell function under metabolic stress. This study provides novel insights into therapeutic strategies for the prevention and treatment of obesity and diabetes.

Adult obesity treatment and prevention: A trans-agency commentary on the research landscape, gaps, and future opportunities.

Given the high and growing prevalence of obesity among adults in the United States, obesity treatment and prevention are important topics in biomedical and public health research. Although researchers recognize the significance of this problem, much remains unknown about safe and effective prevention and treatment of obesity in adults. In response to the worsening obesity epidemic and the many unknowns regarding the disease, a group of key scientific and program staff members of the National Institutes of Health (NIH) and other federal and non-government agencies gathered virtually in September 2021 to discuss the current state of obesity research, research gaps, and opportunities for future research in adult obesity prevention and treatment. The current article synthesizes presentations given by attendees and shares their organizations' current initiatives and identified gaps and opportunities. By integrating the information discussed in the meeting and current initiatives, we identify potential targets and overlapping priorities for future research, including health equity and disparities in obesity, the heterogeneity of obesity, and the use of technological and innovative approaches in interventions.

The role of tetrahydrocurcumin in disease prevention and treatment.

In recent decades, natural compounds derived from herbal medicine or dietary sources have played important roles in prevention and treatment of various diseases and have attracted more and more attention. Curcumin, extracted from the Curcumae Longae Rhizoma and widely used as food spice and coloring agent, has been proven to possess high pharmacological value. However, the pharmacological application of curcumin is limited due to its poor systemic bioavailability. As a major active metabolite of curcumin, tetrahydrocurcumin (THC) has higher bioavailability and stability than curcumin. Increasing evidence confirmed that THC had a wide range of biological activities and significant treatment effects on diseases. In this paper, we reviewed the research progress on the biological activities and therapeutic potential of THC on different diseases such as neurological disorders, metabolic syndromes, cancers, and inflammatory diseases. The extensive pharmacological effects of THC involve the modulation of various signaling transduction pathways including MAPK, JAK/STAT, NF-κB, Nrf2, PI3K/Akt/mTOR, AMPK, Wnt/ß-catenin. In addition, the pharmacokinetics, drug combination and toxicology of THC were discussed, thus providing scientific basis for the safe application of THC and the development of its dietary supplements and drugs.

Association between serum vitamin E and bacterial vaginitis in women: a cross-sectional study.

INTRODUCTION: Bacterial vaginitis (BV) is a common vaginal disease. Vitamin E has been shown to reduce BV by enhancing immune function, but no studies have analyzed the relationship between vitamin E and BV at different BMIs and ages. METHOD: This study used 2242 participants from four cycles of NHANES 1999-2006 in American. Participants' vitamin E levels were divided into four groups, and analyses such as study population description, stratified analysis, multiple logistic regression analysis, and curve fitting were performed. To perform data processing, the researchers used the statistical package R (The R Foundation; http://www.r-project.org ; version 3.6.3) and Empower Stats software ( www.empowerstats.net , X&Y solutions, Inc. Boston, Massachusetts). RESULT: The concentrations of serum vitamin E were negatively correlated with the risk of BV, especially when vitamin E were at 1198-5459ug/dL with (OR = -0.443, 95%CI = 0.447-0.923, P = 0.032) or without (OR = -0.521, 95%CI = 0.421-0.837, P = 0.006) adjustment for variables. At the same time, at lower levels, there was no significant association. Vitamin E supplementation may significantly reduce the risk of BV (p < 0.001). In addition, the risk of having BV decreased and then increased with increasing vitamin E concentrations at high BMI levels (p < 0.01). CONCLUSION: Vitamin E at moderate to high concentrations may significantly reduce BV risk, says the study, providing clinical evidence for the prevention and the treatment of BV.

The CD8+ T cell tolerance checkpoint triggers a distinct differentiation state defined by protein translation defects.

Peripheral CD8+ T cell tolerance is a checkpoint in both autoimmune disease and anti-cancer immunity. Despite its importance, the relationship between tolerance-induced states and other CD8+ T cell differentiation states remains unclear. Using flow cytometric phenotyping, single-cell RNA sequencing (scRNA-seq), and chromatin accessibility profiling, we demonstrated that in vivo peripheral tolerance to a self-antigen triggered a fundamentally distinct differentiation state separate from exhaustion, memory, and functional effector cells but analogous to cells defectively primed against tumors. Tolerant cells diverged early and progressively from effector cells, adopting a transcriptionally and epigenetically distinct state within 60 h of antigen encounter. Breaching tolerance required the synergistic actions of strong T cell receptor (TCR) signaling and inflammation, which cooperatively induced gene modules that enhanced protein translation. Weak TCR signaling during bystander infection failed to breach tolerance due to the uncoupling of effector gene expression from protein translation. Thus, tolerance engages a distinct differentiation trajectory enforced by protein translation defects.

Maize grain filling characteristics in China: Response to meteorological factors.

To investigate the dynamic changes in dry matter accumulation in maize after anthesis, we established a logistic model to describe grain filling characteristics (GFC), and analyzed differences between spring and summer maize, and the influence of meteorological factors. The results showed that the logistic model accurately simulated the dynamic changes in grain growth. For spring maize, the fitted hundred-grain weight at maturity was closely related to the average grain filling rate until maturity, days of the active grain filling period, time of the maximum grain filling rate, and duration of the rapid increase in grain weight. For summer maize, it was closely related to the time of the maximum grain filling rate, days of active grain filling period, duration of gradual grain weight, and the rapidly increasing period. The filling characteristics of spring and summer maize differed because of the different meteorological conditions and biological characteristics. The grain filling duration of spring maize was longer than that of summer maize. The maximum grain filling rate of spring maize occurred later than that of summer maize. Temperature and precipitation were the main meteorological factors affecting the hundred-grain weight of spring maize, whereas temperature was the main factor affecting summer maize. The response of spring maize GFC to meteorological factors was more complex than that of summer maize. These results are important for the development of appropriate strategies for improving maize productivity in China.

Wearable Motion Analysis System for Thoracic Spine Mobility With Inertial Sensors.

This study presents a wireless wearable portable system designed for the automatic quantitative spatio-temporal analysis of continuous thoracic spine motion across various planes and degrees of freedom (DOF). This includes automatic motion segmentation, computation of the range of motion (ROM) for six distinct thoracic spine movements across three planes, tracking of motion completion cycles, and visualization of both primary and coupled thoracic spine motions. To validate the system, this study employed an Inter-days experimental setting to conduct experiments involving a total of 957 thoracic spine movements, with participation from two representatives of varying age and gender. The reliability of the proposed system was assessed using the Intraclass Correlation Coefficient (ICC) and Standard Error of Measurement (SEM). The experimental results demonstrated strong ICC values for various thoracic spine movements across different planes, ranging from 0.774 to 0.918, with an average of 0.85. The SEM values ranged from 0.64° to 4.03°, with an average of 1.93°. Additionally, we successfully conducted an assessment of thoracic spine mobility in a stroke rehabilitation patient using the system. This illustrates the feasibility of the system for actively analyzing thoracic spine mobility, offering an effective technological means for non-invasive research on thoracic spine activity during continuous movement states.

Circulating neuropeptide Y as a biomarker in postoperative atrial fibrillation cases administered off-pump coronary bypass Graft surgery.

Background and aims: Postoperative atrial fibrillation (POAF) is considered the most prevalent irregular heart rhythm after heart surgery. The cardiac autonomic nervous system significantly affects POAF, and neuropeptide Y (NPY), an abundant neuropeptide in the cardiovascular system, is involved in this autonomic regulation. The current work aimed to examine the potential association of NPY with POAF in individuals administered isolated off-pump coronary artery bypass grafting. Methods: From January 1 to May 31, 2020, we examined consecutive cases administered successful isolated off-pump coronary artery bypass grafting with no previously diagnosed atrial fibrillation (AF). Clinical characteristics and plasma samples were collected before surgery. NPY was quantified by enzyme-linked immunosorbent assay (ELISA) in peripheral blood, and POAF cases were identified through a 7-day Holter monitoring. Results: Among 120 cases with no previously diagnosed AF, 33 (27.5 %) developed POAF during hospitalization. Median NPY levels were markedly elevated in the POAF group in comparison with the sinus rhythm group (31.72 vs. 27.95, P = 0.014). Multivariable logistic regression analysis revealed age (OR = 1.135, 95%CI 1.054-1.223; P = 0.001), left atrial size (OR = 1.136, 95%CI 1.004-1.285; P = 0.043), and NPY levels in peripheral blood (OR = 1.055, 95%CI 1.002-1.111; p = 0.041) independently predicted POAF. Additionally, NPY levels were positively correlated with high-frequency (HF) (r = 0.2774, P = 0.0022) and low-frequency (LF) (r = 0.2095, P = 0.0217) components of heart rate variability. Conclusion: In summary, this study demonstrates an association between elevated NPY levels in peripheral blood before surgery and POAF occurrence.

Fracture resistance of cement-retained lithium disilicate implant-supported crowns: Effect of material used for two-piece abutments.

PURPOSE: This study compared the fracture strength of single lithium disilicate implant-supported crowns fabricated on two-piece abutments with various materials: ceramic-reinforced PEEK, zirconia, and lithium disilicate. MATERIALS AND METHODS: Thirty-six implants were embedded in acrylic cylinders. A two-piece abutment and a crown were designed following a pre-operation scan for a maxillary left central incisor. The designed crown was used to fabricate 36 lithium disilicate crowns. The designed abutment was used to manufacture 36 abutments from 3 materials, 12 each: (A) zirconia; (B) lithium disilicate; and (C) ceramic-reinforced PEEK. Abutments were surface treated and bonded on the titanium base abutments with resin cement. Then, lithium disilicate crowns were bonded on the assigned abutments. Specimens were then subjected to dynamic loading for 1,200,000 cycles. The fracture strength (N) of the assembly was assessed using a universal testing machine. One-way ANOVA followed by multiple comparison tests was used to evaluate the effect of abutment material on the fracture strength of single implant-supported restorations at a significance of .05. RESULTS: The average fracture strength for the groups with zirconia, PEEK, and lithium disilicate two-piece abutments were 1362N ± 218N, 1235N ± 115N, and 1472N ± 171N, respectively. There was a significant (p < 0.05) difference in fracture strength among the groups. The lithium disilicate group had significantly higher fracture strength (p = 0.0058) than the group with PEEK; however, there was no significant (p > 0.05) difference between the other groups. CONCLUSIONS: Two-piece abutments restored with lithium disilicate crowns investigated in the study have the potential to withstand the average physiological occlusal forces in the anterior region.

Influence of chronotype on pain incidence during early adolescence.

ABSTRACT: During adolescence major shifts in sleep and circadian systems occur with a notable circadian phase delay. Yet, the circadian influence on pain during early adolescence is largely unknown. Using 2 years of data from the Adolescent Brain Cognitive Development study, we investigated the impact of chronotype on pain incidence, moderate-to-severe pain, and multiregion pain 1 year later in U.S. adolescents. Based on the Munich ChronoType Questionnaire, chronotype was calculated as the midpoint between sleep onset and offset on free days, corrected for sleep debt over the week. Adolescents reported pain presence over the past month, and if present, rated pain intensity (0-10 numerical rating scale; ≥ 4 defined as moderate-to-severe pain) and body site locations (Collaborative Health Outcomes Information Registry Body Map; ≥2 regions defined as multiregion pain). Three-level random intercept logistic regression models were specified for each pain outcome, adjusting for baseline sociodemographic and developmental characteristics. Among 5991 initially pain-free adolescents (mean age 12.0 years, SD 0.7), the mean chronotype was 3:59 am (SD 97 minutes), and the 1-year incidence of pain, moderate-to-severe pain, and multiregion pain was 24.4%, 15.2%, and 13.5%, respectively. Each hour later chronotype at baseline was associated with higher odds of developing any pain (odds ratio [OR] = 1.06, 95% confidence interval [CI] = 1.01, 1.11), moderate-to-severe pain (OR = 1.10, 95% CI = 1.05-1.17), and multiregion pain (OR = 1.08, 95% CI = 1.02-1.14) during 1-year follow-up. In this diverse U.S. adolescent sample, later chronotype predicted higher incidence of new-onset pain.

Attentional control influence habituation through modulation of connectivity patterns within the prefrontal cortex: Insights from stereo-EEG.

Attentional control, guided by top-down processes, enables selective focus on pertinent information, while habituation, influenced by bottom-up factors and prior experiences, shapes cognitive responses by emphasizing stimulus relevance. These two fundamental processes collaborate to regulate cognitive behavior, with the prefrontal cortex and its subregions playing a pivotal role. Nevertheless, the intricate neural mechanisms underlying the interaction between attentional control and habituation are still a subject of ongoing exploration. To our knowledge, there is a dearth of comprehensive studies on the functional connectivity between subsystems within the prefrontal cortex during attentional control processes in both primates and humans. Utilizing stereo-electroencephalogram (SEEG) recordings during the Stroop task, we observed top-down dominance effects and corresponding connectivity patterns among the orbitofrontal cortex (OFC), the middle frontal gyrus (MFG), and the inferior frontal gyrus (IFG) during heightened attentional control. These findings highlighting the involvement of OFC in habituation through top-down attention. Our study unveils unique connectivity profiles, shedding light on the neural interplay between top-down and bottom-up attentional control processes, shaping goal-directed attention.

Multi-strategy learning-based particle swarm optimization algorithm for COVID-19 threshold segmentation.

With advancements in science and technology, the depth of human research on COVID-19 is increasing, making the investigation of medical images a focal point. Image segmentation, a crucial step preceding image processing, holds significance in the realm of medical image analysis. Traditional threshold image segmentation proves to be less efficient, posing challenges in selecting an appropriate threshold value. In response to these issues, this paper introduces Inner-based multi-strategy particle swarm optimization (IPSOsono) for conducting numerical experiments and enhancing threshold image segmentation in COVID-19 medical images. A novel dynamic oscillatory weight, derived from the PSO variant for single-objective numerical optimization (PSOsono) is incorporated. Simultaneously, the historical optimal positions of individuals in the particle swarm undergo random updates, diminishing the likelihood of algorithm stagnation and local optima. Moreover, an inner selection learning mechanism is proposed in the update of optimal positions, dynamically refining the global optimal solution. In the CEC 2013 benchmark test, PSOsono demonstrates a certain advantage in optimization capability compared to algorithms proposed in recent years, proving the effectiveness and feasibility of PSOsono. In the Minimum Cross Entropy threshold segmentation experiments for COVID-19, PSOsono exhibits a more prominent segmentation capability compared to other algorithms, showing good generalization across 6 CT images and further validating the practicality of the algorithm.

MR2CPPIS: Accurate prediction of protein-protein interaction sites based on multi-scale Res2Net with coordinate attention mechanism.

Proteins play a vital role in various biological processes and achieve their functions through protein-protein interactions (PPIs). Thus, accurate identification of PPI sites is essential. Traditional biological methods for identifying PPIs are costly, labor-intensive, and time-consuming. The development of computational prediction methods for PPI sites offers promising alternatives. Most known deep learning (DL) methods employ layer-wise multi-scale CNNs to extract features from protein sequences. But, these methods usually neglect the spatial positions and hierarchical information embedded within protein sequences, which are actually crucial for PPI site prediction. In this paper, we propose MR2CPPIS, a novel sequence-based DL model that utilizes the multi-scale Res2Net with coordinate attention mechanism to exploit multi-scale features and enhance PPI site prediction capability. We leverage the multi-scale Res2Net to expand the receptive field for each network layer, thus capturing multi-scale information of protein sequences at a granular level. To further explore the local contextual features of each target residue, we employ a coordinate attention block to characterize the precise spatial position information, enabling the network to effectively extract long-range dependencies. We evaluate our MR2CPPIS on three public benchmark datasets (Dset 72, Dset 186, and PDBset 164), achieving state-of-the-art performance. The source codes are available at https://github.com/YyinGong/MR2CPPIS.

Semi-supervised multi-modal medical image segmentation with unified translation.

The two major challenges to deep-learning-based medical image segmentation are multi-modality and a lack of expert annotations. Existing semi-supervised segmentation models can mitigate the problem of insufficient annotations by utilizing a small amount of labeled data. However, most of these models are limited to single-modal data and cannot exploit the complementary information from multi-modal medical images. A few semi-supervised multi-modal models have been proposed recently, but they have rigid structures and require additional training steps for each modality. In this work, we propose a novel flexible method, semi-supervised multi-modal medical image segmentation with unified translation (SMSUT), and a unique semi-supervised procedure that can leverage multi-modal information to improve the semi-supervised segmentation performance. Our architecture capitalizes on unified translation to extract complementary information from multi-modal data which compels the network to focus on the disparities and salient features among each modality. Furthermore, we impose constraints on the model at both pixel and feature levels, to cope with the lack of annotation information and the diverse representations within semi-supervised multi-modal data. We introduce a novel training procedure tailored for semi-supervised multi-modal medical image analysis, by integrating the concept of conditional translation. Our method has a remarkable ability for seamless adaptation to varying numbers of distinct modalities in the training data. Experiments show that our model exceeds the semi-supervised segmentation counterparts in the public datasets which proves our network's high-performance capabilities and the transferability of our proposed method. The code of our method will be openly available at https://github.com/Sue1347/SMSUT-MedicalImgSegmentation.

Multi-medium residues and ecological risk of herbicides in a typical agricultural watershed of the Mollisols region, Northeast China.

The widespread use of herbicides impacts non-target organisms, promotes weed resistance, posing a serious threat to the global goal of green production in agriculture. Although the herbicide residues have been widely reported in individual environmental medium, their presence across different media has received scant attention, particularly in Mollisols regions with intensive agricultural application of herbicides. A systematic investigation was conducted in this study to clarify the occurrence of herbicide residues in soil, surface water, sediments, and grains from a typical agricultural watershed in the Mollisols region of Northeast China. Concentrations of studied herbicides ranged from 0.30 to 463.49 µg/kg in soil, 0.31-29.73 µg/kg in sediments, 0.006-1.157 µg/L in water, and 0.32-2.83 µg/kg in grains. Among these, Clomazone was the most priority herbicide detected in soil, sediments, and water, and Pendimethalin in grains. Crop types significantly affected the residue levels of herbicides in grains. Clomazone posed high ecological risks in soil and water, with 86.4 % of water samples showing high risks from herbicide mixtures (RQ > 1). These findings aid in enhancing our comprehension of the pervasive occurrence and potential ecological risks of herbicides in different media within typical agricultural watersheds, providing detailed data to inform the development of targeted mitigation strategies.