A new horizon for neuroscience: terahertz biotechnology in brain research.

Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences. In this article, we review the development of terahertz biotechnology and its applications in the field of neuropsychiatry. Available evidence indicates promising prospects for the use of terahertz spectroscopy and terahertz imaging techniques in the diagnosis of amyloid disease, cerebrovascular disease, glioma, psychiatric disease, traumatic brain injury, and myelin deficit. In vitro and animal experiments have also demonstrated the potential therapeutic value of terahertz technology in some neuropsychiatric diseases. Although the precise underlying mechanism of the interactions between terahertz electromagnetic waves and the biosystem is not yet fully understood, the research progress in this field shows great potential for biomedical noninvasive diagnostic and therapeutic applications. However, the biosafety of terahertz radiation requires further exploration regarding its two-sided efficacy in practical applications. This review demonstrates that terahertz biotechnology has the potential to be a promising method in the field of neuropsychiatry based on its unique advantages.

Fucoidan alleviates high sucrose-induced metabolic disorders and enhances intestinal homeostasis through modulation of Notch signaling.

INTRODUCTION: The therapeutic potential of fucoidan (FUC), a natural polysaccharide, in metabolic disorders is recognized, yet its underlying mechanisms remain unclear. METHODS: We conducted investigations into the therapeutic mechanisms of FUC sourced from Sargassum fulvellum concerning metabolic disorders induced by a high-sucrose diet (HSD), employing Drosophila melanogaster and mice models. Drosophila larvae were subjected to HSD exposure to monitor growth inhibition, reduced pupation, and developmental delays. Additionally, we examined the impact of FUC on growth- and development-related hormones in Drosophila. Furthermore, we assessed the modulation of larval intestinal homeostasis by FUC, focusing on the regulation of Notch signaling. In mice, we evaluated the effects of FUC on HSD-induced impairments in intestinal epithelial barrier integrity and gut hormone secretion. RESULTS: FUC supplementation significantly enhanced pupal weight in Drosophila larvae and effectively countered HSD-induced elevation of glucose and triglyceride levels. It notably influenced the expression of growth- and development-related hormones, particularly augmenting insulin-like peptides production while mitigating larval growth retardation. FUC also modulated larval intestinal homeostasis by negatively regulating Notch signaling, thereby protecting against HSD-induced metabolic stress. In mice, FUC ameliorated HSD-induced impairments in ileum epithelial barrier integrity and gut hormone secretion. CONCLUSIONS: Our findings demonstrate the multifaceted therapeutic effects of FUC in mitigating metabolic disorders and maintaining intestinal health. FUC holds promise as a therapeutic agent, with its effects attributed partly to the sulfate group and its ability to regulate Notch signaling, emphasizing its potential for addressing metabolic disorders.

Effect of different inhalant allergens on T-cell subsets in adults with bronchial asthma.

Objective: We analyzed the impact of different inhalant allergens on T-lymphocyte subsets in patients diagnosed with bronchial asthma. Methods: The study included 57 bronchial asthma patients and 22 healthy controls. Asthma patients were categorized into dust mite, animal hair, pollen, and mold groups. Flow cytometry was used to measure the cells in the case group and control group. These T-lymphocyte subset markers were evaluated among patients with bronchial asthma caused by different allergens as well as between the case group and control group. Results: Peripheral blood CD4+ T-cells, CD8+ T-cells, CD4/CD8 ratio, and Th17/Treg ratios were all higher in the case group than in the control group (P < 0.05). Peripheral blood T-lymphocyte subsets were compared among the four groups, and it was found that there were statistical differences in the Th17/Treg ratio among the four groups (P < 0.05). There were no significant differences observed among the four groups in terms of CD3+ cells, CD4+ cells, CD8+ cells, Th1 cells, Th2 cells, Th17 cells, Treg cells, Th9 cells, and Th22 cells. Further pairwise comparison was made, and the results suggested that the peripheral blood Th17/Treg ratio in the pollen mixed group was lower than that in the dust mite mixed group, animal hair mixed group, and mold mixed group (P < 0.05). Conclusion: Patients with bronchial asthma show varied T-lymphocyte subset responses to different inhalant allergens. Elevated CD4+ T cells and Th17 cells in peripheral blood could indicate asthma risk. However, small sample size may introduce bias to these findings.

Prognosis and diagnosis of prostate cancer based on hypergraph regularization sparse least partial squares regression algorithm.

BACKGROUND: Prostate cancer (PCa) is a malignant tumor of the male reproductive system, and its incidence has increased significantly in recent years. This study aimed to further identify candidate biomarkers with prognostic and diagnostic significance by integrating gene expression and DNA methylation data from PCa patients through association analysis. MATERIAL AND METHODS: To this end, this paper proposes a sparse partial least squares regression algorithm based on hypergraph regularization (HR-SPLS) by integrating and clustering two kinds of data. Next, module 2, with the most significant weight, was selected for further analysis according to the weight of each module related to DNA methylation and mRNAs. Based on the DNA methylation sites in module 2, this paper uses multiple machine learning methods to construct a PCa diagnosis-related model of 10-DNA methylation sites. RESULTS: The results of Receiver Operating Characteristic (ROC) analysis showed that the DNA methylation-related diagnostic model we constructed could diagnose PCa patients with high accuracy. Subsequently, based on the mRNAs in module 2, we constructed a prognostic model for 7-mRNAs (MYH11, ACTG2, DDR2, CDC42EP3, MARCKSL1, LMOD1, and MYLK) using multivariate Cox regression analysis. The prognostic model could predict the disease free survival of PCa patients with moderate to high accuracy (area under the curve (AUC) =0.761). In addition, Gene Set EnrichmentAnalysis (GSEA) and immune analysis indicated that the prognosis of patients in the risk group might be related to immune cell infiltration. CONCLUSIONS: Our findings may provide new methods and insights for identifying disease-related biomarkers by integrating DNA methylation and gene expression data.

Anterior Shoulder Stabilization Using Single Needle-Assisted Outside-In Remplissage Technique and Bankart Repair.

Arthroscopic repair of Bankart injury is the first choice for the treatment of anterior shoulder instability. How to avoid recurring shoulder joint dislocation is a challenge, especially when combined with Hill-Sachs lesions. The arthroscopy technology allows for broader vision and less surgical trauma but is limited by a smaller operating space. At present, extensive descriptions about the surgical procedure of arthroscopic Bankart repair have been published. In this Technical Note, we describe the use of remplissage filling with Hill-Sachs lesion combined with Bankart repair to further improve the surgical accuracy and clinical efficacy. In particular, the application of single needle-assisted outside-in remplissage technique and Bankart repair is introduced in detail.

Strictosamide promotes wound healing through activation of the PI3K/AKT pathway.

Nauclea officinalis, as a Chinese medicine in Hainan province, had the effect of treating lower limb ulcers, burn infections. In this paper, we studied the effect of Strictosamide (STR), the main bioactive compound in Nauclea officinals, on wound healing and explored its internal mechanism. Firstly, the wound healing potential of STR was evaluated in a rat model, demonstrating its ability to expedite wound healing, mitigate inflammatory infiltration, and enhance collagen deposition. Additionally, immunofluorescence analysis revealed that STR up-regulated the expression of CD31 and PCNA. Subsequently, target prediction, protein-protein interaction (PPI), gene ontology (GO), and pathway enrichment analyses were used to obtain potential targets, specific biological processes, and molecular mechanisms of STR for the potential treatment of wound healing. Furthermore, molecular docking was conducted to predict the binding affinity between STR and its associated targets. Additionally, in vivo and in vitro experiments confirmed that STR could increase the expression of P-PI3K, P-AKT and P-mTOR by activating the PI3K/AKT signaling pathway. In summary, this study provided a new explanation for the mechanism by which STR promotes wound healing through network pharmacology, suggesting that STR may be a new candidate for treating wound.

Community Assembly Processes of Deadwood Mycobiome in a Tropical Forest Revealed by Long-Read Third-Generation Sequencing.

Despite the importance of wood-inhabiting fungi on nutrient cycling and ecosystem functions, their ecology, especially related to their community assembly, is still highly unexplored. In this study, we analyzed the wood-inhabiting fungal richness, community composition, and phylogenetics using PacBio sequencing. Opposite to what has been expected that deterministic processes especially environmental filtering through wood-physicochemical properties controls the community assembly of wood-inhabiting fungal communities, here we showed that both deterministic and stochastic processes can highly contribute to the community assembly processes of wood-inhabiting fungi in this tropical forest. We demonstrated that the dynamics of stochastic and deterministic processes varied with wood decomposition stages. The initial stage was mainly governed by a deterministic process (homogenous selection), whereas the early and later decomposition stages were governed by the stochastic processes (ecological drift). Deterministic processes were highly contributed by wood physicochemical properties (especially macronutrients and hemicellulose) rather than soil physicochemical factors. We elucidated that fine-scale fungal-fungal interactions, especially the network topology, modularity, and keystone taxa of wood-inhabiting fungal communities, strongly differed in an initial and decomposing deadwood. This current study contributes to a better understanding of the ecological processes of wood-inhabiting fungi in tropical regions where the knowledge of wood-inhabiting fungi is highly limited.

Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce sepsis mortality. This article used artificial intelligence (AI) technology to predict the risk of death effectively and quickly in children with sepsis in the pediatric intensive care unit (PICU). STUDY DESIGN: This retrospective observational study was conducted in the PICUs of the First Affiliated Hospital of Sun Yat-sen University from December 2016 to June 2019 and Shenzhen Children's Hospital from January 2019 to July 2020. The children were divided into a death group and a survival group. Different machine language (ML) models were used to predict the risk of death in children with sepsis. RESULTS: A total of 671 children with sepsis were enrolled. The accuracy (ACC) of the artificial neural network model was better than that of support vector machine, logical regression analysis, Bayesian, K nearest neighbor method and decision tree models, with a training set ACC of 0.99 and a test set ACC of 0.96. CONCLUSIONS: The AI model can be used to predict the risk of death due to sepsis in children in the PICU, and the artificial neural network model is better than other AI models in predicting mortality risk.

Nickel-catalysed highly regioselective synthesis of ß-acyl naphthalenes under reductive conditions.

Over the past decade, significant progress has been made in the direct C-H acylation of naphthalenes, occurring at the α or ß-positions to yield valuable ketones through Friedel-Crafts acylation or transition-metal-catalysed carbonylative coupling reactions. Nevertheless, highly regioselective acylation of naphthalenes remains a formidable challenge. Herein, we developed a nickel-catalysed reductive ring-opening reaction of 7-oxabenzonorbornadienes with acyl chlorides as the electrophilic coupling partner, providing a new method for the exclusive preparation of ß-acyl naphthalenes.

MMP-9 upregulation may predict hemorrhagic transformation after endovascular thrombectomy.

Background: Hemorrhagic transformation (HT) is a serious complication after endovascular thrombectomy (EVT) for patients with acute ischemic stroke (AIS). We analyzed the plasma levels of MMP-9 before and after EVT and assessed the temporal changes of MMP-9 that may be associated with, and therefore predict, HT after EVT. Methods: We enrolled 30 AIS patients who received EVT, and 16 (53.3%) developed HT. The levels of MMP-9 in plasma collected from the arteries of AIS patients before and immediately after EVT were measured using ELISA. The percent change in MMP-9 after EVT (after/before) was calculated and compared between patients with and without HT. Results: The median age of the AIS patients was 70 years, and 13 patients (43.3%) were men. The median National Institutes of Health Stroke Scale (NIHSS) scores of patients with HT were 18 on admission and 18 after EVT. The median NIHSS scores of patients without HT were 17 on admission and 11 after EVT. Patients with HT demonstrated significantly greater percentage increases in arterial MMP-9 levels after EVT. Conclusion: Patients with AIS who developed HT had significantly increased arterial MMP-9 levels after EVT, suggesting that the upregulation of MMP-9 following EVT could serve as a predictive biomarker for HT.

The longitudinal associations between ambient air pollution exposure and dementia in the UK: results from the cognitive function and ageing study II and Wales.

BACKGROUND: Air pollution has been recognised as a potential risk factor for dementia. Yet recent epidemiological research shows mixed evidence. The aim of this study is to investigate the longitudinal associations between ambient air pollution exposure and dementia in older people across five urban and rural areas in the UK. METHODS: This study was based on two population-based cohort studies of 11329 people aged ≥ 65 in the Cognitive Function and Ageing Study II (2008-2011) and Wales (2011-2013). An algorithmic diagnosis method was used to identify dementia cases. Annual concentrations of four air pollutants (NO2, O3, PM10, PM2.5) were modelled for the year 2012 and linked via the participants' postcodes. Multistate modelling was used to examine the effects of exposure to air pollutants on incident dementia incorporating death and adjusting for sociodemographic factors and area deprivation. A random-effect meta-analysis was carried out to summarise results from the current and nine existing cohort studies. RESULTS: Higher exposure levels of NO2 (HR: 1.04; 95% CI: 0.94, 1.14), O3 (HR: 0.90; 95% CI: 0.70, 1.15), PM10 (HR: 1.17; 95% CI: 0.86, 1.58), PM2.5 (HR: 1.41; 95% CI: 0.71, 2.79) were not strongly associated with dementia in the two UK-based cohorts. Inconsistent directions and strengths of the associations were observed across the two cohorts, five areas, and nine existing studies. CONCLUSIONS: In contrast to the literature, this study did not find clear associations between air pollution and dementia. Future research needs to investigate how methodological and contextual factors can affect evidence in this field and clarity the influence of air pollution exposure on cognitive health over the lifecourse.

Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR.

Deciphering the Prognostic Efficacy of MRI Radiomics in Nasopharyngeal Carcinoma: A Comprehensive Meta-Analysis.

This meta-analysis investigates the prognostic value of MRI-based radiomics in nasopharyngeal carcinoma treatment outcomes, specifically focusing on overall survival (OS) variability. The study protocol was registered with INPLASY (INPLASY202420101). Initially, a systematic review identified 15 relevant studies involving 6243 patients through a comprehensive search across PubMed, Embase, and Web of Science, adhering to PRISMA guidelines. The methodological quality was assessed using the Quality in Prognosis Studies (QUIPS) tool and the Radiomics Quality Score (RQS), highlighting a low risk of bias in most domains. Our analysis revealed a significant average concordance index (c-index) of 72% across studies, indicating the potential of radiomics in clinical prognostication. However, moderate heterogeneity was observed, particularly in OS predictions. Subgroup analyses and meta-regression identified validation methods and radiomics software as significant heterogeneity moderators. Notably, the number of features in the prognosis model correlated positively with its performance. These findings suggest radiomics' promising role in enhancing cancer treatment strategies, though the observed heterogeneity and potential biases call for cautious interpretation and standardization in future research.

Sinensetin protects against periodontitis through binding to Bach1 enhancing its ubiquitination degradation and improving oxidative stress.

Periodontitis is a chronic inflammatory and immune reactive disease induced by the subgingival biofilm. The therapeutic effect for susceptible patients is often unsatisfactory due to excessive inflammatory response and oxidative stress. Sinensetin (Sin) is a nature polymethoxylated flavonoid with anti-inflammatory and antioxidant activities. Our study aimed to explore the beneficial effect of Sin on periodontitis and the specific molecular mechanisms. We found that Sin attenuated oxidative stress and inflammatory levels of periodontal ligament cells (PDLCs) under inflammatory conditions. Administered Sin to rats with ligation-induced periodontitis models exhibited a protective effect against periodontitis in vivo. By molecular docking, we identified Bach1 as a strong binding target of Sin, and this binding was further verified by cellular thermal displacement assay and immunofluorescence assays. Chromatin immunoprecipitation-quantitative polymerase chain reaction results also revealed that Sin obstructed the binding of Bach1 to the HMOX1 promoter, subsequently upregulating the expression of the key antioxidant factor HO-1. Further functional experiments with Bach1 knocked down and overexpressed verified Bach1 as a key target for Sin to exert its antioxidant effects. Additionally, we demonstrated that Sin prompted the reduction of Bach1 by potentiating the ubiquitination degradation of Bach1, thereby inducing HO-1 expression and inhibiting oxidative stress. Overall, Sin could be a promising drug candidate for the treatment of periodontitis by targeting binding to Bach1.

Eco-climate drivers shape virome diversity in a globally invasive tick species.

Spillovers of viruses into human occur more frequently under warmer conditions, particularly arboviruses. The invasive tick species Haemaphysalis longicornis poses a significant public health threat due to its global expansion and its potential to carry a wide range of pathogens. We analyzed meta-transcriptomic data from 3595 adult H. longicornis ticks collected between 2016 and 2019 in 22 provinces across China, encompassing diverse ecological conditions. Generalized additive modelling revealed that climate factors exerted a stronger influence on the virome of H. longicornis compared to other ecological factors, such as ecotypes, distance to coastline, animal host, tick gender, and anti-viral immunity. We investigated the mechanistic understanding of how climate changes drive the tick virome using causality inference and emphasized its significance for public health. Our findings demonstrated that higher temperatures and lower relative humidity/precipitation contribute to variations in animal host diversity, leading to an increased diversity of tick virome, particularly the evenness of vertebrate associated viruses. This finding may explain the evolution of tick-borne viruses into generalists across multiple hosts, thereby increasing the probability of spillover events involving tick-borne pathogens. Deep learning projections indicate that the diversity of H. longicornis virome is expected to increase in 81.9% of regions under the SSP8.5 scenario from 2019-2030. Extension of surveillance should be implemented to avert the spread of tick-borne diseases.

The long-term changing patterns of suicide mortality in China from 1987 to 2020: continuing urban-rural disparity.

BACKGROUND: Over the past three decades, China has experienced significant changes in urban-rural, gender, and age-specific suicide mortality patterns. This study aimed to investigate the long-term trends in suicide mortality in China from 1987 to 2020. METHODS: Suicide mortality data were obtained from China's National Health Commission. Joinpoint regression analysis was used to examine changes in trends and age-period-cohort modeling to estimate age, period, and cohort effects on suicide mortality from 1987 to 2020. Net drift, local drift, longitudinal age curves, and period relative risks were also calculated. RESULTS: Crude and age-standardized suicide mortality in China showed continuing downward trends from 1987 to 2020, with a more pronounced decrease in rural areas (net drift = -7.07%, p<0.01) compared to urban areas (net drift = -3.41%, p<0.01). The decline curve of urban areas could be divided into three substages. Period and cohort effects were more prominent in rural areas. Suicide risk was highest among individuals aged 20-24 and gradually increased after age 60. Females, particularly those of childbearing age, had higher suicide risk than males, with a reversal observed after age 50. This gender reversal showed distinct patterns in urban and rural areas, with a widening gap in urban areas and a relatively stable gap in rural areas. CONCLUSIONS: Suicide mortality in China has consistently declined over the past three decades. However, disparities in age, gender, and urban-rural settings persist, with new patterns emerging. Targeted suicide prevention programs are urgently needed for high-risk groups, including females of childbearing age and the elderly, and to address the slower decrease and reversing urban-rural gender trends.

Veliparib exerts protective effects in intracerebral hemorrhage mice by inhibiting the inflammatory response and accelerating hematoma resolution.

Poly (ADP-ribose) polymerase (PARP) inhibitors have potent anti-inflammatory effects, including the suppression of brain microglial activation. Veliparib, a well-known PARP1/2 inhibitor, exhibits particularly high brain penetration, but its effects on stroke outcome is unknown. Here, the effects of veliparib on the short-term outcome of intracerebral hemorrhage (ICH), the most lethal type of stroke, were investigated. Collagenase-induced mice ICH model was applied, and the T2-weighted magnetic resonance imaging was performed to evaluate lesion volume. Motor function and hematoma volume were also measured. We further performed immunofluorescence, enzyme linked immunosorbent assay, flow cytometry, and blood-brain barrier assessment to explore the potential mechanisms. Our results demonstrated veliparib reduced the ICH lesion volume dose-dependently and at a dosage of 5 mg/kg, veliparib significantly improved mouse motor function and promoted hematoma resolution at days 3 and 7 post-ICH. Veliparib inhibited glial activation and downregulated the production of pro-inflammatory cytokines. Veliparib significantly decreased microglia counts and inhibited peripheral immune cell infiltration into the brain on day 3 after ICH. Veliparib improved blood-brain barrier integrity at day 3 after ICH. These findings demonstrate that veliparib improves ICH outcome by inhibiting inflammatory responses and may represent a promising novel therapy for ICH.

Pentacyclic triterpenoids as potential ACL inhibitors from the rare medicinal plant Semiliquidambar cathayensis.

An extensive phytochemical investigation on the rare medicinal plant Semiliquidambar cathayensis (family: Hamamelidaceae) led to the isolation of four new (1-4, named semiliquidacids A-D, respectively) and 25 related known pentacyclic triterpenoids. The new structures with absolute configurations were elucidated by spectroscopic methods, electronic circular dichroism (ECD) calculations, and single-crystal X-ray diffraction analysis. Compound 1 represents the first naturally occurring ursane-type triterpenoid featuring an uncommon C-25 formyl group. Compound 4 and oleanolic acid (13) exhibited remarkable inhibitory effects against the ATP-citrate lyase (ACL, an emerging drug target for hyperlipidemia and related metabolic disorders) with IC50 values of 6.5 and 11.9 µM, respectively. The molecular interaction and binding mode between the bioactive triterpenoids and ACL were elaborated by conducting a molecular docking study. Meanwhile, the chemotaxonomic significance of the isolated triterpenoids has been briefly discussed.