Regulation of the PD-1/PD-L1 Axis and NK Cell Dysfunction by Exosomal miR-552-5p in Gastric Cancer.

OBJECTIVE: NK cells play a vital role in tumor immune resistance. Various factors affect NK cell activity. While NK cell dysfunction has been observed in numerous malignancies, the underlying mechanisms in gastric cancer remain unclear. METHOD: Flow cytometry was used to identify the phenotypic distribution and expression of activated receptors on NK cells. ELISA was used to determine the expression of cytokines. We examined the expression of NK cell-related genes and explored their association with survival and prognosis. Additionally, we conducted PCR detection of miR-552-5p expression levels in plasma exosomes of patients and investigated its correlation with phenotypic distribution and activated receptors. We used flow cytometry and ELISA to verify the role of miR-552-5p in NK cell dysfunction. Furthermore, we investigated the potential role of PD-1/PD-L1 in regulating NK cell dysfunction in patients' cells. RESULTS: We observed a significant decrease in the percentage of NKG2D and NKp30 and IFN-γ and TNF-α in patients than in healthy volunteers. Patients with low levels of CD56, CD16, NKG2D, and NKP46 exhibited poorer survival prognoses. Moreover, increased expression levels of plasma exosomal miR-552-5p in patients were negatively associated with NK cell phenotypic distribution and activated receptor expression. MiR-552-5p downregulated the secretion of perforin, granzyme, and IFN-γ as well as the expression of NKp30, NKp46, and NKG2D. Additionally, it suppressed the cytotoxicity of NK cells. The inhibitory effect of miR-552-5p, on NK cell function was reversed when anti-PD-L1 antibodies were used. CONCLUSION: Exosomal miR-552-5p targets the PD-1/PD-L1 axis, leading to impaired NK cell function.

Cohort profile: migraine exposures and cardiovascular health in Hong Kong Chinese women (MECH-HK).

PURPOSE: Evidence about the associations of migraine features with cardiovascular risk profiles in Chinese population is lacking. The Migraine Exposures and Cardiovascular Health in Hong Kong Chinese Women (MECH-HK) cohort was constructed to investigate longitudinal migraine features and their cardiovascular implications in Hong Kong Chinese women. PARTICIPANTS: We enrolled 4221 Hong Kong Chinese women aged 30 years or above from October 2019 to December 2020. Demographics, reproductive information, lifestyle factors, disease history, blood lipids and glucose, anthropometrics and body compositions were measured during baseline and follow-up. Migraine diagnosis followed the International Classification of Headache Disorders-3 criteria. Migraine features were longitudinally tracked using a migraine diary and summarised by a wide range of epidemiological metrics. Cardiovascular health was assessed using the Framingham risk score (FRS). FINDINGS TO DATE: From October 2021 to June 2023, 3455 women completed the first follow-up measurement. The retention rate was 81.9%. The average age at baseline was 54.40 years. The mean blood glucose, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol levels were 6.44 mmol/L, 65.06 mg/dL and 102.40 mg/dL, respectively. The average FRS was 0.06. Participants had a 10.3% prevalence of migraine or probable migraine. After 1.27 years of follow-up, the median migraine attack frequency was 0.99 attacks/month, with an incidence rate of 2.55 attacks/person-month and a median duration of 7.70 hours/attack. Sleep problems (64.7%) and stress (54.0%) were the top triggers, while prevalent accompanying symptoms were nausea (67.4%), photophobia (39.9%), phonophobia (30.0%) and vomiting (26.2%). Migraine auras included blurred visions (59.6%), flashing lights (41.3%), blind spots (33.0%), pins and needles (6.4%) and halo (1.8%). FUTURE PLANS: The follow-up for the cohort will be implemented every 2 years. MECH-HK will provide unique longitudinal data on migraine features in Hong Kong women. The linkage between migraine features and cardiovascular disease risk progression will be identified by a long-term observation.

Effects of botulinum toxin type A in patients with painful temporomandibular joint disorders: a systematic review and meta-analysis.

Objective: To assess the therapeutic efficacy of botulinum toxin type A (BTX-A) for managing myofascial pain related to temporomandibular disorders (TMDs). Methods: This study was conducted according to the PRISMA 2020 statement guidelines. The PubMed, Embase, and Cochrane Library databases were searched. Only randomized controlled trials were included. The primary outcome was a pain score on the visual analog scale, and the secondary outcomes were maximum mouth opening and adverse effects. The Cochrane risk of bias tool was used to assess risk bias. A meta-analysis of studies with the same interventions, controls, assessment methods, and follow-up durations was performed. Results: A total of 519 studies were retrieved, of which 20 randomized controlled trials were included in the qualitative analysis and six were included in the meta-analysis. The results showed that, compared with placebo, BTX-A injection was more effective at relieving myofascial pain, and its effect was similar to that of conventional methods. However, there was no difference in maximum mouth opening between the two groups. After the study assessment with the RoB 2.0 tool, six studies showed a low risk of bias, 13 studies showed some concerns regarding the reported results, and only one study showed a high risk of bias. Adverse effects of BTX-A injection were observed in four studies. Conclusions: In conclusion, BTX-A is effective at relieving pain in TMD patients but does not improve mouth opening. To minimize adverse effects, we recommend a low dose of BTX-A for TMD patients who do not experience complete pain relief from conservative treatments.

Video-Instrument Synergistic Network for Referring Video Instrument Segmentation in Robotic Surgery.

Surgical instrument segmentation is fundamentally important for facilitating cognitive intelligence in robot-assisted surgery. Although existing methods have achieved accurate instrument segmentation results, they simultaneously generate segmentation masks of all instruments, which lack the capability to specify a target object and allow an interactive experience. This paper focuses on a novel and essential task in robotic surgery, i.e., Referring Surgical Video Instrument Segmentation (RSVIS), which aims to automatically identify and segment the target surgical instruments from each video frame, referred by a given language expression. This interactive feature offers enhanced user engagement and customized experiences, greatly benefiting the development of the next generation of surgical education systems. To achieve this, this paper constructs two surgery video datasets to promote the RSVIS research. Then, we devise a novel Video-Instrument Synergistic Network (VIS-Net) to learn both video-level and instrument-level knowledge to boost performance, while previous work only utilized video-level information. Meanwhile, we design a Graph-based Relation-aware Module (GRM) to model the correlation between multi-modal information (i.e., textual description and video frame) to facilitate the extraction of instrument-level information. Extensive experimental results on two RSVIS datasets exhibit that the VIS-Net can significantly outperform existing state-of-the-art referring segmentation methods. We will release our code and dataset for future research (Git).

Ultrasound Characteristics Can Predict Response to Biologics Therapy in Stricturing Crohn's Disease.

INTRODUCTION: Stricture is a common complication in Crohn's disease (CD). Accurate identification of strictures that poorly respond to biologic therapy is essential for making optimal therapeutic decisions. The aim of this study was to determine the association between ultrasound characteristics of strictures and their therapeutic outcomes. METHODS: Consecutive CD patients with symptomatic strictures scheduled for biologic therapy were retrospectively recruited at a tertiary hospital. Baseline intestinal ultrasound was conducted to assess stricture characteristics, including bowel wall thickness, length, stratification, vascularity, and creeping fat wrapping angle. Patients were followed up for a minimum of 1 year, during which long-term outcomes including surgery, steroid-free clinical remission, and mucosal healing were recorded. Statistical analyses were performed. RESULTS: A total of 43 patients were enrolled. Strictures were located in the ileocecal region (39.5%), colon (37.2%), anastomosis (20.9%), and small intestine (2.3%). The median follow-up time was 17 months (interquartile range 7-25), with 27 patients (62.8%) undergoing surgery. On multivariant analysis, creeping fat wrapping angle > 180° (odds ratio: 6.2, 95% confidence interval [CI]: 1.1-41.1) and a high Limberg score (odds ratio: 2.3, 95% CI: 1.4-6.0) were independent predictors of surgery, with an area under the curve of 0.771 (95% CI: 0.602-0.940), accuracy of 83.7%, sensitivity of 96.3%, and specificity of 62.5%. On Cox survival analysis, creeping fat >180° was significantly associated with surgery (hazard ratio, 5.2; 95% CI: 1.2-21.8; P = 0.03). In addition, creeping fat was significantly associated with steroid-free clinical remission ( P = 0.015) and mucosal healing ( P = 0.06). DISCUSSION: Intestinal ultrasound characteristics can predict outcomes in patients with stricturing CD who undertook biologic therapy.

Tumor mutation burden and FAT3 mutation influence long-term survival in surgically resected small cell lung cancer.

Background: Small cell lung cancer (SCLC) is highly malignant and has a higher risk of recurrence even in patients who undergo early surgery. However, a subgroup of patients survived for many years. So far, the factors that determine the long-term survivorship remain largely unknown. To determine the genetic characteristics of long-term survival (LTS) after surgery in SCLC, we performed comprehensive comparative genomic profiling and tumor mutation burden (TMB) analysis of resected tumor tissues from patients with LTS and short-term survival (STS) after surgery. Methods: The present study screened 11 patients from 52 patients with SCLC who underwent surgery at Zhejiang Cancer Hospital from April 2008 to December 2017. A total of six LTS patients (≥4 years) with stage IIB or IIIA SCLC and five STS patients (<2 years) with stage IA or IB SCLC were included in the study. The STS patients were used as a control. All the patients underwent resection without neoadjuvant therapy. We assessed the genomic profiles of the resected tumor tissues and calculated the TMB using next-generation sequencing. We then analyzed and compared the molecular characteristics between the LTS and STS groups. Results: Our data indicated that tumor tissues from patients with LTS harbor a high TMB. The median TMB for LTS patients was high (approximately 16.4 mutations/Mb), while that for STS patients was low (approximately 8.5 mutations/Mb). The median TMB of patients with LTS and STS showed a trend of significant difference (P=0.08). Gene alterations characterized the survival differences between the two groups. The FAT3 mutation was only found in the LTS group, and the P value determined by Fisher's exact test was 0.06. Conclusions: A high non-synonymous TMB and the FAT3 mutation could potentially influence LTS after SCLC resection. This study provides valuable information about the molecular differences between LTS and STS patients. Studies with larger sample sizes need to be conducted to confirm our findings in the future.

Structural characterization of extracellular polysaccharides from Phellinus igniarius SH-1 and their therapeutic effects on DSS induced colitis in mice.

Phellinus igniarius is a valuable medicinal and edible mushroom, and its polysaccharides exhibit excellent anti-inflammatory activity. During liquid fermentation to produce P. igniarius mycelia, the fermentation liquid is often discarded, but it contains extracellular polysaccharides. To better utilize these resources, P. igniarius SH-1 was fermented in a 100 L fermenter, and PIPS-2 was isolated and purified from the fermentation broth. The structural characteristics and anti-inflammatory activity of PIPS-2 were determined. PIPS-2 had a molecular weight of 22.855 kDa and was composed of galactose and mannose in a molar ratio of 0.38:0.62. Structural analysis revealed that the main chain of PIPS-2 involved →2)-α-D-Manp-(1 â†’ 3)-ß-D-Galf-(1→, and the side chains involved α-D-Manp-(1 â†’ 6)-α-D-Manp-(1→, α-D-Manp-(1 â†’ 3)-α-D-Manp-(1→, and α-D-Manp-(1. PIPS-2 alleviated the symptoms of dextran sodium sulfate (DSS)-induced colitis in mice, improved the imbalance of inflammatory factors and antioxidant enzymes, and increased short-chain fatty acid contents. Combining the intestinal flora and metabolite results, PIPS-2 was found to regulate the abundance of Firmicutes, Lachnospiraceae_NK4A136_group, Proteobacteria, Bacteroides, and many serum metabolites including hexadecenal, copalic acid, 8-hydroxyeicosatetraenoic acid, artepillin C, and uric acid, thereby ameliorating metabolite related disorders in mice with colitis. In summary, PIPS-2 may improve colitis in mice by regulating the gut microbiota and metabolites.

Investigating the Pharmacological Mechanisms of Total Flavonoids from Eucommia ulmoides Oliver Leaves for Ischemic Stroke Protection.

The aim of this study was to explore how the total flavonoids from Eucommia ulmoides leaves (EULs) regulate ischemia-induced nerve damage, as well as the protective effects mediated by oxidative stress. The cell survival rate was significantly improved compared to the ischemic group (p < 0.05) after treatment with the total flavonoids of EULs. The levels of reactive oxygen species (ROS), lactate dehydrogenase (LDH), and malondialdehyde (MDA) decreased, while catalase (CAT) and glutathione (GSH) increased, indicating that the total flavonoids of EULs can significantly alleviate neurological damage caused by ischemic stroke by inhibiting oxidative stress (p < 0.01). The mRNA expression level of VEGF increased (p < 0.01), which was consistent with the protein expression results. Meanwhile, the protein expression of ERK and CCND1 increased (p < 0.01), suggesting that the total flavonoids of EULs could protect PC12 cells from ischemic injury via VEGF-related pathways. MCAO rat models indicated that the total flavonoids of EULs could reduce brain ischemia-reperfusion injury. In conclusion, this study demonstrates the potential mechanisms of the total flavonoids of EULs in treating ischemic stroke and their potential therapeutic effects in reducing ischemic injury, which provides useful information for ischemic stroke drug discovery.

Bioinformatics analysis of potential common pathogenic mechanisms for COVID-19 and venous thromboembolism.

BACKGROUND: A growing body of research has shown that patients with coronavirus disease 2019 (COVID-19) have significantly higher rates of venous thromboembolism (VTE) than healthy. However, the mechanism remains incompletely elucidated. This study aimed to further investigate the molecular mechanisms underlying the development of this complication. METHODS: The gene expression profiles of COVID-19 and VTE were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for COVID-19 and VTE, functional annotation, a protein-protein interactions (PPI) network, module construction, and hub gene identification were performed. Finally, we constructed a transcription factor (TF)-gene regulatory network and a TF-miRNA regulatory network for hub genes. RESULTS: A total of 42 common DEGs were selected for subsequent analyses. Functional analyses showed that biological function and signaling pathways collectively participated in the development and progression of VTE and COVID-19. Finally, 8 significant hub genes were identified using the cytoHubba plugin, including RSL24D1, RPS17, RPS27, HINT1, COX7C, RPL35, RPL34, and NDUFA4, which had preferable values as diagnostic markers for COVID-19 and VTE. CONCLUSIONS: Our study revealed the common pathogenesis of COVID-19 and VTE. These common pathways and pivotal genes may provide new ideas for further mechanistic studies.

Peripheral CD8+PD-1+ T cells as novel biomarker for neoadjuvant chemoimmunotherapy in humanized mice of non-small cell lung cancer.

Neoadjuvant immunotherapy has shown promising clinical activity in the treatment of early non-small cell lung cancer (NSCLC); however, further clarification of the specific mechanism and identification of biomarkers are imperative prior to implementing it as a daily practice. The study investigated the reprogramming of T cells in both tumor and peripheral blood following neoadjuvant chemoimmunotherapy in a preclinical NSCLC mouse model engrafted with a human immune system. Samples were also collected from 21 NSCLC patients (Stage IA-IIIB) who received neoadjuvant chemoimmunotherapy, and the dynamics of potential biomarkers within these samples were measured and further subjected to correlation analysis with prognosis. Further, we initially investigated the sources of the potential biomarkers. We observed in the humanized mouse model, neoadjuvant chemoimmunotherapy could prevent postoperative recurrence and metastasis by increasing the frequency and cytotoxicity of CD8+ T cells in both peripheral blood (p < 0.001) and tumor immune microenvironment (TIME) (p < 0.001). The kinetics of peripheral CD8+PD-1+ T cells reflected the changes in the TIME and pathological responses, ultimately predicting survival outcome of mice. In the clinical cohort, patients exhibiting an increase in these T cells post-treatment had a higher rate of complete or major pathological response (p < 0.05) and increased immune infiltration (p = 0.0012, r = 0.792). We identified these T cells originating from tumor draining lymph nodes and subsequently entering the TIME. In conclusion, the kinetics of peripheral CD8+PD-1+ T cells can serve as a predictor for changes in TIME and optimal timing for surgery, ultimately reflecting the outcomes of neoadjuvant chemoimmunotherapy in both preclinical and clinical setting.

Hand Hygiene Education Components Among First-Year Nursing Students: A Cluster Randomized Clinical Trial.

Importance: Few studies have directly and objectively measured the individual and combined effects of multifaceted hand hygiene education programs. Objective: To evaluate the individual and combined immediate effects of an instructional video and hand scan images on handwashing quality, decontamination, and knowledge improvement. Design, Setting, and Participants: This cluster randomized clinical trial was conducted in June to July 2023 among first-year nursing students at a university in Hong Kong. The study used an intention-to-treat analysis. Intervention: Hand hygiene education sessions featuring an instructional video, hand scan images, or both. Main Outcomes and Measures: The primary outcome was the change in residue from fluorescent lotion remaining on participants' hands after handwashing before and after the intervention. The secondary outcomes included handwashing quality and knowledge of hand hygiene. Results: A total of 270 of 280 students (mean [SD] age, 19 [1] years; 182 [67.4%] female) participated in the trial (96.4% participation rate). Participants were randomized to a control group (66 participants), hand scan image group (68 participants), instructional video group (67 participants), and hand scan image with instructional video group (69 participants). All intervention groups had greater reductions in residue after the intervention compared with the control group, although none reached statistical significance (hand scan image group: 3.9 [95% CI, 2.0-5.8] percentage points; instructional video group: 4.8 [95% CI, 2.9-6.7] percentage points; hand scan image with instructional video: 3.5 [95% CI, 1.6-5.4] percentage points; control group: 3.2 [95% CI, 1.3-5.2] percentage points). The instructional video group showed a significant improvement in their handwashing performance, with a higher percentage of participants correctly performing all 7 steps compared with the control group (22.4% [95% CI, 13.1% to 31.6%] vs 1.5% [-7.9% to 10.9%]; P < .001). Hand scan images revealed that wrists, fingertips, and finger webs were the most commonly ignored areas in handwashing. Conclusions and Relevance: In this cluster randomized clinical trial of an education program for hand hygiene, a handwashing instructional video and hand scan images did not enhance the level of decontamination. The intervention group had improved handwashing techniques compared with the control group, a secondary outcome. Trial Registration: ClinicalTrials.gov Identifier: NCT05872581.

CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI.

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow imaging speed, resulting in low patient throughput and compromised clinical diagnostic quality. The limited temporal resolution also causes patient discomfort and introduces artifacts in the images, further diminishing their overall quality and diagnostic value. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have so far not been made publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. The 'CMRxRecon' dataset contains raw k-space data and auto-calibration lines. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community.

Network Pharmacology Analysis of the Potential Pharmacological Mechanism of a Sleep Cocktail.

Insomnia, also known as sleeplessness, is a sleep disorder due to which people have trouble sleeping, followed by daytime sleepiness, low energy, irritability, and a depressed mood. It may result in an increased risk of accidents of all kinds as well as problems focusing and learning. Dietary supplements have become popular products for alleviating insomnia, while the lenient requirements for pre-market research result in unintelligible mechanisms of different combinations of dietary supplements. In this study, we aim to systematically identify the molecular mechanisms of a sleep cocktail's pharmacological effects based on findings from network pharmacology and molecular docking. A total of 249 targets of the sleep cocktail for the treatment of insomnia were identified and enrichment analysis revealed multiple pathways involved in the nervous system and inflammation. Protein-protein interaction (PPI) network analysis and molecular complex detection (MCODE) analysis yielded 10 hub genes, including AKT1, ADORA1, BCL2, CREB1, IL6, JUN, RELA, STAT3, TNF, and TP53. Results from weighted correlation network analysis (WGCNA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of insomnia-related transcriptome data from peripheral blood mononuclear cells (PBMCs) showed that a sleep cocktail may also ease insomnia via regulating the inflammatory response. Molecular docking results reveal good affinity of Sleep Cocktail to 9 selected key targets. It is noteworthy that the crucial target HSP90AA1 binds to melatonin most stably, which was further validated by MD simulation.

Loss of ß-arrestin2 aggravated condylar cartilage degeneration at the early stage of temporomandibular joint osteoarthritis.

OBJECTIVE: Temporomandibular joint osteoarthritis (TMJOA) is a chronic degenerative joint disorder characterized by extracellular matrix degeneration and inflammatory response of condylar cartilage. ß-arrestin2 is an important regulator of inflammation response, while its role in TMJOA remains unknown. The objective of this study was to investigate the role of ß-arrestin2 in the development of TMJOA at the early stage and the underlying mechanism. METHODS: A unilateral anterior crossbite (UAC) model was established on eight-week-old wild-type (WT) and ß-arrestin2 deficiency mice to simulate the progression of TMJOA. Hematoxylin-eosin (HE) staining and microcomputed tomography (micro-CT) analysis were used for histological and radiographic assessment. Immunohistochemistry was performed to detect the expression of inflammatory and degradative cytokines, as well as autophagy related factors. Terminal-deoxynucleotidyl transferase mediated nick end labeling (TUNEL) assay was carried out to assess chondrocyte apoptosis. RESULTS: The loss of ß-arrestin2 aggravated cartilage degeneration and subchondral bone destruction in the model of TMJOA at the early stage. Furthermore, in UAC groups, the expressions of degradative (Col-X) and inflammatory (TNF-α and IL-1ß) factors in condylar cartilage were increased in ß-arrestin2 null mice compared with WT mice. Moreover, the loss of ß-arrestin2 promoted apoptosis and autophagic process of chondrocytes at the early stage of TMJOA. CONCLUSION: In conclusion, we demonstrated for the first time that ß-arrestin2 plays a protective role in the development of TMJOA at the early stage, probably by inhibiting apoptosis and autophagic process of chondrocytes. Therefore, ß-arrestin2 might be a potential therapeutic target for TMJOA, providing a new insight for the treatment of TMJOA at the early stage.

Alzheimer's disease diagnosis from multi-modal data via feature inductive learning and dual multilevel graph neural network.

Multi-modal data can provide complementary information of Alzheimer's disease (AD) and its development from different perspectives. Such information is closely related to the diagnosis, prevention, and treatment of AD, and hence it is necessary and critical to study AD through multi-modal data. Existing learning methods, however, usually ignore the influence of feature heterogeneity and directly fuse features in the last stages. Furthermore, most of these methods only focus on local fusion features or global fusion features, neglecting the complementariness of features at different levels and thus not sufficiently leveraging information embedded in multi-modal data. To overcome these shortcomings, we propose a novel framework for AD diagnosis that fuses gene, imaging, protein, and clinical data. Our framework learns feature representations under the same feature space for different modalities through a feature induction learning (FIL) module, thereby alleviating the impact of feature heterogeneity. Furthermore, in our framework, local and global salient multi-modal feature interaction information at different levels is extracted through a novel dual multilevel graph neural network (DMGNN). We extensively validate the proposed method on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and experimental results demonstrate our method consistently outperforms other state-of-the-art multi-modal fusion methods. The code is publicly available on the GitHub website. (https://github.com/xiankantingqianxue/MIA-code.git).

An automated approach for predicting HAMD-17 scores via divergent selective focused multi-heads self-attention network.

This study introduces the Divergent Selective Focused Multi-heads Self-Attention Network (DSFMANet), an innovative deep learning model devised to automatically predict Hamilton Depression Rating Scale-17 (HAMD-17) scores in patients with depression. This model introduces a multi-branch structure for sub-bands and artificially configures attention focus factors on various branches, resulting in distinct attention distributions for different sub-bands. Experimental results demonstrate that when DSFMANet processes sub-band data, its performance surpasses current benchmarks in key metrics such as mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). This success is particularly evident in terms of MSE and MAE, where the performance of sub-band data is significantly superior, highlighting the model's potential in accurately predicting HAMD-17 scores. Concurrently, the experiment also compared the model's performance with sub-band and full-band data, affirming the superiority of the selective focus attention mechanism in electroencephalography (EEG) signal processing. DSFMANet, when utilizing sub-band data, exhibits higher data processing efficiency and reduced model complexity. The findings of this study underscore the significance of employing deep learning models based on sub-band analysis in depression diagnosis. The DSFMANet model not only effectively enhances the accuracy of depression diagnosis but also offers valuable research directions for similar applications in the future. This deep learning-based automated approach can effectively ascertain the HAMD-17 scores of patients with depression, thus offering more accurate and reliable support for clinical decision-making.

Effectiveness of high-risk human papillomavirus genotyping for cervical cancer screening. A multicentre screening cohort study in rural China.

BACKGROUND: This study aimed to assess the effectiveness of high-risk human papillomavirus (HR-HPV) primary testing for cervical cancer screening in China's rural areas. METHODS: Women aged 21-64 years were recruited. Cervical cytology was diagnosed following the Bethesda 2001 classification system, HPV infection (HR-HPV, HPV-16, HPV-18, and other 12 genotypes) identified by Cobas-4800, and colposcopy and biopsy performed when required. Primary outcomes were defined as the cumulative incidence of cervical intraepithelial neoplasia grade 2/3/higher (CIN2/3+) and its relative risk at baseline and at the 36-month follow-up. RESULTS: The study included 9,218 women; mean age was 45.15 years (SD: 8.74); 81% completed the follow-up. The most frequent type of cytological lesions (12.4% ) were ASCUS (8.4%) and LSIL (2.2%). HR-HPV infection (16.3%) was more prevalent in HPV-16 than in HPV-18 (3 vs 1.5%); a positive relationship with the severity of the lesions, from 29.8% in ASCUS to 89.6% in HSIL was found. At baseline, 3.5% of the patients underwent colposcopy; 20% had a positive diagnosis. At the 36-month follow-up, the cumulative incidences of CIN2+ and CIN3+ were higher in women with HR-HPV infection (16.9 vs 0.5% and 8.2 vs 0.2%). The relative risk of CIN2/3+ was lower in HR-HPV-negative women compared to those with a negative cytology at baseline (0.4; 95%CI: 0.3-0.4). CONCLUSIONS: High-risk HPV-based screening may significantly reduce the risk of CIN2/3+ compared with cytology testing. This may be a new resource for public health demands in China's rural areas.

Microstructure and Texture Evolution in Cold-Rolled and Annealed Oxygen-Free Copper Sheets.

Commercial oxygen-free copper sheets were cold-rolled with reduction rates ranging from 20% to 87% and annealed at 400, 500 and 600 °C. The microstructure and texture evolution during the cold-rolling and annealing processes were studied using optical microscopy (OM), scanning electron microscopy (SEM) and electron back-scattered diffraction (EBSD). The results show that the deformation textures of {123}<634> (S), {112}<111> (Copper) and {110}<112> (Brass) were continuously enhanced with the increase in cold-rolling reduction. The orientations along the α-oriented fiber converged towards Brass, and the orientation density of ß fiber obviously increased when the rolling reduction exceeded 60%. The recrystallization texture was significantly affected by the cold-rolling reduction. After 60% cold-rolling reduction, Copper and S texture components gradually decreased, and the {011}<511> recrystallization texture component formed with the increase in annealing temperature. After 87% cold-rolling reduction, a strong Cube texture formed, and other textures were inhibited with the increase in annealing temperature. The strong Brass and S deformation texture was conducive to the formation of a strong Cube annealing texture. The density of the annealing twin boundary decreased with the increase in annealing temperature, and more annealing twin boundaries formed in the oxygen-free copper sheets with the increase in cold-rolling reduction.

CENTRAL VENOUS-TO-ARTERIAL CARBON DIOXIDE PARTIAL PRESSURE DIFFERENCE AS A GUIDING PARAMETER FOR CARDIOTONIC DRUG ADMINISTRATION IN PATIENTS WITH EARLY-STAGE SEPTIC SHOCK.

ABSTRACT: Objective: This study aimed to investigate the effect of the central venous-to-arterial carbon dioxide partial pressure difference (Pcv-aCO2) on the administration of cardiotonic drugs in patients with early-stage septic shock. Methods: A retrospective study was conducted on 120 patients suffering from septic shock. At admission, the left ventricular ejection fraction (LVEF) and Pcv-aCO2 of the patients were obtained. On the premise of mean arterial pressure ≥ 65 mm Hg, the patients were divided into two groups according to the treatment approaches adopted by different doctors-control group: LVEF ≤50% and observation group: Pcv-aCO2 ≥ 6. Both groups received cardiotonic therapy. Results: The two groups of patients had similar general conditions and preresuscitation conditions ( P > 0.05). Compared with the control group, the observation group had a higher mean arterial pressure, lactic acid clearance rate, and urine output after 6 h of resuscitation ( P < 0.05), but a lower absolute value of lactic acid, total fluid intake in 24 h, and a lower number of patients receiving renal replacement therapy during hospitalization ( P < 0.05). After 6 hours of resuscitation, the percentages of patients meeting central venous oxygen saturation and central venous pressure targets were not significantly different between the control and observation groups ( P > 0.05). There was no difference in the 28-day mortality rate between the two groups ( P > 0.05). Conclusion: Pcv-aCO2 is more effective than LVEF in guiding the administration of cardiotonic drugs in the treatment of patients with septic shock.

Efficient data integration under prior probability shift.

Conventional supervised learning usually operates under the premise that data are collected from the same underlying population. However, challenges may arise when integrating new data from different populations, resulting in a phenomenon known as dataset shift. This paper focuses on prior probability shift, where the distribution of the outcome varies across datasets but the conditional distribution of features given the outcome remains the same. To tackle the challenges posed by such shift, we propose an estimation algorithm that can efficiently combine information from multiple sources. Unlike existing methods that are restricted to discrete outcomes, the proposed approach accommodates both discrete and continuous outcomes. It also handles high-dimensional covariate vectors through variable selection using an adaptive least absolute shrinkage and selection operator penalty, producing efficient estimates that possess the oracle property. Moreover, a novel semiparametric likelihood ratio test is proposed to check the validity of prior probability shift assumptions by embedding the null conditional density function into Neyman's smooth alternatives (Neyman, 1937) and testing study-specific parameters. We demonstrate the effectiveness of our proposed method through extensive simulations and a real data example. The proposed methods serve as a useful addition to the repertoire of tools for dealing dataset shifts.