Acupuncture and Escitalopram for Treating Major Depression Clinical Study (AE-TMDCS): protocol for a factorial randomised controlled trial.

INTRODUCTION: Major depressive disorder (MDD), the second leading cause of disability globally, is considered to be associated with a consequent deterioration in the quality of life and can lead to a major economic burden on medical service and suicide-related costs. Previous research has shown that acupuncture may be beneficial for treating MDD. However, there is a lack of rigorous evidence from previous studies comparing acupuncture with antidepressant medications. This study aims to assess the therapeutic potential of acupuncture in the management of depressive disorders. METHODS AND ANALYSIS: A multicentre, randomised, participant-blind, sham-controlled, 2×2 factorial clinical trial, Acupuncture and Escitalopram for Treating Major Depression Clinical Study, aims to compare the efficacy of acupuncture versus escitalopram in treating depression. This study will be conducted at three hospitals in China, enrolling 260 patients with moderate-to-severe major depression, as defined by DSM-5 criteria and Hamilton Depression Rating Scale (HDRS-17) Scores above 17. Participants will be randomly assigned in equal proportions to one of four groups (acupuncture/escitalopram, sham acupuncture/escitalopram, acupuncture/placebo and sham acupuncture/placebo) and undergo 30 sessions across 10 weeks. The primary outcome is change in HDRS-17 Score and secondary outcomes include BDI, Clinical Global Impression, Generalised Anxiety Disorder-7 and Mini-Mental State Examination Scores, alongside potential biological markers. ETHICS AND DISSEMINATION: Ethical approval for the study was granted by the Ethics Committees of the Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine (2023-7th-HIRB-020), Shanghai Mental Health Centre (2022-86) and Shanghai Pudong New Area Hospital of Traditional Chinese Medicine (2023-003). Informed consent will be obtained from all participants. The study's findings are intended for publication in a scholarly journal. TRIAL REGISTRATION: NCT05901571.

Physical Compatibility of Reduced Glutathione for Injection With 44 Intravenous Drugs During Simulated Y-site Administration.

PURPOSE: Reduced glutathione (GSH) is extensively used in clinical therapeutics due to its antioxidative and cytoprotective properties. It is essential in the management of various chronic and acute conditions and serves as an adjunct therapy in oncology. Despite its widespread use, the physical compatibility of GSH with other intravenous drugs during Y-site administration has not been thoroughly investigated, posing risks such as reduced efficacy and adverse reactions. This study fills this critical gap by examining the physical compatibility of GSH with 44 commonly used intravenous drugs in simulated Y-site administration with 0.9% sodium chloride injection (NS) and 5% dextrose injection, aiming to enhance patient safety and clinical outcomes. METHODS: Simulated Y-site administration was conducted in vitro by mixing 24 mg/mL of GSH with equal volumes of 44 diluted intravenous drugs. Physical compatibility was assessed by observing visual changes, checking for the Tyndall effect, measuring turbidity, and monitoring pH levels at 0, 0.5, 1, 2, and 4 hours post-mixing. Physical compatibility was defined as the absence of color changes, gas evolution, particulate formation, and the Tyndall effect within 4 hours, with turbidity changes of less than 0.5 nephelometric turbidity units from baseline and pH variations of less than 10% from initial values. FINDINGS: GSH exhibited physical incompatibility with 11 of the 44 intravenous drugs evaluated, while it remained compatible with 33 drugs over 4 hours. IMPLICATIONS: This study reveals that while GSH is physically compatible with the majority of tested intravenous drugs, incompatibilities with 11 drugs under simulated Y-site conditions necessitate rigorous compatibility testing prior to co-administration in clinical settings. These findings emphasize the importance of such testing to prevent potential treatment failures and adverse effects. Further research is needed to explore chemical stability and therapeutic efficacy in clinical settings, ensuring the safe and effective use of GSH in medical treatments.

HDAC1 and HDAC2 orchestrate Wnt signaling to regulate neural progenitor transition during brain development.

Tightly controlled neurogenesis is crucial for generating the precise number of neurons and establishing the intricate architecture of the cortex, with deficiencies often leading to neurodevelopmental disorders. Neuroepithelial progenitors (NPs) transit into radial glial progenitors (RGPs) to initiate neural differentiation, yet the governing mechanisms remain elusive. Here, we found that histone deacetylases 1 and 2 (HDAC1/2) mediated suppression of Wnt signaling is essential for the NP-to-RGP transition. Conditional depletion of HDAC1/2 from NPs upregulated Wnt signaling genes, impairing the transition to RGPs and resulting in rosette structures within the neocortex. Multi-omics analysis revealed that HDAC1/2 are critical for downregulating Wnt signaling, identifying Wnt9a as a key target. Overexpression of Wnt9a led to an increased population of NPs and the disruption of cortical organization. Notably, Wnt inhibitor administration partially rescued the disrupted cortical architecture. Our findings reveal the significance of tightly controlled Wnt signaling through epigenetic mechanisms in neocortical development.

Internal Space Modulation of Yolk-Shell FeSe2@Carbon Anode with Peanut-Shaped Morphology Enabling Ultra-Stable and Fast Potassium-Ion Storage.

The poor cycling stability and rate performance of transition metal selenides (TMSs) are caused by their intrinsic low conductivity and poor structural stability, which hinders their application in potassium-ion batteries (PIBs). To address this issue, encapsulating TMSs within carbon nanoshells is considered a viable strategy. However, due to the lack and uncontrollability of internal void space, this structure cannot effectively mitigate the volume expansion induced by large K+, resulting in unsatisfactory electrochemical performance. Herein, peanut-shaped FeSe2@carbon yolk-shell capsules are prepared by modulation of the internal space. The active FeSe2 is encapsulated within a robust carbon shell and an optimal void space is retained between them. The outer carbon shell promotes electronic conductivity and avoids FeSe2 aggregation, while the internal void mitigates volume expansion and effectively ensures the structural integrity of the electrode. Consequently, the FeSe2@carbon anode demonstrates exceptional rate performance (242 mAh g-1 at 10 A g-1) and long cycling stability (350 mAh g-1 after 500 cycles at 1 A g-1). Furthermore, the effect of internal space modulation on electrochemical properties is elucidated. Meanwhile, ex situ characterizations elucidate the K+ storage mechanism. This work provides effective guidance for the design and the internal space modulation of advanced TMSs yolk-shell structures.

Impact of ginsenoside Rb1 on gut microbiome and associated changes in pharmacokinetics in rats.

Ginsenoside Rb1 exhibits a wide range of biological activities, and gut microbiota is considered the main metabolic site for Rb1. However, the impact of gut microbiota on the pharmacokinetics of Rb1 are still uncertain. In this study, we investigated the gut microbiome changes and the pharmacokinetics after a 30 d Rb1 intervention. Results reveal that the systemic exposure and metabolic clearance rate of Rb1 and Rd were substantially affected after orally supplementing Rb1 (60 mg/kg) to rats. Significant increase in the relative abundance of Bacteroides cellulosilyticus in gut microbiota and specific glycoside hydrolase (GH) families, such as GH2, GH92, and GH20 were observed based on microbiome and metagenomic analysis. Moreover, a robust association was identified between the pharmacokinetic parameters of Rb1 and the relative abundance of specific Bacteroides species, and glycoside hydrolase families. Our study demonstrates that Rb1 administration significantly affects the gut microbiome, revealing a complex relationship between B. cellulosilyticus, key GH families, and Rb1 pharmacokinetics.

Investigating the influence of urban morphology on pluvial flooding: Insights from urban catchments in England (UK).

As climate change intensifies, cities globally are experiencing more severe rainfall and frequent pluvial floods. Urban expansion is altering the permeability of the land, thus increasing the risk of flooding. This study investigates the impact of urban morphology on pluvial floodwater distribution in 15 urban catchments across England, UK, to provide an analysis of how urban morphology influences flood magnitude. Using a cellular automata-based model, pluvial flood simulations were conducted for catchments characterized by diverse urban morphologies. Then a series of machine learning models were adopted to reveal the relationships between the morphological characteristics of urban configurations (e.g., building footprints, impervious surfaces, street network, topography) and pluvial flooding. These models were used to identify and quantify the effects of key urban morphological indicators on pluvial flooding. The results indicate that, although the total area of impervious surfaces plays the most significant role in floodwater distribution, the edge density (ED) of building footprints and impervious surfaces also influences this process. Synthetic experiments with an exemplary urban fabric show that decreasing "ED of building footprint" and increasing "ED of impervious surface" can mitigate flood volume by up to 6.3 % at 100 % drainage efficiency and 7.8 % at 50 % efficiency. The results of this study are anticipated to aid urban planners and policymakers in developing strategies for implementing flood-resilient cities.

Mapping the constituent preference of tree species for capturing particulate matter on leaf surfaces using single-particle mass spectrometry and supervised machine learning.

Respiratory health is negatively influenced by the dimensions and constituents of particulate matter (PM). Although mass concentration is widely acknowledged to be key to assessing dust retention by urban trees, the role of plant leaves in filtering PM from the urban atmosphere, particularly regarding the particle dimensions and chemical constituents of retained PM on the leaf, remains elusive. Here we combined single-particle aerosol mass spectrometry and a particle resuspension chamber to investigate how urban tree species capture PM constituents. Results indicate that leaves are efficient in capturing relatively larger particles (1.0-2.0 µm). Compositionally, airborne particles were mostly composed of elemental carbon (EC, 20%), organic carbon (OC, 17%), and secondary reaction products (13%). However, leaf surfaces revealed a preference for retaining crustal species, comprising 55% of captured particulates. Notably, specific tree species demonstrated varied affinities for different PM constituents: Osmanthus fragrans Lour. predominantly captured levoglucosan (LEV), indicative of its efficiency against biomass burning particles, whereas Cinnamomum camphora (L.) J.Presl and Sabina chinensis var. kaizuca W.C.Cheng & W.T.Wang were more effective in capturing heavy metals (HMs). XGBoost modelling identified indicator ions, e.g., CN-, NO3-, NO2-, PO3-, with SHAP values surpassing 0.035, suggesting a preferential adsorption of these ions among different tree species. These findings demonstrate that the particulate capture efficiency of urban tree species varies with species-specific leaf properties, particularly in their ability to selectively adsorb particles containing hazardous constituents such as LEV and HMs. This study provides a scientific basis for the strategic selection of tree species in urban forestry initiatives aimed at improving air quality and public health.

Evaluation of Phenazine Derivatives from the Lichen-Associated Streptomyces flavidovirens as Potent Antineuroinflammatory Agents In Vitro and In Vivo.

Eighteen nitrogen-containing compounds (1-18) were isolated from cultures of the lichen-associated Streptomyces flavidovirens collected from the Qinghai-Tibet Plateau, including seven phenazine derivatives with three new ones, named subphenazines A-C (2-4), two new furan pyrrolidones (8-9), and nine known alkaloids. The structures were elucidated by spectroscopic data analysis, and absolute configurations were determined by single-crystal X-ray diffraction and ECD calculations. The phenazine-type derivatives, in particular compound 3, exhibited significantly better antineuroinflammatory activity than other isolated compounds (8-18). Compound 3 inhibited the release of proinflammatory cytokines including IL-6, TNF-α, and PGE2, and the nuclear translocation of NF-κB; it also reduced the oxidative stress and activated the Nrf2 signaling pathway in LPS-induced BV2 microglia cells. In vivo anti-inflammatory activity in zebrafish indicated that 3 inhibited LPS-stimulated ROS generation. These findings suggested that compound 3 might be a potent antineuroinflammatory agent through the regulation of the NF-κB/Nrf2 signaling pathways.

From crisis to cure: harnessing the potential of mycobacteriophages in the battle against tuberculosis.

Tuberculosis (TB) is a serious and fatal disease caused by Mycobacterium tuberculosis (Mtb). The World Health Organization reported an estimated 1.30 million TB-related deaths in 2022. The escalating prevalence of Mtb strains classified as being multi-, extensively, extremely, or totally drug resistant, coupled with the decreasing efficacies of conventional therapies, necessitates the development of novel treatments. As viruses that infect Mycobacterium spp., mycobacteriophages may represent a strategy to combat and eradicate drug-resistant TB. More exploration is needed to provide a comprehensive understanding of mycobacteriophages and their genome structure, which could pave the way toward a definitive treatment for TB. This review focuses on the properties of mycobacteriophages, their potential in diagnosing and treating TB, the benefits and drawbacks of their application, and their use in human health. Specifically, we summarize recent research on mycobacteriophages targeted against Mtb infection and newly developed mycobacteriophage-based tools to diagnose and treat diseases caused by Mycobacterium spp. We underscore the urgent need for innovative approaches and highlight the potential of mycobacteriophages as a promising avenue for developing effective diagnosis and treatment to combat drug-resistant Mycobacterium strains.

KMT2D mutations promoted tumor progression in diffuse large B-cell lymphoma through altering tumor-induced regulatory T cell trafficking via FBXW7-NOTCH-MYC/TGF-ß1 axis.

Histone methyltransferase KMT2D is one of the most frequently mutated genes in diffuse large B-cell lymphoma (DLBCL) and has been identified as an important pathogenic factor and prognostic marker. However, the biological relevance of KMT2D mutations on tumor microenvironment remains to be determined. KMT2D mutations were assessed by whole-genome/exome sequencing (WGS/WES) in 334 patients and by targeted sequencing in 427 patients with newly diagnosed DLBCL. Among all 761 DLBCL patients, somatic mutations in KMT2D were observed in 143 (18.79%) patients and significantly associated with advanced Ann Arbor stage and MYC expression ≥ 40%, as well as inferior progression-free survival and overall survival. In B-lymphoma cells, the mutation or knockdown of KMT2D inhibited methylation of lysine 4 on histone H3 (H3K4), downregulated FBXW7 expression, activated NOTCH signaling pathway and downstream MYC/TGF-ß1, resulting in alterations of tumor-induced regulatory T cell trafficking. In B-lymphoma murine models established with subcutaneous injection of SU-DHL-4 cells, xenografted tumors bearing KMT2D mutation presented lower H3K4 methylation, higher regulatory T cell recruitment, thereby provoking rapid tumor growth compared with wild-type KMT2D via FBXW7-NOTCH-MYC/TGF-ß1 axis.

Five-year follow-up of OCT-guided percutaneous coronary intervention in patients with ST-segment elevation myocardial infarction.

BACKGROUND: Compared with intravascular ultrasound guidance, there is limited evidence for optical coherence tomography (OCT) guidance during primary percutaneous coronary intervention (pPCI) in ST-segment elevation myocardial infarction (STEMI) patients. AIMS: We investigated the role of OCT in guiding a reperfusion strategy and improving the long-term prognosis of STEMI patients. METHODS: All patients who were diagnosed with STEMI and who underwent pPCI between January 2017 and December 2020 were enrolled and divided into OCT-guided versus angiography-guided cohorts. They had routine follow-up for up to 5 years or until the time of the last known contact. All-cause death and cardiovascular death were designated as the primary and secondary endpoints, respectively. RESULTS: A total of 3,897 patients were enrolled: 2,696 (69.2%) with OCT guidance and 1,201 (30.8%) with angiographic guidance. Patients in the OCT-guided cohort were less often treated with stenting during pPCI (62.6% vs 80.2%; p<0.001). The 5-year cumulative rates of all-cause mortality and cardiovascular mortality in the OCT-guided cohort were 10.4% and 8.0%, respectively, significantly lower than in the angiography-guided cohort (19.0% and 14.1%; both log-rank p<0.001). All 4 multivariate models showed that OCT guidance could significantly reduce 5-year all-cause mortality (hazard ratio [HR] in model 4: 0.689, 95% confidence interval [CI]: 0.551-0.862) and cardiovascular mortality (HR in model 4: 0.692, 95% CI: 0.536-0.895). After propensity score matching, the benefits of OCT guidance were consistent in terms of all-cause mortality (HR: 0.707, 95% CI: 0.548-0.913) and cardiovascular mortality (HR: 0.709, 95% CI: 0.526-0.955). CONCLUSIONS: Compared with angiography alone, OCT guidance may change reperfusion strategies and lead to better long-term survival in STEMI patients undergoing pPCI. Findings in the current observational study should be further corroborated in randomised trials.

Evaluating Safety and Clinical Activity of Front-line Treatment with Cadonilimab plus Chemotherapy in Advanced/Metastatic Nonsmall Cell Lung Cancer Harboring STK11 Genetic Aberration: A Protocol of Phase II Study.

BACKGROUND: Cadonilimab is a first-in-class bispecific PD-1/CTLA-4 antibody. Serine/threonine kinase (STK11) mutation was shown to be related to low PD-L1 expression and objective response rate (ORR) in nonsmall cell lung cancer (NSCLC), resulting in poor progression-free survival (PFS) and overall survival (OS). Herein, we hypothesized that combining cadonilimab with chemotherapy could enhance antitumor immunity and extend survival in these patients. Consequently, we designed this study to explore the clinical activity and safety of cadonilimab combined with chemotherapy in patients with advanced/metastatic NSCLC harboring STK11 alteration. TRIAL DESIGN: This single-center, open-label, single-arm phase II trial is conducted at the first affiliated hospital of Guangzhou Medical University. Treatment-naïve advanced/metastatic NSCLC patients harboring STK11 mutation will be enrolled in this study. Eligible patients will receive either cadonilimab (10mg/kg on Day 1) plus pemetrexed (500 mg/m2) and carboplatin (AUC = 5) for nonsquamous NSCLC or abraxane (100 mg/m2) and carboplatin (AUC = 5) for squamous NSCLC for 4 cycles, followed by maintenance therapy (cadonilimab plus pemetrexed or abraxane). The treatment will be discontinued when disease progression, intolerability to cadonilimab, and/or chemotherapy occurs. Measurable lesions were assessed according to the Response Evaluation Criteria in Solid Tumors (1.1). The main endpoint is ORR and safety. Subordinate endpoints include PFS, disease control rate, and duration of response. RESULTS: The study commenced enrolment in September 2023, with preliminary findings regarding the primary endpoint anticipated by January 2025.

Problem-solving ability and future time perspective among the Chinese nursing interns: The mediating role of future work self.

BACKGROUND: The significance of problem-solving ability has been confirmed in numerous studies worldwide, highlighting its role in enhancing the skills of nursing interns and reducing psychological pressure. However, existing research indicates that the problem-solving ability of nursing interns urgently needs to be further improved. Limited research has been conducted on the problem-solving ability of nursing interns, and the correlations among problem-solving ability, future time perspective, and future work self of Chinese nursing interns are unclear. OBJECTIVES: To investigate problem-solving ability, future time perspective, and future work self among the Chinese nursing interns, and to examine the relationships among these variables. Additionally, the study aims to explore the mediating role of future work self between problem-solving ability and future time perspective. METHODS: A cross-sectional and correlational design was employed, adhering to the quality reporting conformed to the STROBE Checklist. From May 8, 2023, to February 15, 2024, 1,251 nursing interns were recruited from 15 tertiary grade-A hospitals across six cities in China. The Demographic Characteristics Questionnaire, Social Problem-Solving Inventory, Future Time Perspective Inventory, and Future Work Self Scale were used. The data was analyzed using descriptive statistics, univariate, correlation, and process plug-in mediation effect analyses. RESULTS: The total scores for problem-solving ability, future time perspective, and future work self were 64.39 ± 18.55, 45.08 ± 11.37, and 16.92 ± 5.28, respectively. Problem-solving ability was positively correlated with future time perspective (r = 0.638, p < 0.001) and future work self (r = 0.625, p < 0.001). Additionally, future work self partially mediated mediating role between problem-solving ability and future time perspective, accounting for 39.7% of the total effect. CONCLUSION: The problem-solving ability, future time perspective, and future work self among the Chinese nursing interns were relatively moderate, indicating a need for improvement. It is suggested that nursing managers and educators should actively implement career management and planning programs. By enhancing the future time perspective and future work self of nursing interns, their problem-solving ability can be improved. This, in turn, will facilitate their adaptation to clinical work, enhance the quality of nursing care, and promote the development of their nursing profession.

[Robot-assisted versus traditional fluoroscopy-assisted posterior fixation in treatment of thoracolumbar fractures with ankylosing spondylitis: a retrospective study].

Objective: To compare the effectiveness of robot-assisted (RA) minimally invasive surgery versus traditional fluoroscopy-assisted (FA) open posterior fixation surgery in treating thoracolumbar fractures with ankylosing spondylitis (AS). Methods: A clinical data of 21 cases of thoracolumbar fractures with AS who met the selection criteria between December 2016 and December 2023 was retrospectively analyzed. Ten cases underwent RA minimally invasive surgery group (RA group) and 11 cases underwent FA open posterior fixation surgery (FA group). There was no significant difference in gender, age, fracture segment distribution, fracture type, time from injury to surgery, visual analogue scale (VAS) score, and American Spinal Injury Association (ASIA) grading between RA group and FA group ( P>0.05). The operation time, intraoperative blood loss, radiation exposure time, radiation dose, hospital stay, and complications of the two groups were recorded. According to Gertzbein-Robbins criteria, the accuracy of screw implantation was evaluated by CT within 1 week after surgery. During follow-up, pain and nerve function were evaluated by VAS score and ASIA grading. Results: All patients underwent surgery successfully, and there was no significant difference in operation time ( P>0.05). The intraoperative blood loss and hospital stay in the RA group were significantly less than those in the FA group ( P<0.05), and the radiation exposure time and radiation dose were significantly more than those in the FA group ( P<0.05). A total of 249 pedicle screws were implanted in the two groups, including 118 in the RA group and 131 in the FA group. According to the Gertzbein-Robbins criteria, the proportion of clinically acceptable screws (grades A and B) in the RA group was significantly higher than that in the FA group ( P<0.05). Patients in both groups were followed up 3-12 months, with an average of 6.8 months. The VAS scores of the two groups after surgery were significantly lower than those before surgery, and the differences were significant ( P<0.05). The RA group had lower scores than the fluoroscopy group at 1 week and 3 months after surgery ( P<0.05). There was no significant difference in neurological function grading between groups at 1 week and 3 months after surgery ( P>0.05). In the FA group, 1 case of deep infection and 1 case of deep vein thrombosis of lower extremity occurred, while no complication occurred in the RA group, and there was no significant difference in the incidence of complications between groups ( P>0.05). Conclusion: Both RA minimally invasive surgery and FA open posterior fixation surgery can achieve good effectiveness. Compared with the latter, the former has more advantages in terms of intraoperative blood loss, hospital stay, and accuracy of pedicle screw insertion.

GMMID: genetically modified mice information database.

Genetically engineered mouse models (GEMMs) are vital for elucidating gene function and disease mechanisms. An overwhelming number of GEMM lines have been generated, but endeavors to collect and organize the information of these GEMMs are seriously lagging behind. Only a few databases are developed for the information of current GEMMs, and these databases lack biological descriptions of allele compositions, which poses a challenge for nonexperts in mouse genetics to interpret the genetic information of these mice. Moreover, these databases usually do not provide information on human diseases related to the GEMM, which hinders the dissemination of the insights the GEMM provides as a human disease model. To address these issues, we developed an algorithm to annotate all the allele compositions that have been reported with Python programming and have developed the genetically modified mice information database (GMMID; http://www.gmmid.cn), a user-friendly database that integrates information on GEMMs and related diseases from various databases, including National Center for Biotechnology Information, Mouse Genome Informatics, Online Mendelian Inheritance in Man, International Mouse Phenotyping Consortium, and Jax lab. GMMID provides comprehensive genetic information on >70 055 alleles, 65 520 allele compositions, and ∼4000 diseases, along with biologically meaningful descriptions of alleles and allele combinations. Furthermore, it provides spatiotemporal visualization of anatomical tissues mentioned in these descriptions, shown alongside the allele compositions. Compared to existing mouse databases, GMMID considers the needs of researchers across different disciplines and presents obscure genetic information in an intuitive and easy-to-understand format. It facilitates users in obtaining complete genetic information more efficiently, making it an essential resource for cross-disciplinary researchers. Database URL: http://www.gmmid.cn.

A precise microdissection strategy enabled spatial heterogeneity analysis on the targeted region of formalin-fixed paraffin-embedded tissues.

In recent years, the development of spatial transcriptomic technologies has enabled us to gain an in-depth understanding of the spatial heterogeneity of gene expression in biological tissues. However, a simple and efficient tool is required to analyze multiple spatial targets, such as mRNAs, miRNAs, or genetic mutations, at high resolution in formalin-fixed paraffin-embedded (FFPE) tissue sections. In this study, we developed hydrogel pathological sectioning coupled with the previously reported Sampling Junior instrument (HPSJ) to assess the spatial heterogeneity of multiple targets in FFPE sections at a scale of 180 µm. The HPSJ platform was used to demonstrate the spatial heterogeneity of 9 ferroptosis-related genes (TFRC, NCOA4, FTH1, ACSL4, LPCAT3, ALOX12, SLC7A11, GLS2, and GPX4) and 2 miRNAs (miR-185-5p and miR522) in FFPE tissue samples from patients with triple-negative breast cancer (TNBC). The results validated the significant heterogeneity of ferroptosis-related mRNAs and miRNAs. In addition, HPSJ confirmed the spatial heterogeneity of the L858R mutation in 7 operation-sourced and 4 needle-biopsy-sourced FFPE samples from patients with lung adenocarcinoma (LUAD). The successful detection of clinical FFPE samples indicates that HPSJ is a precise, high-throughput, cost-effective, and universal platform for analyzing spatial heterogeneity, which is beneficial for elucidating the mechanisms underlying drug resistance and guiding the prescription of mutant-targeted drugs in patients with tumors.

CTHNet: a network for wheat ear counting with local-global features fusion based on hybrid architecture.

Accurate wheat ear counting is one of the key indicators for wheat phenotyping. Convolutional neural network (CNN) algorithms for counting wheat have evolved into sophisticated tools, however because of the limitations of sensory fields, CNN is unable to simulate global context information, which has an impact on counting performance. In this study, we present a hybrid attention network (CTHNet) for wheat ear counting from RGB images that combines local features and global context information. On the one hand, to extract multi-scale local features, a convolutional neural network is built using the Cross Stage Partial framework. On the other hand, to acquire better global context information, tokenized image patches from convolutional neural network feature maps are encoded as input sequences using Pyramid Pooling Transformer. Then, the feature fusion module merges the local features with the global context information to significantly enhance the feature representation. The Global Wheat Head Detection Dataset and Wheat Ear Detection Dataset are used to assess the proposed model. There were 3.40 and 5.21 average absolute errors, respectively. The performance of the proposed model was significantly better than previous studies.

Study on the treatment of dysphagia after stroke with electromyographic biofeedback intensive training.

BACKGROUND: Dysphagia, or swallowing disorder, is a common complication following stroke, significantly impacting patients' quality of life. Electromyographic biofeedback (EMGBF) therapy has emerged as a potential rehabilitation technique to improve swallowing function, but its efficacy in comparison with conventional treatments remains to be further explored. AIM: To investigate the effects of different treatment intensities of EMGBF on swallowing function and motor speed after stroke. METHODS: The participants were divided into three groups, all of which received routine neurological drug therapy and motor function rehabilitation training. On the basis of routine swallowing disorder training, the EMGBF group received additional EMGBF training, while the enhanced EMGBF group received two additional training sessions. Four weeks before and after treatment, the degree of swallowing disorder was evaluated using the degree of swallowing disorder score (VGF) and the Rosenbek penetration-aspiration scale (PAS). RESULTS: Initially, there was no significant difference in VGF and PAS scores among the groups (P > 0.05). After four weeks, all groups showed significant improvement in both VGF scores and PAS scores. Furthermore, the standardized swallowing assessment and videofluoroscopic dysphagia scale scores also improved significantly post-treatment, indicating enhanced swallowing function and motor function of the hyoid-bone laryngeal complex, particularly in the intensive EMGBF group. CONCLUSION: EMGBF training is more effective than traditional swallowing training in improving swallowing function and the movement rate of the hyoid laryngeal complex in patients with post-stroke dysphagia.

Mechano-growth factor regulates periodontal ligament stem cell proliferation and differentiation through Fyn-RhoA-YAP signaling.

BACKGROUND: Mechano-growth factor (MGF), which is a growth factor produced specifically in response to mechanical stimuli, with potential of tissue repair and regeneration. Our previous research has shown that MGF plays a crucial role in repair of damaged periodontal ligaments by promoting differentiation of periodontal ligament stem cells (PDLSCs). However, the molecular mechanism is not fully understood. This study aimed to investigated the regulatory effect of MGF on differentiation of PDLSCs and its molecular mechanism. METHODS: Initially, we investigated how MGF impacts cell growth and differentiation, and the relationship with the activation of Fyn-p-YAPY357 and LATS1-p-YAPS127. Then, inhibitors were used to interfere Fyn phosphorylation to verify the role of Fyn-p-YAP Y357 signal after MGF stimulation; moreover, siRNA was used to downregulate YAP expression to clarify the function of YAP in PDLSCs proliferation and differentiation. Finally, after C3 was used to inhibit the RhoA expression, we explored the role of RhoA in the Fyn-p-YAP Y357 signaling pathway in PDLSCs proliferation and differentiation. RESULTS: Our study revealed that MGF plays a regulatory role in promoting PDLSCs proliferation and fibrogenic differentiation by inducing Fyn-YAPY357 phosphorylation but not LATS1-YAP S127 phosphorylation. Moreover, the results indicated that Fyn could not activate YAP directly but rather activated YAP through RhoA in response to MGF stimulation. CONCLUSION: The research findings indicated that the Fyn-RhoA-p-YAPY357 pathway is significant in facilitating the proliferation and fibrogenic differentiation of PDLSCs by MGF. Providing new ideas for the study of MGF in promoting periodontal regenerative repair.

AI-Based multimodal Multi-tasks analysis reveals tumor molecular heterogeneity, predicts preoperative lymph node metastasis and prognosis in papillary thyroid carcinoma: A retrospective study.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the predominant form of thyroid cancer globally, especially when lymph node metastasis (LNM) occurs. Molecular heterogeneity, driven by genetic alterations and tumor microenvironment components, contributes to the complexity of PTC. Understanding these complexities is essential for precise risk stratification and therapeutic decisions. METHODS: This study involved a comprehensive analysis of 521 patients with PTC from our hospital and 499 patients from The Cancer Genome Atlas (TCGA). The real-world cohort 1 comprised 256 patients with stage I-III PTC. Tissues from 252 patients were analyzed by DNA-based next-generation sequencing, and tissues from four patients were analyzed by single-cell RNA sequencing (scRNA-seq). Additionally, 586 PTC pathological sections were collected from TCGA, and 275 PTC pathological sections were collected from the real-world cohort 2. A deep learning multimodal model was developed using matched histopathology images, genomic, transcriptomic, and immune cell data to predict LNM and disease-free survival (DFS). RESULTS: This study included a total of 1,011 PTC patients, comprising 256 patients from cohort 1, 275 patients from cohort 2, and 499 patients from TCGA. In cohort 1, we categorized PTC into four molecular subtypes based on BRAF, RAS, RET, and other mutations. BRAF mutations were significantly associated with LNM and impacted DFS. ScRNA-seq identified distinct T cell subtypes and reduced B cell diversity in BRAF-mutated PTC with LNM. The study also explored cancer-associated fibroblasts and macrophages, highlighting their associations with LNM. The deep learning model was trained using 405 pathology slides and RNA sequences from 328 PTC patients and validated with 181 slides and RNA sequences from 140 PTC patients in the TCGA cohort. It achieved high accuracy, with an AUC of 0.86 in the training cohort, 0.84 in the validation cohort, and 0.83 in the real-world cohort 2. High-risk patients in the training cohort had significantly lower DFS rates (P<0.001). Model AUCs were 0.91 at 1 year, 0.93 at 3 years, and 0.87 at 5 years. In the validation cohort, high-risk patients also had lower DFS (P<0.001); the AUCs were 0.89, 0.87, and 0.80 at 1, 3, and 5 years. We utilized the GradCAM algorithm to generate heatmaps from pathology-based deep learning models, which visually highlighted high-risk tumor areas in PTC patients. This enhanced clinicians' understanding of the model's predictions and improved diagnostic accuracy, especially in cases with lymph node metastasis. CONCLUSION: The AI-based analysis uncovered vital insights into PTC molecular heterogeneity, emphasizing BRAF mutations' impact. The integrated deep learning model shows promise in predicting metastasis, offering valuable contributions to improved diagnostic and therapeutic strategies.