A review of functions and mechanisms of clay soil conditioners and catalysts in thermal remediation compared to emerging photo-thermal catalysis.

High temperatures and providing sufficient time for the thermal desorption of persistent organic pollutants (POPs) from contaminated clay soils can lead to intensive energy consumption. Therefore, this article provides a critical review of the potential additives which can improve soil texture and increase the volatility of POPs, and then discusses their enhanced mechanisms for contributing to a green economy. Ca-based additives have been used to reduce plasticity of bentonite clay, absorb water and replenish system heat. In contrast, non-Ca-based additives have been used to decrease the plasticity of kaolin clay. The soil structure and soil plasticity can be changed through cation exchange and flocculation processes. The transition metal oxides and alkali metal oxides can be applied to catalyze and oxidize polycyclic aromatic hydrocarbons, petroleum and emerging contaminants. In this system, reactive oxygen species (•O2- and •OH) are generated from thermal excitation without strong chemical oxidants. Moreover, multiple active ingredients in recycled solid wastes can be controlled to reduce soil plasticity and enhance thermal catalysis. Alternatively, the alkali, nano zero-valent iron and nano-TiN can catalyze hydrodechlorination of POPs under reductive conditions. Especially, photo and photo-thermal catalysis are discussed to accelerate replacement of fossil fuels by renewable energy in thermal remediation.

Postnatal development of rat retina: a continuous observation and comparison between the organotypic retinal explant model and in vivo development.

JOURNAL/nrgr/04.03/01300535-202503000-00033/figure1/v/2024-06-17T092413Z/r/image-tiff The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures. However, the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies. Thus, we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina. In this study, we showed that postnatal retinal explants undergo normal development, and exhibit a consistent structure and timeline with retinas in vivo. Initially, we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells. We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin, respectively. Ki-67- and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis, and exhibited a high degree of similarity in abundance and distribution between groups. Additionally, we used Ceh-10 homeodomain-containing homolog, glutamate-ammonia ligase (glutamine synthetase), neuronal nuclei, and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells, Müller glia, mature neurons, and microglia, respectively. The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas. Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development. The findings confirm the accuracy and credibility of this model and support its use for long-term, systematic, and continuous observation.

Subclassification of lung adenocarcinoma through comprehensive multi-omics data to benefit survival outcomes.

OBJECTIVES: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of great clinical significance. This study aims to identify novel molecular markers associated with LUAD subtypes, with the goal of improving the precision of LUAD subtype classification. Additionally, optimization efforts are directed towards enhancing insights from the perspective of patient survival analysis. MATERIALS AND METHODS: We propose an innovative feature-selection approach that focuses on LUAD classification, which is comprehensive and robust. The proposed method integrates multi-omics data from The Cancer Genome Atlas (TCGA) and leverages a synergistic combination of max-relevance and min-redundancy, least absolute shrinkage and selection operator, and Boruta algorithms. These selected features were deployed in six machine-learning classifiers: logistic regression, random forest, support vector machine, naive Bayes, k-Nearest Neighbor, and XGBoost. RESULTS: The proposed approach achieved an area under the receiver operating characteristic curve (AUC) of 0.9958 for LR. Notably, the accuracy and AUC of a composite model incorporating copy number, methylation, as well as RNA- sequencing data for expression of exons, genes, and miRNA mature strands surpassed the accuracy and AUC metrics of models with single-omics data or other multi-omics combinations. Survival analyses, revealed the SVM classifier to elicit optimal classification, outperforming that achieved by TCGA. To enhance model interpretability, SHapley Additive exPlanations (SHAP) values were utilized to elucidate the impact of each feature on the predictions. Gene Ontology (GO) enrichment analysis identified significant biological processes, molecular functions, and cellular components associated with LUAD subtypes. CONCLUSION: In summary, our feature selection process, based on TCGA multi-omics data and combined with multiple machine learning classifiers, proficiently identifies molecular subtypes of lung adenocarcinoma and their corresponding significant genes. Our method could enhance the early detection and diagnosis of LUAD, expedite the development of targeted therapies and, ultimately, lengthen patient survival.

pH-responsive oxygen self-sufficient smart nanoplatform for enhanced tumor chemotherapy and photodynamic therapy.

Premature drug release in chemotherapy and hypoxic conditions in photodynamic therapy (PDT) are perplexing problems in tumor treatment. Thus, it is of great significance to develop the novel therapeutic system with controllable drug release and effective oxygen generation. Herein, a pH-responsive oxygen self-sufficient smart nanoplatform (named DHCCC), integrating hollow mesoporous silica nanoparticles (HMSNs), chitosan (CS), doxorubicin hydrochloride (DOX), chlorin e6 (Ce6) and catalase (CAT), is fabricated to enhance the tumor therapeutic efficacy efficiently through avoiding premature drug release and mitigating hypoxia of tumor microenvironment (TME). The drug DOX can be efficiently loaded into the HMSNs with large cavity and be controllable released because of the pH responsiveness of CS to the weak acidic TME, thereby elevating the chemotherapy efficacy. Meanwhile, CAT can catalyze the decomposition of endogenous hydrogen peroxide in situ generating oxygen to alleviate the hypoxia and enhance the PDT efficiency considerably. In vitro and in vivo results demonstrate that the combined chemo-photodynamic therapy based on the DHCCC nanoplatform exerts more effective antitumor efficacy than chemotherapy or PDT alone. The current study provides a promising inspiration to construct the pH-responsive oxygen self-sufficient smart nanomedicine with potentials to prevent premature drug leakage and overcome hypoxia for efficient tumor therapy.

Self-Assembled MXene Supported on Carbonization-Free Wood for a Symmetrical All-Wood Eco-Supercapacitor.

As an emerging two-dimensional (2D) material, MXene has garnered significant interest in advanced energy storage systems, yet the stackable structure, poor mechanical stability, and lack of moldability limit its large-scale applications. To address this challenge, herein, the self-assembly of MXene on carbonization-free wood was obtained to serve as high-performance electrodes for symmetrical all-wood eco-supercapacitors by a steam-driven self-assembly method. This method can be implemented in a low-temperature environment, significantly simplifying traditional high-temperature annealing processes and generating minimal impact on the environment, human health, and resource consumption. The environmentally friendly steam-driven self-assembly strategy can be further extended into various wood-based electrodes, regardless of the types and structures of wood. As a typical platform electrode, the optimized MXene@delignified balsa wood (MDBW) achieves high areal capacitance and specific capacitance values of 2.99 F cm-2 and 580.55 F g-1 at an extensive mass loading of 5.16 mg cm-2, respectively, with almost loss-free capacitance after 10,000 cycles at 50 mA cm-2. In addition, an all-solid-state symmetrical all-wood eco-supercapacitor was further assembled based on MDBW-20 as both positive and negative electrodes to achieve a high energy density of 19.22 µWh cm-2 at a power density of 0.58 mW cm-2. This work provides an effective strategy to optimize wood-based electrodes for the practical application of biomass eco-supercapacitors.

Branch Chain Amino Acid Metabolism Promotes Brain Metastasis of NSCLC through EMT Occurrence by Regulating ALKBH5 activity.

Metabolic reprogramming is one of the essential features of tumors that may dramatically contribute to cancer metastasis. Employing liquid chromatography-tandem mass spectrometry-based metabolomics, we analyzed the metabolic profile from 12 pairwise serum samples of NSCLC brain metastasis patients before and after CyberKnife Stereotactic Radiotherapy. We evaluated the histopathological architecture of 144 surgically resected NSCLC brain metastases. Differential metabolites were screened and conducted for functional clustering and annotation. Metabolomic profiling identified a pathway that was enriched in the metabolism of branched-chain amino acids (BCAAs). Pathologically, adenocarcinoma with a solid growth pattern has a higher propensity for brain metastasis. Patients with high BCAT1 protein levels in lung adenocarcinoma tissues were associated with a poor prognosis. We found that brain NSCLC cells had elevated catabolism of BCAAs, which led to a depletion of α-KG. This depletion, in turn, reduced the expression and activity of the m6A demethylase ALKBH5. Thus, ALKBH5 inhibition participated in maintaining the m6A methylation of mesenchymal genes and promoted the occurrence of epithelial-mesenchymal transition (EMT) in NSCLC cells and the proliferation of NSCLC cells in the brain. BCAA catabolism plays an essential role in the metastasis of NSCLC cells.

Symbiosis of a lytic bacteriophage and Yersinia pestis and characteristics of plague in Marmota himalayana.

Surveillance for animal plague was conducted in the Marmota himalayana plague focus of the Qinghai-Tibet Plateau from 2020 to 2023. A 22.89% positive rate of serum F1 antibody was detected in live-caught marmots, alongside a 43.40% incidence of Yersinia pestis isolation from marmot carcasses. Marmot carcasses infected with plague exhibited a significantly higher spleen-somatic index (P < 0.05). Twenty-one Y. pestis-specific phages were isolated, among which one Y. pestis lytic phage (AKS2022HT87GU_phi) was isolated from the bone marrow of a marmot carcass (no. AKS2022HT87) and was found to be symbiotic with Y. pestis. Microscopy revealed the coexistence of lysed and non-lysed colonies of Y. pestis AKS2022HT87. Genome-wide analysis showed that certain strains of the Y. pestis AKS2022HT87 carried phage DNA fragments consistent with phage AKS2022HT87GU_phi. The rare symbiotic relationship between a lytic phage and Y. pestis observed in vitro was highlighted in this study, laying the basis for further exploring the relationship between Y. pestis and its bacteriophages.IMPORTANCEBacteriophages and host bacteria commonly coexist in vivo or in soil environments through complex and interdependent microbial interactions. However, recapitulating this symbiotic state remains challenging in vitro due to limited medium nutrients. In this work, the natural symbiosis between Yersinia pestis and specific phages has been discovered in a Marmota himalayana specimen. Epidemiological analysis presented the characteristics of the Y. pestis and specific phages in the area with a strong plague epidemic. Crucially, comparative genomics has been conducted to analyze the genetic changes in both the Y. pestis and phages over different periods, revealing the dynamic and evolving nature of their symbiosis. These are the critical steps to study the mechanism of the symbiosis.

FABP3 Induces Mitochondrial Autophagy to Promote Neuronal Cell Apoptosis in Brain Ischemia-Reperfusion Injury.

This study elucidates the molecular mechanisms by which FABP3 regulates neuronal apoptosis via mitochondrial autophagy in the context of cerebral ischemia-reperfusion (I/R). Employing a transient mouse model of middle cerebral artery occlusion (MCAO) established using the filament method, brain tissue samples were procured from I/R mice. High-throughput transcriptome sequencing on the Illumina CN500 platform was performed to identify differentially expressed mRNAs. Critical genes were selected by intersecting I/R-related genes from the GeneCards database with the differentially expressed mRNAs. The in vivo mechanism was explored by infecting I/R mice with lentivirus. Brain tissue injury, infarct volume ratio in the ischemic penumbra, neurologic deficits, behavioral abilities, neuronal apoptosis, apoptotic factors, inflammatory factors, and lipid peroxidation markers were assessed using H&E staining, TTC staining, Longa scoring, rotation experiments, immunofluorescence staining, and Western blot. For in vitro validation, an OGD/R model was established using primary neuron cells. Cell viability, apoptosis rate, mitochondrial oxidative stress, morphology, autophagosome formation, membrane potential, LC3 protein levels, and colocalization of autophagosomes and mitochondria were evaluated using MTT assay, LDH release assay, flow cytometry, ROS/MDA/GSH-Px measurement, transmission electron microscopy, MitoTracker staining, JC-1 method, Western blot, and immunofluorescence staining. FABP3 was identified as a critical gene in I/R through integrated transcriptome sequencing and bioinformatics analysis. In vivo experiments revealed that FABP3 silencing mitigated brain tissue damage, reduced infarct volume ratio, improved neurologic deficits, restored behavioral abilities, and attenuated neuronal apoptosis, inflammation, and mitochondrial oxidative stress in I/R mice. In vitro experiments demonstrated that FABP3 silencing restored OGD/R cell viability, reduced neuronal apoptosis, and decreased mitochondrial oxidative stress. Moreover, FABP3 induced mitochondrial autophagy through ROS, which was inhibited by the free radical scavenger NAC. Blocking mitochondrial autophagy with sh-ATG5 lentivirus confirmed that FABP3 induces mitochondrial dysfunction and neuronal apoptosis by activating mitochondrial autophagy. In conclusion, FABP3 activates mitochondrial autophagy through ROS, leading to mitochondrial dysfunction and neuronal apoptosis, thereby promoting cerebral ischemia-reperfusion injury.

Rotating magnetic field inhibits Aß protein aggregation and alleviates cognitive impairment in Alzheimer's disease mice.

Amyloid beta (Aß) monomers aggregate to form fibrils and amyloid plaques, which are critical mechanisms in the pathogenesis of Alzheimer's disease (AD). Given the important role of Aß1-42 aggregation in plaque formation, leading to brain lesions and cognitive impairment, numerous studies have aimed to reduce Aß aggregation and slow AD progression. The diphenylalanine (FF) sequence is critical for amyloid aggregation, and magnetic fields can affect peptide alignment due to the diamagnetic anisotropy of aromatic rings. In this study, we examined the effects of a moderate-intensity rotating magnetic field (RMF) on Aß aggregation and AD pathogenesis. Results indicated that the RMF directly inhibited Aß amyloid fibril formation and reduced Aß-induced cytotoxicity in neural cells in vitro. Using the AD mouse model APP/PS1, RMF restored motor abilities to healthy control levels and significantly alleviated cognitive impairments, including exploration and spatial and non-spatial memory abilities. Tissue examinations demonstrated that RMF reduced amyloid plaque accumulation, attenuated microglial activation, and reduced oxidative stress in the APP/PS1 mouse brain. These findings suggest that RMF holds considerable potential as a non-invasive, high-penetration physical approach for AD treatment.

Research on the correlation between clinical nurses' self-efficacy, future time perspective, and occupational burnout.

Background: The number of clinical nurses in China experiencing professional burnout is increasing yearly, posing a serious challenge to the public health sector. Implementing effective intervention strategies is key to reducing the level of occupational burnout. At present, training aimed at alleviating occupational burnout among clinical nurses is very limited, with common training programs focusing on addressing external factors of occupational burnout rather than the internal cognitive issues of clinical nurses. Self-efficacy and future time perspective are both aspects of an individual's internal self-cognition. Meanwhile, the relationship between clinical nurses' self-efficacy, future time perspective, and occupational burnout is not clear, and further research is needed to verify this. Objective: This study aims to reveal the relationship between clinical nurses' self-efficacy, future time perspective, and occupational burnout, and to explore the mediating role of future time perspective between self-efficacy and occupational burnout among clinical nurses, providing a scientific reference for training directions to improve occupational burnout. Methods: This study used a cross-sectional design, conducting a questionnaire survey with 529 practicing clinical nurses using the General Demographics Questionnaire (GDQ), the General Self-Efficacy Scale (GSES), the Zimbardo Time Perspective Inventory (ZTPI), and the Maslach Burnout Inventory-General Survey (MBI-GS). SPSS software version 26.0 was used to analyze the correlation between variables, and AMOS 26.0 was used to test the mediation effect. Results: Clinical nurses' self-efficacy had a negative predictive effect on occupational burnout (r = -0.503, p < 0.001). Future time perspective showed significant differences in regression coefficients on both the paths of self-efficacy (r = 0.615, p < 0.001) and occupational burnout (r = -0.374, p < 0.001). Future time perspective played a partial mediating role between self-efficacy and occupational burnout, accounting for 33.8% of the total effect. Conclusion: This study suggests a significant correlation between clinical nurses' self-efficacy, future time perspective, and occupational burnout. Self-efficacy can directly affect occupational burnout in clinical nurses and can also indirectly affect occupational burnout through the future time perspective.

Isolation, whole genome sequencing and application of a broad-spectrum Salmonella phage.

Salmonella is considered as one of the most common zoonotic /foodborne pathogens in the world. The application of bacteriophages as novel antibacterial agents in food substrates has become an emerging strategy. Bacteriophages have the potential to control Salmonella contamination.We have isolated and characterized a broad-spectrum Salmonella phage, SP154, which can lyse 9 serotypes, including S. Enteritidis, S. Typhimurium, S. Pullorum, S. Arizonae, S. Dublin, S. Cholerasuis, S. Chester, S. 1, 4, [5], 12: i: -, and S. Derby, accounting for 81.9% of 144 isolates. SP154 showed a short latent period (40 min) and a high burst size (with the first rapid burst size at 107 PFUs/cell and the second rapid burst size at approximately 40 PFUs/cell). Furthermore, SP154 activity has higher survival rates across various environmental conditions, including pH 4.0-12.0 and temperatures ranging from 4 to 50 °C for 60 min, making it suitable for diverse food processing and storage applications. Significant reductions in live Salmonella were observed in different foods matrices such as milk and chicken meat, with a decrease of up to 1.9 log10 CFU/mL in milk contamination and a 1 log10 CFU/mL reduction in chicken meat. Whole genome sequencing analysis revealed that SP154 belongs to the genus Ithacavirus, subfamily Humphriesvirinae, within the family Schitoviridae. Phylogenetic analysis based on the terminase large subunit supported this classification, although an alternate tree using the tail spike protein gene suggested affiliation with the genus Kuttervirus, underscoring the limitations of relying on a single gene for phylogenetic inference. Importantly, no virulence or antibiotic resistance genes were detected in SP154. Our research highlights the potential of using SP154 for biocontrol of Salmonella in the food industry.

Evolutionary Ensemble Learning for EEG-Based Cross-Subject Emotion Recognition.

Electroencephalogram (EEG) has been widely utilized in emotion recognition due to its high temporal resolution and reliability. However, the individual differences and non-stationary characteristics of EEG, along with the complexity and variability of emotions, pose challenges in generalizing emotion recognition models across subjects. In this paper, an end-to-end framework is proposed to improve the performance of cross-subject emotion recognition. A novel evolutionary programming (EP)-based optimization strategy with neural network (NN) as the base classifier termed NN ensemble with EP (EPNNE) is designed for cross-subject emotion recognition. The effectiveness of the proposed method is evaluated on the publicly available DEAP, FACED, SEED, and SEED-IV datasets. Numerical results demonstrate that the proposed method is superior to state-of-the-art cross-subject emotion recognition methods. The proposed end-to-end framework for cross-subject emotion recognition aids biomedical researchers in effectively assessing individual emotional states, thereby enabling efficient treatment and interventions.

Interim analysis of short-term outcomes after laparoscopic spleen-preserving distal pancreatectomy with or without preservation of splenic vessels: a randomised controlled trial.

BACKGROUND: Laparoscopic spleen-preserving distal pancreatectomy (LSPDP) is a widely adopted surgical approach for benign and low-grade malignant neoplasms of the distal pancreas. The Kimura and Warshaw techniques represent two principal strategies, yet it still needs to be determined which one is superior. Our investigation aimed to evaluate the clinical outcomes associated with each technique. MATERIALS AND METHODS: This single-center, parallel-group, patient-blinded randomized controlled trial (RCT) was conducted at the XXXXX University. Stratified block randomization was utilized to enroll 114 patients starting in March 2022, with an interim analysis of short-term outcomes scheduled after 45%-50% of participant enrollment. Patients were randomized to receive LSPDP via either the Kimura or Warshaw technique. The primary endpoint was intraoperative blood loss, while secondary endpoints included a range of outcomes from composite outcome to quality of life, as quantified by the EQ-5D-5L. RESULTS: From March 2022 to November 2023, 53 patients were randomly allocated to the Kimura (n=25) or Warshaw (n=28) groups for LSPDP. Baseline characteristics and postoperative outcomes were similar between the groups, such as pancreatic fistula incidence, EQ-5D-5L index scores, and delayed gastric emptying rates. Per-protocol (PP) analysis revealed that the Kimura group experienced significantly less blood loss (52.5±51.6 mL vs. 91.7±113.5 mL, P=0.007) and a reduced rate of composite outcome (23.8% vs. 56.7%, P=0.019), but incurred higher costs in the Warshaw group (¥56,227.4±¥7,027.0 vs. ¥63,513.8±¥12,944.5, P=0.013). Splenic infarction rates were higher in the Warshaw group, though not statistically significant (ITT: 39.3% vs. 12.5%, P=0.058; PP: 36.7% vs. 14.3%, P=0.113), without necessitating intervention. Neither group experienced postpancreatectomy haemorrhage, 90-day mortality, or ICU admissions, and all postoperative complications were mild (Clavien-Dindo Grade

Elimination of GGTA1, CMAH, ß4GalNT2 and CIITA genes in pigs compromises human versus pig xenogeneic immune reactions.

BACKGROUND: Pig organ xenotransplantation is a potential solution for the severe organ shortage in clinic, while immunogenic genes need to be eliminated to improve the immune compatibility between humans and pigs. Current knockout strategies are mainly aimed at the genes causing hyperacute immune rejection (HAR) that occurs in the first few hours while adaptive immune reactions orchestrated by CD4 T cell thereafter also cause graft failure, in which process the MHC II molecule plays critical roles. METHODS: Thus, we generate a 4-gene (GGTA1, CMAH, ß4GalNT2, and CIITA) knockout pig by CRISPR/Cas9 and somatic cell nuclear transfer to compromise HAR and CD4 T cell reactions simultaneously. RESULTS: We successfully obtained 4KO piglets with deficiency in all alleles of genes, and at cellular and tissue levels. Additionally, the safety of our animals after gene editing was verified by using whole-genome sequencing and karyotyping. Piglets have survived for more than one year in the barrier, and also survived for more than 3 months in the conventional environment, suggesting that the piglets without MHC II can be raised in the barrier and then gradually mated in the conventional environment. CONCLUSIONS: 4KO piglets have lower immunogenicity, are safe in genomic level, and are easier to breed than the model with both MHC I and II deletion.

AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: An exploratory study.

BACKGROUND AND AIMS: Lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a pivotal role in the outcome of MASH clinical trials. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses can provide an automated quantitative assessment of fibrosis features on a continuous scale called qFibrosis. In this exploratory study, we used this approach to gain insight into the effect of lifestyle intervention-induced fibrosis changes in MASH. METHODS: We examined unstained sections from paired liver biopsies (baseline and end-of-intervention) from MASH individuals who had received either routine lifestyle intervention (RLI) (n = 35) or strengthened lifestyle intervention (SLI) (n = 17). We quantified liver fibrosis with qFibrosis in the portal tract, periportal, transitional, pericentral, and central vein regions. RESULTS: About 20% (7/35) and 65% (11/17) of patients had fibrosis regression in the RLI and SLI groups, respectively. Liver fibrosis tended towards no change or regression after each lifestyle intervention, and this phenomenon was more prominent in the SLI group. SLI-induced liver fibrosis regression was concentrated in the periportal region. CONCLUSION: Using digital pathology, we could detect a more pronounced fibrosis regression with SLI, mainly in the periportal region. With changes in fibrosis area in the periportal region, we could differentiate RLI and SLI patients in the placebo group in the MASH clinical trial. Digital pathology provides new insight into lifestyle-induced fibrosis regression and placebo responses, which is not captured by conventional histological staging.

THUMPD3-AS1 inhibits ovarian cancer cell apoptosis through the miR-320d/ARF1 axis.

Ovarian cancer is one of the most common gynecologic malignancies that has a poor prognosis. THUMPD3-AS1 is an oncogenic long noncoding RNA (lncRNA) in several cancers. Moreover, miR-320d is downregulated and inhibited proliferation in ovarian cancer cells, whereas ARF1 was upregulated and promoted the malignant progression in epithelial ovarian cancer. Nevertheless, the role of THUMPD3-AS1 in ovarian cancer and the underlying mechanism has yet to be elucidated. Human normal ovarian epithelial cells (IOSE80) and ovarian cancer cell lines (CAVO3, A2780, SKOV3, OVCAR3, and HEY) were adopted for in vitro experiments. The functional roles of THUMPD3-AS1 in cell viability and apoptosis were determined using CCK-8, flow cytometry, and TUNEL assays. Western blot was performed to assess the protein levels of ARF1, Bax, Bcl-2, and caspase 3, whereas RT-qPCR was applied to measure ARF1 mRNA, THUMPD3-AS1, and miR-320d levels. The targeting relationship between miR-320d and THUMPD3-AS1 or ARF1 was validated with dual luciferase assay. THUMPD3-AS1 and ARF1 were highly expressed in ovarian cancer cells, whereas miR-320d level was lowly expressed. THUMPD3-AS1 knockdown was able to repress cell viability and accelerate apoptosis of OVCAR3 and SKOV3 cells. Also, THUMPD3-AS1 acted as a sponge of miR-320d, preventing the degradation of ARF1. MiR-320d downregulation reversed the tumor suppressive function induced by THUMPD3-AS1 depletion. Additionally, miR-320d overexpression inhibited ovarian cancer cell viability and accelerated apoptosis, which was overturned by overexpression of ARF1. THUMPD3-AS1 inhibited ovarian cancer cell apoptosis by modulation of miR-320d/ARF1 axis. The discoveries might provide a prospective target for ovarian cancer treatment.

Global research hotspots and trends in constraint-induced movement therapy in rehabilitation over the past 30 years: a bibliometric and visualization study.

Background: Stroke is a cerebrovascular disease with high prevalence and mortality, and upper limb hemiparesis is a major factor limiting functional recovery in stroke patients. Improvement of motor function in stroke patients through various forms of constraint-induced movement therapy (CITM) has been recognized as safe and effective in recent years. This research field lacks a comprehensive systematic and clear vein combing analysis, analyzing the literature research of CIMT in the field of rehabilitation in the past three decades, summarizing the research hotspots and cutting-edge trends in this field, in an effort to offer ideas and references for subsequent researchers. Methods: Relevant literature on CIMT in rehabilitation was collected from 1996 to 2024 within the Web of Science database's core dataset by using CiteSpace6.1, VOSviewer1.6.18, R-bibliometrix4.6.1, Pajek5.16, Scimago Graphica 1.0.26 software for visualization and analysis. Results: There were 970 papers in all United States was ranked first with 401 papers. Alabama Univ was ranked first for institutions with 53 papers. Neurorehabilitation and Neural Repair was ranked first for journals with 78 papers, and Taub E was ranked first for author publications with 64 papers. Research keywords were CIMT, stroke rehabilitation, upper extremity function, lower extremity gait balance, randomized controlled trials, physical therapy techniques (transcranial magnetic stimulation and sensory amplitude electrical stimulation), primary motor cortex plasticity, lateral dominance (spatial behaviors), cerebral vascular accidents, activities of daily living, hand function, disability, functional restoration, bimanual training, aphasia, acquired invalidity, type A Botulinum toxin and joystick riding toys. Conclusion: The current state of research shows that CIMT still has a vast potential for development in the field of rehabilitation research. The research hotspots are the clinical efficacy of CIMT combined with other therapies (botulinum toxin type A, transcranial direct current stimulation, virtual reality, mirror therapy, robotic-assisted) to enhance the functionality of upper limb hemiparesis in stroke patients, the mechanism of CIMT to improve the plasticity of the motor cortex through electrophysiological and imaging methods, and improvement of lower limb gait balance function in stroke patients and aphasia applications, the optimal intervention time and dose, and exploration of CIMT in new settings such as robot-assisted, telemedicine, and home rehabilitation.

[Establishment and Validation of a Predictive Model for Gallstone Disease in the General Population: A Multicenter Study]. / èƒ†ç»“çŸ³æ‚£ç— é£Žé™©é¢„æµ‹æ¨¡åž‹çš„æž„å»ºå’Œå¤šä¸­å¿ƒéªŒè¯ç ”ç©¶.

Objective: Gallstone disease (GSD) is one of the common digestive tract diseases with a high worldwide prevalence. The effects of GSD on patients include but are not limited to the symptoms of nausea, vomiting, and biliary colic directly caused by GSD. In addition, there is mounting evidence from cohort studies connecting GSD to other conditions, such as cardiovascular diseases, biliary tract cancer, and colorectal cancer. Early identification of patients at a high risk of GSD may help improve the prevention and control of the disease. A series of studies have attempted to establish prediction models for GSD, but these models could not be fully applied in the general population due to incomplete prediction factors, small sample sizes, and limitations in external validation. It is crucial to design a universally applicable GSD risk prediction model for the general population and to take individualized intervention measures to prevent the occurrence of GSD. This study aims to conduct a multicenter investigation involving more than 90000 people to construct and validate a complete and simplified GSD risk prediction model. Methods: A total of 123634 participants were included in the study between January 2015 and December 2020, of whom 43929 were from the First Affiliated Hospital of Chongqing Medical University (Chongqing, China), 11907 were from the First People's Hospital of Jining City (Shandong, China), 1538 were from the Tianjin Medical University Cancer Institute and Hospital (Tianjin, China), and 66260 were from the People's Hospital of Kaizhou District (Chongqing, China). After excluding patients with incomplete clinical medical data, 35976 patients from the First Affiliated Hospital of Chongqing Medical University were divided into a training data set (n=28781, 80%) and a validation data set (n=7195, 20%). Logistic regression analyses were performed to investigate the relevant risk factors of GSD, and a complete risk prediction model was constructed. Factors with high scores, mainly according to the nomograms of the complete model, were retained to simplify the model. In the validation data set, the diagnostic accuracy and clinical performance of these models were validated using the calibration curve, area under the curve (AUC) of the receiver operating characteristic curve, and decision curve analysis (DCA). Moreover, the diagnostic accuracy of these two models was validated in three other hospitals. Finally, we established an online website for using the prediction model (The complete model is accessible at https://wenqianyu.shinyapps.io/Completemodel/, while the simplified model is accessible at https://wenqianyu.shinyapps.io/Simplified/). Results: After excluding patients with incomplete clinical medical data, a total of 96426 participants were finally included in this study (35876 from the First Affiliated Hospital of the Chongqing Medical University, 9289 from the First People's Hospital of Jining City, 1522 from the Tianjin Medical University Cancer Institute, and 49639 from the People's Hospital of Kaizhou District). Female sex, advanced age, higher body mass index, fasting plasma glucose, uric acid, total bilirubin, gamma-glutamyl transpeptidase, and fatty liver disease were positively associated with risks for GSD. Furthermore, gallbladder polyps, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and aspartate aminotransferase were negatively correlated to risks for GSD. According to the nomograms of the complete model, a simplified model including sex, age, body mass index, gallbladder polyps, and fatty liver disease was constructed. All the calibration curves exhibited good consistency between the predicted and observed probabilities. In addition, DCA indicated that both the complete model and the simplified model showed better net benefits than treat-all and treat-none. Based on the calibration plots, DCA, and AUCs of the complete model (AUC in the internal validation data set=74.1% [95% CI: 72.9%-75.3%], AUC in Shandong=71.7% [95% CI: 70.6%-72.8%], AUC in Tianjin=75.3% [95% CI: 72.7%-77.9%], and AUC in Kaizhou=72.9% [95% CI: 72.5%-73.3%]) and the simplified model (AUC in the internal validation data set=73.7% [95% CI: 72.5%-75.0%], AUC in Shandong=71.5% [95% CI: 70.4%-72.5%], AUC in Tianjin=75.4% [95% CI: 72.9%-78.0%], and AUC in Kaizhou=72.4% [95% CI: 72.0%-72.8%]), we concluded that the complete and simplified risk prediction models for GSD exhibited excellent performance. Moreover, we detected no significant differences between the performance of the two models (P>0.05). We also established two online websites based on the results of this study for GSD risk prediction. Conclusions: This study innovatively used the data from 96426 patients from four hospitals to establish a GSD risk prediction model and to perform risk prediction analyses of internal and external validation data sets in four cohorts. A simplified model of GSD risk prediction, which included the variables of sex, age, body mass index, gallbladder polyps, and fatty liver disease, also exhibited good discrimination and clinical performance. Nonetheless, further studies are needed to explore the role of low-density lipoprotein cholesterol and aspartate aminotransferase in gallstone formation. Although the validation results of the complete model were better than those of the simplified model to a certain extent, the difference was not significant even in large samples. Compared with the complete model, the simplified model uses fewer variables and yields similar prediction and clinical impact. Hence, we recommend the application of the simplified model to improve the efficiency of screening high-risk groups in practice. The use of the simplified model is conducive to enhancing the self-awareness of prevention and control in the general population and early intervention for GSD.

Disentangled Representation Learning.

Disentangled Representation Learning (DRL) aims to learn a model capable of identifying and disentangling the underlying factors hidden in the observable data in representation form. The process of separating underlying factors of variation into variables with semantic meaning benefits in learning explainable representations of data, which imitates the meaningful understanding process of humans when observing an object or relation. As a general learning strategy, DRL has demonstrated its power in improving the model explainability, controlability, robustness, as well as generalization capacity in a wide range of scenarios such as computer vision, natural language processing, and data mining. In this article, we comprehensively investigate DRL from various aspects including motivations, definitions, methodologies, evaluations, applications, and model designs. We first present two well-recognized definitions, i.e., Intuitive Definition and Group Theory Definition for disentangled representation learning. We further categorize the methodologies for DRL into four groups from the following perspectives, the model type, representation structure, supervision signal, and independence assumption. We also analyze principles to design different DRL models that may benefit different tasks in practical applications. Finally, we point out challenges in DRL as well as potential research directions deserving future investigations. We believe this work may provide insights for promoting the DRL research in the community.