A Rat Model of Middle Cerebral Artery Occlusion/Reperfusion without Damaging the Anatomical Structure of Cerebral Vessels.

Ischemic stroke stands as the primary cause of long-term disability and mortality among adults worldwide. Animal models of ischemic stroke have significantly contributed to our understanding of its pathological mechanisms and the development of potential treatments. Presently, there are two common methods involving filament (endovascular suture) techniques to induce animal models of cerebral ischemia. However, these methods have inherent limitations, such as reduced blood perfusion to the brain, damage to the external carotid artery system, impaired food and/or water intake, and sensory dysfunction of the face. This article introduces a new method for inducing a rat ischemic stroke model without compromising the cerebral vascular anatomy. In this study, the common carotid artery (CCA) of Sprague-Dawley rats was exposed, and an incision was made. A filament was then inserted through the incision into the internal carotid artery to occlude the middle cerebral artery. After 1.5 h of induced ischemia, the occluding filament was fully removed from both the internal carotid artery and the CCA. The incision in the CCA was subsequently sutured using 11-0 microsurgical sutures under a microscope (magnification 4x). Through the utilization of microsurgical techniques to repair the CCA, this study successfully developed a unique method to induce an ischemic stroke model in rats while preserving the anatomical integrity of cerebral blood vessels.

Discovery of an immunosuppressive functional metabolite from the insect-derived endophytic Aspergillus taichungensis SMU01.

Three p-terphenyl metabolites (1-3), three indole-diterpenoids (4-6), an herbicide sesquiterpene (7), a flavonoid (8), and five other small molecules containing nitrogen (9-13) were isolated from the medicinal insect (Periplaneta americana)-derived endophytic Aspergillus taichungensis SMU01. Their chemical structures were elucidated on the basis of spectroscopic data and quantum chemical computational methods. Biological activity of these isolates in the differentiation of mouse CD4+ T cell subsets was evaluated. Importantly, metabolites 2 targeting JAK-STAT signaling pathway could hold potential benefits in maintaining peripheral immune homeostasis and alleviating the progression of autoimmune diseases.

An NGS-based assay for accurate detection and quantification of immune gene expression in mouse tumor models.

Tumor microenvironment (TME) is a complex dynamic system with many tumor-interacting components including tumor-infiltrating leukocytes (TILs), cancer associated fibroblasts, blood vessels, and other stromal constituents. It intrinsically affects tumor development and pharmacology of oncology therapeutics, particularly immune-oncology (IO) treatments. Accurate measurement of TME is therefore of great importance for understanding the tumor immunity, identifying IO treatment mechanisms, developing predictive biomarkers, and ultimately, improving the treatment of cancer. Here, we introduce a mouse-IO NGS-based (NGSmIO) assay for accurately detecting and quantifying the mRNA expression of 1080 TME related genes in mouse tumor models. The NGSmIO panel was shown to be superior to the commonly used microarray approach by hosting 300 more relevant genes to better characterize various lineage of immune cells, exhibits improved mRNA and protein expression correlation to flow cytometry, shows stronger correlation with mRNA expression than RNAseq with 10x higher sequencing depth, and demonstrates higher sensitivity in measuring low-expressed genes. We describe two studies; firstly, detecting the pharmacodynamic change of interferon-γ expression levels upon anti-PD-1: anti-CD4 combination treatment in MC38 and Hepa 1-6 tumors; and secondly, benchmarking baseline TILs in 14 syngeneic tumors using transcript level expression of lineage specific genes, which demonstrate effective and robust applications of the NGSmIO panel.

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study.

BACKGROUND: Nonprofit organizations are increasingly using social media to improve their communication strategies with the broader population. However, within the domain of human service nonprofits, there is hesitancy to fully use social media tools, and there is limited scope among organizational personnel in applying their potential beyond self-promotion and service advertisement. There is a pressing need for greater conceptual clarity to support education and training on the varied reasons for using social media to increase organizational outcomes. OBJECTIVE: This study leverages the potential of Twitter (subsequently rebranded as X [X Corp]) to examine the online communication content within a sample (n=133) of nonprofit sexual assault (SA) centers in Canada. To achieve this, we developed a typology using a qualitative and supervised machine learning model for the automatic classification of tweets posted by these centers. METHODS: Using a mixed methods approach that combines machine learning and qualitative analysis, we manually coded 10,809 tweets from 133 SA centers in Canada, spanning the period from March 2009 to March 2023. These manually labeled tweets were used as the training data set for the supervised machine learning process, which allowed us to classify 286,551 organizational tweets. The classification model based on supervised machine learning yielded satisfactory results, prompting the use of unsupervised machine learning to classify the topics within each thematic category and identify latent topics. The qualitative thematic analysis, in combination with topic modeling, provided a contextual understanding of each theme. Sentiment analysis was conducted to reveal the emotions conveyed in the tweets. We conducted validation of the model with 2 independent data sets. RESULTS: Manual annotation of 10,809 tweets identified seven thematic categories: (1) community engagement, (2) organization administration, (3) public awareness, (4) political advocacy, (5) support for others, (6) partnerships, and (7) appreciation. Organization administration was the most frequent segment, and political advocacy and partnerships were the smallest segments. The supervised machine learning model achieved an accuracy of 63.4% in classifying tweets. The sentiment analysis revealed a prevalence of neutral sentiment across all categories. The emotion analysis indicated that fear was predominant, whereas joy was associated with the partnership and appreciation tweets. Topic modeling identified distinct themes within each category, providing valuable insights into the prevalent discussions surrounding SA and related issues. CONCLUSIONS: This research contributes an original theoretical model that sheds light on how human service nonprofits use social media to achieve their online organizational communication objectives across 7 thematic categories. The study advances our comprehension of social media use by nonprofits, presenting a comprehensive typology that captures the diverse communication objectives and contents of these organizations, which provide content to expand training and education for nonprofit leaders to connect and engage with the public, policy experts, other organizations, and potential service users.

Interleukin-21 receptor signaling promotes metabolic dysfunction-associated steatohepatitis-driven hepatocellular carcinoma by inducing immunosuppressive IgA+ B cells.

BACKGROUND: Dysregulation of immune surveillance is tightly linked to the development of metabolic dysfunction-associated steatohepatitis (MASH)-driven hepatocellular carcinoma (HCC); however, its underlying mechanisms remain unclear. Herein, we aimed to determine the role of interleukin-21 receptor (IL-21R) in MASH-driven HCC. METHODS: The clinical significance of IL-21R was assessed in human HCC specimens using immunohistochemistry staining. Furthermore, the expression of IL-21R in mice was assessed in the STAM model. Thereafter, two different MASH-driven HCC mouse models were applied between IL-21R-deficient mice and wild type controls to explore the role of IL-21R in MASH-driven HCC. To further elucidate the potential mechanisms by which IL-21R affected MASH-driven HCC, whole transcriptome sequencing, flow cytometry and adoptive lymphocyte transfer were performed. Finally, flow cytometry, enzyme-linked immunosorbent assay, immunofluorescent staining, chromatin immunoprecipitation assay and western blotting were conducted to explore the mechanism by which IL-21R induced IgA+ B cells. RESULTS: HCC patients with high IL-21R expression exhibited poor relapse-free survival, advanced TNM stage and severe steatosis. Additionally, IL-21R was demonstrated to be upregulated in mouse liver tumors. Particularly, ablation of IL-21R impeded MASH-driven hepatocarcinogenesis with dramatically reduction of lipid accumulation. Moreover, cytotoxic CD8+ T lymphocyte activation was enhanced in the absence of IL-21R due to the reduction of immunosuppressive IgA+ B cells. Mechanistically, the IL-21R-STAT1-c-Jun/c-Fos regulatory axis was activated in MASH-driven HCC and thus promoted the transcription of Igha, resulting in the induction of IgA+ B cells. CONCLUSIONS: IL-21R plays a cancer-promoting role by inducing IgA+ B cells in MASH-driven hepatocarcinogenesis. Targeting IL-21R signaling represents a potential therapeutic strategy for cancer therapy.

Effect of Cytochrome P450 3A4 on Tissue Distribution of Humantenmine, Koumine, and Gelsemine, three Alkaloids from the Toxic Plant Gelsemium.

Humantenmine, koumine, and gelsemine are three indole alkaloids found in the highly toxic plant Gelsemium. Humantenmine was the most toxic, followed by gelsemine and koumine. The aim of this study was to investigate and analyze the effects of these three substances on tissue distribution and toxicity in mice pretreated with the Cytochrome P450 3A4 (CYP3A4) inducer ketoconazole and the inhibitor rifampicin. The in vivo test results showed that the three alkaloids were absorbed rapidly and had the ability to penetrate the blood-brain barrier. At 5minutes after intraperitoneal injection, the three alkaloids were widely distributed in various tissues and organs, the spleen and pancreas were the most distributed, and the content of all tissues decreased significantly at 20minutes. Induction or inhibition of CYP3A4 in vivo can regulate the distribution and elimination effects of the three alkaloids in various tissues and organs. Additionally, induction of CYP3A4 can reduce the toxicity of humantenmine, and vice versa. Changes in CYP3A4 levels may account for the difference in toxicity of humantenmine. These findings provide a reliable and detailed dataset for drug interactions, tissue distribution, and toxicity studies of Gelsemium alkaloids.

Non-Hermitian Strongly Interacting Dirac Fermions.

Exotic quantum phases and phase transition in the strongly interacting Dirac systems have attracted tremendous interests. On the other hand, non-Hermitian physics, usually associated with dissipation arising from the coupling to environment, emerges as a frontier of modern physics in recent years. In this Letter, we investigate the interplay between non-Hermitian physics and strong correlation in Dirac-fermion systems. We generalize the projector quantum Monte-Carlo (PQMC) algorithm to the non-Hermitian interacting fermionic systems. Employing PQMC simulation, we decipher the ground-state phase diagram of the honeycomb Hubbard model with spin resolved non-Hermitian asymmetric hopping processes. The antiferromagnetic (AFM) ordering induced by Hubbard interaction is enhanced by the non-Hermitian asymmetric hopping. Combining PQMC simulation and renormalization group analysis, we reveal that the quantum phase transition between Dirac semi-metal and AFM phases belongs to Hermitian chiral XY universality class, implying that a Hermitian Gross-Neveu transition is emergent at the quantum critical point although the model is non-Hermitian.

Narazaciclib, a novel multi-kinase inhibitor with potent activity against CSF1R, FLT3 and CDK6, shows strong anti-AML activity in defined preclinical models.

CSF1R is a receptor tyrosine kinase responsible for the growth/survival/polarization of macrophages and overexpressed in some AML patients. We hypothesized that a novel multi-kinase inhibitor (TKi), narazaciclib (HX301/ON123300), with high potency against CSF1R (IC50 ~ 0.285 nM), would have anti-AML effects. We tested this by confirming HX301's high potency against CSF1R (IC50 ~ 0.285 nM), as well as other kinases, e.g. FLT3 (IC50 of ~ 19.77 nM) and CDK6 (0.53 nM). An in vitro proliferation assay showed that narazaciclib has a high growth inhibitory effect in cell cultures where CSF1R or mutant FLT3-ITD variants that may be proliferation drivers, including primary macrophages (IC50 of 72.5 nM) and a subset of AML lines (IC50 < 1.5 µM). In vivo pharmacology modeling of narazaciclib using five AML xenografts resulted in: inhibition of MV4-11 (FLT3-ITD) subcutaneous tumor growth and complete suppression of AM7577-PDX (FLT3-ITD/CSF1Rmed) systemic growth, likely due to the suppression of FLT3-ITD activity; complete suppression of AM8096-PDX (CSF1Rhi/wild-type FLT3) growth, likely due to the inhibition of CSF1R ("a putative driver"); and nonresponse of both AM5512-PDX and AM7407-PDX (wild-type FLT3/CSF1Rlo). Significant leukemia load reductions in bone marrow, where disease originated, were also achieved in both responders (AM7577/AM8096), implicating that HX301 might be a potentially more effective therapy than those only affecting peripheral leukemic cells. Altogether, narazaciclib can potentially be a candidate treatment for a subset of AML with CSF1Rhi and/or mutant FLT3-ITD variants, particularly second generation FLT3 inhibitor resistant variants.

Fe-TiO2-x/TiO2 S-scheme homojunction for efficient photocatalytic CO2 reduction.

CO2-to-high value-added chemicals via a photocatalytic route is of interest but strangled by the low efficiency. Herein, a novel Fe-TiO2-x/TiO2 S-scheme homojunction was designed and constructed by using a facile surface modification approach whereby oxygen vacancy (OV) and Fe introducing on the TiO2 nanorod surface. The as-synthesized Fe-TiO2-x/TiO2 S-scheme homojunction exhibits positive properties on promoting photocatalytic CO2 reduction: i) the nanorod structure provides numerous active sites and a radical charge transfer path; ii) the doped Fe and OV not only synergistically enhance light utilization but also promote CO2 adsorption; iii) the Fe-TiO2-x/TiO2 S-scheme homojunction benefits photoexcited charge separation and retains stronger redox capacity. Thanks to those good characters, the Fe-TiO2-x/TiO2 homojunction exhibits superior CO2 reduction performances with optimized CO/CH4 generation rates of 122/22 µmol g-1h-1 which exceed those of pure TiO2 by more than 9.4/7.3 folds and most currently reported catalytic systems. This manuscript develops a facile and universal approach to synthesize well-defined homojunction and may inspire the construction of other more high-efficiency photocatalysts toward CO2 reduction and beyond.

Association between the cumulative triglyceride-glucose index and the recurrence of atrial fibrillation after radiofrequency catheter ablation.

BACKGROUND: Triglyceride-glucose (TyG) index values are a new surrogate marker for insulin resistance. This study aimed to explore the relationship between cumulative TyG index values and atrial fibrillation (AF) recurrence after radiofrequency catheter ablation (RFCA). METHODS: A total of 576 patients with AF who underwent RFCA at the Second Affiliated Hospital of Xi'an Jiaotong University were included in this study. The participants were grouped based on cumulative TyG index values tertiles within 3 months after ablation. Cox regression and restricted cubic spline analyses were used to determine the relationship between cumulative TyG index values and AF recurrence. The predictive value of all risk factors was assessed by receiver operating curve analysis. RESULTS: There were 375 patients completed the study (age: 63.23 ± 10.73 years, 64.27% male). The risk of AF recurrence increased with increasing cumulative TyG index values tertiles. After adjusting for potential confounders, patients in the medium cumulative TyG index group [hazard ratio (HR) = 4.949, 95% CI: 1.778-13.778, P = 0.002] and the high cumulative TyG index group (HR = 8.716, 95% CI: 3.371-22.536, P < 0.001) had a higher risk of AF recurrence than those in the low cumulative TyG index group. The restricted cubic spline regression model also showed an increased risk of AF recurrence with increasing cumulative TyG index values. When considering cumulative TyG index values, left atrial diameter, and lactate dehydrogenase levels as a comprehensive factor, the model could effectively predict AF recurrence after RFCA [area under the curve (AUC) = 0.847, 95% CI: 0.797-0.897, P < 0.001]. CONCLUSIONS: Cumulative TyG index values were a risk factor for AF recurrence after RFCA. Monitoring longitudinal TyG index values may assist with optimized for risk stratification and outcome prediction for AF recurrence.

Bridging and Bonding Social Capital by Analyzing the Demographics, User Activities, and Social Network Dynamics of Sexual Assault Centers on Twitter: Mixed Methods Study.

BACKGROUND: Social media platforms have gained popularity as communication tools for organizations to engage with clients and the public, disseminate information, and raise awareness about social issues. From a social capital perspective, relationship building is seen as an investment, involving a complex interplay of tangible and intangible resources. Social media-based social capital signifies the diverse social networks that organizations can foster through their engagement on social media platforms. Literature underscores the great significance of further investigation into the scope and nature of social media use, particularly within sectors dedicated to service delivery, such as sexual assault organizations. OBJECTIVE: This study aims to fill a research gap by investigating the use of Twitter by sexual assault support agencies in Canada. It seeks to understand the demographics, user activities, and social network structure within these organizations on Twitter, focusing on building social capital. The research questions explore the demographic profile, geographic distribution, and Twitter activity of these organizations as well as the social network dynamics of bridging and bonding social capital. METHODS: This study used purposive sampling to investigate sexual assault centers in Canada with active Twitter accounts, resulting in the identification of 124 centers. The Twitter handles were collected, yielding 113 unique handles, and their corresponding Twitter IDs were obtained and validated. A total of 294,350 tweets were collected from these centers, covering >93.54% of their Twitter activity. Preprocessing was conducted to prepare the data, and descriptive analysis was used to determine the center demographics and age. Furthermore, geolocation mapping was performed to visualize the center locations. Social network analysis was used to explore the intricate relationships within the network of sexual assault center Twitter accounts, using various metrics to assess the network structure and connectivity dynamics. RESULTS: The results highlight the substantial presence of sexual assault organizations on Twitter, particularly in provinces such as Ontario, British Columbia, and Quebec, underscoring the importance of tailored engagement strategies considering regional disparities. The analysis of Twitter account creation years shows a peak in 2012, followed by a decline in new account creations in subsequent years. The monthly tweet activity shows November as the most active month, whereas July had the lowest activity. The study also reveals variations in Twitter activity, account creation patterns, and social network dynamics, identifying influential social queens and marginalized entities within the network. CONCLUSIONS: This study presents a comprehensive landscape of the demographics and activities of sexual assault centers in Canada on Twitter. This study suggests that future research should explore the long-term consequences of social media use and examine stakeholder perceptions, providing valuable insights to improve communication practices within the nonprofit human services sector and further the missions of these organizations.

Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.

OBJECTIVE: This retrospective observational study aims to develop and validate artificial intelligence (AI) pathomics models based on pathological Hematoxylin-Eosin (HE) slides and pathological immunohistochemistry (Ki67) slides for predicting the pathological staging of colorectal cancer. The goal is to enable AI-assisted accurate pathological staging, supporting healthcare professionals in making efficient and precise staging assessments. METHODS: This study included a total of 267 colorectal cancer patients (training cohort: n = 213; testing cohort: n = 54). Logistic regression algorithms were used to construct the models. The HE image features were used to build the HE model, the Ki67 image features were used for the Ki67 model, and the combined model included features from both the HE and Ki67 images, as well as tumor markers (CEA, CA724, CA125, and CA242). The predictive results of the HE model, Ki67 model, and tumor markers were visualized through a nomogram. The models were evaluated using ROC curve analysis, and their clinical value was estimated using decision curve analysis (DCA). RESULTS: A total of 260 deep learning features were extracted from HE or Ki67 images. The AUC for the HE model and Ki67 model in the training cohort was 0.885 and 0.890, and in the testing cohort, it was 0.703 and 0.767, respectively. The combined model and nomogram in the training cohort had AUC values of 0.907 and 0.926, and in the testing cohort, they had AUC values of 0.814 and 0.817. In clinical DCA, the net benefit of the Ki67 model was superior to the HE model. The combined model and nomogram showed significantly higher net benefits compared to the individual HE model or Ki67 model. CONCLUSION: The combined model and nomogram, which integrate pathomics multi-modal data and clinical-pathological variables, demonstrated superior performance in distinguishing between Stage I-II and Stage III colorectal cancer. This provides valuable support for clinical decision-making and may improve treatment strategies and patient prognosis. Furthermore, the use of immunohistochemistry (Ki67) slides for pathomics modeling outperformed HE slide, offering new insights for future pathomics research.

Skeletal Editing of Benzene Motif: Photopromoted Transannulation for Synthesis of DNA-Encoded Seven-Membered Rings.

In this report, we present a photopromoted, metal-free transannulation of phenyl azides for the synthesis of DNA-encoded seven-membered rings. The transformation is efficiently achieved through a skeletal editing strategy targeting the benzene motif coupled with a Reversible Adsorption to Solid Support (RASS) strategy. A variety of valuable DNA-encoded seven-membered ring compounds, including DNA-encoded 3H-azepines, azepinones, and unnatural amino acids, are now accessible. Crucially, this DNA-compatible protocol can also be applied for the introduction of complex molecules, as exemplified by Lorcaserin and Betahistine. The selective conversion of readily available phenyl rings into high-value seven-membered rings offers a promising avenue for the construction of diversified and drug-like DNA-encoded library.

Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer.

OBJECTIVE: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). METHODS: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). RESULTS: A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. CONCLUSION: The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

ATG-101 Is a Tetravalent PD-L1×4-1BB Bispecific Antibody That Stimulates Antitumor Immunity through PD-L1 Blockade and PD-L1-Directed 4-1BB Activation.

Immune checkpoint inhibitors (ICI) have transformed cancer treatment. However, only a minority of patients achieve a profound response. Many patients are innately resistant while others acquire resistance to ICIs. Furthermore, hepatotoxicity and suboptimal efficacy have hampered the clinical development of agonists of 4-1BB, a promising immune-stimulating target. To effectively target 4-1BB and treat diseases resistant to ICIs, we engineered ATG-101, a tetravalent "2+2″ PD-L1×4-1BB bispecific antibody. ATG-101 bound PD-L1 and 4-1BB concurrently, with a greater affinity for PD-L1, and potently activated 4-1BB+ T cells when cross-linked with PD-L1-positive cells. ATG-101 activated exhausted T cells upon PD-L1 binding, indicating a possible role in reversing T-cell dysfunction. ATG-101 displayed potent antitumor activity in numerous in vivo tumor models, including those resistant or refractory to ICIs. ATG-101 greatly increased the proliferation of CD8+ T cells, the infiltration of effector memory T cells, and the ratio of CD8+ T/regulatory T cells in the tumor microenvironment (TME), rendering an immunologically "cold" tumor "hot." Comprehensive characterization of the TME after ATG-101 treatment using single-cell RNA sequencing further revealed an altered immune landscape that reflected increased antitumor immunity. ATG-101 was well tolerated and did not induce hepatotoxicity in non-human primates. According to computational semimechanistic pharmacology modeling, 4-1BB/ATG-101/PD-L1 trimer formation and PD-L1 receptor occupancy were both maximized at around 2 mg/kg of ATG-101, providing guidance regarding the optimal biological dose for clinical trials. In summary, by localizing to PD-L1-rich microenvironments and activating 4-1BB+ immune cells in a PD-L1 cross-linking-dependent manner, ATG-101 safely inhibits growth of ICI resistant and refractory tumors. SIGNIFICANCE: The tetravalent PD-L1×4-1BB bispecific antibody ATG-101 activates 4-1BB+ T cells in a PD-L1 cross-linking-dependent manner, minimizing the hepatotoxicity of existing 4-1BB agonists and suppressing growth of ICI-resistant tumors. See related commentary by Ha et al., p. 1546.

Construction of a Metal-Silica Interface for Semihydrogenation of Alkynes.

Fabricating optimum surface structures represents an attractive approach for synthesizing supported catalysts with high activity and specific selectivity. New active sites could be flexibly constructed via the strong metal-support interaction under the redox condition. Herein, we demonstrated the formation of a new Rh-Si surface on a silica-modified carbon nanotube supported Rh catalyst under the high-temperature reduction condition as well as a thin amorphous silica coating layer and weak chemisorption toward the CO molecule. The electronic interactions between Rh and Si, along with the particular structure, guarantee desirable catalytic performance for the semihydrogenation of phenylacetylene under mild conditions. This facile approach might be extensively used in constructing new active sites with robust activity and specific selectivity in diverse heterogeneous catalysis systems.

Supportive Interventions of Chinese Police in Domestic Violence: Do Officer Knowledge and Training Matter?

Policing domestic violence (DV) poses significant challenges in China due to cultural, legal, and organizational complexities. Policing DV in China favors mediation over assertive interventions, complicating law enforcement's role. While previous research has focused on coercive interventions by Chinese police, there is limited information on non-coercive, supportive approaches. This study investigates the relationship between police officers' knowledge and training regarding the Anti-DV law and their willingness to provide supportive services to DV victims in China. It also considers various individual and organizational factors. The data used in this study are derived from the Policing DV in China project, with a sample of 1,353 respondents who had experience dealing with DV cases within the past 3 years. The study focuses on three dependent variables representing supportive approaches to DV cases: Referral, Counseling, and Protection orders. Independent variables include officers' knowledge of the Anti-DV law and agency training. Control variables include the use of body-worn cameras (BWC) and attitudes toward Violence Tolerance, Male Dominance, and Gender Equality. Additionally, demographic variables, working environment, length of service, and police rank are considered. The analytical approach involves a three-step strategy, incorporating descriptive, bivariate analyses, and regression analyses. The results are interpreted using odds ratios and average marginal effects, and statistical software such as SPSS by IBM and R by Open-Source Model is utilized for data analysis. Key findings indicate that more than half of the officers referred intimate partner violence survivors to shelters and assisted victims in filing protection orders. Counseling practices varied across provinces and between male and female officers. Agency training and the use of BWC were positively associated with non-coercive and supportive approaches, while knowledge of the DV Act, male dominance score, and gender equality score did not predict the use of such approaches. Demographic characteristics, including police rank, length of service, and province of employment, influenced the utilization of non-coercive and supportive approaches. This study examines the challenges faced by Chinese police officers when responding to DV cases and their willingness to provide supportive interventions. The study highlights the complexities surrounding the initiation of protection orders due to officers' legal knowledge and discretion. The study emphasizes the importance of police support in addressing DV in China and the role of agency training in promoting non-coercive responses. It highlights regional variations in police support and underscores the need for addressing disparities in service provision across different provinces.

Diabetes mellitus and Alzheimer's disease: Vacuolar adenosine triphosphatase as a potential link.

Globally, the incidence of diabetes mellitus (DM) and Alzheimer's disease (AD) is increasing year by year, causing a huge economic and social burden, and their pathogenesis and aetiology have been proven to have a certain correlation. In recent years, more and more studies have shown that vacuolar adenosine triphosphatases (v-ATPases) in eukaryotes, which are biomolecules regulating lysosomal acidification and glycolipid metabolism, play a key role in DM and AD. This article describes the role of v-ATPase in DM and AD, including its role in glycolysis, insulin secretion and insulin resistance (IR), as well as its relationship with lysosomal acidification, autophagy and ß-amyloid (Aß). In DM, v-ATPase is involved in the regulation of glucose metabolism and IR. v-ATPase is closely related to glycolysis. On the one hand, v-ATPase affects the rate of glycolysis by affecting the secretion of insulin and changing the activities of key glycolytic enzymes hexokinase (HK) and phosphofructokinase 1 (PFK-1). On the other hand, glucose is the main regulator of this enzyme, and the assembly and activity of v-ATPase depend on glucose, and glucose depletion will lead to its decomposition and inactivation. In addition, v-ATPase can also regulate free fatty acids, thereby improving IR. In AD, v-ATPase can not only improve the abnormal brain energy metabolism by affecting lysosomal acidification and autophagy but also change the deposition of Aß by affecting the production and degradation of Aß. Therefore, v-ATPase may be the bridge between DM and AD.