A tumour-associated macrophage-based signature for deciphering prognosis and immunotherapy response in prostate cancer.

For the multistage progression of prostate cancer (PCa) and resistance to immunotherapy, tumour-associated macrophage is an essential contributor. Although immunotherapy is an important and promising treatment modality for cancer, most patients with PCa are not responsive towards it. In addition to exploring new therapeutic targets, it is imperative to identify highly immunotherapy-sensitive individuals. This research aimed to establish a signature risk model, which derived from the macrophage, to assess immunotherapeutic responses and predict prognosis. Data from the UCSC-XENA, GEO and TISCH databases were extracted for analysis. Based on both single-cell datasets and bulk transcriptome profiles, a macrophage-related score (MRS) consisting of the 10-gene panel was constructed using the gene set variation analysis. MRS was highly correlated with hypoxia, angiogenesis, and epithelial-mesenchymal transition, suggesting its potential as a risk indicator. Moreover, poor immunotherapy responses and worse prognostic performance were observed in the high-MRS group of various immunotherapy cohorts. Additionally, APOE, one of the constituent genes of the MRS, affected the polarisation of macrophages. In particular, the reduced level of M2 macrophage and tumour progression suppression were observed in PCa xenografts which implanted in Apolipoprotein E-knockout mice. The constructed MRS has the potential as a robust prognostic prediction tool, and can aid in the treatment selection of PCa, especially immunotherapy options.

ISRIB ameliorates spatial learning and memory impairment induced by adolescent intermittent ethanol exposure in adult male rats.

Alcohol exposure in adolescence is considered a major cause of cognitive impairments later in life including spatial learning and memory. Integrated stress response (ISR), a program of conservative translation and transcription, is crucial in synaptic plasticity and memory. Although previous studies have elucidated ISR in different brain areas involved in learning and memory disorders, the impact of ISR on learning and memory following adolescent alcohol exposure remains unclear. Here, we demonstrated that adolescent intermittent ethanol (AIE) exposure caused spatial learning and memory impairment, combined with neuronal damage in the medial prefrontal cortex (mPFC), nucleus accumbens (NAc) and hippocampus (HIP) in adult rats. Moreover, integrated stress response inhibitor (ISRIB) administration not only improved spatial learning and memory impairment and neuronal damage but also inhibited the endoplasmic reticulum stress (ER) and reversed changes in synaptic proteins. These findings suggested that ISRIB ameliorates AIE exposure-induced spatial learning and memory deficits by improving neural morphology and synaptic function through inhibiting ER stress signaling pathway in the mPFC, NAc and HIP in adulthood. Our findings may enhance comprehension of cognitive function and neuronal effects of adolescent ethanol exposure and ISRIB treatment may be an underlying potential option for addressing alcohol-induced learning and memory deficits.

Correlation between Neutrophil-to-Lymphocyte Ratio and Diabetic Neuropathy in Chinese Adults with Type 2 Diabetes Mellitus Using Machine Learning Methods.

Objective: One of the most frequent consequences of diabetes mellitus has been identified as diabetic peripheral neuropathy (DPN), and numerous inflammatory disorders, including diabetes, have been documented to be reflected by the neutrophil-to-lymphocyte ratio (NLR). This study aimed to explore the correlation between peripheral blood NLR and DPN, and to evaluate whether NLR could be utilized as a novel marker for early diagnosis of DPN among those with type 2 Diabetes Mellitus (T2DM). Methods: We reviewed the medical records of 1154 diabetic patients treated at Tongji Hospital Affiliated to Tongji University from January 2022 to March 2023. These patients did not have evidence of acute infections, chronic inflammatory status within the past three months. The information included the clinical, laboratory, and demographic characteristics of the patient. Finally, a total of 442 T2DM individuals with reliable, complete, and accessible medical records were recruited, including 216 T2DM patients without complications (DM group) and 226 T2DM patients with complications of DPN (DPN group). One-way ANOVA and multivariate logistic regression were applied to analyze data from the two groups, including peripheral blood NLR values and other biomedical indices. The cohort was divided in a 7 : 3 ratio into training and internal validation datasets following feature selection and data balancing. Based on machine learning, training was conducted using extreme gradient boosting (XGBoost) and support vector machine (SVM) methods. K-fold cross-validation was applied for model assessment, and accuracy, precision, recall, F1-score, and the area under the receiver operating characteristic curve (AUC) were used to validate the models' discrimination and clinical applicability. Using Shapley Additive Explanations (SHAP), the top-performing model was interpreted. Results: The values of 24-hour urine volume (24H UV), lower limb arterial plaque thickness (LLAB thickness), carotid plaque thickness (CP thickness), D-dimer and onset time were significantly higher in the DPN group compared to the DM group, whereas the values of urine creatinine (UCr), total cholesterol (TC), low-density lipoprotein (LDL), alpha-fetoprotein (AFP), fasting c-peptide (FCP), and nerve conduction velocity and wave magnitude of motor and sensory nerve shown in electromyogram (EMG) were considerably lower than those in the DM group (P < 0.05, respectively). NLR values were significantly higher in the DPN group compared to the DM group (2.60 ± 4.82 versus 1.85 ± 0.98, P < 0.05). Multivariate logistic regression analysis revealed that NLR (P = 0.008, C = 0.003) was a risk factor for DPN. The multivariate logistic regression model scores were 0.6241 for accuracy, 0.6111 for precision, 0.6667 for recall, 0.6377 for F1, and 0.6379 for AUC. Machine learning methods, XGBoost and SVM, built prediction models, showing that NLR can predict the onset of DPN. XGBoost achieved an accuracy of 0.6541, a precision of 0.6316, a recall of 0.7273, a F1 value of 0.6761, and an AUC value of 0.690. SVM scored an accuracy of 0.5789, a precision of 0.5610, a recall of 0.6970, an F1 value of 0.6216, and an AUC value of 0.6170. Conclusions: Our findings demonstrated that NLR is highly correlated with DPN and is an independent risk factor for DPN. NLR might be a novel indicator for the early diagnosis of DPN. XGBoost and SVM models have great predictive performance and could be reliable tools for the early prediction of DPN in T2DM patients. This trial is registered with ChiCTR2400087019.

Ligustrazine alleviates the progression of coronary artery calcification by inhibiting caspase-3/GSDME mediated pyroptosis.

Coronary artery calcification (CAC) is an early marker for atherosclerosis and is mainly induced by the osteoblast-like phenotype conversion of vascular smooth muscle cells (VSMCs). Recent reports indicate that NOD-like receptor protein 3 (NLRP3)-mediated pyroptosis plays a significant role in the calcification of vascular smooth muscle cells (VSMCs), making it a promising target for treating calcific aortic valve disease (CAC). Ligustrazine, or tetramethylpyrazine (TMP), has been found effective in various cardiovascular and cerebrovascular diseases and is suggested to inhibit NLRP3-mediated pyroptosis. However, the function of TMP in CAC is unknown. Herein, influences of TMP on ß-glycerophosphate (ß-GP)-stimulated VSMCs and OPG-/- mice were explored. Mouse Aortic Vascular Smooth Muscle (MOVAS-1) cells were stimulated by ß-GP with si- caspase-3, si- Gasdermin E (GSDME) or TMP. Increased calcification, reactive oxygen species (ROS) level, Interleukin-1beta (IL-1ß) and Interleukin-18 (IL-18) levels, lactate dehydrogenase (LDH) release, enhanced apoptosis, and activated cysteine-aspartic acid protease-3 (caspase-3)/GSDME signaling were observed in ß-GP-stimulated MOVAS-1 cells, which was sharply alleviated by si-caspase-3, si-GSDME or TMP. Furthermore, the impact of TMP on the ß-GP-induced calcification and injury in MOVAS-1 cells was abolished by raptinal, an activator of caspase-3. Subsequently, OPG-/- mice were dosed with TMP or TMP combined with raptinal. Calcium deposition, increased nodules, elevated IL-1ß and IL-18 levels, upregulated CASP3 and actin alpha 2, smooth muscle (ACTA2), and activated caspase-3/GSDME signaling in OPG-/- mice were markedly alleviated by TMP, which were notably reversed by the co-administration of raptinal. Collectively, TMP mitigated CAC by inhibiting caspase-3/GSDME mediated pyroptosis.

Screening of Intermetallic Compounds Based on Intermediate Adsorption Equilibrium for Electrocatalytic Nitrate Reduction to Ammonia.

Electrocatalytic nitrate (NO3-) reduction reaction (NO3RR) holds great potential for the conversion of NO3- contaminants into valuable NH3 in a sustainable method. Unfortunately, the nonequilibrium adsorption of intermediates and sluggish multielectron transfer have detrimental impacts on the electrocatalytic performance of the NO3RR, posing obstacles to its practical application. Herein, we initially screen the adsorption energies of three key intermediates, i.e., *NO3, *NO, and *H2O, along with the d-band centers on 21 types of transition metal (IIIV and IB)-Sb/Bi-based intermetallic compounds (IMCs) as electrocatalysts. The results reveal that hexagonal CoSb IMCs possess the optimal adsorption equilibrium for key intermediates and exhibit outstanding electrocatalytic NO3RR performance with a Faradaic efficiency of 96.3%, a NH3 selectivity of 89.1%, and excellent stability, surpassing the majority of recently reported NO3RR electrocatalysts. Moreover, the integration of CoSb IMCs/C into a novel Zn-NO3- battery results in a high power density of 11.88 mW cm-2.

Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors.

BACKGROUND: Diabetic peripheral neuropathy (DPN) and lower extremity arterial disease (LEAD) are significant contributors to diabetic foot ulcers (DFUs), which severely affect patients' quality of life. This study aimed to develop machine learning (ML) predictive models for DPN and LEAD and to identify both shared and distinct risk factors. METHODS: This retrospective study included 479 diabetic inpatients, of whom 215 were diagnosed with DPN and 69 with LEAD. Clinical data and laboratory results were collected for each patient. Feature selection was performed using three methods: mutual information (MI), random forest recursive feature elimination (RF-RFE), and the Boruta algorithm to identify the most important features. Predictive models were developed using logistic regression (LR), random forest (RF), and eXtreme Gradient Boosting (XGBoost), with particle swarm optimization (PSO) used to optimize their hyperparameters. The SHapley Additive exPlanation (SHAP) method was applied to determine the importance of risk factors in the top-performing models. RESULTS: For diagnosing DPN, the XGBoost model was most effective, achieving a recall of 83.7%, specificity of 86.8%, accuracy of 85.4%, and an F1 score of 83.7%. On the other hand, the RF model excelled in diagnosing LEAD, with a recall of 85.7%, specificity of 92.9%, accuracy of 91.9%, and an F1 score of 82.8%. SHAP analysis revealed top five critical risk factors shared by DPN and LEAD, including increased urinary albumin-to-creatinine ratio (UACR), glycosylated hemoglobin (HbA1c), serum creatinine (Scr), older age, and carotid stenosis. Additionally, distinct risk factors were pinpointed: decreased serum albumin and lower lymphocyte count were linked to DPN, while elevated neutrophil-to-lymphocyte ratio (NLR) and higher D-dimer levels were associated with LEAD. CONCLUSIONS: This study demonstrated the effectiveness of ML models in predicting DPN and LEAD in diabetic patients and identified significant risk factors. Focusing on shared risk factors may greatly reduce the prevalence of both conditions, thereby mitigating the risk of developing DFUs.

Ratiometric fluorescent test strips based on CB-Ni2+@CDs probes for visual detection of histamine.

Histamine is a biogenic amine with various physiological functions. However, excessive consumption of histamine can lead to various symptoms, and pose a threat to human lives. A ratiometric fluorescent test strip for visual detection of histamine was developed based on CB-Ni2+@CDs probes. As the concentration of histamine increases, the test strips exhibit a transition in fluorescence signal from yellow-green to blue. The RGB values were extracted from the images, and used for quantitative analysis of histamine. The method had a linear range of 0-1.0 mM, with a detection limit of 0.086 mM. The test strips were employed for the detection of histamine, and the recovery rate was found to be in the range of 88.3% to 104.69%, indicating a high level of accuracy. The uniqueness of the test strips lies in their ability to be produced simply by mixing CB, Ni2+ on a suitable polyvinyl alcohol/wood cellulose fiber substrate.

The Role and Mechanism of the Histone Methyltransferase G9a in Tumors: Update.

Methylation-mediated gene silencing is closely related to the occurrence and development of human tumors. The euchromatic histone lysine methyltransferase 2 (EHMT2, also known as G9a) is highly expressed in many tumors and is generally considered to be an oncogene, which is associated with the poor outcome of many tumors. Combined immunotherapy and immune checkpoint blockade therapy also have good efficacy and certain safety. However, there are still many difficulties in the drugs targeting G9a, and the combined effect and safety of G9a with many drugs is still under study. This article aims to summarize the role and mechanism of G9a and its inhibitors in tumors in the past two years, and to understand the application prospect of G9a from the perspective of diagnosis and treatment.

Utilization of Pickering emulsion stabilized by chitin nanofibers for improving water and oxygen resistance of gelatin films.

The hydrophilicity of gelatin films obviously limits their application. In this work, novel protonated chitin nanofiber was prepared with green methods, surficial deacetylation combined with acidic and mechanical treatment. Composite films with excellent water and oxygen barrier properties were successfully prepared by blending O/W Pickering emulsions stabilized by chitin nanofibers with gelatin substrates. The films were characterized by Fourier-transform infrared, X-ray diffraction, mechanical properties, water and oxygen permeability, moisture content, water solubility, water contact angle and optical properties. The results demonstrated that the amino groups of chitin nanofibers bound to the carboxyl groups of gelatin via electrostatic interactions, which contributing to the excellent mechanical and barrier properties of composite films. The elongation at break of composite film (the concentration of chitin nanofiber was 0.2 wt%) was 2.66 times of gelatin film. And the water vapor and oxygen permeability of composite films lowered to 65.9 % and 52.9 %, respectively. The introduction of O/W Pickering emulsion significantly enhanced the hydrophobicity of gelatin-based film and the chitin nanofibers played a positive role in stabilizing the gelatin chains to a certain extent. This study expands the application fields of gelatin-based films and provides valuable technical route for the preparation of barrier films.

Heterophase Intermetallic Compounds for Electrocatalytic Hydrogen Production at Industrial-Scale Current Densities.

Heterophase nanomaterials have sparked significant research interest in catalysis due to their distinctive properties arising from synergistic effects of different components and the formed phase boundary. However, challenges persist in the controlled synthesis of heterophase intermetallic compounds (IMCs), primarily due to the lattice mismatch of distinct crystal phases and the difficulty in achieving precise control of the phase transitions. Herein, orthorhombic/cubic Ru2Ge3/RuGe IMCs with engineered boundary architecture are synthesized and anchored on the reduced graphene oxide. The Ru2Ge3/RuGe IMCs exhibit excellent hydrogen evolution reaction (HER) performance with a high current density of 1000 mA cm-2 at a low overpotential of 135 mV. The presence of phase boundaries enhances charge transfer and improves the kinetics of water dissociation while optimizing the processes of hydrogen adsorption/desorption, thus boosting the HER performance. Moreover, an anion exchange membrane electrolyzer is constructed using Ru2Ge3/RuGe as the cathode electrocatalyst, which achieves a current density of 1000 mA cm-2 at a low voltage of 1.73 V, and the activity remains virtually undiminished over 500 h.

Confronting Inequalities and Bridging the Divide: A Retrospective Study Assessment of Country-Level COVID-19 Vaccine Equality with a Cox Regression Model.

COVID-19 vaccination is vital in reducing illness, hospitalization, and mortality in the face of this global pandemic. However, COVID-19 vaccination rates worldwide remain below WHO public health targets, and persistent structural inequities reduce vaccine uptake likelihood among populations of low socioeconomic status. We conducted a cross-sectional study based on publicly available data from the Our World in Data project. We included all 124 countries with available open epidemic data and a population of more than 5 million. We used a Cox Regression Model, with population, population density, median age, human development index, GDP per capita, gender inequality index, healthcare access and quality index, hospital beds per thousand people, completion rate of primary education, infection cases of COVID-19 by the end of 2022, and death rate due to COVID-19 by the end of 2022 as predictors for model hazard rates of completion of 50% population vaccination. According to our study, countries with higher populations, higher population density, higher human development index, lower gender inequality index, and lower hospital beds per 1000 people had a higher hazard rate, which means they were more likely to achieve 50% population vaccination faster. By utilizing the time to achieve vaccination rate goals as our primary endpoint, we evaluated inequity from a dual perspective, considering both the differences in vaccination rates and the duration required to attain them. Consequently, this study employed survival analysis approaches to gain a comprehensive understanding of vaccine drivers and population-level trends nationally and inform all communities from a statistical perspective to prepare for health emergencies. Development-level standing modified the effects of equal access to COVID-19 vaccination on cumulative cases and mortality, for which countries of low or medium human development tended to fare worse in outcomes than high human development countries. As COVID-19 vaccination efforts evolve, healthcare professionals, scholars, and policymakers need to identify the structural impediments to equitable vaccination awareness, access, and uptake so that future vaccination campaigns are not impeded by these barriers to immunization. Recognizing the complex nature of this significant barrier, it is evident that no single statistical analysis method can comprehensively address all intricacies.

Current evidence on the relationships among five polymorphisms in the matrix metalloproteinases genes and prostate cancer risk.

Matrix metalloproteinases (MMPs) had a variety of subtypes, which may be related to tumor invasion and angiogenesis, and the polymorphisms from MMPs have been also associated with the susceptibility to a variety of tumors, including prostate cancer (PCa). However, previous studies have not systematically analyzed the association between MMP and prostate cancer, so we conducted systematic data collection and analyzed to evaluate the relationship among polymorphisms in MMPs and PCa susceptibility. We searched PubMed, Web of Science, Embase and Google Scholar for all papers published up to Apr 3rd, 2023, and systematically analyzed the relationship among MMP1-1607 2G/1G, MMP2-1306 T/C, MMP2-735 T/C, MMP7-181 G/A, MMP9-1562 T/C and PCa susceptibility using multiple comparative models and subgroup analyses. We found that MMP2-1306 T/C polymorphism showed associations with PCa susceptibility, with the Ethnicity subgroup (Asian) being more pronounced. Similarly, MMP9-1562 T/C has also had associations with PCa susceptibility. Our current study found that the polymorphisms of, MMP2-1306 T/C, and MMP9-1562 T/C had strong associations with PCa risk.

Identification of key genes related to heart failure by analysis of expression profiles.

Introduction: To elucidate the candidate biomarkers involved in the pathogenesis process of heart failure (HF) via analysis of differentially expressed genes (DEGs) of the dataset from the Gene Expression Omnibus (GEO). Material and methods: The GSE76701 gene expression profiles regarding the HF and control subjects were respectively analysed. Briefly, DEGs were firstly identified and subjected to Cytoscape plug-in ClueGO + CluePedia and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein-protein interaction (PPI) network was then built to analyse the interaction between DEGs, followed by the construction of an interaction network by combining with hub genes with the targeted miRNA genes of DEGs to identify the key molecules of HF. In addition, potential drugs targeting key DEGs were sought using the drug-gene interaction database (DGIdb), and a drug-mRNA-miRNA interaction network was also constructed. Results: A total of 489 DEGs were verified between HF and control, which mainly enriched in type I interferon and leukocyte migration according to molecular function. Significantly increased levels of GAPDH, GALM1, MMP9, CCL5, and GNAL2 were found in the HF setting and were identified as the hub genes based on the PPI network. Furthermore, according to the drug-mRNA-miRNA network, FCGR2B, CCND1, and NF-κb, as well as corresponding miRNA-605-5p, miRNA-147a, and miRNA-671-5p were identified as the drug targets of HF. Conclusions: The hub genes GAPDH, GALM1, MMP9, CCL5, and GNAL2 were significantly increased in HF. miRNA-605-5p, miRNA-147a, and miRNA-671-5p were predicted as the drug target-interacted gene-miRNA of HF.

Breaking Highly Ordered PtPbBi Intermetallic with Disordered Amorphous Phase for Boosting Electrocatalytic Hydrogen Evolution and Alcohol Oxidation.

Constructing amorphous/intermetallic (A/IMC) heterophase structures by breaking the highly ordered IMC phase with disordered amorphous phase is an effective way to improve the electrocatalytic performance of noble metal-based IMC electrocatalysts because of the optimized electronic structure and abundant heterophase boundaries as active sites. In this study, we report the synthesis of ultrathin A/IMC PtPbBi nanosheets (NSs) for boosting hydrogen evolution reaction (HER) and alcohol oxidation reactions. The resulting A/IMC PtPbBi NSs exhibit a remarkably low overpotential of only 25 mV at 10 mA cm-2 for the HER in an acidic electrolyte, together with outstanding stability for 100 h. In addition, the PtPbBi NSs show high mass activities for methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR), which are 13.2 and 14.5 times higher than those of commercial Pt/C, respectively. Density functional theory calculations demonstrate that the synergistic effect of amorphous/intermetallic components and multimetallic composition facilitate the electron transfer from the catalyst to key intermediates, thus improving the catalytic activity of MOR. This work establishes a novel pathway for the synthesis of heterophase two-dimensional nanomaterials with high electrocatalytic performance across a wide range of electrochemical applications.

Stability and 3D-printing performance of high-internal-phase emulsions based on ultrafine soybean meal particles.

There are numerous studies on the application of soybean whey protein in three-dimensional (3D) printing. In this study, the effects of soybean meal particles (5%, 6%, 7%, 8%, 9%, and 10%) and oil-phase concentrations (70%, 72%, 74%, 76%, and 78%) on the stability and 3D-printing performance of a soybean-meal-based high-internal-phase emulsion were investigated. The results showed that the particle size of the emulsion decreased with increasing soybean meal particle concentration, and that increasing the concentration of the oil phase improved the viscoelasticity of the emulsion. Rheological tests further showed that the higher storage modulus of the emulsion indicated better support and stability. The emulsion with 8% soybean meal-particles and 76% oil-phase concentration exhibited the best printing effect. This study provides an effective solution for the preparation of stabilized high-internal-phase emulsions of soybean meal particles suitable for 3D printing.

Highly Sensitive Iontronic Pressure Sensor with Side-by-Side Package Based on Alveoli and Arch Structure.

Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double-sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side-by-side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa-300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa-1, pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non-contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.

A new bufadienolide from Bufo gargarizans Cantor.

Bufo gargarizans Cantor (B. gargarizans) is the most widely distributed and abundant species of toad in China. Bufadienolides and indole alkaloids have cardiotonic and anti-tumor activities and are important pharmacological components of B. bufo gargarizans. In this experiment, a novel compound (1) and two known compounds (2 and 3) were isolated and identified from the dry skin of B. bufo gargarizans, both of which are bufadienolides. Various column chromatography methods were used to separate and purify the extract from the dried skin of B. bufo gargarizans. Accurate molecular weights were measured by HR-ESI-MS, and the chemical structure of the compounds was determined by NMR spectrometers. The structures were named as (2ß,5ß,16α)-2,5,16-trihydroxide bufa-14,20,22 dienolide (1), gamabufotalin (2) and desacetylbufotalin (3). In vitro cytotoxic activity assay indicated that compound 1 showed a moderate cytotoxicity against A549 cells with IC50 value of 12.65 µM.

Discovery of Novel 4-Hydroxyquinazoline Derivatives: In Silico, In Vivo and In Vitro Studies Using Primary PARPi-Resistant Cell Lines.

A series of novel 4-Hydroxyquinazoline derivatives were designed and synthesized to enhance sensitivity in primary PARPi-resistant cells. Among them, the compound B1 has been found to have superior cytotoxicity in primary PARPi-resistant HCT-15 and HCC1937 cell lines, and dose-dependently suppressed the intracellular PAR formation and enhanced the γH2AX aggregation. Mechanistic study showed that B1 stimulated the formation of intracellular ROS and the depolarization of the mitochondrial membrane, which could increase apoptosis and cytotoxicity. An in vivo study showed that B1 significantly suppressed tumor growth at a dose of 25 mg/kg, and an acute toxicity study confirmed its safety. Molecular docking and dynamics simulations revealed that hydrogen bonding between B1 and ASP766 may be helpful to enhance anti-drug resistance ability. This study suggests that B1 is a potent PARP inhibitor that can overcome PARPi resistance and deserves further investigation.

Self-Powered Intelligent Water Droplet Monitoring Sensor Based on Solid-Liquid Triboelectric Nanogenerator.

Real-time monitoring of rainwater is a critical issue in the development of autonomous vehicles and smart homes, while the corresponding sensors play a pivotal role in ensuring their sensitivity. Here, we study a self-powered intelligent water droplet monitoring sensor based on a solid-liquid triboelectric nanogenerator (SL-TENG). The sensor comprises a SL-TENG, a signal acquisition module, a central processing unit (CPU), and a wireless transmission module, facilitating the real-time monitoring of water droplet signals. It is worth noting that the SL-TENG has self-powering characteristics and can convert the kinetic energy of water droplets into electrical energy. The excellent output performance, with open-circuit voltage of 9 V and short-circuit current of 2 µA without any treatment of the SL-TENG, can provide an effective solution to the problem that traditional sensor need battery replacement. In addition, the SL-TENG can generate stable amplitude electrical signals through water droplets, exemplified by the absence of decay in a short-circuit current within 7 days. More importantly, the sensor is equipped with intelligent analytical capabilities, allowing it to assess rainfall based on variables such as amplitude and frequency. Due to its excellent stability and intelligent analysis, this sensor can be used for roof rainwater monitoring, intravenous administration monitoring, and especially in automobile automatic wipers and other fields.

Efficacy of Internet-Based Cognitive Behavioral Therapy for Subthreshold Depression Among Older Adults in Institutional Long-Term Care Settings: Pragmatic Randomized Controlled Trial.

BACKGROUND: Subthreshold depression (sD) is prevalent in older populations in long-term care (LTC) settings, but psychological therapy in LTC settings in China is not readily available. Thus, internet-based cognitive behavioral therapy (ICBT) may be suitable for this population, but research on the efficacy of ICBT for older adults with sD, especially those living in LTC settings, is limited. OBJECTIVE: This study aimed to evaluate the efficacy and acceptability of ICBT treatment for sD among LTC residents in China. We also examined whether ICBT is as effective as group-based cognitive behavioral therapy (CBT) for treating sD in this population. METHODS: We conducted a pragmatic randomized controlled trial, which included 18 LTC institutions. A total of 354 participants were randomized to ICBT, group-based CBT, or a waiting list and were followed up for 12 months. The primary outcome was self-reported depressive symptoms on the Center for Epidemiological Studies Depression Scale (CES-D). Secondary outcomes were the scores of the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-Item (GAD-7), and Geriatric Depression Scale (GDS). A mixed-effects model was used to assess the efficacy of ICBT. RESULTS: The ICBT group showed a significant improvement in self-reported depressive symptoms, which was maintained at the 12-month follow-up (all P<.001). The ICBT group exhibited a significantly larger reduction in the scores of the CES-D (Cohen d=0.07, 95% CI 0.04-0.09; P=.01), PHQ-9 (d=0.30, 95% CI 0.28-0.33; P<.001), GDS (d=0.10, 95% CI 0.08-0.13; P<.001), and GAD-7 (d=0.19, 95% CI 0.17-0.22; P<.001) compared with a waiting list at postintervention. ICBT had significantly stronger effects than CBT on the PHQ-9 and GAD-7 at postintervention (d=0.15, 95% CI 0.13-0.17; P<.001 and d=0.21, 95% CI 0.19-0.23; P<.001, respectively), 6-month follow-up (d=0.18, 95% CI 0.16-0.21; P<.001 and d=0.18, 95% CI 0.15-0.21; P<.001, respectively), and 12-month follow-up (d=0.15, 95% CI 0.11-0.19; P<.001 and d=0.18, 95% CI 0.14-0.21; P<.001, respectively). CONCLUSIONS: ICBT is a relatively effective and acceptable intervention for reducing depressive symptoms among Chinese LTC residents with sD. These findings indicate the usefulness of ICBT application for sD in LTC settings. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000030697; https://www.chictr.org.cn/showproj.aspx?proj=50781.