Design of Multifunctional Electrocatalysts for ORR/OER/HER/HOR: Janus Makes Difference.

Multifunctional electrocatalysts for hydrogen evolution reaction (HER), hydrogen oxidation reaction (HOR), oxygen evolution reaction (OER), and oxygen reduction reaction (ORR) have broad application prospects; However, realization of such kinds of materials remain difficulties because it requires the materials to have not only unique electronic properties, but multiple active centers to deal with different reactions. Here, employing density functional theory (DFT) computations, it is demonstrated that by decorating the Janus-type 2D transition metal dichalcogenide (TMD) of TaSSe with the single atoms, the materials can achieve multifunctionality to catalyze the ORR/OER/HER/HOR. Out of sixteen catalytic systems, Pt-VS (i.e., Pt atom embedded in the sulfur vacancy), Pd-VSe, and Pt-VSe@TaSSe are promising multifunctional catalysts with superior stability. Among them, the Pt-VS@TaSSe catalyst exhibits the highest activity with theoretical overpotentials ηORR = 0.40 V, ηOER = 0.39 V, and ηHER/HOR = 0.07 V, respectively, better than the traditional Pt (111), IrO2 (110). The interplays between the catalyst and the reaction intermediate over the course of the reaction are then systematically investigated. Generally, this study presents a viable approach for the design and development of advanced multifunctional electrocatalysts. It enriches the application of Janus, a new 2D material, in electrochemical energy storage and conversion technology.

Distribution and typologies of anthropogenic seafloor litter in the Pearl River Estuary and adjacent coastal waters, China.

Marine litter pollution poses a significant threat to offshore ecosystems, eliciting widespread concern. We investigated seafloor litter patterns in the Pearl River Estuary and adjacent coastal waters of China in 2023 via bottom trawl survey. Average number and weight densities were found to be 154.34 ± 30.95 n/km2 and 2384.63 ± 923.98 g/km2, respectively. Plastic was the most abundant material by number density (79.07 %), and rubber the highest by weight density (22.93 %). Overall number density varied from 40.50 ± 22.50 to 221.13 ± 52.44 n/km2, with the highest in Daya Bay and the lowest in Guanghai Bay. Weight density varied from 189.93 ± 71.94 to 5386.70 ± 3050.30 g/km2, with the highest in Qiao Island and the lowest in Honghai Bay. The main source was plastic bags and wrappers. The Pearl River Delta and Daya Bay were identified as seafloor litter distribution hotspots. Controlling plastic waste input is crucial for reducing seafloor litter in the Pearl River Estuary.

Solvent-free synthesis of defective Zr-based metal-organic framework from waste plastic bottles for highly efficient lomefloxacin removal.

Large amount of polyethylene terephthalate (PET) plastics waster and emerging contaminants in water, including fluoroquinolone antibiotics, pose challenges to human survival. In this work, a green synthesis scheme is proposed in which the defective UiO-66 (d-UiO-66) is fabricated via a solvent-free routine by using PET plastics waster as raw materials for lomefloxacin (LOM) removal. In comparison with defect-free UiO-66, the created defect imparts d-UiO-66 with higher porosity and abundant defective Zr sites, which are beneficial to boost LOM adsorption. As expected, d-UiO-66 exhibited excellent LOM adsorption performances, showcasing a saturation adsorption capacity of 588 mg g-1 and a kinetic rate constant of 0.204 g mg-1 h-1, which are 3.5 and 2.0 times higher than those of the pristine UiO-66, respectively. Remarkably, the LOM saturation adsorption capacity of d-UiO-66 surpasses that of all reported adsorbents. Mechanism study reveals that this outstanding adsorption performance of d-UiO-66 is mainly ascribed to the abundant defective sites, high porosity, together with the strong hydrogen bonding interaction and π-π stacking interaction between d-UiO-66 and LOM. Therefore, the d-UiO-66 obtained by the solvent-free method can not only effectively upcycle PET plastic waster, but also efficiently remove LOM, demonstrating a potential routine to simultaneous address the solid PET waster and wastewater.

CMYC-initiated HNF1A-AS1 overexpression maintains the stemness of gastric cancer cells.

Cancer stem cells (CSCs) are believed to be responsible for cancer metastasis and recurrence due to their self-renewal ability and resistance to treatment. However, the mechanisms that regulate the stemness of CSCs remain poorly understood. Recently, evidence has emerged suggesting that long non-coding RNAs (lncRNAs) play a crucial role in regulating cancer cell function in different types of malignancies, including gastric cancer (GC). However, the specific means by which lncRNAs regulate the function of gastric cancer stem cells (GCSCs) are yet to be fully understood. In this study, we investigated a lncRNA known as HNF1A-AS1, which is highly expressed in GCSC s and serves as a critical regulator of GCSC stemness and tumorigenesis. Our experiments, both in vitro and in vivo, demonstrated that HNF1A-AS1 maintained the stemness of GC cells. Further analysis revealed that HNF1A-AS1, transcriptionally activated by CMYC, functioned as a competing endogenous RNA by binding to miR-150-5p to upregulate ß-catenin expression. This in turn facilitated the entry of ß-catenin into the nucleus to activate the Wnt/ß-catenin pathway and promote CMYC expression, thereby forming a positive feedback loop that sustained the stemness of GCSCs. We also found that blocking the Wnt/ß-catenin pathway effectively inhibited the function of HNF1A-AS1, ultimately resulting in the inhibition of GCSC stemness. Taken together, our results demonstrated that HNF1A-AS1 is a regulator of the stemness of GCSCs and could serve as a potential marker for targeted GC therapy.

Development and Validation of a Deep Learning Model to Reduce the Interference of Rectal Artifacts in MRI-based Prostate Cancer Diagnosis.

Purpose To develop an MRI-based model for clinically significant prostate cancer (csPCa) diagnosis that can resist rectal artifact interference. Materials and Methods This retrospective study included 2203 male patients with prostate lesions who underwent biparametric MRI and biopsy between January 2019 and June 2023. Targeted adversarial training with proprietary adversarial samples (TPAS) strategy was proposed to enhance model resistance against rectal artifacts. The automated csPCa diagnostic models trained with and without TPAS were compared using multicenter validation datasets. The impact of rectal artifacts on the diagnostic performance of each model at the patient and lesion levels was compared using the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUPRC). The AUC between models was compared using the DeLong test, and the AUPRC was compared using the bootstrap method. Results The TPAS model exhibited diagnostic performance improvements of 6% at the patient level (AUC: 0.87 vs 0.81, P < .001) and 7% at the lesion level (AUPRC: 0.84 vs 0.77, P = .007) compared with the control model. The TPAS model demonstrated less performance decline in the presence of rectal artifact-pattern adversarial noise than the control model (ΔAUC: -17% vs -19%, ΔAUPRC: -18% vs -21%). The TPAS model performed better than the control model in patients with moderate (AUC: 0.79 vs 0.73, AUPRC: 0.68 vs 0.61) and severe (AUC: 0.75 vs 0.57, AUPRC: 0.69 vs 0.59) artifacts. Conclusion This study demonstrates that the TPAS model can reduce rectal artifact interference in MRI-based csPCa diagnosis, thereby improving its performance in clinical applications. Keywords: MR-Diffusion-weighted Imaging, Urinary, Prostate, Comparative Studies, Diagnosis, Transfer Learning Clinical trial registration no. ChiCTR23000069832 Supplemental material is available for this article. Published under a CC BY 4.0 license.

Case Report: A rare case of intramedullary spinal cord abscess with brain abscess caused by Klebsiella pneumoniae underwent surgical intervention.

Background: Intramedullary Spinal Cord Abscess (ISCA) is an uncommon infectious disease of the central nervous system. Since its first report in 1830, there have been very few documented cases associated with it. Here, we present a case of ISCA with cerebral abscess caused by Klebsiella pneumoniae. Case presentation: A 55-year-old male patient presented with head and neck pain, fever, and left limb weakness for 5 days. The diagnosis of ISCA with brain abscess caused by Klebsiella pneumoniae was confirmed through sputum culture, cerebrospinal fluid gene test, pus culture, and magnetic resonance imaging (MRI) as well as computerized tomography (CT) scan. The patient had a history of pulmonary tuberculosis and old tuberculous foci were observed in the lung. Initially considering tuberculosis as the cause due to unclear etiology at that time, anti-tuberculosis treatment was administered. However, due to rapid deterioration in the patient's condition and severe neurological dysfunction within a short period of time after admission, surgical intervention including incision and drainage for intramedullary abscess along with removal of brain abscess was performed. Subsequent postoperative follow-up showed improvement in both symptoms and imaging findings. Conclusion: Early diagnosis of central nervous system (CNS) abscess coupled with prompt surgical intervention and administration of appropriate antibiotics are crucial factors in preventing disease progression and reducing mortality rates.

STGIC: A graph and image convolution-based method for spatial transcriptomic clustering.

Spatial transcriptomic (ST) clustering employs spatial and transcription information to group spots spatially coherent and transcriptionally similar together into the same spatial domain. Graph convolution network (GCN) and graph attention network (GAT), fed with spatial coordinates derived adjacency and transcription profile derived feature matrix are often used to solve the problem. Our proposed method STGIC (spatial transcriptomic clustering with graph and image convolution) is designed for techniques with regular lattices on chips. It utilizes an adaptive graph convolution (AGC) to get high quality pseudo-labels and then resorts to dilated convolution framework (DCF) for virtual image converted from gene expression information and spatial coordinates of spots. The dilation rates and kernel sizes are set appropriately and updating of weight values in the kernels is made to be subject to the spatial distance from the position of corresponding elements to kernel centers so that feature extraction of each spot is better guided by spatial distance to neighbor spots. Self-supervision realized by Kullback-Leibler (KL) divergence, spatial continuity loss and cross entropy calculated among spots with high confidence pseudo-labels make up the training objective of DCF. STGIC attains state-of-the-art (SOTA) clustering performance on the benchmark dataset of 10x Visium human dorsolateral prefrontal cortex (DLPFC). Besides, it's capable of depicting fine structures of other tissues from other species as well as guiding the identification of marker genes. Also, STGIC is expandable to Stereo-seq data with high spatial resolution.

MS3 Imaging Enables the Simultaneous Analysis of Phospholipid C═C and sn-Position Isomers in Tissues.

Mass spectrometry (MS) imaging of lipids in tissues with high structure specificity is challenging in the effective fragmentation of position-selective structures and the sensitive detection of multiple lipid isomers. Herein, we develop an MS3 imaging method for the simultaneous analysis of phospholipid C═C and sn-position isomers by on-tissue photochemical derivatization, nanospray desorption electrospray ionization (nano-DESI), and a dual-linear ion trap MS system. A novel laser-based sensing probe is developed for the real-time adjustment of the probe-to-surface distance for nano-DESI. This method is validated in mouse brain and kidney sections, showing its capability of sensitive resolving and imaging of the fatty acyl chain composition, the sn-position, and the C═C location of phospholipids in an MS3 scan. MS3 imaging of phospholipids has shown the capability of differentiation of cancerous, fibrosis, and adjacent normal regions in liver cancer tissues.

Corrigendum to: Investigation of the Apoptosis Inducing and ß-catenin Silencing by Tetradentate Schiff Base Zinc(II) Complex on the T-47D Breast Cancer Cells.

A typographical error appeared in the author affiliation titled "Investigation of the Apoptosis Inducing and ß-catenin Silencing by Tetradentate Schiff Base Zinc(II) Complex on the T-47D Breast Cancer Cells", published in Anti-Cancer Agents in Medicinal Chemistry, 2023, 23(15) [1]. Details of the error and a correction are provided here. Original: Author Affiliation: 2Department of Breast Medicine, Cancer Hospital Chinese Academy of Medical Science, Liaoning Provincial Cancer Hospital, Shenyang, Liaoning, 110042, China Corrected: Author Affiliation: 2Department of Breast Medicine, Cancer Hospital of China Medical University, Liaoning Cancer Hospital, Shenyang, China We regret the error and apologize to readers. The original article can be found online at https://www.eurekaselect.com/article/131718.

Genomic prediction for root and yield traits of barley under a water availability gradient: a case study comparing different spatial adjustments.

BACKGROUND: In drought periods, water use efficiency depends on the capacity of roots to extract water from deep soil. A semi-field phenotyping facility (RadiMax) was used to investigate above-ground and root traits in spring barley when grown under a water availability gradient. Above-ground traits included grain yield, grain protein concentration, grain nitrogen removal, and thousand kernel weight. Root traits were obtained through digital images measuring the root length at different depths. Two nearest-neighbor adjustments (M1 and M2) to model spatial variation were used for genetic parameter estimation and genomic prediction (GP). M1 and M2 used (co)variance structures and differed in the distance function to calculate between-neighbor correlations. M2 was the most developed adjustment, as accounted by the Euclidean distance between neighbors. RESULTS: The estimated heritabilities ([Formula: see text]) ranged from low to medium for root and above-ground traits. The genetic coefficient of variation ([Formula: see text]) ranged from 3.2 to 7.0% for above-ground and 4.7 to 10.4% for root traits, indicating good breeding potential for the measured traits. The highest [Formula: see text] observed for root traits revealed that significant genetic change in root development can be achieved through selection. We studied the genotype-by-water availability interaction, but no relevant interaction effects were detected. GP was assessed using leave-one-line-out (LOO) cross-validation. The predictive ability (PA) estimated as the correlation between phenotypes corrected by fixed effects and genomic estimated breeding values ranged from 0.33 to 0.49 for above-ground and 0.15 to 0.27 for root traits, and no substantial variance inflation in predicted genetic effects was observed. Significant differences in PA were observed in favor of M2. CONCLUSIONS: The significant [Formula: see text] and the accurate prediction of breeding values for above-ground and root traits revealed that developing genetically superior barley lines with improved root systems is possible. In addition, we found significant spatial variation in the experiment, highlighting the relevance of correctly accounting for spatial effects in statistical models. In this sense, the proposed nearest-neighbor adjustments are flexible approaches in terms of assumptions that can be useful for semi-field or field experiments.

Relationship between methylenetetrahydrofolate reductase C677T gene polymorphism and neutrophil gelatinase-associated lipocalin in early renal injury in H-type hypertension.

OBJECTIVE: To analyse the relationship between the polymorphisms of the H-type hypertensive methylenetetrahydrofolate reductase (MTHFR) C677T gene and neutrophil gelatinase-associated lipocalin (NGAL) in early kidney injury. METHOD: A total of 279 hospitalised patients with hypertension were selected and grouped according to their homocysteine (Hcy) level. If their blood Hcy level was ≥ 10 µmol/L they were assigned to the H-type hypertensive group, and if it was < 10 µmol/L they were assigned to the non-H-type hypertensive group. Blood lipid indexes, renal function indexes and blood glucose indexes were collected, and the differences between the two groups were compared. Furthermore, MTHFR C677T genotype distribution and allele frequency and Hcy level of MTHFR C677T genotype were compared, and logistic multiple regression analysis was conducted for the correlation of different genotypes of MTHFR C677T and the early kidney injury marker NGAL. RESULTS: In the non-H-type hypertensive group, the levels of Hcy and NGAL, cystatin, blood urea nitrogen, serum creatinine, uric acid, serum ß2-microglobulin and urinary microalbumin-to-creatinine ratio increased significantly, and the glomerular filtration rate level decreased significantly, when compared with the H-type hypertensive group, with statistical differences (p < 0.05). The H-type hypertensive group and the non-H-type hypertensive group had significant differences in the CC, CT and TT genotypes and allele frequencies at the MTHFR C677T locus. The MTHFR C677T gene mutation rate of the H-type hypertensive group was significantly higher than that of the non-H-type hypertensive group. The H-type hypertensive group had higher levels of the TT genotype and CT genotype Hcy. There was a statistical difference (p < 0.05). CONCLUSION: Methylenetetrahydrofolate reductase C677T polymorphism is correlated with the Hcy level, and its gene polymorphism will affect the Hcy level. Methylenetetrahydrofolate reductase C677T polymorphism has an interactive effect with NGAL. Screening NGAL and reducing Hcy levels are valuable methods for the prevention and treatment of early renal injury in patients with H-type hypertension and help improve the prognosis of patients and their quality of life.

Genetically modified non-human primate models for research on neurodegenerative diseases.

Neurodegenerative diseases (NDs) are a group of debilitating neurological disorders that primarily affect elderly populations and include Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS). Currently, there are no therapies available that can delay, stop, or reverse the pathological progression of NDs in clinical settings. As the population ages, NDs are imposing a huge burden on public health systems and affected families. Animal models are important tools for preclinical investigations to understand disease pathogenesis and test potential treatments. While numerous rodent models of NDs have been developed to enhance our understanding of disease mechanisms, the limited success of translating findings from animal models to clinical practice suggests that there is still a need to bridge this translation gap. Old World non-human primates (NHPs), such as rhesus, cynomolgus, and vervet monkeys, are phylogenetically, physiologically, biochemically, and behaviorally most relevant to humans. This is particularly evident in the similarity of the structure and function of their central nervous systems, rendering such species uniquely valuable for neuroscience research. Recently, the development of several genetically modified NHP models of NDs has successfully recapitulated key pathologies and revealed novel mechanisms. This review focuses on the efficacy of NHPs in modeling NDs and the novel pathological insights gained, as well as the challenges associated with the generation of such models and the complexities involved in their subsequent analysis.

LncRNA LY6E-DT and its encoded metastatic-related protein play oncogenic roles via different pathways and promote breast cancer progression.

Abnormal long noncoding RNA (lncRNA) expression plays an important role in tumor invasion and metastasis. Here, we show that lncRNA LY6E divergent transcript (LY6E-DT) levels are increased in breast cancer (BC) tissues. Transcription factor SP3 binds directly to the LY6E-DT promoter, activating its transcription. Moreover, LY6E-DT N6-methyladenosine modification by methyltransferase-like protein 14 (METTL14) promotes its expression, dependent on the "reader" insulin-like growth factor 2 mRNA binding protein 1(IGF2BP1)-dependent pathway. Notably, we discovered that the lncRNA LY6E-DT encodes a conserved 153-aa protein, "Metastatic-Related Protein" (MRP). Both LY6E-DT and MRP promote BC invasion and metastasis, and MRP expression could distinguish BC patients with lymph node metastasis from those without. Mechanistically, MRP binds heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC), enhancing the interaction between HNRNPC and epidermal growth factor receptor (EGFR) mRNA, increasing EGFR mRNA stability and protein expression and subsequently activating the phosphatidylinositol 3­kinase/protein kinase B signaling (PI3K) pathway. LncRNA LY6E-DT promotes the interaction between Y box binding protein 1 (YBX1) and importin α1 and increases YBX1 protein entry into the nucleus, where it transcriptionally activates zinc finger E-box-binding homeobox 1(ZEB1). Our findings uncover a novel regulatory mechanism underlying BC invasion orchestrated by LY6E-DT and its encoded MRP.

Object Counting via Group and Graph Attention Network.

Object counting, defined as the task of accurately predicting the number of objects in static images or videos, has recently attracted considerable interest. However, the unavoidable presence of background noise prevents counting performance from advancing further. To address this issue, we created a group and graph attention network (GGANet) for dense object counting. GGANet is an encoder-decoder architecture incorporating a group channel attention (GCA) module and a learnable graph attention (LGA) module. The GCA module groups the feature map into several subfeatures, each of which is assigned an attention factor through the identical channel attention. The LGA module views the feature map as a graph structure in which the different channels represent diverse feature vertices, and the responses between channels represent edges. The GCA and LGA modules jointly avoid the interference of irrelevant pixels and suppress the background noise. Experiments are conducted on four crowd-counting datasets, two vehicle-counting datasets, one remote-sensing counting dataset, and one few-shot object-counting dataset. Comparative results prove that the proposed abbr achieves superior counting performance.

Mobility-Modulated Sequential Dissociation Analysis Enables Structural Lipidomics in Mass Spectrometry Imaging.

Spatial lipidomics based on mass spectrometry imaging (MSI) is a powerful tool for fundamental biology studies and biomarker discovery. But the structure-resolving capability of MSI is limited because of the lack of multiplexed tandem mass spectrometry (MS/MS) method, primarily due to the small sample amount available from each pixel and the poor ion usage in MS/MS analysis. Here, we report a mobility-modulated sequential dissociation (MMSD) strategy for multiplex MS/MS imaging of distinct lipids from biological tissues. With ion mobility-enabled data-independent acquisition and automated spectrum deconvolution, MS/MS spectra of a large number of lipid species from each tissue pixel are acquired, at no expense of imaging speed. MMSD imaging is highlighted by MS/MS imaging of 24 structurally distinct lipids in the mouse brain and the revealing of the correlation of a structurally distinct phosphatidylethanolamine isomer (PE 18 : 1_18 : 1) from a human hepatocellular carcinoma (HCC) tissue. Mapping of structurally distinct lipid isomers is now enabled and spatial lipidomics becomes feasible for MSI.

Tunable-performance all-oxide structure field-effect transistor based atomic layer deposited Hf-doped In2O3 thin films.

The relocation of peripheral transistors from the front-end-of-line (FEOL) to the back-end-of-line (BEOL) in fabrication processes is of significant interest, as it allows for the introduction of novel functionality in the BEOL while providing additional die area in the FEOL. Oxide semiconductor-based transistors serve as attractive candidates for BEOL. Within these categories, In2O3 material is particularly notable; nonetheless, the excessive intrinsic carrier concentration poses a limitation on its broader applicability. Herein, the deposition of Hf-doped In2O3 (IHO) films via atomic layer deposition for the first time demonstrates an effective method for tuning the intrinsic carrier concentration, where the doping concentration plays a critical role in determine the properties of IHO films and all-oxide structure transistors with Au-free process. The all-oxide transistors with In2O3: HfO2 ratio of 10:1 exhibited optimal electrical properties, including high on-current with 249 µA, field-effect mobility of 13.4 cm2 V-1 s-1, and on/off ratio exceeding 106, and also achieved excellent stability under long time positive bias stress and negative bias stress. These findings suggest that this study not only introduces a straightforward and efficient approach to improve the properties of In2O3 material and transistors, but as well paves the way for development of all-oxide transistors and their integration into BEOL technology.

Metabolomic-genomic prediction can improve prediction accuracy of breeding values for malting quality traits in barley.

BACKGROUND: Metabolomics measures an intermediate stage between genotype and phenotype, and may therefore be useful for breeding. Our objectives were to investigate genetic parameters and accuracies of predicted breeding values for malting quality (MQ) traits when integrating both genomic and metabolomic information. In total, 2430 plots of 562 malting spring barley lines from three years and two locations were included. Five MQ traits were measured in wort produced from each plot. Metabolomic features used were 24,018 nuclear magnetic resonance intensities measured on each wort sample. Methods for statistical analyses were genomic best linear unbiased prediction (GBLUP) and metabolomic-genomic best linear unbiased prediction (MGBLUP). Accuracies of predicted breeding values were compared using two cross-validation strategies: leave-one-year-out (LOYO) and leave-one-line-out (LOLO), and the increase in accuracy from the successive inclusion of first, metabolomic data on the lines in the validation population (VP), and second, both metabolomic data and phenotypes on the lines in the VP, was investigated using the linear regression (LR) method. RESULTS: For all traits, we saw that the metabolome-mediated heritability was substantial. Cross-validation results showed that, in general, prediction accuracies from MGBLUP and GBLUP were similar when phenotypes and metabolomic data were recorded on the same plots. Results from the LR method showed that for all traits, except one, accuracy of MGBLUP increased when including metabolomic data on the lines of the VP, and further increased when including also phenotypes. However, in general the increase in accuracy of MGBLUP when including both metabolomic data and phenotypes on lines of the VP was similar to the increase in accuracy of GBLUP when including phenotypes on the lines of the VP. Therefore, we found that, when metabolomic data were included on the lines of the VP, accuracies substantially increased for lines without phenotypic records, but they did not increase much when phenotypes were already known. CONCLUSIONS: MGBLUP is a useful approach to combine phenotypic, genomic and metabolomic data for predicting breeding values for MQ traits. We believe that our results have significant implications for practical breeding of barley and potentially many other species.

CAP2 promotes gastric cancer metastasis by mediating the interaction between tumor cells and tumor-associated macrophages.

The metastasis of cancer cells is the main cause of death in patients with gastric cancer (GC). Mounting evidence has demonstrated the vital importance of tumor-associated macrophages in promoting tumor invasion and metastasis; however, the interaction between tumor cells and macrophages in GC is largely unknown. In this study, we demonstrated that cyclase-associated protein 2 (CAP2) was upregulated in GC, especially in cases with lymph node metastasis, and was correlated with a poorer prognosis. The transcription factor JUN directly bound to the promoter region of CAP2 and activated CAP2 transcription. The N-terminal domain of CAP2 bound to the WD5 to WD7 domains of receptor for activated C kinase 1 (RACK1) and induced M2 macrophage polarization by activating the SRC/focal adhesion kinase (FAK)/ERK signaling pathway, which resulted in IL-4 and IL-10 secretion. Polarized M2 macrophages induced premetastatic niche formation and promoted GC metastasis by secreting TGFB1, which created a TGFB1/JUN/CAP2 positive-feedback loop to activate CAP2 expression continuously. Furthermore, we identified salvianolic acid B as an inhibitor of CAP2, which effectively inhibited GC cell invasion capabilities by suppressing the SRC/FAK/ERK signaling pathway. Our data suggest that CAP2, a key molecule mediating the interaction between GC cells and tumor-associated macrophages, may be a promising therapeutic target for suppressing tumor metastasis in GC.

Periodontal disease and subsequent risk of cardiovascular outcome and all-cause mortality: A meta-analysis of prospective studies.

Studies reported periodontal disease (PD) periodontal disease is associated with many systemic diseases, including cardiovascular outcomes and all-cause mortality. However, the precise mechanistic link for these relationship remained unclear. We therefore performed a meta-analysis of cohort studies to investigate the association of PD with the risk of cardiovascular outcomes and all-cause mortality. We systematically searched the databases of PubMed, EmBase, and the Cochrane library to identify eligible studies until April 2023. The investigated outcomes included major adverse cardiovascular events (MACEs), coronary heart disease (CHD), myocardial infarction (MI), stroke, cardiac death, and all-cause mortality. The summary relative risk (RR) with 95% confidence interval (CI) were calculated using the random-effects model. Thirty-nine cohort studies with 4,389,263 individuals were selected for final meta-analysis. We noted PD were associated with elevated risk of MACEs (RR: 1.24; 95%CI: 1.15-1.34; P<0.001), CHD (RR: 1.20; 95%CI: 1.12-1.29; P<0.001), MI (RR: 1.14; 95%CI: 1.06-1.22; P = 0.001), stroke (RR: 1.26; 95%CI: 1.15-1.37; P<0.001), cardiac death (RR: 1.42; 95%CI: 1.10-1.84; P = 0.007), and all-cause mortality (RR: 1.31; 95%CI: 1.07-1.61; P = 0.010). Sensitivity analyses indicated the pooled conclusions for cardiovascular outcomes and all-cause mortality are robustness. The associations of PD with the risk of ardiovascular outcomes and all-cause mortality could affected by region, study design, PD definition, follow-up duration, and study quality. This study found the risk of cardiovascular outcomes and all-cause mortality were elevated in PD patients, and the intervention for PD should be applied to prevent the risk of cardiovascular outcomes.

Mutant HTT does not affect glial development but impairs myelination in the early disease stage.

Introduction: Huntington's disease (HD) is caused by expanded CAG repeats in the huntingtin gene (HTT) and is characterized by late-onset neurodegeneration that primarily affects the striatum. Several studies have shown that mutant HTT can also affect neuronal development, contributing to the late-onset neurodegeneration. However, it is currently unclear whether mutant HTT impairs the development of glial cells, which is important for understanding whether mutant HTT affects glial cells during early brain development. Methods: Using HD knock-in mice that express full-length mutant HTT with a 140 glutamine repeat at the endogenous level, we analyzed the numbers of astrocytes and oligodendrocytes from postnatal day 1 to 3 months of age via Western blotting and immunocytochemistry. We also performed electron microscopy, RNAseq analysis, and quantitative RT-PCR. Results: The numbers of astrocytes and oligodendrocytes were not significantly altered in postnatal HD KI mice compared to wild type (WT) mice. Consistently, glial protein expression levels were not significantly different between HD KI and WT mice. However, at 3 months of age, myelin protein expression was reduced in HD KI mice, as evidenced by Western blotting and immunocytochemical results. Electron microscopy revealed a slight but significant reduction in myelin thickness of axons in the HD KI mouse brain at 3 months of age. RNAseq analysis did not show significant reductions in myelin-related genes in postnatal HD KI mice. Conclusion: These data suggest that cytoplasmic mutant HTT, rather than nuclear mutant HTT, mediates myelination defects in the early stages of the disease without impacting the differentiation and maturation of glial cells.