Model test study of bridge pile horizontal bearing behavior under landslide deformation.

Pile is a common foundation on the slope, which poses a serious threat to the construction and operation if the slope deformation and causes landslide. In this study, a model device of pile foundation on landslide was independently developed by relative displacement loading between pile and soil to explore the influence of landslide deformation on pile and analysis the soil failure rule and the deformation characteristics of pile in different stages of landslide deformation, a few model tests were completed including the relative displacement between soil and pile from 1 to 17 cm, and the pile diameter and the modulus of slide bed were also considered. The results indicated that: the evolution process of landslide deformation with pile foundation on could be divided into four stages including soil compaction, cracks growth, yield stage, and failure stage; ratios of the maximum soil pressure and bending moment growth from the soil compaction stage to the cracks growth stage to the total growth in these four stages are both exceeding 60%; the soil pressure increases with the increase of pile diameter and sliding bed modulus. Therefore, it is best to effectively monitor and control the landslide in the initial soil compression stage that in soil compaction stage and methods such as increasing pile foundations or reinforcing the sliding bed can be used for protection.

Multi-FusNet: fusion mapping of features for fine-grained image retrieval networks.

As the diversity and volume of images continue to grow, the demand for efficient fine-grained image retrieval has surged across numerous fields. However, the current deep learning-based approaches to fine-grained image retrieval often concentrate solely on the top-layer features, neglecting the relevant information carried in the middle layer, even though these information contains more fine-grained identification content. Moreover, these methods typically employ a uniform weighting strategy during hash code mapping, risking the loss of critical region mapping-an irreversible detriment to fine-grained retrieval tasks. To address the above problems, we propose a novel method for fine-grained image retrieval that leverage feature fusion and hash mapping techniques. Our approach harnesses a multi-level feature cascade, emphasizing not just top-layer but also intermediate-layer image features, and integrates a feature fusion module at each level to enhance the extraction of discriminative information. In addition, we introduce an agent self-attention architecture, marking its first application in this context, which steers the model to prioritize on long-range features, further avoiding the loss of critical regions of the mapping. Finally, our proposed model significantly outperforms existing state-of-the-art, improving the retrieval accuracy by an average of 40% for the 12-bit dataset, 22% for the 24-bit dataset, 16% for the 32-bit dataset, and 11% for the 48-bit dataset across five publicly available fine-grained datasets. We also validate the generalization ability and performance stability of our proposed method by another five datasets and statistical significance tests. Our code can be downloaded from https://github.com/BJFU-CS2012/MuiltNet.git.

The Role of Interferon Regulatory Factors in Liver Diseases.

The interferon regulatory factors (IRFs) family comprises 11 members that are involved in various biological processes such as antiviral defense, cell proliferation regulation, differentiation, and apoptosis. Recent studies have highlighted the roles of IRF1-9 in a range of liver diseases, including hepatic ischemia-reperfusion injury (IRI), alcohol-induced liver injury, Con A-induced liver injury, nonalcoholic fatty liver disease (NAFLD), cirrhosis, and hepatocellular carcinoma (HCC). IRF1 is involved in the progression of hepatic IRI through signaling pathways such as PIAS1/NFATc1/HDAC1/IRF1/p38 MAPK and IRF1/JNK. The regulation of downstream IL-12, IL-15, p21, p38, HMGB1, JNK, Beclin1, ß-catenin, caspase 3, caspase 8, IFN-γ, IFN-ß and other genes are involved in the progression of hepatic IRI, and in the development of HCC through the regulation of PD-L1, IL-6, IL-8, CXCL1, CXCL10, and CXCR3. In addition, IRF3-PPP2R1B and IRF4-FSTL1-DIP2A/CD14 pathways are involved in the development of NAFLD. Other members of the IRF family also play moderately important functions in different liver diseases. Therefore, given the significance of IRFs in liver diseases and the lack of a comprehensive compilation of their molecular mechanisms in different liver diseases, this review is dedicated to exploring the molecular mechanisms of IRFs in various liver diseases.

Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis.

O6-methylguanine-DNA methyltransferase (MGMT) has been demonstrated to be an important prognostic and predictive marker in glioblastoma (GBM). To establish a reliable radiomics model based on MRI data to predict the MGMT promoter methylation status of GBM. A total of 183 patients with glioblastoma were included in this retrospective study. The visually accessible Rembrandt images (VASARI) features were extracted for each patient, and a total of 14676 multi-region features were extracted from enhanced, necrotic, "non-enhanced, and edematous" areas on their multiparametric MRI. Twelve individual radiomics models were constructed based on the radiomics features from different subregions and different sequences. Four single-sequence models, three single-region models and the combined radiomics model combining all individual models were constructed. Finally, the predictive performance of adding clinical factors and VASARI characteristics was evaluated. The ComRad model combining all individual radiomics models exhibited the best performance in test set 1 and test set 2, with the area under the receiver operating characteristic curve (AUC) of 0.839 (0.709-0.963) and 0.739 (0.581-0.897), respectively. The results indicated that the radiomics model combining multi-region and multi-parametric MRI features has exhibited promising performance in predicting MGMT methylation status in GBM. The Modeling scheme that combining all individual radiomics models showed best performance among all constructed moels.

Evidence of synergistic mechanisms of hepatoprotective botanical herbal preparation of Pueraria montana var. lobata and Schisandra sphenanthera.

Background: Pueraria montana var. lobata (Willd.) Maesen & S.M.Almeida ex Sanjappa & Predeep (syn. Pueraria lobata (Willd.) Ohwi) and Schisandra sphenanthera Rehder & E.H. Wilson are traditional edible and medicinal hepatoprotective botanical drugs. Studies have shown that the combination of two botanical drugs enhanced the effects of treating acute liver injury (ALI), but the synergistic effect and its action mechanisms remain unclear. This study aimed to investigate the synergistic effect and its mechanism of the combination of Pueraria montana var. lobata (Willd.) Maesen & S.M.Almeida ex Sanjappa & Predeep (syn. Pueraria lobata (Willd.) Ohwi) (PM) and Schisandra sphenanthera Rehder & E.H. Wilson (SS) in the treatment of ALI. Methods: High performance liquid chromatography (HPLC) were utilized to conduct the chemical interaction analysis. Then the synergistic effects of botanical hybrid preparation of PM-SS (BHP PM-SS) against ALI were comprehensively evaluated by the CCl4 induced ALI mice model. Afterwards, symptom-oriented network pharmacology, transcriptomics and metabolomics were applied to reveal the underlying mechanism of action. Finally, the key target genes were experimentally by RT-qPCR. Results: Chemical analysis and pharmacodynamic experiments revealed that BHP PM-SS was superior to the single botanical drug, especially at 2:3 ratio, with a better dissolution rate of active ingredients and synergistic anti-ALI effect. Integrated symptom-oriented network pharmacology combined with transcriptomics and metabolomics analyses showed that the active ingredients of BHP PM-SS could regulate Glutathione metabolism, Pyrimidine metabolism, Arginine biosynthesis and Amino acid sugar and nucleotide sugar metabolism, by acting on the targets of AKT1, TNF, EGFR, JUN, HSP90AA1 and STAT3, which could be responsible for the PI3K-AKT signaling pathway, MAPK signaling pathway and Pathway in cancer to against ALI. Conclusion: Our study has provided compelling evidence for the synergistic effect and its mechanism of the combination of BHP PM-SS, and has contributed to the development and utilization of BHP PM-SS dietary supplements.

Genesis of the hydrothermal gold system in the kibaran metallogenic province (D.R.Congo): A review for the Twangiza-Namoya gold belt.

The Twangiza-Namoya Gold Deposit within the Kibaran Belt of the Democratic Republic of the Congo represents a crucial manifestation of the hydrothermal gold system. This review investigates its intricate origin and the subsequent metallogenic evolution that has shaped its present-day characteristics and offers a systematic categorization based on its deposition processes and geotectonic settings. The findings reveal that the gold deposits are predominantly derived from sedimentary fluid sources. Within this vast metallogenic province, two stages of gold deposition have been constrained: (a) the early-stage formation related to the accretion of Rodinia assembly with subduction-collisional event where diagenesis cemented the syngenetic pyrite carbonaceous sediments and (b) the later stage deposition related to the continent-collisional event during the last stage of Rodinia supercontinent amalgamation. Previous isotopic investigations, with a particular emphasis on pyrite sulfur isotopes on both host rocks and vein-bearing sulfides, have been instrumental in tracing the origins of gold-bearing fluids in the study region. The isotopic variance in the four deposits: Twangiza (-5.2 % to +3 %, avg. -0.3 %), Kamituga (-0.6 % to -0.9.1 %, avg. -5%), Lugushwa (+3.0 % to -18.4 %), and Namoya, on the southernmost end, has a vast range but with much heavier isotope compositions, ranging between +1.3 % and to +22.6 %, with an average of +12.2 %. The data predominantly points to the sedimentary origins of ore fluids in the Twangiza-Namoya Gold belt, highlighting the pivotal role of sedimentary processes in shaping the metallogenic landscape of the region. The fluids inclusions depicted the deposits to be formed from H2O-Nacl-H2O with abundant CH4 and N2 ore-forming fluid, moderate temperature (350-500 °C), and low salinity. The overall results confirm the genetic style of the Twangiza-Namoya Gold Belt to be an orogenic gold-style deposit that was emplaced during the early Neoproterozoic era in low greenschist facies terrain.

Application of 5T glutamate chemical exchange saturation transfer imaging in brain tumors: preliminary results.

PURPOSE: Glutamate chemical exchange saturation transfer (GluCEST) is a non-invasive CEST imaging technique for detecting glutamate levels in tissues. We aimed to investigate the reproducibility of the 5T GluCEST technique in healthy volunteers and preliminarily explore its potential clinical application in patients with brain tumors. METHODS: Ten volunteers (4 males, mean age 29 years) underwent three 5T GluCEST imaging scans. The reproducibility of the three imaging GluCEST measurements was assessed using one-way repeated measures analysis of variance (ANOVA), generalized estimating equations, and linear mixed models. Twenty-eight patients with brain tumors (10 males, mean age 54 years) underwent a single GluCEST scan preoperatively, and t-tests were used to compare the differences in GluCEST values between different brain tumors. In addition, the diagnostic accuracy of GluCEST values in differentiating brain tumors was assessed using the receiver work characteristics (ROC) curve. RESULTS: The coefficients of variation of GluCEST values in healthy volunteers were less than 5% for intra-day, inter-day, and within-subjects and less than 10% for between-subjects. High-grade gliomas (HGG) had higher GluCEST values compared to low-grade gliomas (LGG) (P < 0.001). In addition, cerebellopontine angle (CPA) meningiomas had higher GluCEST values than acoustic neuromas (P < 0.001). The area under the curve (AUC) of the GluCEST value for differentiating CPA meningioma from acoustic neuroma was 0.93. CONCLUSION: 5T GluCEST images are highly reproducible in healthy brains. In addition, the 5T GluCEST technique has potential clinical applications in differentiating LGG from HGG and CPA meningiomas from acoustic neuromas.

Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models.

In deep learning, different kinds of deep networks typically need different optimizers, which have to be chosen after multiple trials, making the training process inefficient. To relieve this issue and consistently improve the model training speed across deep networks, we propose the ADAptive Nesterov momentum algorithm, Adan for short. Adan first reformulates the vanilla Nesterov acceleration to develop a new Nesterov momentum estimation (NME) method, which avoids the extra overhead of computing gradient at the extrapolation point. Then Adan adopts NME to estimate the gradient's first- and second-order moments in adaptive gradient algorithms for convergence acceleration. Besides, we prove that Adan finds an ϵ-approximate first-order stationary point within O(ϵ-3.5) stochastic gradient complexity on the non-convex stochastic problems (e.g.deep learning problems), matching the best-known lower bound. Extensive experimental results show that Adan consistently surpasses the corresponding SoTA optimizers on vision, language, and RL tasks and sets new SoTAs for many popular networks and frameworks, eg ResNet, ConvNext, ViT, Swin, MAE, DETR, GPT-2, Transformer-XL, and BERT. More surprisingly, Adan can use half of the training cost (epochs) of SoTA optimizers to achieve higher or comparable performance on ViT, GPT-2, MAE, etc, and also shows great tolerance to a large range of minibatch size, e.g.from 1k to 32k. Code is released at https://github.com/sail-sg/Adan, and has been used in multiple popular deep learning frameworks or projects.

Nano co-delivery of doxorubicin and plumbagin achieves synergistic chemotherapy of hepatocellular carcinoma.

Doxorubicin (DOX) is a chemotherapy drug used for hepatocellular carcinoma (HCC) treatment, but its effectiveness can be dramatically dampened by cancer cell chemoresistance. Signal transducer and activator of transcription 3 (STAT3) is implicated with drug resistance in a range of cancers (e.g., HCC), and the STAT3 inhibition can reverse the resistance of cancer cells to chemotherapeutic drugs. In the present study, a combination regimen to improve the efficiency of DOX was provided via the STAT3 blockade using plumbagin (PLB). A poly(lactic-co-glycolic acid) decorated by polyethylene glycol and aminoethyl anisamide was produced in the present study with the hope of generating the nanoparticles for co-delivery of DOX and PLB. The resulting co-formulation suppressed the STAT3 activity and achieved the synergistic chemotherapy, which led to tumor inhibition in the mice with subcutaneous DOX-resistant HCC, without causing any toxicity. The present study reveals the synergism of DOX and PLB, and demonstrates a promising combinatorial approach for treating HCC.

NAT10 Overexpression Promotes Tumorigenesis and Epithelial-Mesenchymal Transition Through AKT Pathway in Gastric Cancer.

BACKGROUND: N-acetyltransferase 10 (NAT10), the only RNA cytosine acetyltransferase known in humans, contributes to cancer tumorigenesis and progression. This study aims to investigate the effect of NAT10 on the malignant biological properties of gastric cancer (GC) and its underlying mechanism. METHODS: The expression and prognostic significance of NAT10 in GC were analyzed using The Cancer Genome Atlas (TCGA) and Sun Yat-sen University (SYSU) cohorts. The influence of NAT10 on the malignant biological behaviors of GC was detected by Cell Counting Kit-8 (CCK-8) assay, plate colony formation assay, 5-ethynyl-2'-deoxyuridine (EdU), Transwell migration and invasion assays, scratch wound assay, flow cytometric analysis, and animal studies. The overall level of N4 acetylcytidine (ac4C) in GC was detected by liquid chromatography with tandem mass spectrometry (LC-MS/MS). The downstream signal pathways of NAT10 were analyzed by Gene Set Enrichment Analysis (GSEA) and verified by Western blot (WB) and immunofluorescence (IF). RESULTS: The significant upregulation of NAT10 expression in GC was associated with a poor prognosis. The knockdown of NAT10 markedly suppressed GC cell proliferation, migration, invasion, and cell cycle progression. Downregulating NAT10 reduced ac4C levels and inhibited AKT phosphorylation and epithelial-mesenchymal transition (EMT) in GC. CONCLUSIONS: NAT10 functions as an oncogene and may provide a new therapeutic target in GC.

Efficacy and Safety of Sacubitril/Valsartan in Hemodialysis Patients with Chronic Heart Failure: A Retrospective Study at a Single Center.

BACKGROUND Heart failure and end-stage renal disease often coexist, and management of heart failure can be challenging in patients during hemodialysis. Sacubitril-valsartan (SV) is the first drug to receive regulatory approval for use in patients with chronic heart failure with reduced ejection fraction (HFrEF) and New York Heart Association (NYHA) classification II, III, or IV. This study aimed to evaluate the efficacy and safety of SV for use in chronic heart failure patients on maintenance hemodialysis (MHD). MATERIAL AND METHODS From September 2021 to October 2022, 28 patients on MHD with chronic heart failure at the hemodialysis center of Shaanxi Second Provincial People's Hospital were regularly followed. During the 12-week follow-up period, all patients were administered SV at doses of 100-400 mg per day. Biochemical indicators, echocardiographic parameters, life quality scores, and adverse events were evaluated. RESULTS We enrolled 28 patients. Compared with the baseline levels, NYHA class III in these patients treated with SV was significantly decreased from 60.71% to 32.14% (P<0.05), left ventricular ejection fraction (LVEF) was significantly improved from 44.29±8.92% to 53.32±7.88% (P<0.001), the Physical Component Summary (PCS) score was significantly improved from 40.0±6.41 to 56.20±9.86 (P<0.001), and the Mental Component Summary (MCS) score was significantly improved from 39.99±6.14 to 52.59±11.0 (P<0.001). CONCLUSIONS We demonstrated that SV improved NYHA classification and LVEF values of patients on MHD with chronic heart failure and also improved their quality of life.

Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.

Trace elements in plants primarily derive from soils, subsequently influencing human health through the food chain. Therefore, it is essential to understand the relationship of trace elements between plants and soils. Since trace elements from soils absorbed by plants is a nonlinear process, traditional multiple linear regression (MLR) models failed to provide accurate predictions. Zinc (Zn) was chosen as the objective element in this case. Using soil geochemical data, artificial neural networks (ANN) were utilized to develop predictive models that accurately estimated Zn content within wheat grains. A total of 4036 topsoil samples and 73 paired rhizosphere soil-wheat samples were collected for the simulation study. Through Pearson correlation analysis, the total content of elements (TCEs) of Fe, Mn, Zn, and P, as well as the available content of elements (ACEs) of B, Mo, N, and Fe, were significantly correlated with the Zn bioaccumulation factor (BAF). Upon comparison, ANN models outperformed MLR models in terms of prediction accuracy. Notably, the predictive performance using ACEs as input factors was better than that using TCEs. To improve the accuracy, a two-step model was established through multiple testing. Firstly, ACEs in the soil were predicted using TCEs and properties of the rhizosphere soil as input factors. Secondly, the Zn BAF in grains was predicted using ACE as input factors. Consequently, the content of Zn in wheat grains corresponding to 4036 topsoil samples was predicted. Results showed that 85.69 % of the land was suitable for cultivating Zn-rich wheat. This finding offers a more accurate method to predict the uptake of trace elements from soils to grains, which helps to warn about abnormal levels in grains and prevent potential health risks.

Research on the Welding Process and Weld Formation in Multiple Solid-Flux Cored Wires Arc Hybrid Welding Process for Q960E Ultrahigh-Strength Steel.

This paper proposes a novel welding process for ultrahigh-strength steel. The effects of welding parameters on the welding process and weld formation were studied to obtain the optimal parameter window. It was found that the metal transfer modes of solid wires were primarily determined by electrical parameters, while flux-cored wires consistently exhibited multiple droplets per pulse. The one droplet per pulse possessed better welding stability and weld formation, whereas the short-circuiting transfer or one droplet multiple pulses easily caused abnormal arc ignition that decreased welding stability, which could easily lead to a "sawtooth-shaped" weld formation or weld offset towards one side with more spatters. Thus, the electrical parameters corresponding to one droplet per pulse were identified as the optimal parameter window. Furthermore, the weld zone (WZ) was predominantly composed of AF, and the heat-affected zone (HAZ) primarily consisted of TM and LM. Consequently, the welded joint still exhibited excellent mechanical properties, particularly toughness, despite higher welding heat input. The average tensile strength reached 928 MPa, and the impact absorbed energy at -40 °C for the WZ and HAZ were 54 J and 126 J, respectively. In addition, the application of triple-wire welding for ultrahigh-strength steel (UHSS) demonstrated a significant enhancement in post-weld deposition rate, with increases of 106% and 38% compared to single-wire and twin-wire welding techniques, respectively. This process not only utilized flux-cored wire to enhance the mechanical properties of joints but also achieved high deposition rate welding.

Estimation of complete mutual information exploiting nonlinear magnitude-phase dependence: Application to spatial FNC for complex-valued fMRI data.

BACKGROUND: Real-valued mutual information (MI) has been used in spatial functional network connectivity (FNC) to measure high-order and nonlinear dependence between spatial maps extracted from magnitude-only functional magnetic resonance imaging (fMRI). However, real-valued MI cannot fully capture the group differences in spatial FNC from complex-valued fMRI data with magnitude and phase dependence. METHODS: We propose a complete complex-valued MI method according to the chain rule of MI. We fully exploit the dependence among magnitudes and phases of two complex-valued signals using second and fourth-order joint entropies, and propose to use a Gaussian copula transformation with a lower bound property to avoid inaccurate estimation of joint probability density function when computing the joint entropies. RESULTS: The proposed method achieves more accurate MI estimates than the two histogram-based (normal and symbolic approaches) and kernel density estimation methods for simulated signals, and enhances group differences in spatial functional network connectivity for experimental complex-valued fMRI data. COMPARISON WITH EXISTING METHODS: Compared with the simplified complex-valued MI and real-valued MI, the proposed method yields higher MI estimation accuracy, leading to 17.4 % and 145.5 % wider MI ranges, and more significant connectivity differences between healthy controls and schizophrenia patients. A unique connection between executive control network (EC) and right frontal parietal areas, and three additional connections mainly related to EC are detected than the simplified complex-valued MI. CONCLUSIONS: With capability in quantifying MI fully and accurately, the proposed complex-valued MI is promising in providing qualified FNC biomarkers for identifying mental disorders such as schizophrenia.

Machine learning for the prediction of delirium in elderly intensive care unit patients.

PURPOSE: This study aims to develop and validate a prediction model for delirium in elderly ICU patients and help clinicians identify high-risk patients at the early stage. METHODS: Patients admitted to ICU for at least 24 h and using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database (76,943 ICU stays from 2008 to 2019) were considered. Patients with a positive delirium test in the first 24 h and under 65 years of age were excluded. Two prediction models, machine learning extreme gradient boosting (XGBoost) and logistic regression (LR) model, were developed and validated to predict the onset of delirium. RESULTS: Of the 18,760 patients included in the analysis, 3463(18.5%) were delirium positive. A total of 22 significant predictors were selected by LASSO regression. The XGBoost model demonstrated superior performance over the LR model, with the Area Under the Receiver Operating Characteristic (AUC) values of 0.853 (95% confidence interval [CI] 0.846-0.861) and 0.831 (95% CI 0.815-0.847) in the training and testing datasets, respectively. Moreover, the XGBoost model outperformed the LR model in both calibration and clinical utility. The top five predictors associated with the onset of delirium were sequential organ failure assessment (SOFA), infection, minimum platelets, maximum systolic blood pressure (SBP), and maximum temperature. CONCLUSION: The XGBoost model demonstrated good predictive performance for delirium among elderly ICU patients, thus assisting clinicians in identifying high-risk patients at the early stage and implementing targeted interventions to improve outcome.

Ce-4f as an electron-modulation reservoir weakening Fe-O bond to induce iron vacancies in CeFevNi hydroxide for enhancing oxygen evolution reaction.

Designing novel rare-earth-transition metal composites is at the forefront of electrocatalyst research. However, the modulation of transition metal electronic structures by rare earths to induce vacancy defects and enhance electrochemical performance has rarely been reported. In this study, we systematically investigate the mechanism by which Ce-4f electron modulation weakens the Fe-O bond, thereby altering the electronic structure in CeFevNi hydroxide to improve oxygen evolution reaction (OER) performance. Theoretical calculations and experimental characterizations reveal that Ce-4f orbitals function as electron-modulation reservoirs, capable not only of retaining or donating electrons but also of influencing the material's electronic structure. Moreover, Ce-4f bands optimize the Fe lower Hubbard bands (LHB) and O-2p bands, leading to weakened Fe-O bonds and the formation of cationic vacancies. This change results in the upshift of the d-band center at the active sites, favoring the reaction energy barrier for oxygen intermediates in the OER process. The synthesized catalyst demonstrated an overpotential of 201 mV at 10 mA cm-2 and a lifetime exceeding 200 h at 100 mA cm-2 under alkaline conditions. This work offers a proof-of-concept for the application of the mechanism of rare earth-induced transition metal vacancy defects, providing a general guideline for the design and development of novel highly efficient catalysts.

Recent advances in the development of P2Y14R inhibitors: a patent and literature review (2018-present).

INTRODUCTION: The P2Y14 receptor (P2Y14R), a member of the G protein-coupled receptor family, is activated by extracellular nucleotides. Due to its involvement in inflammatory, immunological and other associated processes, P2Y14R has emerged as a promising therapeutic target. Despite lacking a determined three-dimensional crystal structure, the homology modeling technique based on closely related P2Y receptors' crystallography has been extensively utilized for developing active compounds targeting P2Y14R. Recent discoveries have unveiled numerous highly effective and subtype-specific P2Y14R inhibitors. This study presents an overview of the latest advancements in P2Y14R inhibitors. AREAS COVERED: This review presents an overview of the advancements in P2Y14R inhibitor research over the past five years, encompassing new patents, journal articles, and highlighting the therapeutic prospects inherent in these compounds. EXPERT OPINION: The recent revelation of the vast potential of P2Y14R inhibitors has led to the development of novel compounds that exhibit promising capabilities for the treatment of sterile inflammation of the kidney, potentially diabetes, and asthma. Despite being a relatively nascent class of compounds, certain members have already exhibited their capacity to surmount specific challenges posed by conventional P2Y14R inhibitors. Targeting P2Y14R through small molecules may present a promising therapeutic strategy for effectively managing diverse inflammatory diseases.

Effects of acetate-producing Blautia wexlerae on oxidative stress and NLRP3 inflammasome in obesity-associated male infertility.

BACKGROUND: Obesity-associated male infertility is a common complication of obesity and has been increasing in prevalence. Blautia wexlerae has modulation effects on obesity. However, the action of B. wexlerae on obesity-associated male infertility is unclear. The nod-like receptor protein 3 (NLRP3) inflammasome has become a major target for addressing many diseases, including obesity-associated male infertility. This study aims to investigate the action of B. wexlerae on obesity-associated male infertility and the influence of B. wexlerae on NLRP3 inflammasome. MATERIALS AND METHODS: The fecal samples were collected from 60 infertile men with or without obesity and 30 healthy men. The obesity mice model was established through high-fat diet (HFD) induction. The mating assays evaluated the male infertility of obese mice. A mouse-derived spermatogonia (GC-1 spg) cell viability was detected using the Cell Counting Kit-8 assay. The reactive oxygen species (ROS) were assessed using flow cytometry. Furthermore, immunofluorescence, enzyme-linked immunosorbent assay, and western blotting were applied to measure the gene expressions. RESULTS: Blautia wexlerae was decreased and negatively correlated with interleukin-1 beta (IL-1ß) or IL-18 levels in infertile men with obesity. On the other hand, B. wexlerae improved the mating capability of obese male mice and suppressed oxidative stress and NLRP3 inflammasome via the activation of the acetate receptor. Furthermore, sodium acetate regulated oxidative stress and NLRP3 inflammasome via the activation of the acetate receptor in GC-1 spg cells in vitro. CONCLUSION: The administration of Blautia wexlerae improved obesity-associated male infertility and regulated oxidative stress and NLRP3 inflammasome activities. In general, its administration may be an effective strategy for the treatment of obesity-associated male infertility.

Colorimetric detection of diamine using diamine oxidase and horseradish peroxidase co-incorporated hybrid microsphere as biomimetic cascade enzymes.

Dual-enzyme co-embedded materials have shown high potential for achieving efficient detection due to the convenience of two-enzyme cascade reactions. Herein, we developed a dual-enzyme hybrid microsphere (HM) based biosensor to detect diamines (histamine was included for ease of description) in aquatic products. The HM was made from diamine oxidase, horseradish peroxidase, and copper phosphate through the biomineralization method. Under optimal conditions, the system displayed linear color response to histamine of different concentrations ranging from 0 to 200 µg/mL. The detection limit of histamine was 0.15 µg/mL, showing higher sensitivity than the two-step free enzyme assay. Moreover, the detection system exhibited good specificity to diamines. The method was used to detect diamines in commercial samples, and the results were compared with those measured by the high-performance liquid chromatography method. Overall, the proposed assay exhibited high potential in diamine quantification and was readily extended to other cascade enzymatic reaction-based detection strategies.

Lead Iodide Redistribution Enables In Situ Passivation for Blading Inverted Perovskite Solar Cells with 24.5% Efficiency.

Blade-coating stands out as an alternative for fabricating scalable perovskite solar cells. However, it demands special control of the precursor composition regarding nucleation and crystallization and currently exhibits lower performance than the spin-coating process. It is mainly the resulting film morphology and excess lead iodide (PbI2) distribution that influences the optoelectronic properties. Here, the effectiveness of introducing N-Methyl-2-pyrrolidone (NMP) to regulate the structure of the perovskite layer and the redistribution of PbI2 is found. The introduction of NMP leads to the accumulation of excess PbI2, mainly on the top surface, reducing residual PbI2 at the perovskite buried interface. This not only facilitates the passivation of perovskite grain boundaries but also eliminates the potential degradation of the PbI2 triggered by light illumination in the perovskite buried interface. The optimized NMP-modified inverted perovskite solar cell achieves a champion efficiency of 24.5%, among the highest reported blade-coated perovskite solar cells. Furthermore, 13.68 cm2 blading perovskite solar modules are fabricated and demonstrate an efficiency of up to 20.4%. These findings underscore that with proper modulation of precursor composition, blade-coating can be a feasible and superior alternative for manufacturing high-quality perovskite films, paving the way for their large-scale applications in photovoltaic technology.