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Abstract Background CLDN is a core component of tight junctions (TJs). Abnormal expressions of CLDNs are commonly detected in various types of tumors. CLDNs are of interest as a potential therapeutic target. CLDNs are closely associated with most cancers of epithelial origin, especially when CLDN7 promotes cancer cell metastasis, such as in gastric, cervical, and ovarian cancers.Its expression and prognosis in breast cancer (BC) remain unknown.The purpose of this study was to investigate the expression pattern of CLDN7 and related immune factors in BC and shed light on a better therapeutic avenue for BC patients. Method The cBioPortal, GEPIA, and TCGA databases were used to comprehensively assess the expression of CLDN7 in BC. The Kaplan-Meier Plotter (KMP) database was applied to examine the relationship among the CLDN7 overexpression (OE), prognosis, and overall survival (OS) of BC patients. Immunohistochemical staining was performed on 92 BC tissue samples and 20 benign breast tumors to verify the expression level of CLDN-7 protein and its correlation with clinicopathological features and prognosis. TIMER2.0 was used to analyze the correlation between the CLDN7 OE and immune gene activation using BC-related transcriptomic data. Enrichment analyses of CLDN7-related immune pathways were conducted using online databases. The risk of expression of CLDN7-related immune genes was assessed and differentially expressed (DE) genes were included in the construction of the risk prognosis nomogram. Results Both database analysis and clinical sample validation results showed that CLDN7 was significantly overexpressed (OE) in BC, and the OE was correlated with poor DFS in BC patients (p

Abstract Accurate and reliable prediction of porosity forms the foundational basis for evaluating reservoir quality, which is essential for the systematic deployment of oil and gas exploration and development plans. When data quality of samples is low, and critical model parameters are typically determined through subjective experience, resulting in diminished accuracy and reliability of porosity prediction methods utilizing gated recurrent units (GRU), a committee-voting ensemble learning (EL) method, and an enhanced particle swarm optimization (PSO) algorithm are proposed to optimize the GRU-based porosity prediction model. Initially, outliers are eliminated through box plots and the min–max normalization is applied to enhance data quality. To address issues related to model accuracy and high training costs arising from dimensional complexity, substantial noise, and redundant information in logging data, a committee-voting EL strategy based on four feature selection algorithms is introduced. Following data preprocessing, this approach is employed to identify logging parameters highly correlated with porosity, thereby furnishing the most pertinent data samples for the GRU model, mitigating constraints imposed by single-feature selection methods. Second, an improved PSO algorithm is suggested to tackle challenges associated with low convergence accuracy stemming from random population initialization, alongside the absence of global optimal solutions due to overly rapid particle movement during iteration. This algorithm uses a good-point set for population initialization and incorporates a compression factor to devise an adaptive velocity updating strategy, thereby enhancing search efficacy. The enhanced PSO algorithm’s superiority is substantiated through comparison with four alternative swarm intelligent algorithms across 10 benchmark test functions. Ultimately, optimal hyper-parameters for the GRU model are determined using the improved PSO algorithm, thereby minimizing the influence of human factors. Experimental findings based on approximately 15,000 logging data points from well A01 in an operational field validate that, relative to three other deep learning methodologies, the proposed model proficiently extracts spatiotemporal features from logging data, yielding enhanced accuracy in porosity prediction. The mean squared error on the test set was 7.19 × 10–6, the mean absolute error stood at 0.0082, and coefficient of determination reached 0.99, offering novel insights for predicting reservoir porosity.

Abstract Purpose Various complications following hypospadias surgery present distinct manifestations when examined with ultrasound. Utilizing high-frequency ultrasound, clinicians can promptly identify these complications and initiate appropriate treatment. The aim of this study is to catalogue the ultrasonographic presentations of various postoperative complications following hypospadias surgery, thereby providing a reference for ultrasonographic diagnosis. Methods Ultrasonic images of post-hypospadias surgery from October 1, 2015, to June 30, 2023, recorded at the Plastic Surgery Hospital of the Chinese Academy of Medical Sciences, serve as the basis for this investigation. Drawing on patient clinical diagnoses, this study compiles and selects representative ultrasound images of diverse complications. Results The study encompassed a total of 121 subjects; 26 demonstrated urethral stricture on ultrasonic images, two presented local urethral dilation, six showed intraurethral hair-like structures, 17 revealed intraurethral septum, two exhibited intraurethral fold, one had urethral calculus, one displayed urethral calcification, 12 indicated intraurethral urine accumulation, and two showed urethral diverticulum. Conclusion Ultrasound examination is helpful for postoperative diagnosis following hypospadias, detecting complications such as urethral stricture, urethral hair growth, and urethral diverticulum, which can help doctors choose appropriate clinical treatment strategies.

Hydrocarbon production in oil and gas fields generally progresses through stages of production ramp-up, plateau (peak), and decline during field development, with the whole process primarily modeled and forecasted using lifecycle models. SINOPEC's conventional gas reservoirs are dominated by carbonates, low-permeability tight sandstone, condensate, volcanic rocks, and medium-to-high-permeability sandstone. This study identifies the optimal production forecasting models by comparing the fitting coefficients of different models and calculating the relative errors in technically recoverable reserves. To improve forecast precision, it suggests substituting exponential smoothing method-derived predictions for anomalous data caused by subjective influences like market dynamics and maintenance activities. The preferred models for carbonate gas reservoir production forecasts are the generalized Weng's, Beta, Class-I generalized mathematical, and Hu-Chen models. The Vapor pressure and Beta models are optimal for forecasting the annual productivity of wells (APW) from gas-bearing low-permeability tight sandstone reservoirs. The Wang-Li, Beta, and Yu QT tb models are apt for moderate-to-small-reserves, single low-permeability tight sandstone gas reservoirs. The Rayleigh, Hu-Chen, and generalized Weng's models are suitable for condensate gas reservoirs. For medium-to-high-permeability sandstone gas reservoirs, the lognormal, generalized gamma, and Beta models are recommended.

Summary: Background: Type 2 diabetes (T2DM) remains a challenge to treat despite the expansion of various therapeutic classes. Visepegenatide (PB-119) is a once a week, subcutaneous, glucagon-like peptide-1 receptor agonist (GLP-1 RA) injection without the requirement of dose titration that has shown glycaemic control and safety profile in two phase 2 studies conducted in China and the United States, respectively. The aim of this study was to evaluate the efficacy and safety of visepegenatide as a monotherapy in treatment-naïve patients with T2DM. Methods: This was a multicentre, double-blind, parallel, placebo-controlled, phase 3 trial conducted in 30 centres in China. Adult participants (aged 18–75 years) with T2DM, glycated haemoglobin (HbA1c) of 7.5%–11.0% [58.47–96.73 mmol/mol], body mass index (BMI) of 18–40 kg/m2, and who had been treated with diet and exercise alone for at least 8 weeks before the screening visit were eligible for enrolment. After a 4-week placebo injection run-in period, participants with HbA1c of 7.0%–10.5% [53.0–91.3 mmol/mol] and fasting plasma glucose (FPG)

Introduction Lung isolation is primarily accomplished using a double-lumen tube (DLT) or bronchial blocker. A precise and accurate size of the DLT is a prerequisite for ensuring its accurate placement. Three-dimensional (3D) reconstruction technology can be used to accurately reproduce tracheobronchial structures to improve the accuracy of DLT size selection. Therefore, we have developed automatic comparison software for 3D reconstruction based on CT data (3DRACS). In this study, we aimed to evaluate the efficiency of using 3DRACS to select the DLT size for endobronchial intubation in comparison with using the ‘blind’ DLT intubation method to determine the DLT size, which is based on height and sex.Methods and analysis This is a prospective, single-centre, double-blind randomised controlled trial. In total, 200 patients scheduled for lung resection using a left DLT will be randomly allocated to the 3D group or the control group at a 1:1 ratio. A 3DRACS will be used for the 3D group to determine the size of the DLT, while in the case of the control group, the size of the DLT will be determined according to patient height and sex. The primary outcome is the success rate of placement of the left DLT without fibreoptic bronchoscopy (FOB). The secondary outcomes include the following: successful intubation time, degree of pulmonary atrophy, grade of airway injury, oxygenation during one-lung ventilation, postoperative sore throat and hoarseness, and number of times FOB is used.Ethics and dissemination Ethical approval has been obtained from our local ethics committee (approval number: SCCHEC-02-2022-155). Written informed consent will be obtained from all participants before randomisation, providing them with clear instructions about the purpose of the study. The results will be disseminated through peer-reviewed publications and conferences.Trial registration number NCT06258954.

Tight gas reservoirs with mobile water exhibit multi-phase flow and high stress sensitivity. Accurately analyzing the reservoir and well parameters using conventional single-phase rate transient analysis methods proves challenging. This study introduces novel rate transient analysis methods incorporating evaluation processes based on the conventional flowing material balance method and the Blasingame type-curve method to examine fractured gas wells producing water. By positing a gas-water two-phase equivalent homogenous phase that considers characteristics of mobile water, gas, and high stress sensitivity, the conventional single-phase rate transient analysis methods can be applied by integrating the phase's characteristics and defining the phase's normalized parameters and material balance pseudo-time. The rate transient analysis methods based on the equivalent homogenous phase can be used to quantitatively assess the parameters of wells and gas reservoirs, such as original gas-in-place, fracture half-length, reservoir permeability, and well drainage radius. This facilitates the analysis of production dynamics of fractured wells and well-controlled areas, subsequently aiding in locating residual gas and guiding the configuration of well patterns. The specific evaluation processes are detailed. Additionally, a numerical simulation mechanism model was constructed to verify the reliability of the developed methods. The methods introduced have been successfully implemented in field water-producing gas wells within tight gas reservoirs containing mobile water.

Obesity can lead to excessive lipid accumulation in non-adipose tissues, such as the liver and skeletal muscles, leading to ectopic lipid deposition and damaging target organ function through lipotoxicity. FGF-21 is a key factor in regulating lipid metabolism, so we aim to explore whether FGF-21 is involved in improving ectopic lipid deposition. We observed the characteristics of ectopic lipid deposition in the liver and skeletal muscles of obesity-resistant mice, detected the expression of FGF-21 and perilipin, and found that obesity-resistant mice showed a decrease in ectopic lipid deposition in the liver and skeletal muscles and increased expression of FGF-21. After inhibiting the expression of FGF-21, a more severe lipid deposition in liver cells and skeletal muscle cells was found. The results indicate that inhibiting FGF-21 can exacerbate ectopic lipid deposition via regulating lipid droplet synthesis and decomposition, as well as free fatty acid translocation and oxidation. In conclusion, FGF-21 is involved in improving ectopic lipid deposition caused by obesity in the liver and skeletal muscles.

Auricularia auricula-judae (AAJ) has been cultivated for food in China for centuries, and is also used as a folk medicine for the regulation of glucose and lipid metabolism. However, there are few studies on the effects of different processing technologies on the therapeutic efficacy of AAJ to date. This study investigated the effectiveness of the AAJ made by using superfine grinding and enzymatic pre-digestion technologies, respectively, in a high-fat diet obese rat model. It was found that oral administrations of two AAJ products significantly alleviated dyslipidemia by decreasing serum lipid levels and restoring liver functions. AAJ products made by using pre-digestion technology have appreciable potential to ameliorate lipid metabolic disorders over other products, possibly due to the higher levels of dietary fiber, crude polysaccharides, and total flavonoids released from AAJ during processing. By analysis of transcriptome sequencing and protein expression, it was clear that starch and sucrose metabolism and glycerolipid metabolism-related factors involved in fatty acid synthesis and metabolism in the liver of obese rats were significantly improved. This study gives further evidence that AAJ significantly ameliorates the progression of glucose and lipid metabolism in obese rats. Moreover, this study demonstrated for the first time that the pre-digestion method may be a better and more efficient processing approach for the improvement of AAJ bioavailability.

Background: Drought stress limits significantly the crop productivity. However, plants have evolved various strategies to cope with the drought conditions by adopting complex molecular, biochemical, and physiological mechanisms. Members of the nuclear factor Y (NF-Y) transcription factor (TF) family constitute one of the largest TF classes and are involved in plant responses to abiotic stresses. Results: TaNF-YB2, a NY-YB subfamily gene in T. aestivum, was characterized in this study focusing on its role in mediating plant adaptation to drought stress. Yeast two-hybrid (Y-2 H), biomolecular fluoresence complementation (BiFC), and Co-immunoprecipitation (Co-IP) assays indicated that TaNF-YB2 interacts with the NF-YA member TaNF-YA7 and NF-YC family member TaNF-YC7, which constitutes a heterotrimer TaNF-YB2/TaNF-YA7/TaNF-YC7. The TaNF-YB2 transcripts are induced in roots and aerial tissues upon drought signaling; GUS histochemical staining analysis demonstrated the roles of cis-regulatory elements ABRE and MYB situated in TaNF-YB2 promoter to contribute to target gene response to drought. Transgene analysis on TaNF-YB2 confirmed its functions in regulating drought adaptation via modulating stomata movement, osmolyte biosynthesis, and reactive oxygen species (ROS) homeostasis. TaNF-YB2 possessed the abilities in transcriptionally activating TaP5CS2, the P5CS family gene involving proline biosynthesis and TaSOD1, TaCAT5, and TaPOD5, the genes encoding antioxidant enzymes. Positive correlations were found between yield and the TaNF-YB2 transcripts in a core panel constituting 45 wheat cultivars under drought condition, in which two types of major haplotypes including TaNF-YB2-Hap1 and -Hap2 were included, with the former conferring more TaNF-YB2 transcripts and stronger plant drought tolerance. Conclusions: TaNF-YB2 is transcriptional response to drought stress. It is an essential regulator in mediating plant drought adaptation by modulating the physiological processes associated with stomatal movement, osmolyte biosynthesis, and reactive oxygen species (ROS) homeostasis, depending on its role in transcriptionally regulating stress response genes. Our research deepens the understanding of plant drought stress underlying NF-Y TF family and provides gene resource in efforts for molecular breeding the drought-tolerant cultivars in T. aestivum. [ABSTRACT FROM AUTHOR]

Background: Etomidate can induce myoclonus with an incidence of 50 ~ 85% during anesthesia induction. Dexamethasone, as a long-acting synthetic glucocorticoid, has neuroprotective effects. However, the effects of dexamethasone on the etomidate-induced myoclonus remain uncertain. Methods: Adult male Sprague-Dawley rats were randomly assigned to receive etomidate (1.5 mg/kg) plus dexamethasone (4 mg/kg) (etomidate plus dexamethasone group) or etomidate (1.5 mg/kg) plus the same volume of normal saline (NS) (etomidate plus NS group). The mean behavioral scores, local field potentials and muscular tension were recorded to explore the effects of dexamethasone on etomidate-induced myoclonus. Liquid chromatography coupled with tandem mass spectrometric system (LC-MS/MS), quantitative real-time polymerase chain reaction (qRT-PCR), and western blotting were applied to analyze the levels of glutamate and α-aminobutyric acid (GABA), the mRNA and protein expression of excitatory amino acid transporters (EAATs), and plasma corticosterone levels at different time points after anesthesia. Results: Compared with the etomidate plus NS treatment, the etomidate plus dexamethasone treatment significantly decreased the mean behavioral score at 1, 3, 4, and 5 min after administration; the peak power spectral density (PSD) (p = 0.0197) in the analysis of ripple waves; and the glutamate level (p = 0.0139) in the neocortex. However, compared with etomidate plus NS, etomidate plus dexamethasone increased the expression of the neocortical proteins of EAAT1 (p = 0.0207) and EAAT2 (p = 0.0022) and aggravated the inhibition of corticosterone at 4 h (p = 0.0019), 5 h (p = 0.0041), and 6 h (p = 0.0009) after administration. Conclusion: Dexamethasone can attenuate the myoclonus, inhibit the glutamate accumulation, and reverse the suppression of EAATs in the neocortex induced by etomidate following myoclonus, while conversely aggravating etomidateinduced adrenal suppression. [ABSTRACT FROM AUTHOR]

Heart failure is the most costly cardiovascular disorder. New treatments are urgently needed. This study aims to evaluate the safety, pharmacokinetics, and pharmacodynamic profile of HEC95468, a soluble guanylate cyclase (sGC) stimulator, in healthy volunteers. Sixty-two, eighteen, and forty-eight participants were enrolled in the single ascending dose (SAD) study, the food effect (FE) study, and the multiple ascending dose (MAD) study, respectively. The study conforms to good clinical practice and the Declaration of Helsinki. Overall, HEC95468 was safe and tolerable; a higher proportion of HEC95468-treated participants reported mild headaches, dizziness, decreased blood pressure, increased heart rate, and gastrointestinal-related treatment-emergent adverse events (TEAEs), similar to the sGC stimulators riociguat and vericiguat. In terms of pharmacokinetic parameters, the maximum observed plasma concentration (Cmax) and the area under the concentration-time curve (AUC0-t) were dose-proportional over the dose range. Moderate accumulation was observed after multiple administrations of HEC95468. Systolic blood pressure (SBP) and diastolic blood pressure decreased, while 3′,5′-cyclic guanosine monophosphate (cGMP) concentration in plasma increased and heart rate was induced. Vasoactive hormones (renin, angiotensin II, and norepinephrine) in plasma were compensatorily elevated after oral administration. These data supported further clinical trials of HEC95468 in the treatment of heart failure and pulmonary arterial hypertension. [ABSTRACT FROM AUTHOR]

Objectives: Transvaginal natural orifice transluminal endoscopic surgery (vNOTES) and transumbilical laparoendoscopic single-site surgery (LESS) have shown the prospection as minimally invasive procedures. Here we aimed to compare ovarian cystectomy assisted by vNOTES and by LESS for ovarian mature cystic teratoma (OMCT). Material and methods: A total of 81 premenopausal women with OMCT were randomized to undergo ovarian cystectomy assisted by either vNOTES (n = 41) or LESS (n = 40). The main outcome was the operative time. Secondary outcomes included the length of hospital stay, visual analog scale (VAS) pain scores, abdominal contamination by teratoma contents, and intraoperative and postoperative complications. Results: There were no intergroup differences in age, body mass index, tumor size, or bilaterality of tumor. The operative time for the vNOTES group was significantly shorter than that for the LESS group (68.41 ± 20.92 min vs 85.05 ± 32.94 min, p = 0.008). The highest VAS pain score 24 hours postoperatively was 1.21 ± 0.48 in the vNOTES group and 2.43 ± 0.57 in the LESS group (p < 0.001). Twenty-four of the 40 patients in the LESS group experienced teratoma rupture intraoperatively, leading to abdominal contamination by the teratoma content, while 5 abdominal contamination was observed in the vNOTES group (p = 0.005). No significant differences between the two groups were observed in the other outcomes. Conclusions: vNOTES assisted ovarian cystectomy has short operative time, fast recovery, no scarring, less pain, and low rate of abdominal contamination. Consequently, vNOTES might be superior to LESS for treating OMCTs. [ABSTRACT FROM AUTHOR]

Recent advances in deep neural networks have shed new light on physics, engineering, and scientific computing. Reconciling the data-centered viewpoint with physical simulation is one of the research hotspots. The physics-informed neural network (PINN) is currently the most general framework, which is more popular due to the convenience of constructing NNs and excellent generalization ability. The automatic differentiation (AD)-based PINN model is suitable for the homogeneous scientific problem; however, it is unclear how AD can enforce flux continuity across boundaries between cells of different properties where spatial heterogeneity is represented by grid cells with different physical properties. In this work, we propose a criss-cross physics-informed convolutional neural network (CC-PINN) learning architecture, aiming to learn the solution of parametric PDEs with spatial heterogeneity of physical properties. To achieve the seamless enforcement of flux continuity and integration of physical meaning into CNN, a predefined 2D convolutional layer is proposed to accurately express transmissibility between adjacent cells. The efficacy of the proposed method was evaluated through predictions of several petroleum reservoir problems with spatial heterogeneity and compared against state-of-the-art (PINN) through numerical analysis as a benchmark, which demonstrated the superiority of the proposed method over the PINN. [ABSTRACT FROM AUTHOR]

Kratom has caught the attention of governments, policymakers, and academicians due to its unique characteristics. This paper explores the scholarly works related to the different aspects of Kratom to elucidate its research progress and identify future research agendas. We reviewed existing publications on Kratom using a bibliometric methodology. By analyzing 431 scientific publications, we identified publication sources, document analysis, countries analysis, and research keywords, which helped us understand the research locus on Kratom. After reviewing the publications, we discovered significant disagreements in categorizing and defining Kratom amongst authors based on their nationalities. We also showed the knowledge structure of existing publications via thematic analysis, illustrating that the studies focused on the opioid nature of Kratom. Also, drug abuse-related issues evolved as the motor theme of research, while other aspects are prevalent as niche or emerging research themes. This paper contributes to the literature by providing a broad idea of existing literature and offering a comprehensive outlook on Kratom, which could be helpful for policy formulation in the future. [ABSTRACT FROM AUTHOR]

Abstract Background This study aims to construct a clinical prediction model and create a visual line chart depicting the risk of acute kidney injury (AKI) following resuscitation in cardiac arrest (CA) patients. Additionally, the study aims to validate the clinical predictive accuracy of the developed model. Methods Data were retrieved from the Dryad database, and publicly shared data were downloaded. This retrospective cohort study included 347 successfully resuscitated patients post-cardiac arrest from the Dryad database. Demographic and clinical data of patients in the database, along with their renal function during hospitalization, were included. Through data analysis, the study aimed to explore the relevant influencing factors of acute kidney injury (AKI) in patients after cardiopulmonary resuscitation. The study constructed a line chart prediction model using multivariate logistic regression analysis with post-resuscitation shock status (Post-resuscitation shock refers to the condition where, following successful cardiopulmonary resuscitation after cardiac arrest, some patients develop cardiogenic shock.), C reactive protein (CRP), Lactate dehydrogenase (LDH), and Alkaline phosphatase (ALP) identified as predictive factors. The predictive efficiency of the fitted model was evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Results Multivariate logistic regression analysis showed that post-resuscitation shock status, CRP, LDH, and PAL were the influencing factors of AKI after resuscitation in CA patients. The calibration curve test indicated that the prediction model was well-calibrated, and the results of the Decision Curve Analysis (DCA) demonstrated the clinical utility of the model constructed in this study. Conclusion Post-resuscitation shock status, CRP, LDH, and ALPare the influencing factors for AKI after resuscitation in CA patients. The clinical prediction model constructed based on the above indicators has good clinical discriminability and practicality.

Abstract This study aimed to understand the health status of low-income individuals living alone and to identify influencing factors. Using systematic random sampling methods, low-income individuals living alone were randomly selected. Via telephone interviews, we gathered information about their general health status. A logistic regression model was used to analyze relevant factors about the physical health of this population. The study included 1583 low-income individuals living alone. The prevalence rate of all kinds of diseases in low-income living alone in this survey was 88.63%. The multifactorial logistic regression analysis revealed that the risk factors for illness in this population were age ≥ 60 (OR 1.842, 95% CI 1.135–2.926, P = 0.006), self-rated poor mental health (OR 2.538, 95% CI 1.128–3.828, P = 0.005), and self-rated poor hearing status (OR 2.781, 95% CI 1.586–3.647, P = 0.001). Being female (OR 0.469, 95% CI 0.178–0.821, P = 0.033) was identified as a protective factor. Low-income individuals living alone are a unique group who lack familial care and economic and social support, and are thus in a disadvantaged social position. Therefore, this population requires increased attention, especially regarding their physical health. Implementing targeted assistance policies to improve their health status and enhance their quality of life is essential.