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Abstract Some cases of chronic rhinosinusitis (CRS) require surgical treatment and postoperative nasal packing, but bleeding and adhesion are common complications after nasal surgery. Biodegradable drug-loaded implants hold great therapeutic options for the treatment of CRS, but little data are available regarding the safety and efficacy of a novel drug-loaded haemostatic sponge (DLHS) in the sinus. The aim of this study was to investigate the safety and efficacy of DLHS in the sinus. We conducted a prospective, randomized, controlled, double-blind clinical trial. In this clinical trial, 49 patients were enrolled and randomly divided into 2 groups: group A (n = 25) had the DLHS containing 1 mg budesonide and 0.67 mg sodium hyaluronate placed into the sinus, and group B (n = 24) had the Nasopore placed after ESS. Endoscopic follow-up was performed for 12 weeks, and the findings were classified using the discharge, inflammation, polyps/oedema (DIP) endoscopic appearance scores. All patients completed questionnaires to evaluate their sinonasal symptoms by using the sinonasal outcome test-22 (SNOT-22) Chinese version and visual analogue scale (VAS). Serum cortisol concentration in group A was measured prior to surgery and at days 1, 3, 7, and 14 after nasal surgery. Comparing group A and group B, at 2 weeks, no significant differences were observed in either objective or subjective parameters. The mean value of VAS for rhinorrhoea and DIP for oedema and the mean value of nasal adhesion were significantly lower in Group A than in Group B at 6 and 12 weeks, but a significant difference did not occur in SNOT-22 and VAS for dysosmia between the two groups at 6 and 12 weeks. The mean serum cortisol concentrations in group A at the follow-up were within normal limits without remarkable fluctuations. This study demonstrates the safety and efficacy of a novel biodegradable DLHS with the possibility of being used in CRS patients, and this sponge may reduce inflammation and minimize adhesions via controlled local drug delivery without measurable systemic exposure.

Abstract We investigated the impact of antiviral treatment on the emergence of SARS-CoV-2 resistance during persistent infections in immunocompromised patients (n = 15). All patients received remdesivir and some also received nirmatrelvir-ritonavir (n = 3) or therapeutic monoclonal antibodies (n = 4). Sequence analysis showed that nine patients carried viruses with mutations in the nsp12 (RNA dependent RNA polymerase), while four had viruses with nsp5 (3C protease) mutations. Infectious SARS-CoV-2 with a double mutation in nsp5 (T169I) and nsp12 (V792I) was recovered from respiratory secretions 77 days after initial COVID-19 diagnosis from a patient sequentially treated with nirmatrelvir-ritonavir and remdesivir. In vitro characterization confirmed its decreased sensitivity to remdesivir and nirmatrelvir, which was overcome by combined antiviral treatment. Studies in golden Syrian hamsters demonstrated efficient transmission to contact animals. This study documents the isolation of SARS-CoV-2 carrying resistance mutations to both nirmatrelvir and remdesivir from a patient and demonstrates its transmissibility in vivo.

Abstract Fueled by the rapid advancement of nanofabrication, metasurface has provided unprecedented opportunities for 3D holography. Large depth 3D meta-holography not only greatly increases information storage capacity, but also enables distinguishing of the relative spatial relationship of 3D objects, which has important applications in fields like optical information storage and medical diagnosis. Although the methods based on Fresnel diffraction theory can reconstruct the real depth information of 3D objects, the maximum depth is only 2 mm. Here, we develop a 3D meta-holography based on angular spectrum diffraction theory to break through the depth limit. By developing the angular spectrum diffraction theory into meta-holography, the metasurface structure with independent polarization control is used to create a polarization multiplexing 3D meta-hologram. The fabricated amorphous silicon metasurface increases the depth range by 47.5 times and realizes 0.95 dm depth reconstruction for polarization independent and different color 3D meta-hologram in visible. Such polarization controlled large-depth color meta-holography is expected to open avenue for data storage, display, information security and virtual reality.

Abstract Objectives To establish a nomogram for differentiating malignant and benign focal liver lesions (FLLs) using ultrasomics features derived from contrast-enhanced ultrasound (CEUS). Methods 527 patients were retrospectively enrolled. On the training cohort, ultrasomics features were extracted from CEUS and b-mode ultrasound (BUS). Automatic feature selection and model development were performed using the Ultrasomics-Platform software, outputting the corresponding ultrasomics scores. A nomogram based on the ultrasomics scores from artery phase (AP), portal venous phase (PVP) and delayed phase (DP) of CEUS, and clinical factors were established. On the validation cohort, the diagnostic performance of the nomogram was assessed and compared with seniorexpert and resident radiologists. Results In the training cohort, the AP, PVP and DP scores exhibited better differential performance than BUS score, with area under the curve (AUC) of 84.1-85.1% compared with the BUS (74.6%, P

The utility of bio-isosteres is broad in drug discovery and methodology herein enables the preparation of deuterium-labeled products is the most fundamental of known bio-isosteric replacements. As such we report the use of both [D1]-aldehydes and [D2]-isonitriles across 8 multicomponent reactions (MCRs) to give diverse arrays of deuterated products. A highlight is the synthesis of several FDA-approved calcium channel blockers, selectively deuterated at a t1/2 limiting metabolic soft-spot via use of [D1]-aldehydes. Surrogate pharmacokinetic analyses of microsomal stability confirm prolongation of t1/2 of the new deuterated analogs. We also report the first preparation of [D2]-isonitriles from [D3]-formamides via a modified Leuckart–Wallach reaction and their use in an MCR to afford products with [D2]-benzylic positions and likely significantly enhanced metabolic stability, a key parameter for property-based design efforts.

Abstract Rabbit meat is tender, high in protein, low in fat and cholesterol, and offers several nutritional benefits. However, it has a stronger taste and can be challenging to cook. The global rabbit industry has been developing steadily, and China's total rabbit meat production has exceeded half of the world's total production in 2021. Along with the progress of the production process, the meat of the nutrition and taste at the same time, to improve smell also can get better control, solved the problems met in rabbit meat production. This article discusses the attributes of rabbit meat and outlines the deodorization, texture adjustment, and water retention techniques currently used in rabbit meat processing, aiming to offer a theoretical foundation for the advancement of rabbit meat processing technology.

Abstract The freshness of aquatic products is directly related to the safety and health of the people. Traditional methods of detecting the freshness of Conger myriaster rely on manual operations, which are labor‐intensive, inefficient, and highly subjective. This paper combines computer vision and the DWG‐YOLOv8 network model to establish an intelligent classification method for C. myriaster freshness. Through image augmentation, 484 C. myriaster samples were expanded to 2904 samples. The YOLOv8n model was improved by simplifying the network backbone, introducing Ghost convolution and the new DW‐GhostConv, thereby reducing the number of parameters and computational load. Test results show that the recognition accuracy of the DWG‐YOLOv8 model reached 98.958%, outperforming models such as ResNet18, Mobilenetv3 small, and Swin transformer v2 tiny. The model's parameter count is 16.609 K, the inference time is 57.80 ms, and the model size is only 102 KB. The research provides a reliable method for online intelligent and nondestructive detection of C. myriaster freshness.

Abstract The Nab-paclitaxel combined with gemcitabine (AG) regimen is the main chemotherapy regimen for pancreatic cancer, but drug resistance often occurs. Currently, the ability to promote sensitization in drug-resistant cases is an important clinical issue, and the strategy of repurposing conventional drugs is a promising strategy. This study aimed to identify a classic drug that targets chemotherapy resistance’s core signaling pathways and combine it with the AG regimen to enhance chemosensitivity. We also aimed to find reliable predictive biomarkers of drug combination sensitivity. Using RNA sequencing, we found that abnormal PI3K/Akt pathway activation plays a central role in mediating resistance to the AG regimen. Subsequently, through internal and external verification of randomly selected AG-resistant patient-derived organoid (PDO) and PDO xenograft models, we discovered for the first time that the classic anti-inflammatory drug sulindac K-80003, an inhibitor of the PI3K/Akt pathway that we focused on, promoted sensitization in half (14/28) of AG-resistant pancreatic ductal adenocarcinoma cases. Through RNA-sequencing, multiplex immunofluorescent staining, and immunohistochemistry experiments, we identified cFAM124A as a novel biomarker through which sulindac K-80003 promotes AG sensitization. Its role as a sensitization marker is explained via the following mechanism: cFAM124A enhances both the mRNA expression of cathepsin L and the activity of the cathepsin L enzyme. This dual effect stimulates the cleavage of RXRα, leading to large amounts of truncated RXRα, which serves as a direct target of K-80003. Consequently, this process results in the pathological activation of the PI3K/Akt pathway. In summary, our study provides a new treatment strategy and novel biological target for patients with drug-resistant pancreatic cancer.

Abstract Background Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains challenging. This study aims to develop a predictive model for progression-free survival (PFS) in LC patients with IO based on clinical features and advanced imaging biomarkers. Materials and methods A retrospective analysis was conducted on a cohort of 206 LC patients receiving IO treatment. Pre-treatment computed tomography images were used to extract advanced imaging biomarkers, including intratumoral and peritumoral-vasculature radiomics. Clinical features, including age, gene status, hematology, and staging, were also collected. Key radiomic and clinical features for predicting IO outcomes were identified using a two-step feature selection process, including univariate Cox regression and chi-squared test, followed by sequential forward selection. The DeepSurv model was constructed to predict PFS based on clinical and radiomic features. Model performance was evaluated using the area under the time-dependent receiver operating characteristic curve (AUC) and concordance index (C-index). Results Combining radiomics of intratumoral heterogeneity and peritumoral-vasculature with clinical features demonstrated a significant enhancement (p

Abstract Depression is a significant mental health issue with extensive economic implications, and recent studies suggest it may be transmitted between individuals. However, the mechanisms of this contagion remain unclear, and the social buffering effect has been understudied. This research employs three rodent models, including stress crossover, cohabitation-induced, and non-contact induced depression contagion models, to explore these mechanisms. Here, we report that that naive mice cohabiting with depressed mice showed increased corticosterone levels and depressive behaviors, unlike those with stressed mice, who did not exhibit these changes and even mitigated desperation in stressed mice. Non-contact cohabitation did not produce significant behavioral differences, but exposure to bedding from depressed mice reduced sucrose preference in naive mice. This study introduces reliable models of depression contagion, suggesting it operates independently of stress transmission. The interplay between depression contagion and social buffering may vary in different contexts. These findings provide new insights into the mechanisms of depression contagion and potential strategies for preventing depressive disorders.

Abstract Background Genetic variants in COL4A2 are less common than those of COL4A1 and their fetal clinical phenotype has not been well described to date. We present a fetus from China with an intronic variant in COL4A2 associated with a prenatal diagnosis of severe cerebral encephalomalacia and subdural hemorrhage. Methods Whole exome sequencing (WES) was applied to screen potential genetic causes. Bioinformatic analysis was performed to predict the pathogenicity of the variant. In in vitro experiment, the minigene assays were performed to assess the variant’s effect. Results In this proband, we observed ventriculomegaly, subdural hemorrhage, and extensive encephalomalacia that initially suggested cerebral hypoxic-ischemic and/or hemorrhagic lesions. WES identified a de novo heterozygous variant c.549 + 5G > A in COL4A2 gene. This novel variant leads to the skipping of exon 8, which induces the loss of 24 native amino acids, resulting in a shortened COL4A2 protein (p.Pro161_Gly184del). Conclusion Our study demonstrated that c.549 + 5G > A in COL4A2 gene is a disease-causing variant by aberrant splicing. This finding enriches the variant spectrum of COL4A2 gene, which not only improves the understanding of the fetal neurological disorders associated with hypoxic-ischemic and hemorrhagic lesions from a clinical perspective but also provides guidance on genetic diagnosis and counseling.

Abstract Quorum sensing (QS) inhibition has emerged as a promising target for directed drug design, providing an appealing strategy for developing antimicrobials, particularly against infections caused by drug‐resistant pathogens. In this study, we designed and synthesized a total of 33 β‐nitrostyrene derivatives using 1‐nitro‐2‐phenylethane (NPe) as the lead compound, to target the facultative anaerobic bacterial pathogen Serratia marcescens. The QS‐inhibitory effects of these compounds were evaluated using S. marcescens NJ01 and the reporter strain Chromobacterium violaceum CV026. Among the 33 new β‐nitrostyrene derivatives, (E)‐1‐methyl‐4‐(2‐nitrovinyl)benzene (m‐NPe, compound 28) was proven to be a potent inhibitor that reduced biofilm formation of S. marcescens NJ01 by 79%. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) results revealed that treatment with m‐NPe (50 μg/ml) not only enhanced the susceptibility of the formed biofilms but also disrupted the architecture of biofilms by 84%. m‐NPe (50 μg/ml) decreased virulence factors in S. marcescens NJ01, reducing the activity of protease, prodigiosin, and extracellular polysaccharide (EPS) by 36%, 72%, and 52%, respectively. In S. marcescens 4547, the activities of hemolysin and EPS were reduced by 28% and 40%, respectively, outperforming the positive control, vanillic acid (VAN). The study also found that the expression levels of QS‐ and biofilm‐related genes (flhD, fimA, fimC, sodB, bsmB, pigA, pigC, and shlA) were downregulated by 1.21‐ to 2.32‐fold. Molecular dynamics analysis showed that m‐NPe could bind stably to SmaR, RhlI, RhlR, LasR, and CviR proteins in a 0.1 M sodium chloride solution. Importantly, a microscale thermophoresis (MST) test revealed that SmaR could be a target protein for the screening of a quorum sensing inhibitor (QSI) against S. marcescens. Overall, this study highlights the efficacy of m‐NPe in suppressing the virulence factors of S. marcescens, identifying it as a new potential QSI and antibiofilm agent capable of restoring or improving antimicrobial drug sensitivity.

Abstract Precise, fast, and reliable identification and quantification of microplastic contamination are essential for determining their environmental concentrations for risk assessments. This study investigates the use of nuclear magnetic resonance (NMR) spectroscopy to quantify microplastics by analysing dilution series of polystyrene (PS), polyisoprene-cis (PI), polybutadiene-cis (PB), polylactic acid (PLA), polyvinyl chloride (PVC) and polyurethane (PU). Each polymer type was dissolved in a suitable solvent and an internal standard was utilized for quantification. Detection and quantification limits for each polymer type were established in two ways: (1) by using an equation based on proton signals and an internal standard with known concentration and (2) by using the LOQ based on the signal-to-noise ratio. Both data sets were compared and showed that using the internal standard (method 1) results in more accurate and lower concentration limits in the range of 0.2–8 µg mL−1 for all six polymer types, while the LOQ based on the SNR (method 2) gives consistently higher concentration limits (1–10 µg mL−1). The research shows the accuracy, efficacy, and reliability of quantitative NMR spectroscopy for polymer analysis in these concentration ranges compared to established quantifying methods, such as, PyGC/MS, FTIR, or Raman spectroscopy.

Abstract Background Algae play important roles in urban river ecosystems and are the cornerstones of most water quality monitoring programs. Thus, a better understanding of algal community dynamics is needed to support sustainable management of water resources in urban rivers. Results In this study, we quantified the seasonal variations in planktonic and periphytic algal community structure in the highly urban Fenhe River and identified environmental factors affecting algal community structure and diversity. We monitored planktonic (drifting) and periphytic (attached) algal communities in the Taiyuan section of the Fenhe River over one year. The results indicated that Cyanophyta was the dominant phylum in both communities, followed by Bacillariophyta and Chlorophyta. Significant differences were observed in the composition of the planktonic and periphytic algal communities. In particular, the periphytic algal community was more diverse than the planktonic community. Water temperature and pH were the main environmental factors affecting planktonic and periphytic algal community structure, respectively, while nutrients were the most significant factor affecting planktonic and periphytic algal diversity. Ecological modeling indicated that the variations in the algal communities of the Fenhe River are mainly driven by stochastic processes. A co-occurrence network developed for the communities displayed positive interactions between the planktonic and periphytic algae. Conclusions These findings deepen our understanding of the seasonal interaction between planktonic and periphytic algae and the driving factors affecting community structure in the Fenhe River. They also provide a theoretical basis for the managing and protecting water resources in urban river ecosystems.

Abstract Background Decellularized extracellular matrix (dECM) is an intriguing natural biomaterial that has garnered significant attention due to its remarkable biological properties. In our study, we employed a cell-matrixed nerve graft for the repair of sciatic nerve defects in rats. The efficacy of this approach was assessed, and concurrently, the underlying molecular regulatory mechanisms were explored to elucidate how such grafts facilitate nerve regeneration. Long noncoding RNAs (lncRNAs) regulate mRNA expression via multiple mechanisms, including post-transcriptional regulation, transcription factor effects, and competitive binding with miRNAs. These interactions between lncRNAs and mRNAs facilitate precise control of gene expression, allowing organisms to adapt to varying biological environments and physiological states. By investigating the expression profiles and interaction dynamics of mRNAs and lncRNAs, we can enhance our understanding of the molecular mechanisms through which cell-matrixed nerve grafts influence neural repair. Such studies are pivotal in uncovering the intricate networks of gene regulation that underpin this process. Results Weighted gene co-expression network analysis (WGCNA) utilizes clustering algorithms, such as hierarchical clustering, to aggregate genes with similar expression profiles into modules. These modules, which potentially correspond to distinct biological functions or processes, can subsequently be analyzed for their association with external sample traits. By correlating gene modules with specific conditions, such as disease states or responses to treatments, WGCNA enables a deeper understanding of the genetic architecture underlying various phenotypic traits and their functional implications. We identified seven mRNA modules and five lncRNA modules that exhibited associations with treatment or time-related events by WGCNA. We found the blue (mRNAs) module which displayed a remarkable enrichment in “axonal guidance” and “metabolic pathways”, exhibited strong co-expression with multiple lncRNA modules, including blue (related to “GnRH secretion” and “pyrimidine metabolism”), green (related to “arginine and proline metabolism”), black (related to “nitrogen metabolism”), grey60 (related to “PPAR signaling pathway”), and greenyellow (related to “steroid hormone biosynthesis”). All of the top 50 mRNAs and lncRNAs exhibiting the strongest correlation were derived from the blue module. Validation of key molecules were performed using immunohistochemistry and qRT-PCR. Conclusion Revealing the principles and molecular regulatory mechanisms of the interaction between materials and biological entities, such as cells and tissues, is a direction for the development of biomimetic tissue engineering technologies and clinically effective products.

Abstract Systemic lupus erythematosus (SLE) commonly damages the blood system and often manifests as blood cell abnormalities. The performance of biomarkers for predicting SLE activity still requires further improvement. This study aimed to analyze blood cell parameters to identify key indicators for a SLE activity prediction model. Clinical data of 138 patients with SLE (high activity, n = 40; moderate activity, n = 44; mild activity, n = 37; low activity, n = 17) and 100 healthy controls (HCs) were retrospectively analyzed. Data from 89 paired admission–discharge patients with SLE were collected. Differences and associations between blood cell parameters and disease indicators, as well as the relationship between the these parameters and organ damage, were examined. Machine-learning methods were employed to develop a prediction model for disease activity evaluation. Most blood cell parameters (22/26, 84.62%) differed significantly between patients with SLE and HCs. Analysis of 89 paired patients with SLE revealed significant changes in most blood cell parameters at discharge. The standard deviation of lymphocyte volume (SD-V-LY), red blood cell (RBC) count, lymphocyte percentage (LY%), hemoglobin(HGB), hematocrit(HCT), and neutrophil percentage(NE%) correlated with disease activity. By employing machine learning, an optimal model was established to predict active SLE using SD-V-LY, RBC count, and LY% (area under the curve [AUC] = 0.908, sensitivity = 0.811). External validation indicated impressive performance (AUC = 0.940, sensitivity = 0.833). Correlation analysis revealed that SD-V-LY was positively correlated with ESR, IgG, IgA, and IgM but was negatively correlated with C3 and C4. The RBC count was linked to renal and hematopoietic system impairments, whereas LY% was associated with joint/muscle involvement. In conclusion, SD-V-LY is associated with SLE disease activity. SD-V-LY combined with RBC count and LY% contributes to a prediction model, which can be utilized as an effective tool for assessing SLE activity.

Abstract Background Patients with small-cell lung cancer (SCLC) have few treatment options and dismal overall survival (OS) after failed platinum-based chemotherapy. Methods The eligibility criteria of this phase II clinical trial included patients with measurable disease, age of 18 to 75 years, a confirmed diagnosis of disease progression or recurrence after prior platinum-based chemotherapy with a pathologically proven diagnosis of SCLC. Patients were treated with anlotinib at a dosage of 12 mg once daily (QD) and S-1 at 60 mg twice daily (BID) for 2 weeks, followed by a 1-week treatment-free interval. After six cycles of the above treatment, patients continued the maintenance therapy using S-1 monotherapy at 60 mg/ BID for 2 weeks, followed by a 1-week treatment-free interval until disease progression. Results From March 2019 to June 2020, a total of 71 patients were initially assessed for eligibility in this study. Out of these, 52 patients who met the inclusion criteria were enrolled, and 48 patients received at least two doses of the study drug. The median follow-up time was 25.1 months. The ORR was seen in 21 patients (43.8%). The median PFS was 4.5 months (95% CI, 3.5–5.5 months), and the median OS was 5.9 months (95% CI, 4.6–7.3 months). The most common grade 3–4 treatment-related adverse events were thrombocytopenia (16.7%), anemia (14.6%), neutropenia (14.6%), and hypertension (10.4%). No treatment-related death occurred. Conclusions The combination of anlotinib with oral fluoropyrimidine S-1 demonstrated notable activity in relapsed or refractory SCLC, showing a favorable ORR and an acceptable, manageable safety profile. Trial registration This trial was registered with ClinicalTrial.gov (NCT03823118) on 3 January 2019.

Abstract Background Gastroparesis is a major complication following complete mesocolic excision (CME) and significantly impacts patient outcomes. This study aimed to create a machine learning model to pinpoint key risk factors before, during, and after surgery, effectively predicting the risk of gastroparesis after CME. Methods The study involved 1146 patients with colon cancer, out of which 95 developed gastroparesis. Data were collected on 34 variables, including demographics, chronic conditions, pre-surgery test results, types of surgery, and intraoperative details. Four machine learning techniques were employed: extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN). The evaluation involved k-fold cross-validation, receiver operating characteristic (ROC) analysis, calibration curves, decision curve analysis (DCA), and external validation. Results XGBoost excelled in its performance for predictive models. ROC analysis showed high accuracy for XGBoost, with area under the curve (AUC) scores of 0.976 for the training set and 0.906 for the validation set. K-fold cross-validation confirmed the model's stability, and calibration curves indicated high predictive accuracy. Additionally, DCA highlighted XGBoost’s superior patient benefits for intervention treatments. An AUC of 0.77 in external validation demonstrated XGBoost's strong generalization ability. Conclusion The XGBoost-fueled predictive model for post-surgery colon cancer patients proved highly effective. It underlined gastroparesis as a significant post-operative issue, associated with advanced age, prolonged surgeries, extensive intraoperative blood loss, surgical techniques, low serum protein levels, anemia, diabetes, and hypothyroidism.

Abstract The reverse water gas shift reaction can be considered as a promising route to mitigate global warming by converting CO2 into syngas in a large scale, while it is still challenging for non-Cu-based catalysts to break the trade-off between activity and selectivity. Here, the relatively high loading of Ni species is highly dispersed on hydroxylated TiO2 through the strong Ni and −OH interactions, thereby inducing the formation of rich and stable Ni clusters (~1 nm) on anatase TiO2 during the reverse water gas shift reaction. This Ni cluster/TiO2 catalyst shows a simultaneous high CO2 conversion and high CO selectivity. Comprehensive characterizations and theoretical calculations demonstrate Ni cluster/TiO2 interfacial sites with strong CO2 activation capacity and weak CO adsorption are responsible for its unique catalytic performances. This work disentangles the activity-selectivity trade-off of the reverse water gas shift reaction, and emphasizes the importance of metal−OH interactions on surface.

Abstract Background With the fast-paced advancements of robot technology, human–robot interaction (HRI) has become increasingly popular and complex, and self-efficacy in HRI has received extensive attention. Despite its popularity, this topic remains understudied in China. Objective In order to provide a psychometrically sound instrument in China, this study aimed to translate and validate the Self-Efficacy in Human–Robot Interaction Scale (SE-HRI) in two Chinese adult samples (N1 = 300, N2 = 500). Methods The data was analyzed by SPSS 26.0 and Amos 24.0. Item analysis and exploratory factor analysis were conducted using Sample 1 data. Confirmatory factor analysis, criterion-related validity analysis, and reliability analysis were then performed using Sample 2 data. Results The results revealed that the Chinese SE-HRI scale consisted of 13 items in a two-factor model, suggesting a good model fit. Moreover, general self-efficacy and willingness to accept the use of artificial intelligence (AI) were both positively correlated with self-efficacy in HRI, while negative attitudes toward robots showed an inverse correlation, proving the Chinese SE-HRI scale exhibited excellent criterion-related validity. Conclusion The Chinese SE-HRI scale is a reliable assessment tool for evaluating self-efficacy in HRI in China. The study discussed implications and limitations, and suggested future directions.

In the contemporary era of quality and personalization, this article explores how soft sofa fabrics enhance users’ emotional experience and convey perceptual images. Users’ visual-tactile perception data on 10 common soft sofa fabrics were gathered by questionnaire surveys, utilizing the Kansei engineering approach, and the visual-tactile evaluation theory. With SPSS software, the data were processed and examined in-depth using a variety of techniques, including cluster analysis and factor analysis. The experiment screened fabric samples and emotional vocabularies via the KJ method and expert evaluation, and questionnaires were designed and implemented based on the semantic differential method and Likert scale. Fabrics were categorized into four groups based on cluster analysis, which are suitable for users pursuing different home environments. The two primary factors that comprise the fundamental aspects of the perceptual image of soft sofa fabrics were found to be the texture, quality experience factor, and the typical emotional reaction factor, which were extracted by factor analysis. Both theory and practice were considered, enriching the theoretical framework of emotional imagery and user emotion research while offering valuable practical guidance for the design, production, and marketing of soft sofas.

The resource utilization of calcium carbide residue (CCR) and rice husk ash (RHA) is helpful to save resources and alleviate environmental pollution. In this research, CCR and RHA were used to modify soft clay, and the resonant column test was conducted to explore its small-strain dynamic characteristics. The micro-mechanism of CCR-RHA modified soft clay (CRSC) was investigated by using scanning electron microscopy, X-ray diffraction and mercury intrusion tests. The findings demonstrated that the dynamic shear modulus of the CRSC increased with the increase of RHA content and confining pressure, but decreased with the increase of shear strain. In contrast, the damping ratio presents the opposite change law. The Hardin-Drnevich (H-D) model was used to fit the dynamic shear modulus/maximum dynamic shear modulus (G/Gmax)-shear strain γ and the damping ratio D-shear strain γ. As confining pressure increased, Gmax increased but Dmax dropped in CRSC specimens with the same RHA content. The changes of the fitted G/Gmax-γ curve could be divided into progressively decrease stage and rapid decrease stage, while the changes of the fitted D-γ curve could be separated into linear stage and slow stage, with the same turning point γ = 10−4. Microscopic tests revealed that the incorporation of CCR and RHA helped to promote the hydration reaction, and the generated hydration products such as calcium silicate hydrate were able to enhance the integrity and compactness of the CRSC. The results of this research putfward solid foundation for the application of CCR-RHA in the modification of soft soil.

The tensile strength of clay is an important factor in determining the stability of soil slope. Due to the fragmentation of soil, the understanding of the tensile strength of clay is not clear. In this study, the uniaxial tensile test of remolded clay is carried out to analyze the influence of water content and tensile rate on the tensile strength of remolded clay based on the self-designed direct tensile test device. The test results show that: (1) The tensile strength of remolded clay increases first and then decreases with the increase of water content, as the other conditions (such as tensile rate) remain stable. The peak tensile strength occurs near the optimal water content. (2) The tensile strength of remolded clay increases with the increase of tensile rate, as other conditions such as water content remain unchanged. (3) In the water content range (18%–24%) of this study, the remolded clay undergoes plastic deformation under uniaxial tension, and shows softening failure law after reaching the peak tensile strength. (4) The discrete element simulation method is used to analyze and verify the results obtained from the above experiments. The results of this study can be used for the stability analysis of soil slope and the calculation and design of slope protection.

Abstract Porcine deltacoronavirus (PDCoV) is an emerging swine enteropathogenic coronavirus that can cause acute diarrhea and vomiting in newborn piglets and poses a potential risk for cross-species transmission. It is necessary to develop an effective serological diagnostic tool for the surveillance of PDCoV infection and vaccine immunity effects. In this study, we developed a monoclonal antibody-based competitive ELISA (cELISA) that selected the purified recombinant PDCoV nucleocapsid (N) protein as the coating antigen to detect PDCoV antibodies. To evaluate the diagnostic performance of the cELISA, 122 swine serum samples (39 positive and 83 negative) were tested and the results were compared with an indirect immunofluorescence assay (IFA) as the reference method. By receiver operating characteristic (ROC) curve analysis, the optimum cutoff value of percent inhibition (PI) was determined to be 26.8%, which showed excellent diagnostic performance, with an area under the curve (AUC) of 0.9919, a diagnostic sensitivity of 97.44% and a diagnostic specificity of 96.34%. Furthermore, there was good agreement between the cELISA and virus neutralization test (VNT) for the detection of PDCoV antibodies, with a coincidence rate of 92.7%, and the κ analysis showed almost perfect agreement (κ = 0.851). Overall, the established cELISA showed good diagnostic performance, including sensitivity, specificity and repeatability, and can be used for diagnostic assistance, evaluating the response to vaccination and assessing swine herd immunity.

Abstract Aims This research developed a prognostic model for OS patients based on the Mechanistic Target of Rapamycin Complex 1 (mTORC1) signature. Background The mTORC1 signaling pathway has a critical role in the maintenance of cellular homeostasis and tumorigenesis and development through the regulation of cell growth, metabolism and autophagy. However, the mechanism of action of this signaling pathway in Osteosarcoma (OS) remains unclear. Objective The datasets including the TARGET-OS and GSE39058, and 200 mTORC1 genes were collected. Methods The mTORC1 signaling-related genes were obtained based on the Molecular Signatures Database (MSigDB) database, and the single sample gene set enrichment analysis (ssGSEA) algorithm was utilized in order to calculate the mTORC1 score. Then, the WGCNA were performed for the mTORC1-correlated gene module, the un/multivariate and lasso Cox regression analysis were conducted for the RiskScore model. The immune infiltration analysis was performed by using the ssGSEA method, ESTIMATE tool and MCP-Count algorithm. KM survival and Receiver Operating Characteristic (ROC) Curve analysis were performed by using the survival and timeROC package. Results The mTORC1 score and WGCNA with β = 5 screened the mTORC1 positively correlated skyblue2 module that included 67 genes, which are also associated with the metabolism and hypoxia pathways. Further narrowing of candidate genes and calculating the regression coefficient, we developed a useful and reliable RiskScore model, which can classify the patients in the training and validation set into high and low-risk groups based on the median value of RiskScore as an independent and robust prognostic factor. High-risk patients had a significantly poor prognosis, lower immune infiltration level of multiple immune cells and prone to cancer metastasis. Finally, we a nomogram model incorporating the metastasis features and RiskScore showed excellent prediction accuracy and clinical practicability. Conclusion We developed a useful and reliable risk prognosis model based on the mTORC1 signaling signature.

Abstract Artificial intelligence (AI) is revolutionizing the field of biomedical research and treatment, leveraging machine learning (ML) and advanced algorithms to analyze extensive health and medical data more efficiently. In headache disorders, particularly migraine, AI has shown promising potential in various applications, such as understanding disease mechanisms and predicting patient responses to therapies. Implementing next-generation AI in headache research and treatment could transform the field by providing precision treatments and augmenting clinical practice, thereby improving patient and public health outcomes and reducing clinician workload. AI-powered tools, such as large language models, could facilitate automated clinical notes and faster identification of effective drug combinations in headache patients, reducing cognitive burdens and physician burnout. AI diagnostic models also could enhance diagnostic accuracy for non-headache specialists, making headache management more accessible in general medical practice. Furthermore, virtual health assistants, digital applications, and wearable devices are pivotal in migraine management, enabling symptom tracking, trigger identification, and preventive measures. AI tools also could offer stress management and pain relief solutions to headache patients through digital applications. However, considerations such as technology literacy, compatibility, privacy, and regulatory standards must be adequately addressed. Overall, AI-driven advancements in headache management hold significant potential for enhancing patient care, clinical practice and research, which should encourage the headache community to adopt AI innovations. Graphical Abstract

Abstract Baculovirus is an obligate parasitic virus of the phylum Arthropoda. Baculovirus including Autographa californica multiple nucleopolyhedrovirus (AcMNPV) has been widely used in the laboratory and industrial preparation of proteins or protein complexes. Due to its large packaging capacity and non-replicative and non-integrative natures in mammals, baculovirus has been proposed as a gene therapy vector for transgene delivery. However, the mechanism of baculovirus transduction in mammalian cells has not been fully illustrated. Here, we employed a cell surface protein-focused CRISPR screen to identify host dependency factors for baculovirus transduction in mammalian cells. The screening experiment uncovered a series of baculovirus host factors in human cells, including exostosin-like glycosyltransferase 3 (EXTL3) and NPC intracellular cholesterol transporter 1 (NPC1). Further investigation illustrated that EXTL3 affected baculovirus attachment and entry by participating in heparan sulfate biosynthesis. In addition, NPC1 promoted baculovirus transduction by mediating membrane fusion and endosomal escape. Moreover, in vivo, baculovirus transduction in Npc1 −/+ mice showed that disruption of Npc1 gene significantly reduced baculovirus transduction in mouse liver. In summary, our study revealed the functions of EXTL3 and NPC1 in baculovirus attachment, entry, and endosomal escape in mammalian cells, which is useful for understanding baculovirus transduction in human cells.

Abstract Heat stress (HS) poses a significant challenge to plant survival, necessitating sophisticated molecular mechanisms to maintain cellular homeostasis. Here, we identify SICKLE (SIC) as a key modulator of HS responses in Arabidopsis (Arabidopsis thaliana). SIC is required for the sequestration of RNA DEBRANCHING ENZYME 1 (DBR1), a rate-limiting enzyme of lariat intronic RNA (lariRNA) decay, into stress granules (SGs). The sequestration of DBR1 by SIC enhances the accumulation of lariRNAs, branched circular RNAs derived from excised introns during pre-mRNA splicing, which in turn promote the transcription of their parental genes. Our findings further demonstrate that SIC-mediated DBR1 sequestration in SGs is crucial for plant HS tolerance, as deletion of the N-terminus of SIC (SIC1–244) impairs DBR1 sequestration and compromises plant response to HS. Overall, our study unveils a mechanism of transcriptional regulation in the HS response, where lariRNAs are enriched through DBR1 sequestration, ultimately promoting the transcription of heat stress tolerance genes.

Abstract Background Breakthrough cancer pain (BTcP) has a negative impact on patients’ quality of life, general activities, and is related to worse clinical outcomes. Fentanyl inhalant is a hand-held combination drug-device delivery system providing rapid, multi-dose (25μg/dose) administration of fentanyl via inhalation of a thermally generated aerosol. This multicenter, randomized, placebo-controlled, multiple-crossover, double-blind study evaluated the efficacy, safety, and tolerability of fentanyl inhalant in treating BTcP in opioid-tolerant patients. Methods The trial was conducted in opioid-tolerant cancer patients with 1 ~ 4 BTcP outbursts per day. Each patient was treated and observed for 6 episodes of BTcP (4 with fentanyl inhalant, 2 with placebo). During each episode of targeted BTcP, patients were allowed up to six inhalations, with an interval of at least 4 min between doses. Primary outcome was the time-weighted sum of PID (pain intensity difference) scores at 30 min (SPID30). Results A total of 335 BTcP episodes in 59 patients were treated. The mean SPID30 was -97.4 ± 48.43 for fentanyl inhalant-treated episodes, and -64.6 ± 40.25 for placebo-treated episodes (p

Understanding the temporal and spatial variation of hydrochemical components in large freshwater lakes is crucial for effective management and conversation. In this study, we identify the temporal-spatial characteristics and driving factors of the hydrochemical components in Baiyangdian Lake using geochemical methods (Gibbs diagram, Piper diagram and End-element diagram of ion ratio) and multivariate statistical techniques (Principal component analysis and Correlation analysis). 16 sets of samples were collected from Baiyangdian Lake in May (normal season), July (flood season), and December (dry season) of 2022. Results indicate significant spatial variation in Na+, Cl−, SO42− and NO3− , suggesting a strong influence of human activities. Cation concentrations exhibit greater seasonal variation in the dry season compared to the flood season, while the concentrations of the four anions show inconsistent seasonal changes due to the combined effects of river water chemical composition and human activities. The hydrochemical type of Baiyangdian Lake is primarily HCO3·Cl-Na·Ca2+, Mg2+ and HCO3− originate mainly from silicate and carbonate rock dissolution, while K+, Na+ and Cl− originate mainly from sewage and salt dissolution in sediments. SO42− may mainly stem from industrial wastewater, while NO3− primarily originates from animal feces and domestic sewage. Through the use of Principal Component Analysis, it is identified that water-rock interaction (silicate and carbonate rocks dissolution, and dissolution of salt in sediments), carbonate sedimentation, sewage, agricultural fertilizer and manure, and nitrification are the main driving factors of the variation of hydrochemical components of Baiyangdian Lake across three hydrological seasons. These findings suggest the need for effective control of substandard domestic sewage discharge, optimization of agricultural fertilization strategies, and proper management of animal manure to comprehensively improve the water environment in Baiyangdian Lake.

Abstract Background The triglyceride-glucose (TyG) index is a reliable marker of insulin resistance that is involved in the progression of hypertension. This study aimed to evaluate the association of the TyG index with the risk for major cardiovascular events (MACE) in young adult hypertension. Methods A total of 2,651 hypertensive patients aged 18–40 years were consecutively enrolled in this study. The TyG index was calculated as Ln [triglycerides × fasting plasma glucose/2]. The cutoff value for an elevated TyG index was determined to be 8.43 by receiver-operating characteristic curve analysis. The primary endpoint was MACE, which was a composite of all-cause death, non-fatal myocardial infarction, coronary revascularization, non-fatal stroke, and end-stage renal dysfunction. The secondary endpoints were individual MACE components. Results During the median follow-up time of 2.6 years, an elevated TyG index was associated with markedly increased risk of MACE (adjusted hazard ratio [HR] 3.440, P

Dietary fat content can reduce the methane production of dairy cows; however, the relevance fatty acid (FA) composition has towards this inhibitory effect is debatable. Furthermore, in-depth studies elucidating the effects of unsaturated fatty acids (UFA) on rumen function and the mechanism of reducing methane (CH4) production are lacking. This study exposed 10 Holstein cows with the same parity, similar milk yield to two total mixed rations: low unsaturated FA (LUFA) and high unsaturated FA (HUFA) with similar fat content. The LUFA group mainly added fat powder (C16:0 > 90%), and the HUFA group mainly replaced fat powder with extruded flaxseed. The experiment lasted 26 d, the last 5 d of which, gas exchange in respiratory chambers was conducted to measure gas emissions. We found that an increase in the UFA in diet did not affect milk production (P > 0.05) and could align the profile of milk FAs more closely with modern human nutritional requirements. Furthermore, we found that increasing the UFA content in the diet lead to a decrease in the abundance of Methanobrevibacter in the rumen (|linear discriminant analysis [LDA] score| > 2 and P 2 and P

Heterogeneous grain structures with coherent L12 nanoprecipitates were constructed in a medium entropy alloy with chemical composition of Co34.5Cr32Ni27.5Al3Ti3 (at. %). The volume fraction and size of L12 nanoprecipitates are observed to become higher and larger, and the interspacing is found to become smaller with increasing aging time, resulting in a severer heterogeneity. The domain of tensile properties was expanded by varying the size and volume fraction of coherent L12 nanoprecipitates after aging treatment. The samples after longer-time aging treatment show stronger strain hardening as compared to those after shorter-time aging treatment. The hetero-deformation-induced (HDI) hardening plays a more vital role in the longer-time aged samples than the shorter-time aged samples, especially at the elasto-plastic transition stage. The dominant precipitation hardening mechanism is observed to transit from dislocation-cutting to Orowan dislocation-looping with increasing precipitation size, as predicted by a theoretical model and validated by experimental results. Multiple deformation defects, such as deformation twins, stacking faults and Lomer-Cottrell locks, are the dominant deformation mechanisms for all samples, while interactions between these defects and L12 nanoprecipitates were observed to be more intensive in the longer-time aged samples than in the shorter-time aged samples, resulting in stronger precipitation and HDI hardening.

Background: Tongue inspection, an essential diagnostic method in Traditional Chinese Medicine (TCM), has the potential for early-stage disease screening. This study aimed to evaluate the effectiveness of deep learning-based analysis of tongue images for hepatic fibrosis screening. Methods: A total of 1083 tongue images were collected from 741 patients and divided into training, validation, and test sets. DenseNet-201, a convolutional neural network, was employed to train the AI model using these tongue images. The predictive performance of AI was assessed and compared with that of FIB-4, using real-time two-dimensional shear wave elastography as the reference standard. Results: The proposed AI model achieved an accuracy of 0.845 (95% CI: 0.79–0.90) and 0.814 (95% CI: 0.76–0.87) in the validation and test sets, respectively, with negative predictive values (NPVs) exceeding 90% in both sets. The AI model outperformed FIB-4 in all aspects, and when combined with FIB-4, the NPV reached 94.4%. Conclusion: Tongue inspection, with the assistance of AI, could serve as a first-line screening method for hepatic fibrosis.

Cu pillar bump (CPB) technology as the representative advanced packaging technology possesses the characteristics of miniaturization and high density, thus playing an important role in the reliability of electronic devices. However, the brittle intermetallic compound (IMC) layer in the joints evidently affects the service performance and reliability of CPB joints. Thus, the influence of IMC layer thickness and microstructure needs to be carefully evaluated. In this study, the reliability of CPB joints with different IMC layer thickness under the condition of isothermal storage and room-temperature electromigration was tested, and the effect of initial IMC thickness of joints on the reliability was revealed. The full-IMC joints have the best isothermal storage reliability while the half-IMC joints perform the worst. Meanwhile, the thin-IMC joints own the best electromigration reliability but the full-IMC joints show the worst because that the initial voids in full-IMC joints accelerate the failure caused by electromigration.

Objective: To determine the relationship between cartilage injury, bone marrow edema, and total bone mineral density in patients with knee osteoarthritis (KOA). Methods: Ninety patients with KOA admitted to the Sichuan Province Orthopedic Hospital between March 2023 and October 2023 were selected, all of whom underwent knee joint MRI and chest QCT examinations. The patients were divided into three groups according to the QTC results: normal bone density, reduced bone mass, and osteoporosis. Patient information, such as sex, age, body mass index (BMI), and course of illness, was also obtained. MRIs of the knee joints were scored separately according to the Recht grading and Whole-organ Magnetic Resonance Imaging Score (WORMS). The bone mineral density (BMD) of the patients was calculated and the BMD values were statistically analyzed using the MR score. Results: No statistically significant differences were observed in sex, BMI, or disease duration among the three groups; however, a statistically significant difference was observed in age. The Recht and WORMS scores among the three groups showed statistical significance between the normal bone density group and the reduced bone mass and osteoporosis groups; however, no statistical significance was observed between the reduced bone mass and osteoporosis groups. KOA cartilage injury was negatively correlated with bone density with a correlation coefficient of r=−0.412, while KOA bone marrow edema was negatively correlated with bone density with a correlation coefficient of r=−0.254. Conclusion: The total bone density in patients with KOA is related to knee joint cartilage injury and bone marrow edema. A decrease in total bone density may indicate the severity of knee cartilage injury or bone marrow edema.

Objective: This article aimed to analyze the computed tomography (CT) imaging manifestations and clinical significance of scimitar syndrome to improve our understanding of the disease. Method: A total of 28 patients diagnosed with scimitar syndrome were enrolled in our hospital from January 2019 to January 2024, and their clinical and imaging data were retrospectively analyzed. Results: Among the 28 cases, there were 10 males and 18 females, with 15 and 13 cases of the infantile and adult types, respectively. The average age of patients with the infant type were (6.78±3.50) months, with 10 cases having total anomalous right pulmonary venous drainage. Among them, three cases had stenosis and obstruction at the site of ectopic drainage and two cases had concomitant atrial septal defect and pulmonary arterial hypertension; these five cases underwent surgical treatment. Five cases of partial anomalous right pulmonary venous drainage to the inferior vena cava were found during imaging examination owing to the presence of other deformities and pulmonary infections. The average age of patients with the adult type was (5.53±2.72) years old. Seven cases had total anomalous right pulmonary venous drainage to the inferior vena cava, with one case undergoing surgical treatment. Six cases had ectopic drainage from the right lower pulmonary vein to the inferior vena cava: two underwent elective surgery owing to a clear diagnosis for many years, and two underwent interventional treatment for systemic arterial blood supply owing to extralobar sequestration. Conclusion: There were significant differences in clinical manifestation between patients with infantile and adult types of scimitar syndrome. Using multiple imaging modes of CT examination combined with powerful reconstruction post-processing functions, children with scimitar syndrome can be evaluated comprehensively, providing a basis for the selection of clinical treatment methods and surgical plans.

Background: Lifestyle plays an important role in preventing and managing gastroesophageal reflux disease (GERD). In response to the conflicting results in previous studies, we performed a systematic review and meta-analysis to investigate this association. Methods: Relevant studies published until January 2023 were retrieved from 6 databases, and the prevalence of symptomatic gastroesophageal reflux (GER) or GERD was determined from the original studies. A random effects model was employed to meta-analyze the association by computing the pooled relative risk (RR) with 95% confidence intervals (95%CIs). Furthermore, subgroup and dose–response analyses were performed to explore subgroup differences and the association between cumulative physical activity (PA) time and GERD. Results: This meta-analysis included 33 studies comprising 242,850 participants. A significant negative association was observed between PA and the prevalence of symptomatic GER (RR = 0.74, 95%CI: 0.66–0.83; p < 0.01) or GERD (RR = 0.80, 95%CI: 0.76–0.84; p < 0.01), suggesting that engaging in PA might confer a protective benefit against GERD. Subgroup analyses consistently indicated the presence of this association across nearly all subgroups, particularly among the older individuals (RR

Solar radiation plays a pivotal role in urban microclimate, significantly, impacting building energy consumption and renewable energy utilization. Utilizing a comprehensive three- and-a- half-year dataset of high-precision urban microclimate, this study proposes a three-step approach to solar radiation prediction: 1) Data Preprocessing and Characterization: The microclimate data are meticulously preprocessed and categorized, with solar radiation values categorized into three resolutions: total daily solar radiation, hourly solar radiation, and 30-min solar radiation. 2) Feature Selection: Various climatic parameters are carefully selected for solar radiation prediction at different resolutions. 3) Machine Learning Models: Three machine learning models, namely Long Short-Term Memory (LSTM), Random Forest (RF) and Support Vector Regression (SVR), are employed for solar radiation prediction. The results show that all three models exhibit prediction accuracy with closely matched errors. Particularly noteworthy findings include SVR’s superior performance in predicting total daily solar radiation with a minimal error rate of about 6.0% and an impressive coefficient of determination of 0.9789. LSTM exhibits adaptability, achieving R2 values of 0.9906 and 0.9956 for hourly and 30-min radiation predictions, respectively. This study offers valuable insights into solar radiation and its implications for building energy research. It underscores that large datasets enable accurate solar radiation predictions, even when excluding certain parameters like daily maximum temperature and relative humidity.

A novel small molecule depressant (M-DEP) was used to separate chalcopyrite and molybdenite via flotation. The results showed that M-DEP had an excellent selective depression on molybdenite, while had little effect on the flotation of chalcopyrite. The adsorption capacity of M-DEP on the surface of molybdenite was greater than that on chalcopyrite surface. The adsorption of M-DEP reduced the floatability of molybdenite and had less effect on the floatability of chalcopyrite, which was due to its different adsorption modes on the surface of the two minerals. Furthermore, the interaction between chalcopyrite and M-DEP was mainly chemical interaction, and almost all of the adsorbed M-DEP molecules were removed and replaced by sodium butyl xanthate (SBX). By contrast, hydrophobic interaction was the main way in which M-DEP was adsorbed on the molybdenite surface with little chemical interaction, which was less interfered by SBX addition. Therefore, M-DEP had a super selective depression on molybdenite. The study provided a novel depressant and approach for the deep separation of chalcopyrite and molybdenite via flotation.

Wool quality and yield are two important economic livestock traits. However, there are relatively few molecular studies on lncRNA for improving sheep wool, so these require further exploration. In this study, we examined skin tissue from the upper scapula of Super Merino (SM) and Small-Tailed Han (STH) sheep during the growing period. The apparent difference was verified via histological examination. High-throughput RNA sequencing identified differentially expressed (DE) long non-coding (lncRNAs) and messenger RNAs (mRNAs). The target gene of DE lncRNA and DE genes were enrichment analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). A Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) was used to verify randomly selected DE lncRNAs and mRNAs. Finally, the DE, RAC2, WNT11, and FZD2 genes, which were enriched in the Wnt signaling pathway, were detected via immunohistochemistry. The results showed that a total of 20,888 lncRNAs and 31,579 mRNAs were identified in the skin tissues of the two sheep species. Among these, 56 lncRNAs and 616 mRNAs were differentially expressed. Through qRT-PCR, the trends in the randomly selected DE genes’ expression were confirmed to be aligned with the RNA-seq results. GO and KEGG enrichment analysis showed that DE lncRNA target genes were enriched in GO terms as represented by epidermal and skin development and keratin filature and in KEGG terms as represented by PI3K-Akt, Ras, MAPK, and Wnt signaling pathways, which were related to hair follicle growth and development. Finally, immunohistochemistry staining results indicated that RAC2, WNT11, and FZD2 were expressed in dermal papilla (DP). The lncRNAs MSTRG.9225.1 and MSTRG.98769.1 may indirectly participate in the regulation of hair follicle growth, development, and fiber traits by regulating their respective target genes, LOC114113396(KRTAP15-1), FGF1, and IGF1. In addition, MSTRG.84658.1 may regulate the Wnt signaling pathway involved in the development of sheep hair follicles by targeting RAC2. This study provides a theoretical reference for improving sheep breeding in the future and lays a foundation for further research on the effects of MSTRG.84658.1 and the target gene RAC2 on dermal papilla cells (DPC).

Synergistic effects of herbicidal rice husks and pyrolysis liquid from waste wood-based panels were studied relative to the germination of three common weed species in a tea plantation. The pyrolysis liquid consisted of various organic acids, phenols, alcohols, ketones, and nitrogen compounds, with organic acids accounting for up to 46.8% of the content. Three seeds of smooth crabgrass (Digitaria ischaemum), annual fleabane (Erigeron annuus), and hedge-parsley (Torilis scabra (Thunb.) DC) were treated with 2000 and 4000 L/ha of pyrolysis liquid, as well as 50, 100, and 200 m3/ha of pyrolysis liquid as a cover material. The pre-emergence herbicide tests demonstrated that the combination of rice husks and pyrolysis liquid effectively inhibited seed germination and aboveground biomass of the weeds. The weed control effect increased with the increase in the amount applied. The combination of rice husks (200 m3/ha) and pyrolysis liquid (4000 L/ha) exhibited the highest weed control efficacy, reducing seed germination and aboveground biomass by 69.1%, 79.5%, and 97.6% for smooth crabgrass, annual fleabane, and hedge-parsley, respectively. Discarded furniture materials and rice husks can both be used as sustainable materials for weed control, offering a fresh approach to the efficient utilization of waste materials.

Abstract Kindlin-2 is a cytoskeletal adapter protein that is present in many different cell types. By virtue of its interaction with multiple binding partners, Kindlin-2 intercalates into numerous signaling pathways and cytoskeletal nodes. A specific interaction of Kindlin-2 that is of paramount importance in many cellular responses is its direct binding to the cytoplasmic tails of integrins, an interaction that controls many of the adhesive, migratory and signaling responses mediated by members of the integrin family of cell-surface heterodimers. Kindlin-2 is highly expressed in many cancers and is particularly prominent in prostate cancer cells. CRISPR/cas9 was used as a primary approach to knockout expression of Kindlin-2 in both androgen-independent and dependent prostate cancer cell lines, and the effects of Kindlin-2 suppression on oncogenic properties of these prostate cancer cell lines was examined. Adhesion to extracellular matrix proteins was markedly blunted, consistent with the control of integrin function by Kindlin-2. Migration across matrices was also affected. Anchorage independent growth was markedly suppressed. These observations indicate that Kindlin-2 regulates hallmark features of prostate cancer cells. In androgen expressing cells, testosterone-stimulated adhesion was Kindlin-2-dependent. Furthermore, tumor growth of a prostate cancer cell line lacking Kindlin-2 and implanted into the prostate gland of immunocompromised mice was markedly blunted and was associated with suppression of angiogenesis in the developing tumor. These results establish a key role of Kindlin-2 in prostate cancer progression and suggest that Kindlin-2 represents an interesting therapeutic target for treatment of prostate cancer.

Abstract Intrahepatic cholangiocarcinoma (iCCA) presents a challenging diagnosis due to its nonspecific early clinical manifestations, often resulting in late-stage detection and high mortality. Diagnosing iCCA is further complicated by its limited accuracy, often necessitating multiple invasive procedures for precise identification. Despite carbohydrate antigen 19–9 (CA19-9) having been investigated and employed for iCCA diagnosis, it demonstrates modest diagnostic performance. Consequently, the identification of novel biomarkers with improved sensitivity and specificity remains an imperative yet formidable task. Autoantibodies, as early indicators of the immune response against cancer, offer a promising avenue for enhancing diagnostic accuracy. Our study aimed to identify non-invasive blood-based autoantibody biomarkers capable of distinguishing iCCA patients from healthy individuals (CTRs). We profiled autoantibodies in 26 serum samples (16 iCCAs and 10 CTRs) using protein microarrays containing 1622 functional proteins. Leveraging machine learning techniques, we identified a signature composed of three autoantibody biomarkers (NDE1, PYCR1, and VIM) in conjunction with CA19-9 for iCCA detection. This combined signature demonstrated superior diagnostic performance with an AUC of 96.9%, outperforming CA19-9 alone (AUC: 83.8%). These results suggest the potential of autoantibody biomarkers to develop a complementary non-invasive diagnostic utility for routine iCCA screening.

Abstract The association between insulin resistance (IR) and the risk of all-cause mortality and cardiovascular mortality among osteoarthritis (OA) patients remains uncertain. This study aims to clarify the correlation between a novel marker of IR, the triglyceride glucose-body mass index (TyG-BMI), and the risk of all-cause mortality and cardiovascular mortality in OA patients. Data from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2020 were analyzed. Multivariable Cox proportional hazards regression analysis and restricted cubic spline plots were employed to elucidate the association between the TyG-BMI index and the risk of all-cause mortality or cardiovascular mortality in OA patients. Additionally, subgroup analysis was conducted to explore potential interactions and identify populations at elevated risk of mortality. The study cohort comprised 4097 OA patients who were followed up for a period of 20 years, during which 1197 cases of all-cause mortality and 329 cases of mortality attributed to cardiovascular disease were recorded. Our findings revealed a U-shaped nonlinear relationship between the TyG-BMI index and the risk of all-cause mortality or cardiovascular mortality in OA patients, with the lowest mortality risk thresholds identified at 282 and 270, respectively. Moreover, surpassing these thresholds was associated with a 3% increase in the risk of all-cause mortality and a 5% increase in the risk of cardiovascular mortality for every 10-unit increment in TyG-BMI level. Among American OA patients, a U-shaped nonlinear relationship exists between the TyG-BMI index and the risk of all-cause mortality or cardiovascular mortality. These findings underscore the significant role of IR in the progression of OA.

Abstract The spatial delays of pulmonary tuberculosis (PTB) have been less explored. In this study, a total of 151,799 notified PTB cases were included, with median patient and diagnostic delays of 15 [interquartile range (IOR), 4–35] and 2 (IOR, 0–8) days, respectively. The spatial autocorrelation analysis and spatial–temporal scan statistics were used to determine the clusters, indicating that the regions in the southwestern and northeastern parts of Zhejiang Province exhibited high rates of long-term patient delay (LPD, delay ≥ 15 days) and long-term diagnostic delay (LDD, delay ≥ 2 days). Besides, the Mantel test indicated a moderately positive correlation between public awareness of suspicious symptoms and the LPD rate in 2018 (Mantel's r = 0.4, P

Abstract Background Magnetic resonance spectroscopy (MRS) studies have indicated that the imbalance between gamma-aminobutyric acid (GABA) and glutamate/glutamine (Glx) levels was the potential cause of migraine development. However, the changes in the GABA and Glx levels in patients with New daily persistent headache (NDPH) remain unclear. This study aimed to investigate the changes in GABA and Glx levels in the periaqueductal gray (PAG) and dentate nucleus (DN) in patients with NDPH using the MEGA-PRESS sequence. Methods Twenty-one NDPH patients and 22 age- and sex-matched healthy controls (HCs) were included and underwent a 3.0T MRI examination, using the MEGA-PRESS sequence to analyze GABA and Glx levels of PAG and DN. The correlations between these neurotransmitter levels and clinical characteristics were also analyzed. Results There were no significant differences in the GABA+/Water, GABA+/Cr, Glx/Water, and Glx/Cr levels in both PAG and DN between the two groups (all p > 0.05). Moderate-severe NDPH patients had lower levels of Glx/Water (p = 0.034) and Glx/Cr (p = 0.012) in DN than minimal-mild NDPH patients. In patients with NDPH, higher Glx/Water levels in the PAG (r=-0.471, p = 0.031, n = 21) and DN (r=-0.501, p = 0.021, n = 21) and higher Glx/Cr levels in DN (r=-0.483, p = 0.026, n = 21) were found to be correlated with lower Visual Analogue Scale scores. Additionally, a positive correlation was observed between the GABA+/Cr levels in the DN and the Generalized Anxiety Disorder-7 scores (r = 0.519, p = 0.039, n = 16). Conclusions The results of this study indicated that the GABA and Glx levels in the PAG and DN may not be the primary contributor to the development of NDPH. The correlations between certain clinical scales and the neurotransmitter levels may be derived from the NDPH related symptoms.

Abstract The kidney is vulnerable to ischemia and reperfusion (I/R) injury that can be fatal after major surgery. Currently, there are no effective treatments for I/R-induced kidney injury. Trimethylamine N-oxide (TMAO) is a gut-derived metabolite linked to many diseases, but its role in I/R-induced kidney injury remains unclear. Here, our clinical data reveals an association between preoperative systemic TMAO levels and postoperative kidney injury in patients after post-cardiopulmonary bypass surgery. By genetic deletion of TMAO-producing enzyme flavin-containing monooxygenase 3 (FMO3) and dietary supplementation of choline to modulate TMAO levels, we found that TMAO aggravated acute kidney injury through the triggering of endoplasmic reticulum (ER) stress and worsened subsequent renal fibrosis through TGFβ/Smad signaling activation. Together, our study underscores the negative role of TMAO in I/R-induced kidney injury and highlights the therapeutic potential through the modulation of TMAO levels by targeting FMO3, thereby mitigating acute kidney injury and preventing subsequent renal fibrosis.

Abstract Background The development of acquired EGFR-TKI treatment resistance is still a major clinical challenge in the treatment of non-small cell lung cancer (NSCLC). This study aimed to investigate the role of HDAC1/FOXK1/miR-33a signaling in EGFR-TKI resistance. Methods The expression levels of miR‐33a, HDAC1, and FOXK1 were examined using quantitative polymerase chain reaction (PCR) and bioinformatics analysis. Cell proliferation, migration, and apoptosis were explored by cell number assay, Transwell, and flow cytometry assays, respectively. After overexpression or knockdown of HDAC1, miR-33a expression in the cells, cell functions were tested. Immunoprecipitation and correlation analyses were used to evaluate the interaction between HDAC1 and FOXK1 protein. The tumor-suppressive role of miR-33a was investigated by animal experiments. Results The suppression of miR-33a increased TKI resistance by affecting cell proliferation, migration, and apoptosis in gefitinib-resistant cells. HDAC1 is the key upstream molecule that inhibits miR-33 expression. HDAC1 upregulation increased gefitinib resistance by its binding to FOXK1 in cells to silence miR-33a expression. MiR-33a overexpression exerts tumor-suppressive effects by negatively regulating ABCB7 and p70S6K1 expression. Moreover, overexpression of miR-33a inhibited tumor growth in a xenograft nude mouse model. Conclusions HDAC1/FOXK1 upregulation and miR-33a silencing are new mechanisms of EGFR-TKI resistance in NSCLC.