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Abstract Background Gallstones are a common digestive disorder that threatens human health. Iron deficiency may be related to the formation of gallstones, but there is limited current epidemiological research. The objective of this study was to investigate the relationship between iron status and gallstones. Methods The datasets from the National Health and Nutrition Examination Survey (NHANES) 2017–2020 were used in a cross-sectional investigation. Gallstones were determined by using the 2007–2010 NHANES questionnaire. Multivariate linear regression models were used to examine the association between serum iron, serum ferritin and iron intake with the risk for gallstones. Subgroup analysis based on gender, age, race, and diabetes were performed. Fitted smoothing curves were used to describe the linear relationship. Results The research involved 7847 participants aged 20 and above, among whom 845 were identified as having gallstones. Participants with higher serum iron levels tended to have a lower gallstones prevalence. A negative relationship between serum iron and gallstones prevalence was observed (OR = 0.979, 95% CI:0.965–0.992). The group with the highest serum iron tertile had a 23.7% lower risk of gallstones compared to the lowest tertile (OR = 0.763, 95% CI:0.628‒0.929). Gallstone prevalence was inversely correlated with iron intake in model 1. The negative association between serum iron and gallstones remained stable in stratifications, including gender, age, race, and diabetes. Conclusions Elevated serum iron was associated with a decreased prevalence of gallstones. However, to confirm the impact of long-term iron metabolism on gallstone formation, additional prospective research is necessary.

Abstract Background It is uncertain whether the weekend warrior pattern is associated with all-cause mortality among adults living with type 2 diabetes. This study explored how the ‘weekend warrior’ physical activity (PA) pattern was associated with all-cause mortality among adults living with type 2 diabetes. Methods This prospective cohort study investigated US adults living with type 2 diabetes in the National Health and Nutrition Examination Survey (NHANES). Mortality data was linked to the National Death Index. Based on self-reported leisure-time and occupational moderate-to-vigorous PA (MVPA), participants were categorized into 3 groups: physically inactive (

Macrophages play an important role in the development of vascular diseases, with their homeostasis closely linked to metabolic reprogramming. This study aims to explore the role of circular RNA-mediated epigenetic remodeling in maintaining macrophage homeostasis during diabetes-induced microvascular dysfunction. We identified a circular RNA, circRNA-sperm antigen with calponin homology and coiled-coil domains 1 (cSPECC1), which is significantly up-regulated in diabetic retinas and in macrophages under diabetic stress. cSPECC1 knockdown in macrophages attenuates M1 macrophage polarization and disrupts macrophage-endothelial crosstalk in vitro. cSPECC1 knockdown in macrophages mitigates diabetes-induced retinal inflammation and ameliorates retinal vascular dysfunction. Mechanistically, cSPECC1 regulates GPX2 expression by recruiting eIF4A3, enhancing GPX2 mRNA stability and altering arachidonic acid metabolism. The metabolic intermediate 12-HETE has emerged as a key mediator, regulating both macrophage homeostasis and the crosstalk between macrophages and endothelial cells. Exogenous 12-HETE supplementation interrupts the anti-angiogenic effects of cSPECC1 knockdown. Collectively, circSPECC1 emerges as a novel regulator of macrophage-mediated vascular integrity and inflammation. Targeting the metabolic reprogramming of macrophages presents a promising therapeutic strategy for mitigating diabetes-induced vascular dysfunction.

ObjectivesShear-wave elastography (SWE) provides valuable stiffness within breast masses, making it a useful supplement to conventional ultrasound imaging. Super-resolution ultrasound (SRUS) imaging enhances microvascular visualization, aiding in the differential diagnosis of breast masses. Current clinical ultrasound diagnosis of breast cancer primarily relies on gray-scale ultrasound. The combined diagnostic potential of tissue stiffness and microvascular characteristics, two critical tumor biomarkers, remains insufficiently explored. This study aims to evaluate the correlation between the elastic modulus, assessed using SWE, and microvascular characteristics captured through SRUS, in order to evaluate the effectiveness of combining these techniques in distinguishing between benign and malignant breast masses.Materials and methodsIn this single-center prospective study, 97 patients underwent SWE to obtain parameters including maximum elasticity (Emax), minimum elasticity (Emin), mean elasticity (Emean), standard deviation of elasticity (Esd), and elasticity ratio. SRUS was used to calculate the microvascular flow rate and microvessel density (MVD) within the breast masses. Spearman correlation analysis was used to explore correlations between Emax and MVD. Receiver operating characteristic curves and nomogram were employed to assess the diagnostic efficacy of combining SRUS with SWE, using pathological results as the gold standard.ResultsEmax, Emean, Esd, and MVD were significantly higher in malignant breast masses compared to benign ones (p < 0.001), while Emin was significantly lower in malignant masses (p < 0.05). In Spearman correlation analysis, Emax was significantly positively correlated with MVD (p < 0.01). The area under the curve for SRUS combined with SWE (0.924) was significantly higher than that for SWE (0.883) or SRUS (0.830) alone (p < 0.001), thus indicating improved diagnostic accuracy. The decision curve analysis of the nomogram indicated that SWE combined with SRUS model had a higher net benefit in predicting breast cancer.ConclusionsThe MVD of the breast mass shows a significant positive correlation with Emax. By integrating SRUS with SWE, this study proposes a novel diagnostic approach designed to improve specificity and accuracy in breast cancer detection, surpassing the limitations of current ultrasound-based methods. This approach shows promise for early breast cancer detection, with the potential to reduce the need for unnecessary biopsies and improve patient outcomes.

Tea leaf diseases are significant causes of reduced quality and yield in tea production. In the Yunnan region, where the climate is suitable for tea cultivation, tea leaf diseases are small, scattered, and vary in scale, making their detection challenging due to complex backgrounds and issues such as occlusion, overlap, and lighting variations. Existing object detection models often struggle to achieve high accuracy in detecting tea leaf diseases. To address these challenges, this paper proposes a tea leaf disease detection model, BRA-YOLOv7, which combines a dual-level routing dynamic sparse attention mechanism for fast identification of tea leaf diseases in complex scenarios. BRA-YOLOv7 incorporates PConv and FasterNet as replacements for the original network structure of YOLOv7, reducing the number of floating-point operations and improving efficiency. In the Neck layer, a dual-level routing dynamic sparse attention mechanism is introduced to enable flexible computation allocation and content awareness, enhancing the model’s ability to capture global information about tea leaf diseases. Finally, the loss function is replaced with MPDIoU to enhance target localization accuracy and reduce false detection cases. Experiments and analysis were conducted on a collected dataset using the Faster R-CNN, YOLOv6, and YOLOv7 models, with Mean Average Precision (mAP), Floating-point Operations (FLOPs), and Frames Per Second (FPS) as evaluation metrics for accuracy and efficiency. The experimental results show that the improved algorithm achieved a 4.8% improvement in recognition accuracy, a 5.3% improvement in recall rate, a 5% improvement in balance score, and a 2.6% improvement in mAP compared to the traditional YOLOv7 algorithm. Furthermore, in external validation, the floating-point operation count decreased by 1.4G, FPS improved by 5.52%, and mAP increased by 2.4%. In conclusion, the improved YOLOv7 model demonstrates remarkable results in terms of parameter quantity, floating-point operation count, model size, and convergence time. It provides efficient lossless identification while balancing recognition accuracy, real-time performance, and model robustness. This has significant implications for adopting targeted preventive measures against tea leaf diseases in the future.

ObjectivesWith the increasing application of 5G remote ultrasound robots in healthcare, robust methods are in critical demand to assess participant satisfaction and identify its influencing factors. At present, there is limited empirical research on multi-parametric and multidimensional satisfaction evaluation of participants with 5G remote ultrasound robot examination. Previous studies have demonstrated that structural equation modeling (SEM) effectively integrates various statistical techniques to examine the relationships among multiple variables. Therefore, this study aimed to evaluate the satisfaction of participants with 5G remote ultrasound robot examination and its influencing factors using SEM.MethodsBetween April and June 2022, 213 participants from Wuhan Automobile Manufacturing Company underwent remote ultrasound examinations using the MGIUS-R3 remote ultrasound robot system. After these examinations, the participants evaluated the performance of the 5G remote ultrasound robot based on their personal experiences and emotional responses. They completed a satisfaction survey using a self-developed questionnaire, which included 19 items across five dimensions: examination efficiency, examination perception, communication perception, value perception, and examination willingness. A SEM was established to assess the satisfaction of participants with the 5G remote ultrasound robot examinations and the influencing factors.ResultsA total of 201 valid questionnaires were collected. The overall satisfaction of participants with the 5G remote ultrasound robot examination was 45.43 ± 11.60, with 169 participants (84%) expressing satisfaction. In the path hypothesis relationship test, the dimensions of examination efficiency, examination perception, communication perception, and value perception had positive effects on satisfaction, with standardized path coefficients of 0.168, 0.170, 0.175, and 0.191. Satisfaction had a direct positive effect on examination willingness, with a standardized path coefficient of 0.260. Significant differences were observed across different educational levels in the dimensions of examination perception, communication perception, value perception, and examination willingness. Participants with different body mass indices also showed significant differences in examination perception; all p-values were less than 0.05.ConclusionIn this study, value perception was identified as the most significant factor influencing satisfaction. It could be improved by enhancing participants’ understanding of the accuracy and safety of 5G remote ultrasound robot examinations. This enhances satisfaction and the willingness to undergo examinations. Such improvements not only facilitate the widespread adoption of this technology but also promote the development of telemedicine services.

Abstract Background In Guangdong Province, China, there is lack of information on the HIV epidemic among high-risk groups and the general population, particularly in relation to sexual transmission, which is a predominant route. The new HIV infections each year is also uncertain owing to HIV transmission from men who have sex with men (MSM) to women, as a substantial proportion of MSM also have female sexual partnerships to comply with social demands in China. Methods A deterministic compartmental model was developed to predict new HIV infections in four risk groups, including heterosexual men and women and low- and high-risk MSM, in Guangdong Province from 2016 to 2050, considering HIV transmission from MSM to women. The new HIV infections and its 95% credible interval (CrI) were predicted. An adaptive sequential Monte Carlo method for approximate Bayesian computation (ABC-SMC) was used to estimate the unknown parameter, a mixing index. We calibrated our results based on new HIV diagnoses and proportions of late diagnoses. The Morris and Sobol methods were applied in the sensitivity analysis. Results New HIV infections increased during and 2 years after the COVID-19 pandemic, then declined until 2050. New infections rose from 8,828 [95% credible interval (CrI): 6,435–10,451] in 2016 to 9,652 (95% CrI: 7,027–11,434) in 2019, peaking at 11,152 (95% CrI: 8,337–13,062) in 2024 before declining to 7,084 (95% CrI: 5,165–8,385) in 2035 and 4,849 (95% CrI: 3,524–5,747) in 2050. Women accounted for approximately 25.0% of new HIV infections, MSM accounted for 40.0% (approximately 55.0% of men), and high-risk MSM accounted for approximately 25.0% of the total. The ABC-SMC mixing index was 0.504 (95% CrI: 0.239–0.894). Conclusions Given that new HIV infections and the proportion of women were relatively high in our calibrated model, to some extent, the HIV epidemic in Guangdong Province remains serious, and services for HIV prevention and control are urgently needed to return to the levels before the COVID-19 epidemic, especially in promoting condom-based safe sex and increasing awareness of HIV prevention to general population.

Abstract Learning graph structure from observed signals over graph is a crucial task in many graph signal processing (GSP) applications. Existing approaches focus on inferring static graph, typically assuming that all nodes are available. However, these approaches ignore the situation where only a subset of nodes are available from spatiotemporal measurements, and the remaining nodes are never observed due to application-specific constraints, resulting in time-varying graph estimation accuracy declines dramatically. To handle this problem, we propose a framework that consider the presence of hidden nodes to identify time-varying graph. Specifically, we assume that the graph signals are smooth and stationary on the graphs and only a small number of edges are allowed to change between two consecutive graphs. With these assumptions, we present a challenging time-varying graph inference problem, which models the influence of hidden nodes in terms of estimating the graph-shift operator matrices that have a form of graph Laplacian. Moreover, we emphasize similar edge pattern (column-sparsity) between different graphs. Finally, our method is evaluated on both synthetic and real-world data. The experimental results demonstrate the advantage of our method when compared to existing benchmarking methods.

Supplementation with far-red light in controlled environment agriculture production can enhance yield by triggering the shade avoidance syndrome. However, the effectiveness of this yield enhancement can be further improved through intermittent far-red light supplementation. In this study, the effects are explored of varying far-red light photon intensities and intermittent exposure durations—specifically at 5, 15, 30, and 45 min intervals—on the growth and development of lettuce (Lactuca sativa) in plant factories, while maintaining a constant red light photon flux and daily light integral. The results showed that compared to constant far-red light, 30 min intermittent far-red light increased yield by 11.7% and the number of leaves and buds by 2.66. Furthermore, the various metrics demonstrated that intermittent far-red light supplementation enhanced the overall effectiveness of the far-red light treatment. This was validated by analyzing phytohormone content and the expression of genes related to hormone metabolism and transport at the tip of the lettuce stems. Transcriptome analysis revealed that the differences in gene expression between treatments were primarily concentrated in genes related to signaling, hormone metabolism, and transport. Weighted Gene Co-expression Network Analysis identified the co-expression modules associated with yield and quality. Additionally, dynamic expression analysis showed genes involved to far-red photoreception, response, and hormone metabolism and transport exhibited optimal rhythmic responses only under 30 min intermittent far-red light supplementation. This suggests that intermittent far-red light irradiation at 30 min intervals is the most effective for activating far-red light signaling influencing hormone metabolism and transport, thereby accelerating the growth of lettuce leaves and buds and ultimately increasing yield.

Perivascular epithelioid cell tumors (PEComas) are mesenchymal tumors that exhibit characteristic epithelioid or spindle cell morphology and typically grow around blood vessels. These tumors are characterized by the expression of melanocytic and smooth muscle markers, such as HMB-45, Melan-A, and smooth muscle actin, indicating a dual differentiation phenotype. PEComas are extremely rare diseases, and patients typically have a very poor prognosis. Here, we report a case of malignant cutaneous PEComa with pulmonary metastasis in a Chinese female and review relevant literature. The patient underwent surgical resection of a soft tissue tumor in the left upper arm under general anesthesia, and the subsequent pathological findings suggested a tumor with perivascular epithelioid cell differentiation (PEComa). The patient received adjuvant chemotherapy and radiotherapy after surgical resection, along with monitoring through computed tomography (CT) scans. Three months later, pulmonary metastasis was detected, but both the cutaneous PEComa in the left upper limb and the pulmonary metastatic lesions were stably controlled under active management and treatment. This is a rare case worth reporting and studying, and therefore, we conducted a long-term follow-up, and we hope to provide help for the clinical treatment of PEComa.

ObjectiveIn this study, the impact of inhibiting the PI3K/AKT/NF-κB pathway on lung oxidative damage induced by Echinococcus granulosus cyst fluid was investigated.MethodsTwenty-four mice were randomly assigned to four groups. Three months after inoculation with hydatid cyst segments, mice in group A were treated with intraperitoneal and intratracheal saline injections; mice in group B were administered a caudal vein injection of a PI3K inhibitor, followed by cyst fluid sensitization; mice in group C received an AKT inhibitor via caudal vein, followed by cyst fluid sensitization; and mice in group D were subjected to cyst fluid sensitization without any inhibitor treatment. Cellular changes in lung tissues across all groups were evaluated, including pathological section analysis. Analysis of pulmonary tissue and serum from these mice included the assessment of PI3K/AKT/NF-κB pathway proteins, inflammatory factors, and related mRNA levels.ResultsMice in groups B and C exhibited a higher proportion of M2-type macrophages and significantly lower levels of PI3K/AKT/NF-κB pathway proteins, inflammatory factors (interleukin-6 [IL-6]/tumor necrosis factor-α [TNF-α]), and oxidative markers in lung tissues compared to mice in group D (P < 0.05).ConclusionOur results in this study indicate that activation of the PI3K/AKT/NF-κB pathway contributed to an increase in the M1 macrophage phenotype, leading to enhanced secretion of peroxidases and inflammatory factors. This mechanism plays a crucial role in the oxidative and inflammatory lung damage associated with allergic reactions to E. granulosus cyst fluid.

BackgroundThe Montreal Cognitive Assessment (MoCA) is a valuable tool for detecting cognitive impairment, widely used in many countries. However, there is still a lack of large sample normative data and whose cut-off values for detecting cognitive impairment is considerable controversy.MethodsThe assessment conducted in this study utilizes the MoCA scale, specifically employing the Mandarin-8.1 version. This study recruited a total of 3,097 healthy adults aged over 20 years. We performed multiple linear regression analysis, incorporating age, gender, and education level as predictor variables, to examine their associations with the MoCA total score and subdomain scores. Subsequently, we established normative values stratified by age and education level. Finally, we included 242 patients with vascular cognitive impairment (VCI) and 137 controls with normal cognition, and determined the optimal cut-off value of VCI through ROC curves.ResultsThe participants in this study exhibit a balanced gender distribution, with an average age of 54.46 years (SD = 14.38) and an average education period of 9.49 years (SD = 4.61). The study population demonstrates an average MoCA score of 23.25 points (SD = 4.82). The multiple linear regression analysis indicates that MoCA total score is influenced by age and education level, collectively accounting for 46.8% of the total variance. Higher age and lower education level are correlated with lower MoCA total scores. A score of 22 is the optimal cut-off value for diagnosing vascular cognitive impairment (VCI).ConclusionThis study offered normative MoCA values specific to the Chinese adults. Furthermore, this study indicated that a score of 26 may not represent the most optimal cut-off value for VCI. And for detecting VCI, a score of 22 may be a better cut-off value.

Abstract Background The weight-adjusted-waist index (WWI) is a novel obesity index, and gallstones are associated with obesity. This study aimed to investigate the possible relationship between WWI and gallstones. Methods The datasets from the National Health and Nutrition Examination Survey (NHANES) 2017–2020 were used in a cross-sectional investigation. Multivariate linear regression models were used to examine the linear connection between WWI and gallstones incidence. Fitted smoothing curves and threshold effect analysis were used to describe the nonlinear relationship. Results The study comprised 8004 participants over the age of 20, including 833 reported with gallstones. Participants in the higher WWI tertile tended to have a higher gallstones prevalence. In the final adjusted model, a positive association between WWI and gallstones prevalence was observed (OR = 1.34, 95% CI: 1.20‒1.49). Participants in the highest WWI tertile had a significantly 71% higher risk of gallstones than those in the lowest WWI tertile (OR = 1.71, 95% CI: 1.35‒2.17). A nonlinear correlation was found between the WWI and gallstones prevalence, with an inflection point of 12.7. Conclusions Our study found that higher WWI levels connected with increased prevalence of gallstones. However, more prospective studies are needed to validate our findings.

ABSTRACT: Objectives: Several linezolid population pharmacokinetic (popPK) models have been established to facilitate optimal therapy; however, their extrapolated predictive performance to other clinical sites is unknown. This study aimed to externally evaluate the predictive performance of published pharmacokinetic models of linezolid in adult patients. Methods: For the evaluation dataset, 150 samples were collected from 70 adult patients (72.9% of which were critically ill) treated with linezolid at our center. Twenty-five published popPK models were identified from PubMed and Embase. Model predictability was evaluated using prediction-based, simulation-based, and Bayesian forecasting-based approaches to assess model predictability. Results: Prediction-based diagnostics found that the prediction error within ±30% (F30) was less than 40% in all models, indicating unsatisfactory predictability. The simulation-based prediction- and variability-corrected visual predictive check and normalized prediction distribution error test indicated large discrepancies between the observations and simulations in most of the models. Bayesian forecasting with one or two prior observations significantly improved the models’ predictive performance. Conclusion: The published linezolid popPK models showed insufficient predictive ability. Therefore, their sole use is not recommended, and incorporating therapeutic drug monitoring of linezolid in clinical applications is necessary.

Abstract Retinal pathological neovascularization involves endothelial cells, pericytes, photoreceptor cells, ganglion cells, and glial cells, whose roles remain unclear. Using the Scissor algorithm, we found that microglia are associated with formation of fibrovascular membranes and can promote pathological neovascularization. GO and KEGG results showed that PI3K-AKT pathway activation in retinal microglia was associated with pathological neovascularization, and PIK3IP1 was associated with retinal microglia activation. Then we used PCR, Western blot and Elisa techniques to confirm that the expression of VEGFA, FGF2, HGFα and MMP9 was increased in microglia after Lipopolysaccharide (LPS) induction. We also used cell flow cytometry and OIR models to verify the role of PI3K-AKT pathway and PIK3IP1 in microglia. Targeting of PIK3IP1 regulated the activation of the PI3K-AKT pathway in microglia, microglia function activation, and pro-angiogenic effects. These findings reveal the role of M1-type microglia in pathological neovascularization and suggests that targeting the PI3K-AKT pathway in microglia may be a new strategy for treating retinal pathological neovascularization.

Abstract Background Previous studies have shown that Family with sequence similarity 134 member B (FAM134B) was involved in the occurrence and development of malignancy, however, the function and molecular mechanism of FAM134B in Hepatocellular Carcinoma (HCC) radiotherapy resistance remain unclear. Therefore, it may clinical effective to clarify the molecular mechanism and identify novel biomarker to overcome radiotherapy resistance in HCC. Methods The protein and mRNA expression of FAM134B were determined using Real-time PCR and Western blot, respectively. IHC assay was performed to investigate the association between FAM134B expression and the clinicopathological characteristics of 132 HCC patients. Functional assays, such as in situ model, colon formation, FACS, and Tunel assay were used to determine the oncogenic role of FAM134B in human HCC progression. Furthermore, western blotting and luciferase assay were used to determine the mechanism of FAM134B promotes radiation-sensitive in HCC cells. Results We noted that FAM134B was downregulated in HCC, which was correlated with the radiation resistance in patients with HCC. Overexpression of FAM134B contribute to radiation sensitive in HCC; however, inhibition of FAM134B confers HCC cell lines to radiation resistance both in vitro and in vivo. Moreover, we found that FAM134B interacts with FMS related receptor tyrosine kinase 3 (FLT3) and downregulation of FAM134B activated JAK/Stat3 signaling pathway. Importantly, pharmacological inhibition of JAK/Stat3 signaling pathway significantly counteracted downregulation of FAM134B-induced radiation resistance and enhanced radiation therapeutic efficacy in HCC. Conclusions Our findings suggest that FAM134B may be a potential therapeutic biomarker for the treatment of HCC patients with radiotherapy tolerance.

Strawberries are a commonly used agricultural product in the food industry. In the traditional production model, labor costs are high, and extensive picking techniques can result in food safety issues, like poor taste and fruit rot. In response to the existing challenges of low detection accuracy and slow detection speed in the assessment of strawberry fruit maturity in orchards, a CR-YOLOv9 multi-stage method for strawberry fruit maturity detection was introduced. The composite thinning network, CRNet, is utilized for target fusion, employing multi-branch blocks to enhance images by restoring high-frequency details. To address the issue of low computational efficiency in the multi-head self-attention (MHSA) model due to redundant attention heads, the design concept of CGA is introduced. This concept aligns input feature grouping with the number of attention heads, offering the distinct segmentation of complete features for each attention head, thereby reducing computational redundancy. A hybrid operator, ACmix, is proposed to enhance the efficiency of image classification and target detection. Additionally, the Inner-IoU concept, in conjunction with Shape-IoU, is introduced to replace the original loss function, thereby enhancing the accuracy of detecting small targets in complex scenes. The experimental results demonstrate that CR-YOLOv9 achieves a precision rate of 97.52%, a recall rate of 95.34%, and an mAP@50 of 97.95%. These values are notably higher than those of YOLOv9 by 4.2%, 5.07%, and 3.34%. Furthermore, the detection speed of CR-YOLOv9 is 84, making it suitable for the real-time detection of strawberry ripeness in orchards. The results demonstrate that the CR-YOLOv9 algorithm discussed in this study exhibits high detection accuracy and rapid detection speed. This enables more efficient and automated strawberry picking, meeting the public’s requirements for food safety.

Background: Chemotherapy resistance is an obstacle to promoting the survival of patients with hepatocellular carcinoma (HCC). Thus, finding promising therapeutic targets to enhance HCC chemotherapy is necessary. Methods: Signal sequence receptor subunit (SSR2) expression analysis was performed using quantitative real time polymerase chain reaction (qPCR) and Western blotting assays. Colony formation, apoptosis, anchorage-independent growth assay, and in vivo animal models were used to investigate the effect of SSR2 expression on the resistance of HCC cells to Cisplatin (DDP). Western blotting and luciferase reporter gene techniques were used to explore the molecular mechanism of SSR2 on the resistance of HCC cells to DDP. Results: We found that the SSR2 is upregulated in HCC and associated with poor survival. Further analysis showed that the downregulation of SSR2 increased the sensitivity of HCC to DDP. Mechanically, SSR2 inhibited the Yes-associated protein (YAP) phosphorylation and promoted the transcription of Hippo signaling downstream genes. Finally, the Hippo pathway inhibitor can suppress colony formation and tumorigenesis arising from SSR2 upregulation. Conclusions: Our study shows that SSR2 is important in HCC progression via the Hippo pathway. Thus, targeting the SSR2/Hippo axis might be a potential strategy for overcoming HCC resistance to DDP.

Crop diseases pose a major threat to agricultural production, quality, and sustainable development, highlighting the importance of early disease risk prediction for effective disease control. Tea anthracnose can easily occur in Yunnan under high-temperature and high-humidity environments, which seriously affects the ecosystem of tea gardens. Therefore, the establishment of accurate, non-destructive, and rapid prediction models has a positive impact on the conservation of biodiversity in tea plantations. Because of the linear relationship between disease occurrence and environmental conditions, the growing environmental conditions can be effectively used to predict crop diseases. Based on the climate data collected by Internet of Things devices, this study uses LASSO-COX-NOMOGRAM to analyze the expression of tea anthracrum to different degrees through Limma difference analysis, and it combines Cox single-factor analysis to study the influence mechanism of climate and environmental change on tea anthracrum. Modeling factors were screened by LASSO regression, 10-fold cross-validation and Cox multi-factor analysis were used to establish the basis of the model, the nomogram prediction model was constructed, and a Shiny- and DynNOM-visualized prediction system was built. The experimental results showed that the AUC values of the model were 0.745 and 0.731 in the training set and 0.75 and 0.747 in the verification set, respectively, when the predicted change in tea anthracnose disease risk was greater than 30% and 60%, and the calibration curve was in good agreement with the ideal curve. The accuracy of external verification was 83.3% for predicting tea anthracnose of different degrees. At the same time, compared with the traditional prediction method, the method is not affected by the difference in leaf background, which provides research potential for early prevention and phenotypic analysis, and also provides an effective means for tea disease identification and harm analysis.

Spermatogonial stem cells (SSCs) are essential for continuous spermatogenesis and male fertility. The underlying mechanisms of alternative splicing (AS) in mouse SSCs are still largely unclear. We demonstrated that SRSF1 is essential for gene expression and splicing in mouse SSCs. Crosslinking immunoprecipitation and sequencing data revealed that spermatogonia-related genes (e.g. Plzf, Id4, Setdb1, Stra8, Tial1/Tiar, Bcas2, Ddx5, Srsf10, Uhrf1, and Bud31) were bound by SRSF1 in the mouse testes. Specific deletion of Srsf1 in mouse germ cells impairs homing of precursor SSCs leading to male infertility. Whole-mount staining data showed the absence of germ cells in the testes of adult conditional knockout (cKO) mice, which indicates Sertoli cell-only syndrome in cKO mice. The expression of spermatogonia-related genes (e.g. Gfra1, Pou5f1, Plzf, Dnd1, Stra8, and Taf4b) was significantly reduced in the testes of cKO mice. Moreover, multiomics analysis suggests that SRSF1 may affect survival of spermatogonia by directly binding and regulating Tial1/Tiar expression through AS. In addition, immunoprecipitation mass spectrometry and co-immunoprecipitation data showed that SRSF1 interacts with RNA splicing-related proteins (e.g. SART1, RBM15, and SRSF10). Collectively, our data reveal the critical role of SRSF1 in spermatogonia survival, which may provide a framework to elucidate the molecular mechanisms of the posttranscriptional network underlying homing of precursor SSCs.

Background Cyclophosphamide (CTX) and calcineurin inhibitors (CNIs) based regimens are recommended as immunosuppressive therapies for patients with idiopathic membranous nephropathy (IMN). Focal and segmental glomerular sclerosis (FSGS) lesions, which are common in membranous nephropathy (MN), are poor predictors of outcome. This study compared the differences of prognosis between two regimens in patients with IMN combined with FSGS lesions.Methods This retrospective study enrolled 108 patients with biopsy-proven IMN, accompanied with FSGS lesions, nephrotic syndrome and an estimated glomerular filtration rate (eGFR)≥60 mL/min/1.73 m2 who were treated with CTX or CNIs. We used propensity score matching (PSM) for balancing the confounding variables.Results During follow-up, 10 patients (10/55 [18.2%]; nine males) in the CNIs group showed a 50% decline in eGFR; eight had a not otherwise specified variant. Patients initially treated with CNIs had a significantly higher risk of progression to the primary outcome and a lower probability of complete or total remission. The relapse rate was higher in patients who initially received CNIs- than in those who received CTX-based treatment. Before PSM, age and 24-h urine protein level differed significantly between the groups. The PSM model included data from 72 patients. Worse outcomes were also noted among patients who initially received CNIs than those who received CTX-based treatments after matching.Conclusions Patients with MN combined with FSGS lesions have a higher risk of renal functional decline and a higher rate of relapse after CNIs than after CTX therapy.

Abstract Triple-negative breast cancers (TNBC) frequently harbor defects in DNA double-strand break repair through homologous recombination (HR), such as BRCA1 dysfunction. However, less than 15% of TNBC patients were found to carry BRCA1 mutation, indicating that there are other mechanisms regulating BRCA1-deficient in TNBC. In the current study, we shown that overexpression of TRIM47 correlates with progression and poor prognosis in triple-negative breast cancer. Moreover, we demonstrated that TRIM47 directly interacts with BRCA1 and induces ubiquitin-ligase-mediated proteasome turnover of BRCA1, subsequently leads to a decrease of BRCA1 protein levels in TNBC. Moreover, the downstream gene expression of BRCA1, such as p53, p27, p21 was significantly reduced in the overexpression of TRIM47 cell lines but increased in TRIM47-deleted cells. Functionally, we found that overexpression of TRIM47 in TNBC cells confers an exquisite sensitivity to olaparib, an inhibitor of poly-(ADP-ribose)-polymerase (PARP), but TRIM47 inhibition significantly confers TNBC cells resistance to olaparib both in vitro and in vivo. Furthermore, we showed that overexpression of BRCA1 significant increase the olaparib resistance in TRIM47-overexpression-induced PARP inhibitions sensitivity. Taken together, our results uncover a novel mechanism for BRCA1-deficient in TNBC and targeting TRIM47/BRCA1 axis may be a promising prognostic factor and a valuable therapeutic target for TNBC.

Abstract Neovascularization is a prominent cause of irreversible blindness in a variety of ocular diseases. Current therapies for pathological neovascularization are concentrated on the suppression of vascular endothelial growth factors (VEGF). Despite the remarkable efficacy of anti-VEGF drugs, several problems still exist, including ocular complications and drug resistance. Thus, it is still required to design novel drugs for anti-angiogenic treatment. This study aimed to investigate the anti-angiogenic effects of a small molecule multi-target tyrosine kinase inhibitor, DCZ19931, on ocular neovascularization. The results showed that administration of DCZ19931 at the tested concentrations did not cause obvious cytotoxicity and tissue toxicity. DCZ19931 could reduce the size of choroidal neovascularization (CNV) lesions in laser-induced CNV model and suppress ocular neovascularization in oxygen-induced retinopathy (OIR) model. DCZ19931 could suppress VEGF-induced proliferation, migration, and tube formation ability of endothelial cells, exhibiting similar anti-angiogenic effects as Ranibizumab. DCZ19931 could reduce the levels of intercellular cell adhesion molecule-1 (ICAM-1) expression in vivo and in vitro. Network pharmacology prediction and western blots revealed that DCZ19931 exerted its anti-angiogenic effects through the inactivation of ERK1/2-MAPK signaling and p38-MAPK signaling. In conclusion, this study indicates that DCZ19931 is a promising drug for anti-angiogenic therapy for ocular diseases.

Summary: RNA-binding proteins (RBPs) can bind and mediate RNA-RNA contacts. However, identifying specific RBP-organized RNA-RNA contacts remains challenging. Here, we present a capture RIC-seq (CRIC-seq) technique to map specific RBP-associated RNA-RNA contacts globally. We describe steps for formaldehyde cross-linking to fix RNA in situ conformation, pCp-biotin labeling to mark RNA juncture, and in situ proximity ligation to join proximal RNAs. We then detail immunoprecipitation to isolate specific RBP-associated RNA-RNA contacts, biotin-streptavidin selection to enrich chimeric RNAs, and library construction for paired-end sequencing.For complete information on the generation and use of this protocol, please refer to Ye et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

In order to efficiently identify early tea diseases, an improved YOLOv8 lesion detection method is proposed to address the challenges posed by the complex background of tea diseases, difficulty in detecting small lesions, and low recognition rate of similar phenotypic symptoms. This method focuses on detecting tea leaf blight, tea white spot, tea sooty leaf disease, and tea ring spot as the research objects. This paper presents an enhancement to the YOLOv8 network framework by introducing the Receptive Field Concentration-Based Attention Module (RFCBAM) into the backbone network to replace C2f, thereby improving feature extraction capabilities. Additionally, a mixed pooling module (Mixed Pooling SPPF, MixSPPF) is proposed to enhance information blending between features at different levels. In the neck network, the RepGFPN module replaces the C2f module to further enhance feature extraction. The Dynamic Head module is embedded in the detection head part, applying multiple attention mechanisms to improve multi-scale spatial location and multi-task perception capabilities. The inner-IoU loss function is used to replace the original CIoU, improving learning ability for small lesion samples. Furthermore, the AKConv block replaces the traditional convolution Conv block to allow for the arbitrary sampling of targets of various sizes, reducing model parameters and enhancing disease detection. the experimental results using a self-built dataset demonstrate that the enhanced YOLOv8-RMDA exhibits superior detection capabilities in detecting small target disease areas, achieving an average accuracy of 93.04% in identifying early tea lesions. When compared to Faster R-CNN, MobileNetV2, and SSD, the average precision rates of YOLOv5, YOLOv7, and YOLOv8 have shown improvements of 20.41%, 17.92%, 12.18%, 12.18%, 10.85%, 7.32%, and 5.97%, respectively. Additionally, the recall rate (R) has increased by 15.25% compared to the lowest-performing Faster R-CNN model and by 8.15% compared to the top-performing YOLOv8 model. With an FPS of 132, YOLOv8-RMDA meets the requirements for real-time detection, enabling the swift and accurate identification of early tea diseases. This advancement presents a valuable approach for enhancing the ecological tea industry in Yunnan, ensuring its healthy development.

Pest target identification in agricultural production environments is challenging due to the dense distribution, small size, and high density of pests. Additionally, changeable environmental lighting and complex backgrounds further complicate the detection process. This study focuses on enhancing the recognition performance of tea pests by introducing a lightweight pest image recognition model based on the improved YOLOv8 architecture. First, slicing-aided fine-tuning and slicing-aided hyper inference (SAHI) are proposed to partition input images for enhanced model performance on low-resolution images and small-target detection. Then, based on an ELAN, a generalized efficient layer aggregation network (GELAN) is designed to replace the C2f module in the backbone network, enhance its feature extraction ability, and construct a lightweight model. Additionally, the MS structure is integrated into the neck network of YOLOv8 for feature fusion, enhancing the extraction of fine-grained and coarse-grained semantic information. Furthermore, the BiFormer attention mechanism, based on the Transformer architecture, is introduced to amplify target characteristics of tea pests. Finally, the inner-MPDIoU, based on auxiliary borders, is utilized as a replacement for the original loss function to enhance its learning capacity for complex pest samples. Our experimental results demonstrate that the enhanced YOLOv8 model achieves a precision of 96.32% and a recall of 97.95%, surpassing those of the original YOLOv8 model. Moreover, it attains an mAP@50 score of 98.17%. Compared to Faster R-CNN, SSD, YOLOv5, YOLOv7, and YOLOv8, its average accuracy is 17.04, 11.23, 5.78, 3.75, and 2.71 percentage points higher, respectively. The overall performance of YOLOv8 outperforms that of current mainstream detection models, with a detection speed of 95 FPS. This model effectively balances lightweight design with high accuracy and speed in detecting small targets such as tea pests. It can serve as a valuable reference for the identification and classification of various insect pests in tea gardens within complex production environments, effectively addressing practical application needs and offering guidance for the future monitoring and scientific control of tea insect pests.

In response to the challenge of low recognition rates for similar phenotypic symptoms of tea diseases in low-light environments and the difficulty in detecting small lesions, a novel adaptive method for tea disease severity detection is proposed. This method integrates an image enhancement algorithm based on an improved EnlightenGAN network and an enhanced version of YOLO v8. The approach involves first enhancing the EnlightenGAN network through non-paired training on low-light-intensity images of various tea diseases, guiding the generation of high-quality disease images. This step aims to expand the dataset and improve lesion characteristics and texture details in low-light conditions. Subsequently, the YOLO v8 network incorporates ResNet50 as its backbone, integrating channel and spatial attention modules to extract key features from disease feature maps effectively. The introduction of adaptive spatial feature fusion in the Neck part of the YOLOv8 module further enhances detection accuracy, particularly for small disease targets in complex backgrounds. Additionally, the model architecture is optimized by replacing traditional Conv blocks with ODConv blocks and introducing a new ODC2f block to reduce parameters, improve performance, and switch the loss function from CIOU to EIOU for a faster and more accurate recognition of small targets. Experimental results demonstrate that YOLOv8-ASFF achieves a tea disease detection accuracy of 87.47% and a mean average precision (mAP) of 95.26%. These results show a 2.47 percentage point improvement over YOLOv8, and a significant lead of 9.11, 9.55, and 7.08 percentage points over CornerNet, SSD, YOLOv5, and other models, respectively. The ability to swiftly and accurately detect tea diseases can offer robust theoretical support for assessing tea disease severity and managing tea growth. Moreover, its compatibility with edge computing devices and practical application in agriculture further enhance its value.

Abstract Background The global burden of hepatocellular carcinoma (HCC) is increasing, negatively impacting social health and economies. The discovery of novel and valuable biomarkers for the early diagnosis and therapeutic guidance of HCC is urgently needed. Methods Extracellular matrix (ECM)-related gene sets, transcriptome data and mutation profiles were downloaded from the Matrisome Project and The Cancer Genome Atlas (TCGA)-LIHC datasets. Coexpression analysis was initially performed with the aim of identifying ECM-related lncRNAs (r > 0.4, p

Abstract Objective To investigate the changes in memory T cells and the related factors in mice by the establishment of a BALB/c mouse model of Echinococcus granulosus‐induced sensitization. Methods A sensitized BALB/c mouse model was established by intraperitoneal injection of E. granulosus. A control group (CTRL), a nonsensitized group infected with E. granulosus (CE), and a sensitized group infected with E. granulosus (ANPC) were set up. The pathological changes in lung tissue in mice, the change in memory T cells (CD4 Tm), and the change in peripheral blood nucleated interleukin‐23 (IL‐23) were detected using HE staining, flow cytometry, and liquid‐phase multiple protein quantification techniques, respectively. Results The individual percentage of mouse memory T cells was 9.14 ± 0.45, 25.23 ± 0.17, and 13.29 ± 0.32 in the CTRL, CE, and ANPC groups, respectively. The percentage of memory T cells in the ANPC group was higher than that in the CTRL group (t = 18.410, p

Abstract Objective To determine the pathogenesis and molecular targets of anaphylaxis caused by hydatid cyst fluid leakage. Methods First, Balb/c mice were infected with Echinococcus granulosus, and then the anaphylaxis model was developed. The mice were separated into: anaphylaxis caused by the cystic echinococcosis group (ANPC), the cystic echinococcosis without anaphylaxis group (CE group), and the normal control group (CTRL). Following this, the spleen tissue was collected for microRNA (miRNA) sequencing. Using bioinformatics analysis, differentially expressed miRNAs (DEMs) were identified. Then, through the use of protein–protein interaction (PPI) networks, the key target genes for miRNA regulation associated with echinococcosis‐induced anaphylaxis were identified. Results ANPC and CE groups have 29 and 39 DEMs compared to the CTRL group, respectively. Based on these 25 DEMs, interactions between miRNA and mRNA were screened, and 174 potential target genes were identified. We performed gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis on these 174 target genes, and the results revealed that the three pathways with the highest enrichment were the PI3K‐Akt signaling pathway, FoxO signaling pathway, and Focal adhesion. The interaction analysis of PPI and miRNA‐hub gene networks revealed that interleukin 6 (IL‐6) was regulated by miR‐146a‐5p and miR‐149‐5p, while IL‐10 was regulated by miR‐29b‐3p and miR‐29c‐3. Using reverse transcription polymerase chain reaction, we found that the miRNAs regulating IL‐6 and IL‐10 were significantly upregulated in the ANPC group, and there are three pathways involved in that process: Pathways of PI3K‐Akt signaling, FoxO signaling, and Focal adhesion. IL‐6 and IL‐10 play an important role in cellular pyroptosis and apoptosis. Therefore, the aforementioned results provide significant reference value for elucidating the mechanism of cellular pyroptosis and apoptosis in echinococcosis‐induced anaphylaxis, and for formulating tissue and organ protection strategies for patients with cystic echinococcosis when anaphylaxis is triggered by hydatid cyst rupture.

ObjectiveRegular check-up with ultrasound in underserved rural and/or remote areas is hampered due to the limited availability of sonologists and ultrasound devices. This study aimed to assess the feasibility and satisfaction of health check-ups with a 5G-based robotic teleultrasound diagnostic system.MethodsIn this prospective study, sonologists from two hospitals manipulated the telerobotic ultrasound system to perform teleultrasound check-ups of the liver, gallbladder, pancreas, spleen, kidneys, bladder, prostate (male), uterus and ovaries (female) for the subjects. The feasibility and satisfaction of health check-ups with a 5G-based robotic teleultrasound diagnostic system were evaluated in terms of examination results, examination duration, and satisfaction questionnaire survey.ResultsA total of 546 subjects were included with the most frequently diagnosed being abdominal disorders (n = 343) and male reproductive illnesses (n = 97), of which fatty liver (n = 204) and prostatic calcification (n = 54) were the most. The median teleultrasound examination duration (interquartile range) for men and women was 9 (9–11) min and 9 (7–11) min (p = 0.236), respectively. All the subjects were satisfied with this new type of telerobotic ultrasound check-ups and 96% reported no fear of the robotic arm during the examination.ConclusionThe 5G-based teleultrasound robotic diagnostic system in health check-ups is feasible and satisfactory, indicating that this teleultrasound robot system may have significant application value in underserved rural and/or remote areas to mitigate disparity in achieving health equity.

Candida albicans (C. albicans) is a ubiquitous clinical fungal pathogen. In recent years, combination therapy, a potential treatment method to overcome C. albicans resistance, has gained traction. In this study, we synthesized a series of cyclometalated iridium(III) complexes with the formula [Ir(C-N)2(tpphz)](PF6) (C-N = 2-phenylpyridine (ppy, in Ir1), 2-(2-thienyl)pyridine (thpy, in Ir2), 2-(2,4-difluorophenyl) pyridine (dfppy, in Ir3), tpphz = tetrapyrido[3,2-a:2',3'-c:3'',2''-h:2''',3'''-j]phenazine) and polypyridyl ruthenium(II) complexes with the formula [Ru(N-N)2(tpphz)](PF6)2 (N-N = 2,2'-bipyridine (bpy, in Ru1), 1,10-phenanthroline (phen, in Ru2), 4,7-diphenyl-1,10-phenanthroline (DIP, in Ru3)), and investigated their antifungal activities against drug-resistant C. albicans and their combination with fluconazole (FLC). Of which, the combination of the lead iridium(III) complex Ir2 and FLC showed strong antifungal activity against drug-resistant C. albicans. Mechanism studies have shown that they can inhibit the formation of hyphae and biofilm, damage mitochondrial function and accumulate intracellular ROS. Therefore, iridium(III) complexes combined with FLC can be used as a promising treatment to exert anti-drug-resistant C. albicans activity, in order to improve the treatment efficiency of fungal infection.