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Abstract Shuozhou is a typical coal mining city, and the Pingshuo Antaibao open-pit coal mine in its area is one of the largest open-pit coal mines in China. The mining of coal resources is an important part of ensuring national energy security, and at the same time, it inevitably has a certain impact on the ecology, such as coal dust generated by open-pit mining will affect air quality, soil, water and vegetation. It is of great significance to explore the temporal and spatial variation of ecological environment quality in coal mining cities for ecological protection and sustainable social and economic development. Based on the Google Earth Engine (GEE) platform, this paper combines the index-based coal dust index (ICDI) and Remote Sensing Ecological Index (RSEI) models to construct an improved RSEI (IRSEI) that can reflect coal mining cities. This paper explores the spatial–temporal evolution characteristics and spatial correlation of ecological environment quality in Shuozhou from 2000 to 2020. The results showed that the average value of IRSEI in Shuozhou was between 0.262 and 0.418, and the overall change showed an upward trend. The growth areas of ecological environment quality are mainly located in the eastern and southwestern areas with good vegetation growth, and these regions have vigorously implemented the Northern Shelter Forest Project, afforestation and greening projects, implemented the forest resource management and protection responsibility system, promoted the construction of ecological civilization, and significantly improved the ecological environment. While the declining areas are mainly located in the central and southern regions where mining activities and human activities are more intensive. The IRSEI in the study area showed a significant spatial positive correlation, and the agglomeration types of the spatial pattern were mainly high-high and low-low agglomeration types, with the high-high agglomeration types mainly distributed in the eastern and southwestern regions, and the low-low agglomeration types distributed in the northern and south-central regions of the study area. The trend of low and low agglomeration has decreased, which further proves that the ecological restoration measures taken by the government, such as returning farmland to forests, integrating protection and restoration of mountains, waters, forests, fields, lakes, grasslands, and sands, controlling soil erosion, and stage wise reclamation of coal mining subsidence areas, have improved the ecological environment quality of Shuozhou. This study provides a reference for understanding the spatiotemporal changes of the ecological environment of coal mining cities, and is conducive to formulating appropriate ecological protection strategies.

Abstract The human microbiome plays a key role in drug development and precision medicine, but understanding its complex interactions with drugs remains a challenge. Identifying microbe-drug associations not only enhances our understanding of their mechanisms but also aids in drug discovery and repurposing. Traditional experiments are expensive and time-consuming, making computational methods for predicting microbe-drug associations a new trend. Currently, computational methods specifically designed for this task are still scarce. Therefore, to address the shortcomings of traditional experimental methods in predicting potential microbe-drug associations, this paper proposes a new prediction model named GCNATMDA. The model combines two deep learning models, Graph Convolutional Network and Graph Attention Network, and aims to reveal potential relationships between microbes and drugs by learning related features. Thus improve the efficiency and accuracy of prediction. We first integrated the microbe-drug association matrix from the existing dataset, and then combined the calculated microbe-drug characteristic matrix as the model input. The GCN module is used to dig deeper into the potential characterization of microbes and drugs, while the GAT module further learns the more complex interactions between them and generates the corresponding score matrix. The experimental results show that the GCNATMDA model achieves 96.59% and 93.01% in AUC and AUPR evaluation indexes, respectively, which is significantly better than the existing prediction models. In addition, the reliability of the prediction results is verified by a series of experiments.

BackgroundIntegrating technology with rural development is essential for addressing the unique challenges faced by aging populations in rural areas. China’s national rural revitalization strategy emphasizes the importance of developing characteristic towns that focus on health and wellness demands, particularly for the older adults. However, there is a gap in the literature regarding the systematic use of technology to support the health and daily living needs of this demographic.ObjectiveThis study aims to bridge this gap by proposing a wireless sensor network (WSN)-based system that integrates health monitoring and smart home assistance, specifically tailored for older adults residents in sports and wellness towns.MethodsThe system’s design involves collecting and analyzing historical activity data and basic physiological parameters from older adults residents’ homes. The data are cleaned, combined and stored to prepare it for behavior analysis, which is vital for controlling smart home equipment. Preliminary health assessments are conducted using the collected physiological data. A hybrid network leveraging Sub-G and Wi-Fi technologies is optimized for the purposes of collecting and uploading data, based on a comparative analysis of wireless communication options.SignificanceThis study significantly contributes to the advancement of sports and wellness towns by promoting healthy aging through cutting-edge technological solutions.

BackgroundMalnutrition often occurs in patients with colorectal cancer. This study aims to develop a predictive model based on GLIM criteria for patients with colorectal cancer who underwent radical surgery.MethodsFrom December 2015 to May 2021, patients with colorectal cancer who underwent radical surgery at our center were recruited for this study. We prospectively collected data on GLIM-defined malnutrition and other clinicopathological characteristics. Using Cox regeneration, we developed a novel nomogram for prognostic prediction, which was validated and compared to traditional nutritional factors for predictive accuracy.ResultsAmong the 983 patients enrolled in this study, malnutrition was identified in 233 (23.70%) patients. Multivariate analysis indicated that GLIM-defined malnutrition is the independent risk factor for overall survival (HR = 1.793, 95% CI = 1.390–2.313 for moderate malnutrition and HR = 3.485, 95% CI = 2.087–5.818 for severe malnutrition). The novel nomogram based on the GLIM criteria demonstrated a better performance than existing criteria, with AUC of 0.729, 0.703, and 0.683 for 1-year, 3-year, and 5-year OS, respectively, in the validation cohort. In addition, the risk score determined by this system exhibited significantly poorer short-term and long-term clinical outcomes in high-risk groups in both malnourished and well-nourished patients.ConclusionCombining handgrip strength, serum albumin level, and TNM stage would help improve the predictive effect of GLIM criteria for colorectal cancer patients post-radical surgery and benefit the individual prognostic prediction of colorectal cancer.

The industrialization of resource-based cities exerts a profound influence on their land system. The land use functions (LUFS), are concealed representation of this land system, can highlight issues in human-land relations. To address these challenges, we have developed a bottom-up approach for constructing an LFUS evaluation system tailored to resource-based cities. This system assesses the evolution of the LUFS, its trade-offs, and synergies on a grid scale, with applications in the resource-depleted city of Xintai. The research findings indicate the following:(1) From 1985 to 2021, the LFUS, including production function (PF) and living functions (LF), showed a generally increasing trend. Ecological function (EF), however, fluctuated, initially decreasing, then increasing, and subsequently decreasing again. (2) During this period, the trade-off relationship between PF and LF strengthened from 1985 to 1996, weakened in 2011, and PF-EF showed a weak trade-off in 1985, transitioned to a synergy from 1996 to 2011, and reverted to a trade-off in 2021. (3) The relationships among LUFS elements showed mechanisms for the formation of trade-off and synergy relationships among LUFS. Conflicts between cultivated land and construction land primarily contributed to the trade-off between PF and LF. Meanwhile, conflicts between cultivated land and ecological land led to the trade-off between PF and EF, and conflicts between construction land and ecological land contributed to the trade-off between LF and EF. This study presents a bottom-up approach for constructing a LUFS evaluation indicator system for resource-based cities. This research provides valuable insights for land use decision-making, addressing the sustainability needs of transitioning resource-based cities.

BackgroundIn recent years, the incidence of abdominal obesity among the middle-aged and older adult population in China has significantly increased. However, the gender disparities in the spatial distribution of abdominal obesity incidence and its relationship with meteorological factors among this demographic in China remain unclear. This gap in knowledge highlights the need for further research to understand these dynamics and inform targeted public health strategies.MethodsThis study utilized data from the 2015 China Health and Retirement Longitudinal Study (CHARLS) to analyze the incidence of abdominal obesity among the middle-aged and older adult population in China. Additionally, meteorological data were collected from the National Meteorological Information Center. Using Moran’s I index and Getis-Ord Gi* statistical methods, the spatial distribution characteristics of abdominal obesity incidence were examined. The influence of various meteorological factors on the incidence of abdominal obesity in middle-aged and older adult males and females was investigated using the q statistic from the Geodetector method. Furthermore, Multi-Scale Geographically Weighted Regression (MGWR) analysis was employed to explore the impact of meteorological factors on the spatial heterogeneity of abdominal obesity incidence from a gender perspective.ResultsThe spatial distribution of abdominal obesity among middle-aged and older adult individuals in China exhibits a decreasing trend from northwest to southeast, with notable spatial autocorrelation. Hotspots are concentrated in North and Northeast China, while cold spots are observed in Southwest China. Gender differences have minimal impact on spatial clustering characteristics. Meteorological factors, including temperature, sunlight, precipitation, wind speed, humidity, and atmospheric pressure, influence incidence rates. Notably, temperature and sunlight exert a greater impact on females, while wind speed has a reduced effect. Interactions among various meteorological factors generally demonstrate bivariate enhancement without significant gender disparities. However, gender disparities are evident in the influence of specific meteorological variables such as annual maximum, average, and minimum temperatures, as well as sunlight duration and precipitation, on the spatial heterogeneity of abdominal obesity incidence.ConclusionMeteorological factors show a significant association with abdominal obesity prevalence in middle-aged and older adults, with temperature factors playing a prominent role. However, this relationship is influenced by gender differences and spatial heterogeneity. These findings suggest that effective public health policies should be not only gender-sensitive but also locally adapted.

This study aims to enhance the precision of analyzing athlete behavior characteristics, thereby optimizing sports training and competitive strategies. This study introduces an innovative Ant Colony Optimization (ACO) clustering model designed to address the high-dimensional clustering issues in athlete behavior data by simulating the path selection mechanism of ants searching for food. The development process of this model includes fine-tuning ACO parameters, optimizing for features specific to sports data, and comparing it with traditional clustering algorithms, and similar research models based on the neural network, support vector machines, and deep learning. The results indicate that the ACO model significantly outperforms the comparison algorithms in terms of silhouette coefficient (0.72) and Davies-Bouldin index (1.05), demonstrating higher clustering effectiveness and model stability. Particularly noteworthy is the recall rate (0.82), a key performance indicator, where the ACO model accurately captures different behavioral characteristics of athletes, validating its effectiveness and reliability in athlete behavior analysis. The innovation lies not only in the application of the ACO algorithm to address practical issues in the field of sports but also in showcasing the advantages of the ACO algorithm in handling complex, high-dimensional sports data. However, its generality and efficiency on a larger scale or different types of sports data still need further validation. In conclusion, through the introduction and optimization of the ACO clustering model, this study provides a novel and effective approach for a deeper understanding and analysis of athlete behavior characteristics. This study holds significant importance in advancing sports science research and practical applications.

Abstract Purpose Whether the addition of tislelizumab to gemcitabine and cisplatin (GC) chemotherapy increases the incidence of myelosuppression has not been well established. This study identified the risk factors for the development of myelosuppression in patients with urothelial carcinoma (UC) after receiving GC chemotherapy with or without tislelizumab. Materials and Methods We enrolled 192 UC patients who received GC with or without tislelizumab at the Affiliated Hospital of Xuzhou Medical University between July 2014 and November 2022. Patient baseline characteristics were included in the statistical analyses after adjusting for previously reported risk factors affecting survival using propensity score matching (1:1). Binary logistic regression analysis was used to identify the risk factors associated with posttreatment myelosuppression. Results A total of 192 patients were enrolled, of whom 96 were treated with tislelizumab plus gemcitabine and cisplatin (T + GC) and 96 with GC alone. The incidence of leukopenia, anemia, and thrombocytopenia of any grade was 50.0%, 70.8%, and 42.7%, respectively, in the T + GC group and 41.7%, 72.9%, and 20.8%, respectively, in the GC group. In multivariate analysis, patients aged over 70 years (OR = 2.486, 95% CI: 1.067–5.792, p = 0.035) and those who received T + GC (OR = 3.119, 95% CI: 1.576–6.173, p = 0.001) were more likely to develop thrombocytopenia. Patients aged over 70 years (OR = 3.213, 95% CI: 1.254–8.237, p = 0.015) were more likely to develop anemia, and patients with renal insufficiency (OR = 2.105, 95% CI: 1.035–4.280, p = 0.040) were more likely to develop leukopenia. Eventually, 99 (51.6%) patients with UC successfully completed all the treatment cycles. Conclusions This study demonstrates that the addition of tislelizumab to GC chemotherapy led to a considerable increase in the occurrence of thrombocytopenia, whereas no significant changes were observed regarding anemia or leukopenia. It is crucial to fully inform patients at increased risk for myelosuppression of potential risks and closely monitor changes in their blood routines.

Recombination-activating genes (RAGs) play a crucial role in the V(D)J recombination process and the development of immune cells. The development of the immune system and its mechanisms in pigs exhibit greater similarity to those of humans compared to other animals, thus rendering pigs a valuable tool for biomedical research. In this study, we utilized CRISPR/Cas9 gene editing and somatic cell nuclear transfer technology to generate RAG2 knockout (KO) pigs. Furthermore, we evaluated the impact of RAG2 KO on the immune organs and immune cell development through morphological observations, blood analysis and flow cytometry technology. RAG2 KO cell lines were used as donors for cloning. The reconstructed embryos were transplanted into 4 surrogate sows, and after 116 days of gestation, 2 sows gave birth to 12 live piglets, all of which were confirmed to be RAG2 KO. The thymus and spleen sizes of RAG2 KO pigs were significantly smaller than those of wild-type (WT) pigs. Hematoxylin-eosin staining results revealed that the thymus and spleen tissue structures of RAG2 KO pigs were disorganized and lacked the characteristic structures, indicating that RAG2 KO leads to dysplasia of the thymus and spleen. Hematological analysis demonstrated that the total number of white blood cells and lymphocytes in the circulation of RAG2 KO pigs was significantly lower, while the number of eosinophils was higher. Flow cytometry results indicated that the proportions of mature T and B lymphocytes were significantly reduced compared to WT pigs. These findings successfully verified the immunodeficiency phenotype of RAG2 KO pigs. This study may provide experimental animals for the development of tumor models and humanized animals.

Thioredoxin reductase 1 (TrxR1) has emerged as a promising target for cancer therapy. In our previous research, we discovered several new TrxR1 inhibitors and found that they all have excellent anti-tumor activity. At the same time, we found these TrxR1 inhibitors all lead to an increase in AKT phosphorylation in cancer cells, but the detailed role of AKT phosphorylation in TrxR1 inhibitor-mediated cell death remains unclear. In this study, we identified the combination of AKT and TrxR1 inhibitor displayed a strong synergistic effect in colon cancer cells. Furthermore, we demonstrated that the synergistic effect of auranofin (TrxR1 inhibitor) and MK-2206 (AKT inhibitor) was caused by ROS accumulation. Importantly, we found that ATM inhibitor KU-55933 can block the increase of AKT phosphorylation caused by auranofin, and exhibited a synergistic effect with auranofin. Taken together, our study demonstrated that the activation of ATM/AKT pathway is a compensatory mechanism to cope with ROS accumulation induced by TrxR1 inhibitor, and synergistic targeting of TrxR1 and ATM/AKT pathway is a promising strategy for treating colon cancer.

Very preterm (VPT) infants (born at less than 32 weeks gestational age) are at high risk for various adverse neurodevelopmental deficits. Unfortunately, most of these deficits cannot be accurately diagnosed until the age of 2-5 years old. Given the benefits of early interventions, accurate diagnosis and prediction soon after birth are urgently needed for VPT infants. Previous studies have applied deep learning models to learn the brain structural connectome (SC) to predict neurodevelopmental deficits in the preterm population. However, none of these models are specifically designed for graph-structured data, and thus may potentially miss certain topological information conveyed in the brain SC. In this study, we aim to develop deep learning models to learn the SC acquired at term-equivalent age for early prediction of neurodevelopmental deficits at 2 years corrected age in VPT infants. We directly treated the brain SC as a graph, and applied graph convolutional network (GCN) models to capture complex topological information of the SC. In addition, we applied the supervised contrastive learning (SCL) technique to mitigate the effects of the data scarcity problem, and enable robust training of GCN models. We hypothesize that SCL will enhance GCN models for early prediction of neurodevelopmental deficits in VPT infants using the SC. We used a regional prospective cohort of ∼280 VPT infants who underwent MRI examinations at term-equivalent age from the Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS). These VPT infants completed neurodevelopmental assessment at 2 years corrected age to evaluate cognition, language, and motor skills. Using the SCL technique, the GCN model achieved mean areas under the receiver operating characteristic curve (AUCs) in the range of 0.72∼0.75 for predicting three neurodevelopmental deficits, outperforming several competing models. Our results support our hypothesis that the SCL technique is able to enhance the GCN model in our prediction tasks.

Abstract Colon cancer is a major cause of cancer-related death. Despite recent improvements in the treatment of colon cancer, new strategies to improve the overall survival of patients are urgently needed. Heat shock protein 90 (HSP90) is widely recognized as a promising target for treating various cancers, including colon cancer. However, no HSP90 inhibitor has been approved for clinical use due to limited efficacy. In this study, we evaluated the antitumor activities of HSP90 inhibitors in combination with piperlongumine in colon cancer cells. We show that combination treatment with HSP90 inhibitors and piperlongumine displayed strong synergistic interaction in colon cancer cells. These agents synergize by promoting ER stress, JNK activation, and DNA damage. This process is fueled by oxidative stress, which is caused by the accumulation of reactive oxygen species. These studies nominated piperlongumine as a promising agent for HSP90 inhibitor-based combination therapy against colon cancer.

BackgroundNon-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease globally, with the potential to progress to non-alcoholic steatohepatitis (NASH), cirrhosis, and even hepatocellular carcinoma. Given the absence of effective treatments to halt its progression, novel molecular approaches to the NAFLD diagnosis and treatment are of paramount importance.MethodsFirstly, we downloaded oxidative stress-related genes from the GeneCards database and retrieved NAFLD-related datasets from the GEO database. Using the Limma R package and WGCNA, we identified differentially expressed genes closely associated with NAFLD. In our study, we identified 31 intersection genes by analyzing the intersection among oxidative stress-related genes, NAFLD-related genes, and genes closely associated with NAFLD as identified through Weighted Gene Co-expression Network Analysis (WGCNA). In a study of 31 intersection genes between NAFLD and Oxidative Stress (OS), we identified three hub genes using three machine learning algorithms: Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine - Recursive Feature Elimination (SVM-RFE), and RandomForest. Subsequently, a nomogram was utilized to predict the incidence of NAFLD. The CIBERSORT algorithm was employed for immune infiltration analysis, single sample Gene Set Enrichment Analysis (ssGSEA) for functional enrichment analysis, and Protein-Protein Interaction (PPI) networks to explore the relationships between the three hub genes and other intersecting genes of NAFLD and OS. The distribution of these three hub genes across six cell clusters was determined using single-cell RNA sequencing. Finally, utilizing relevant data from the Attie Lab Diabetes Database, and liver tissues from NASH mouse model, Western Blot (WB) and Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) assays were conducted, this further validated the significant roles of CDKN1B and TFAM in NAFLD.ResultsIn the course of this research, we identified 31 genes with a strong association with oxidative stress in NAFLD. Subsequent machine learning analysis and external validation pinpointed two genes: CDKN1B and TFAM, as demonstrating the closest correlation to oxidative stress in NAFLD.ConclusionThis investigation found two hub genes that hold potential as novel targets for the diagnosis and treatment of NAFLD, thereby offering innovative perspectives for its clinical management.

Due to the demands for both environmental protection and modernization of the goose industry in China, the traditional goose waterside rearing systems have been gradually transitioning to the modern intensive dryland rearing ones, such as the net-floor mixed rearing system (MRS) and cage rearing system (CRS). However, the goose immune responses to different dryland rearing systems remain poorly understood. This study aimed to investigate and compare the age-dependent effects of MRS and CRS on the splenic histomorphological characteristics and immune-related genes expression profiles among three economically important goose breeds, including Sichuan White goose (SW), Gang goose (GE), and Landes goose (LD). Morphological analysis revealed that the splenic weight and organ index of SW were higher under CRS than under MRS (p

As the largest peripheral lymphoid organ in poultry, the spleen plays an essential role in regulating the body’s immune capacity. However, compared with chickens and ducks, information about the age- and breed-related changes in the goose spleen remains scarce. In this study, we systematically analyzed and compared the age-dependent changes in the morphological, histological, and transcriptomic characteristics between Landes goose (LG; Anser anser) and Sichuan White goose (SWG; Anser cygnoides). The results showed a gradual increase in the splenic weights for both LG and SWG until week 10, while their splenic organ indexes reached the peak at week 6. Meanwhile, the splenic histological indexes of both goose breeds continuously increased with age, reaching the highest levels at week 30. The red pulp (RP) area was significantly higher in SWG than in LG at week 0, while the splenic corpuscle (AL) diameter was significantly larger in LG than in SWG at week 30. At the transcriptomic level, a total of 1710 and 1266 differentially expressed genes (DEGs) between week 0 and week 30 were identified in spleens of LG and SWG, respectively. Meanwhile, a total of 911 and 808 DEGs in spleens between LG and SWG were identified at weeks 0 and 30, respectively. Both GO and KEGG enrichment analysis showed that the age-related DEGs of LG or SWG were dominantly enriched in the Cell cycle, TGF−beta signaling, and Wnt signaling pathways, while most of the breed-related DEGs were enriched in the Neuroactive ligand−receptor interaction, Cytokine−cytokine receptor interaction, ECM−receptor interaction, and metabolic pathways. Furthermore, through construction of protein-protein interaction networks using significant DEGs, it was inferred that three hub genes including BUB1, BUB1B, and TTK could play crucial roles in regulating age-dependent goose spleen development while GRIA2, GRIA4, and RYR2 could be crucial for the breed-specific goose spleen development. These data provide novel insights into the splenic developmental differences between Chinese and European domestic geese, and the identified crucial pathways and genes are helpful for a better understanding of the mechanisms regulating goose immune functions.

Autophagy is a common biological phenomenon in eukaryotes that has evolved and reshaped to maintain cellular homeostasis. Under the pressure of starvation, hypoxia, and immune damage, autophagy provides energy and nutrients to cells, which benefits cell survival. In mammals, autophagy is an early embryonic nutrient supply system involved in early embryonic development, implantation, and pregnancy maintenance. Recent studies have found that autophagy imbalance in placental tissue plays a key role in the occurrence and development of pregnancy complications, such as gestational hypertension, gestational obesity, premature birth, miscarriage, and intrauterine growth restriction. This mini-review summarizes the molecular mechanism of autophagy regulation, the autophagy pathways, and related factors involved in placental tissue and comprehensively describes the role of autophagy in pregnancy complications.

Summary: The survival outcomes of patients with chest wall sarcomas (CWS) were evaluated after receiving wide excision and chest wall reconstruction by using three-dimensional printed (3DP) implants. The survival outcomes evaluating the effect of 3DP implants for chest wall reconstruction is lacking. Here, forty-nine patients with CWS underwent radical wide excision and chest wall reconstruction using 3DP implants. The surgical data and long-term survival outcomes were collected and analyzed. With a median follow-up of 36 months, the disease-free survival (DFS) and overall survival (OS) were 31.7% and 58.5%, respectively. In addition, the 3-year DFS and OS can be significantly differentiated using the classification criteria of tumor grade, tumor size tumor area. Hence, wide excision and chest wall reconstruction using three-dimensional printed implants are a safe and effective treatment for chest wall sarcoma. The novel classification criteria of tumor size and area have the potential to predict the prognosis of CWS.

Metabolic reprogramming has been defined as a hallmark of malignancies. Prior studies have focused on the single nucleotide polymorphism (SNP) of POLG2 gene, which is reportedly responsible for encoding mitochondrial DNA genes and is implicated in the material and energy metabolism of tumor cells, whereas its function in prostate cancer has been elusive. Gene expression profile matrix and clinical information were downloaded from TCGA (The Cancer Genome Atlas) data portal, and GSE3325 and GSE8511 were retrieved from GEO (Gene Expression Omnibus) database. We conducted analysis of the relative expression of POLG2, clinical characterization, survival analysis, GO / KEGG and GSEA (Gene Set Enrichment Analysis) enrichment analysis in R and employed STRING portal to acquaint ourselves with the protein-protein interaction (PPI). IHC (Immunohistochemical) profiles of POLG2 protein between normal and cancerous tissues were consulted via HPA (Human protein atlas) database and the immunohistochemical POLG2 were verified between para-cancerous and cancerous tissues in tissue array. At the cellular level, Mitochondrial dysfunction assay, DNA synthesis test, wound healing assay, and invasion assay were implemented to further validate the phenotype of POLG2 knockdown in PCa cell lines. RT-qPCR and western blotting were routinely adopted to verify variations of molecular expression within epithelial mesenchymal transition (EMT). Results showed that POLG2 was over-expressed in most cancer types, and the over-expression of POLG2 was correlated with PCa progression and suggested poor OS (Overall Survival) and PFI (Progress Free Interval). Multivariate analysis showed that POLG2 might be an independent prognostic factor of prostate cancer. We also performed GO/KEGG, GSEA analysis, co-expression genes, and PPI, and observed the metabolism-related gene alterations in PCa. Furthermore, we verified that POLG2 knockdown had an inhibitory effect on mitochondrial function, proliferation, cell motility, and invasion, we affirmed POLG2 could affect the prognosis of advanced prostate cancer via EMT. In summary, our findings indicate that over-expressed POLG2 renders poor prognosis in advanced prostate cancer. This disadvantageous factor can serve as a potential indicator, making it possible to target mitochondrial metabolism to treat advanced prostate cancer.

Canine mammary tumors (CMT) can severely compromise the life quality of the affected dogs through local recurrence, distant metastases and ultimately succumb to death. Recently, more attention has been given to the potential antimetastatic effect of maduramicin (MAD) on breast cancer. However, its poor aqueous solubility and toxicity to normal tissues limit its clinical application. Therefore, to address the drawbacks of MAD and enhance its anticancer and antimetastatic effects, MAD-loaded TPGS polymeric micelles (MAD-TPGS) were prepared by a thin-film hydration technique. The optimized MAD-TPGS exhibited excellent size distribution, stability and improved water solubility. Cellular uptake assays showed that TPGS polymer micelles could enhance drug internalization. Moreover, TPGS synergistically improved the cytotoxicity of MAD by targeting mitochondrial organelles, improving reactive oxygen species levels and reducing the mitochondrial transmembrane potential. More importantly, MAD-TPGS significantly impeded the metastasis of tumor cells. In vivo results further confirmed that, in addition to exhibiting excellent biocompatibility, MAD-TPGS exhibited greater antitumor efficacy than free MAD. Interestingly, MAD-TPGS displayed superior suppression of CMT metastasis via tail vein injection compared to oral administration, indicating its suitability for intravenous delivery. Overall, MAD-TPGS could be applied as a potential antimetastatic cancer agent for CMT.

Background: Selenium (Se) has been reported to have an antagonistic effect on heavy metals in animals. Nevertheless, there is a lack of epidemiological research examining whether Se can mitigate the adverse effects of cadmium (Cd) and lead (Pb) on hand grip strength (HGS) in middle-aged and elderly individuals.Methods: This study used data from the 2011–2014 National Health and Nutrition Examination Survey (NHANES). HGS measurements were conducted by trained examiners with a dynamometer. Concentrations of Se, Cd, and Pb in blood were determined via inductively coupled plasma mass spectrometry. We employed linear regression, restricted cubic splines, and quantile g-computation (qgcomp) to assess individual and combined associations between heavy metals and HGS. The study also explored the potential influence of Se on these associations.Results: In both individual metal and multi-metal models adjusted for confounders, general linear regression showed Se’s positive association with HGS, while Cd and Pb inversely related to it. At varying Se-Cd and Se-Pb concentrations, high Se relative to low Se can attenuate Cd and Pb’s HGS impact. An inverted U-shaped correlation exists between Se and both maximum and combined HGS, with Se’s benefit plateauing beyond approximately 200 μg/L. Stratified analysis by Se quartiles reveals Cd and Pb’s adverse HGS effects diminishing as Se levels increase. Qgcomp regression analysis detected Se alleviating HGS damage from combined Cd and Pb exposure. Subsequent subgroup analyses identified the sensitivity of women, the elderly, and those at risk of diabetes to HGS impairment caused by heavy metals, with moderate Se supplementation beneficial in mitigating this effect. In the population at risk for diabetes, the protective role of Se against heavy metal toxicity-induced HGS reduction is inhibited, suggesting that diabetic individuals should particularly avoid heavy metal-induced handgrip impairment.Conclusion: Blood Cd and Pb levels are negatively correlated with HGS. Se can mitigate this negative impact, but its effectiveness plateaus beyond 200 μg/L. Women, the elderly, and those at risk of diabetes are more vulnerable to HGS damage from heavy metals. While Se supplementation can help, its protective effect is limited in high diabetes risk groups.

BackgroundHypertension has now developed into a major public health problem worldwide. Under the existing antihypertensive drug treatment paradigm, problems such as decreasing drug resistance and increasing drug side effects can occur for elderly patients. Acupuncture, a core technique in the non-pharmacological treatment of Chinese medicine, plays an important role in the treatment of elevated blood pressure.ObjectiveThis study aimed to systematically evaluate the effect of acupuncture alone or in combination with antihypertensive drugs on the efficiency of reducing blood pressure and controlling blood pressure in elderly patients with hypertension.MethodsArticles of randomized controlled trials of acupuncture for hypertension in the elderly published before November 2022 were searched in 7 databases. The methodological quality of the literature was evaluated using the Cochrane Risk of Bias Assessment Tool. The primary outcome was the efficiency rate of blood pressure reduction, and the secondary outcome was the change in blood pressure after treatment.ResultsThis study conducted a systematic review and meta-analysis of 12 randomized controlled trials with a total of 1,466 subjects. Among the primary outcome—efficiency rate, acupuncture-only treatment (RR = 1.11, 95% CI: 1.03–1.20, P

Cyclosporine A (CsA) is a secondary cyclopeptide metabolite produced by Tolypocladium inflatum that is widely used clinically as an immunosuppressant. CsA production and mycelial growth differed when T. inflatum was cultured in different carbon source media. During early fermentation, CsA was preferred to be produced in fructose medium, while the mycelium preferred to accumulate in sucrose medium. On the sixth day, the difference was most pronounced. In this study, high-throughput comparative proteomics methods were applied to analyze differences in protein expression of mycelial samples on day 6, revealing the proteins and mechanisms that positively regulate CsA production related to carbon metabolism. The differences included small molecule acid metabolism, lipid metabolism, organic catabolism, exocrine secretion, CsA substrate Bmt synthesis, and transcriptional regulation processes. The proteins involved in the regulation of mycelial growth related to carbon metabolism were also revealed and were associated with waste reoxidation processes or coenzyme metabolism, small molecule synthesis or metabolism, the stress response, genetic information or epigenetic changes, cell component assembly, cell wall integrity, membrane metabolism, vesicle transport, intramembrane localization, and the regulation of filamentous growth. This study provides a reliable reference for CsA production from high-efficiency fermentation. This study provides key information for obtaining more CsA high-yielding strains through metabolic engineering strategies.

Abstract Objective To investigate the association of the preoperative systemic immune‐inflammation index (SII) with recurrence‐free survival (RFS) after transurethral resection of the bladder tumor (TURBT) of non‐muscle‐invasive bladder cancer (NMIBC) using propensity score matching (PSM) analysis. Methods The clinicopathological characteristics and follow‐up data of NMIBC patients were collected retrospectively from two tertiary medical centers. A 1:1 PSM analysis was carried out using the nearest‐neighbor method (caliper size: 0.02). Cox regression analysis was used to identify the risk factors associated with RFS. Results A total of 416 NMIBC patients were included in this study. Before and after matching, patients with increased SII had worse RFS (p

In surgical training and experimental research, brain tissues immersed in cerebrospinal fluid often exhibit complex deformation and strain rate effects that can compromise their reliability and stability. Therefore, it is essential to develop a high-fidelity human brain tissue simulant material that serves as a physical surrogate model to understand its mechanical behavior, such as traumatic brain injury (TBI). However, the existing simulant materials have failed to meet the required mechanical properties. This study presents a composite hydrogel consisting of both a rigid polysaccharides network (Sodium alginate and Pectin) and a flexible polyacrylamide network, exhibiting brain tissue-like mechanical properties under various solution environments and strain rates. The results show that nonlinear mechanical behavior and good similarity under various external environments (artificial cerebrospinal fluid, normal saline, deionized water, and air environments) and different strain rates (0.001 s−1,900 s−1,1700 s−1). By analyzing the experimental data and theoretical analysis, we examine the effects of complex environments on the mechanical behavior of composite hydrogel and porcine brain tissue. Given that the properties of human brain tissue resemble those of porcine brain tissue, our work has significant reference value in realizing surgical training and advancing related research in biomedical engineering.

Urban form (UF) is an important factor influencing carbon emissions (CE), and it is necessary to fully understand the complex relationship between different UF and CE. The study estimates CE using a grid as a unit and depicts the spatiotemporal pattern of CE in Beijing from 2000 to 2020. Then, based on the demand for sustainable urban development, UF is defined as explicit urban form (EUF) and implicit urban form (IUF), and the effects of different UF on CE are explored using stepwise panel regression models. The results show that (1) from 2000 to 2020, CE in Beijing showed a decreasing trend, with an average annual decrease of 57.09 × 104 t and a decrease rate of 38.58 %. Spatially, the CE gradually decreases from the east-south direction to the surrounding area, and the overall performance shows that the high CE area shrinks and the low CE area expands. (2) The influence of EUF on CE is robust, and the influence of IUF on CE is relatively large but vulnerable to other factors. (3) In EUF, urban patchy connectivity, and agglomeration have a suppressive effect on CE, while urban complexity and expansion have a positive effect on CE, reflecting that regular and compact cities are the direction of low-carbon city construction. (4) In IUF, population density (PD), economic agglomeration (EA), land use diversity (SHEI), and road density (RD) can effectively reduce CE, while industrial structure (IS) greatly contributes to the growth of CE, indicating that IUF significantly affects CE by influencing the daily energy consumption and utilization efficiency, thus has a greater potential for CE. The study reveals the influence of EUF and IUF on CE and provides a scientific basis for policy formulation in urban spatial optimization and low-carbon city construction.

Biomass, widespread and carbon-neutral energy, can provide electric energy and replace fossil fuel-derived production. Pyrolysis is the main way of converting biomass to different bioenergy products with the consumption of material and energy, which will cause environmental impacts. To confirm the actual environmental impact of biomass conversion, life cycle assessment (LCA) is used for analyzing the process. Due to choosing different LCA methods, the results for the same thing in different reports will show obvious fluctuation. This review is devoted to providing recommendations on how to handle methodological issues when analyzing LCA study, by which researchers can better realize the similarities and differences in biomass conversion system. In this review, multiple clarifications and methodological recommendations on the four steps of the LCA process (including goal and scope definition, life cycle inventory, life cycle impact assessment, and interpretation) are provided. Furthermore, the LCA results are discussed systematically, in which the global warming potential gets extra attention. Meanwhile, different biomass feedstocks are divided into agricultural residues, forest residues, and microalgae carefully. Finally, the current challenges and future framework of biomass conversion are expounded in detail from the perspective of LCA.

Abstract Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4–20 ng/mL who underwent prebiopsy bpMRI during 2010–2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4–20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.

Renal cyst development and expansion in autosomal dominant polycystic kidney disease (ADPKD) involves over‐proliferation of cyst‐lining epithelial cells and excessive cystic fluid secretion. While metformin effectively inhibits renal cyst growth in mouse models of ADPKD it exhibits low potency, and thus an adenosine monophosphate‐activated protein kinase (AMPK) activator with higher potency is required. Herein, we adopted a drug repurposing strategy to explore the potential of PF‐06409577, an AMPK activator for diabetic nephropathy, in cellular, ex vivo and in vivo models of ADPKD. Our results demonstrated that PF‐06409577 effectively down‐regulated mammalian target of rapamycin pathway‐mediated proliferation of cyst‐lining epithelial cells and reduced cystic fibrosis transmembrane conductance regulator‐regulated cystic fluid secretion. Overall, our data suggest that PF‐06409577 holds therapeutic potential for ADPKD treatment.

Acute lung injury (ALI) is a respiratory failure disease associated with high mortality rates in patients. The primary pathological damage is attributed to the excessive release of pro-inflammatory mediators in pulmonary tissue. However, specific therapy for ALI has not been developed. In this study, a series of novel ferulic acid-parthenolide (FA-PTL) and ferulic acid-micheliolide (FA-MCL) hybrid derivatives were designed, synthesized, and evaluated for their anti-inflammatory activities in vitro. Compounds 2, 4, and 6 showed pronounced anti-inflammatory activity against LPS-induced expression of pro-inflammatory cytokines in vitro. Importantly, compound 6 displayed good water solubility, and treatment of mice with compound 6 (10 mg/kg) significantly prevented weight loss and ameliorated inflammatory cell infiltration and edema in lung tissue, as well as improving the alveolar structure. These results suggest that compound 6 (((1aR,7aS,8R,10aS,10bS,E)-8-((dimethylamino)methyl)-1a-methyl-9-oxo-1a,2,3,6,7,7a,8,9,10a,10b-decahydrooxireno[2′,3′:9,10]cyclodeca[1,2-b]furan-5-yl)methyl (E)-3-(4-hydroxy-3-methoxyphenyl)acrylate 2-hydroxypropane-1,2,3-tricarboxylate) might be considered as a lead compound for further evaluation as a potential anti-ALI agent.

ABSTRACT: Libido can affect the semen quality of male, and the sperm motility in semen quality parameters is a reliable index to evaluate the fertility of male. In drakes, the sperm motility is gradually acquired in testis, epididymis, and spermaduct. However, the relationship between libido and sperm motility in drakes has not been reported and the mechanisms of testis, epididymis, and spermaduct regulating the sperm motility of drakes are unclear. Therefore, the purpose of the present study was to compare the semen quality of drakes with libido level 4 (LL4) and libido level 5 (LL5), and tried to identify the mechanisms regulating the sperm motility in drakes by performing RNA-seq in testis, epididymis, and spermaduct. Phenotypically, the sperm motility of drakes (P < 0.01), weight of testis (P < 0.05), and organ index of epididymis (P < 0.05) in the LL5 group were significantly better than those in LL4 group. Moreover, compared with the LL4 group, the ductal square of seminiferous tubule (ST) in testis was significantly bigger in the LL5 group (P < 0.05), and the seminiferous epithelial thickness (P < 0.01) of ST in testis and lumenal diameter (P < 0.05) of ductuli conjugentes/dutus epididymidis in epididymis were significantly longer in the LL5 group. In transcriptional regulation, in addition to KEGG pathways related to metabolism and oxidative phosphorylation, lots of KEGG pathways associated with immunity, proliferation, and signaling were also significantly enriched in testis, epididymis, and spermaduct, respectively. Furthermore, through the integrated analysis of coexpression network and protein–protein interaction network, 3 genes (including COL11A1, COL14A1, and C3AR1) involved in protein digestion and absorption pathway and Staphylococcus aureus infection pathway were identified in testis, 2 genes (including BUB1B and ESPL1) involved in cell cycle pathway were identified in epididymis, and 13 genes (including DNAH1, DNAH3, DNAH7, DNAH10, DNAH12, DNAI1, DNAI2, DNALI1, NTF3, ITGA1, TLR2, RELN, and PAK1) involved in Huntington disease pathway and PI3K-Akt signaling pathway were identified in spermaduct. These genes could play crucial roles in the sperm motility of drakes with different libido, and all data the present study obtained will provide new insights into the molecular mechanisms regulating sperm motility of drakes.

Abstract Black phosphorus (BP) receives extensive attention in many fields such as energy storage, microelectronics, and optoelectronics due to its layer‐controlled direct bandgap, excellent carrier mobility, and unique anisotropy. However, in practical applications, atmospheric degradation and the random channel orientation make the actual performance of BP much lower than the theoretical value. Here, clean and complete BP nanosheets with large size and high crystal quality are obtained by poly(dimethylsiloxane)‐assisted mechanical exfoliation. Then, angle‐resolved polarized Raman spectroscopy is used to distinguish the armchair (AC) orientation of BP and a field‐effect transistor (FET) with controllable channel direction can improve the carrier mobility of the device (up to 826.2 cm2 V−1 s−1) because of higher mobility along the AC orientation. Due to the tunneling of electrons through the electron barrier into the conduction band of BP under a positive gate voltage, the transistor possesses a bipolar transport property. In addition, with the change of channel thickness, both the impurity scattering of the substrate and the interlayer resistance will affect the movement of carriers, so the carrier mobility of the device increases first and then decreases with the increase of the channel thickness.

ObjectiveInguinal lymph node metastasis (ILNM) is significantly associated with poor prognosis in patients with squamous cell carcinoma of the penis (SCCP). Patient prognosis could be improved if the probability of ILNM incidence could be accurately predicted at an early stage. We developed a predictive model based on machine learning combined with big data to achieve this.MethodsData of patients diagnosed with SCCP were obtained from the Surveillance, Epidemiology, and End Results Program Research Data. By combing variables that represented the patients' clinical characteristics, we applied five machine learning algorithms to create predictive models based on logistic regression, eXtreme Gradient Boosting, Random Forest, Support Vector Machine, and k-Nearest Neighbor. Model performance was evaluated by ten-fold cross-validation receiver operating characteristic curves, which were used to calculate the area under the curve of the five models for predictive accuracy. Decision curve analysis was conducted to estimate the clinical utility of the models. An external validation cohort of 74 SCCP patients was selected from the Affiliated Hospital of Xuzhou Medical University (February 2008 to March 2021).ResultsA total of 1,056 patients with SCCP from the SEER database were enrolled as the training cohort, of which 164 (15.5%) developed early-stage ILNM. In the external validation cohort, 16.2% of patients developed early-stage ILNM. Multivariate logistic regression showed that tumor grade, inguinal lymph node dissection, radiotherapy, and chemotherapy were independent predictors of early-stage ILNM risk. The model based on the eXtreme Gradient Boosting algorithm showed stable and efficient prediction performance in both the training and external validation groups.ConclusionThe ML model based on the XGB algorithm has high predictive effectiveness and may be used to predict early-stage ILNM risk in SCCP patients. Therefore, it may show promise in clinical decision-making.

BackgroundAs a common clinical symptom, insomnia has a high incidence of combined mental illness and it is also a risk factor for the development of depression, anxiety and suicide. As a new concept in the field of health in recent years, mindfulness therapy can improve insomnia, anxiety and depression, which is a new way to solve such diseases.ObjectiveThis study aims to systematically evaluate the effects of mindfulness compared with conventional treatment on scores of the Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS) in people with insomnia and anxiety-depressive symptoms.MethodsArticles published before October 2022 were searched from seven databases and included in randomized controlled trials (RCTs) to evaluate mindfulness therapy. The assessment tool of Cochrane bias risk was used to evaluate the methodological quality of the literature. The main outcome indicators were HAMD and HAMA scores, and the secondary outcome indicators were SDS and SAS scores.ResultsTen randomized controlled trials including 1,058 subjects were systematically evaluated and meta-analyzed in this study. In the main outcome indicators, there was a significant difference between mindfulness therapy and conventional treatment in reducing HAMD score (MD: −3.67, 95% CI: −5.22–2.11, p

Abstract Background Traditional markets are important trading places for medicinal plants, and researchers performing market surveys often engage in ethnobotanical research to record the herbal plants used locally and any related traditional knowledge. However, information on market-traded medicinal plants from traditional markets in the Lijiang area of Yunnan is not well documented. This research is an ethnobotanical survey focusing on medicinal plants traded in the traditional markets of the Lijiang area and contributes to the understanding of medicinal plants and related information used by the Naxi people. Methods Ethnobotanical surveys were performed for two years (2019–2020). Three traditional markets in the Lijiang area were investigated. The methods we used included literature research, participatory surveys and group discussions. The collected voucher specimens were identified using the botanical taxonomy method and were deposited in the herbarium. The data were analysed through the informant consensus factor and use frequency (UF). These medicinal plants were compared with the Information System of Chinese Rare and Endangered Plants from the Chinese Academy of Sciences. Those results were in turn compared with the Dongba Sutras and Yulong Ben Cao. Results A total of 277 species from 97 families were recorded, with Asteraceae providing the maximum numbers of medicinal plants. Among them, 248 species (89%) were wild plants and 266 species (92.39%) were from the local area. Root (40.43%) was the most common medicinal part. A total of 267 species (96.04%) had a UF value above 0.5. Eighty-three investigated human ailments were grouped into 16 categories. Diseases of the digestive system (166 mentions) were most frequently mentioned in this study. There were 19 species of nationally protected plants in China, including 2 species of first-level nationally protected plants and 17 species of second-level nationally protected plants. A total of 31 species of these medicinal plants can be found in the Dongba Sutra or Yulong Ben Cao. Conclusion We surveyed the herbal medicine in the markets covering the Lijiang area, analysing and revealing the resource composition and current market situations. The medicinal plants used by the Naxi people are diverse and are used to treat a wide spectrum of body disorders. There are many wild medicinal plants, and to ensure sustainable development, their natural protection should be strengthened. Knowledge of the medicinal plants recorded in Naxi medical classics has ethnobotanical value and should be further developed.

Lanzhou City is located in the semi-arid region of northwest China, which experiences serious desertification. Moreover, the high intensity of land development, with the accelerated industrialization and urbanization, causes increasingly aggravated conflict between humans and the environment. Exploring the response of the ecological environment quality to the natural environment and anthropogenic activities is important to protect the sustainable development of urban economic construction and the environment. Based on the Google Earth Engine (GEE) platform, this paper constructed a modified Remote Sensing Ecological Index (MRSEI) model which could reflect the ecological environment quality by integrating the desertification index (DI) into the Remote Sensing Ecological index (RSEI) model. This paper explores the spatiotemporal variation in the environmental quality from 2000 to 2020 in Lanzhou, China, and analyzes the natural and anthropogenic factors affecting the environment quality in terms of temperature, precipitation, gross domestic product (GDP), land use, night lighting, and population. The results showed that the mean value of MRSEI ranged from 0.254 to 0.400. The area undergoing fast growth in ecological quality was in the northwestern part of Lanzhou, and the area of decrease was in the central part. Various factors have different degrees of influence on the ecosystem, with temperature, precipitation, and land use having a greater impact, and GDP and population having a limited impact. Precipitation and temperature showed a strong impact when interacting with other factors, demonstrating that precipitation and temperature were also key factors affecting MRSEI. Overall, climate change and the implementation of ecological restoration projects have led to an improvement in the quality of the ecological environment in Lanzhou. This study provides a reference for understanding the spatiotemporal changes in the ecological environment in semi-arid Lanzhou and is conducive to formulating proper protection strategies.

Background Glucocorticoids (GCs) are commonly used to treat autoimmune diseases and malignancies in children and adolescents. Growth retardation is a common adverse effect of GC treatment in pediatric patients. Accumulating evidence indicates that non-coding RNAs (ncRNAs) are involved in the pathogenesis of glucocorticoid-induced growth retardation (GIGR), but the roles of specific ncRNAs in growth remain largely unknown. Methods In this study, 2-week-old male Sprague-Dawley rats had been treated with 2 mg/kg/d of dexamethasone for 7 or 14 days, after which the growth plate tissues were collected for high-throughput RNA sequencing to identify differentially expressed mRNAs, lncRNAs, circRNAs, and miRNAs in GIGR rats. Results Transcriptomic analysis identified 1,718 mRNAs, 896 lncRNAs, 60 circRNAs, and 72 miRNAs with different expression levels in the 7d group. In the 14d group, 1,515 mRNAs, 880 lncRNAs, 46 circRNAs, and 55 miRNAs with differential expression were identified. Four mRNAs and four miRNAs that may be closely associated with the development of GIGR were further validated by real-time quantitative fluorescence PCR. Function enrichment analysis indicated that the PI3K-Akt signaling pathway, NF-kappa B signaling pathway, and TGF-β signaling pathway participated in the development of the GIGR. Moreover, the constructed ceRNA networks suggested that several miRNAs (including miR-140-3p and miR-127-3p) might play an important role in the pathogenesis of GIGR. Conclusions These results provide new insights and important clues for exploring the molecular mechanisms underlying GIGR.

Background Previous studies suggested that bone metastasis has a significant effect on the time of progression to metastatic castration-resistant prostate cancer (CRPC) for newly diagnosed de novo bone metastatic hormone-sensitive prostate cancer (mHSPC). Nevertheless, the effect of different bone metastasis sites was not fully evaluated. This study aimed to develop and validate a novel bone metastatic risk model. Methods We enrolled 122 patients who were newly diagnosed with de novo bone metastatic prostate cancer following primary androgen deprivation based therapy at our institution from January 2008 to June 2021. The metastatic bone sites were classified into six sites: skull; cervical, thoracic, and lumbar vertebrae; chest (ribs and sternum); pelvis; upper limbs; and lower limbs. We calculated the bone metastatic score (BMS) for each site: 0 points were assigned for non-metastasis and 1 point was assigned for metastasis. The X-tile was adopted to acquire optimal cutoff points of BMS. We defined high-risk group (HRG) as BMS ≥ 3 and low-risk group (LRG) as BMS < 3. The new bone risk stratification was validated by calculating the area under the receiver operating characteristic curve (AUC). Subsequently, the relevant clinical prognostic variables were added to construct a predictive nomogram for predicting CRPC. Results The median patient age was 73 years. Most patients had Gleason score ≤8 (93 cases, 76.2%). The median follow-up duration was 11.5 months (range: 2–92 months). Eighty-six patients progressed to CRPC during the follow-up. The most common bone metastatic site was the pelvis (90.2%). The median BMS was 4. Seventy-six patients had HRG, while forty-six had LRG. The 1-, 2-, and 3-year AUCs for H/LRG were 0.620, 0.754, and 0.793, respectively. The HRG was associated with earlier time to CRPC. A nomogram based on four parameters (Gleason score, H/LRG, prostate-specific antigen [PSA] nadir, and time to PSA nadir) was developed to predict CRPC. Internal validation using bootstrapping demonstrated good accuracy for predicting the CRPC (C-index: 0.727). The calibration analysis demonstrated that the model performed well. Conclusion We established a novel H/LRG risk model for newly diagnosed de novo bone metastatic prostate cancer, which provided evidence to support clinical decision-making.

Background Bone metastasis has been suggested to be a significant impactor on the prognosis of newly diagnosed de novo metastatic hormone-sensitive prostate cancer (mHSPC), and some risk stratification models have been proposed on the basis of this hypothesis. However, the effectiveness of these risk stratification criteria has not been fully evaluated in China. This study aimed to evaluate the effectiveness of the risk stratification models in China. Methods A total of 140 patients who were newly diagnosed with metastatic prostate cancer followed by primary androgen deprivation-based therapy from January 2008 to June 2021 at our institution were enrolled in this study. The patients were divided into different groups on the basis of high- and low-volume disease (H/LVD) criteria, high-and low-risk disease (H/LRD) criteria, extremity bone metastasis criteria (EBM), and extent of disease (EOD) criteria. The area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis (DCA) were used to compare the validity and net benefit of these models. Using the Cox proportional hazards model, we performed univariable and multivariable analyses of the factors influencing overall survival (OS) and the time of progression to metastatic castration-resistant prostate cancer (CRPC). Results The median patient age was 72 years. Most patients had a Gleason score ≥8 (102 cases, 72.9%) and clinical T stage >2 (75 cases, 53.6%). The median follow-up time was 25 months (range, 2–95 months). Ninety-two patients progressed to CRPC and fifty-seven patients died during the follow-up. The AUC of OS and CRPC showed that the EOD model had higher validity than the other risk stratification models. DCA shows that the net benefit of the EOD model on OS was better than that of the other risk stratification models. As for CRPC, the net benefit of the EOD model was second only to that of the H/LRD model when the threshold was 0.5, the EOD model outperformed the other models. The effectiveness of EOD as an independent prognostic variable was verified through univariable and multivariable analyses. Conclusion The EOD model yields reasonable risk stratification for use in Chinese mHSPC patients, providing further evidence supporting its role in clinical decision-making.

Land salinization is a global environmental problem, and how to manage saline soils and promote healthy ecosystems has become a major challenge. China-Singapore Tianjin Eco-City is located in coastal land reclamation areas, so salinization is severe in this region. In this study, geostatistical methods, the ordinary kriging method, and principal component analysis were used. Vertical sampling was performed over three layers (0–20 cm, 20–40 cm, and 40–60 cm) at 184 locations within the study area to produce a total of 542 soil samples. It was found that areas with soluble salt contents greater than 3000 mg/kg account for over 90% of the study area, and high soluble salt content in surface layer soils is the dominant factor in soil salinization. Na+, Cl−, and SO42- are the primary control factors that determine the coefficient of variation of the soils’ soluble salt content. Total salinity and Na+, Cl−, SO42-, K+, and Mg2+ reflect on the salinization of the soils, while effective phosphorus, available potassium, and soil organic carbon reflect on the state of soil nutrition. Based on our results, we proposed site-specific and scientific soil remediation and greening measures.

Urogenital malignancy accounts for one of the major causes of cancer-related deaths globally. Numerous studies have investigated novel molecular markers in the blood circulation, tumor tissue, or urine in order to assist in the clinical identification of tumors at early stages, predict the response of therapeutic strategies, and give accurate prognosis assessment. As an endogenous inhibitor of lysosomal cysteine proteinases, cystatin C plays an integral role in diverse processes. A substantial number of studies have indicated that it may be such a potential promising biomarker. Therefore, this review was intended to provide a detailed overview of the role of cystatin C in urogenital malignancy.

BackgroundLipoid congenital adrenal hyperplasia (LCAH) is a rare and severe disorder that is caused by mutations in the steroidogenic acute regulatory protein (StAR). Non-classic LCAH is defined as late-onset glucocorticoid deficiency and even complete male external genitalia in 46,XY individuals. However, to date, few cases of non-classic LCAH have been reported.MethodsIt was attempted to describe the clinical characteristics of a male child with complete male external genitalia in terms of age of onset, adrenal function, and biochemical indicators. Previously reported cases were also reviewed to investigate the relationship of age of onset with enzymatic activity in non-classic LCAH.ResultsThe patient with complete male external genitalia was diagnosed with non-classic LCAH, in which the reason for his referral to a local hospital at the of age 1.25 years was progressive skin hyperpigmentation, and plasma adrenocorticotropic hormone (ACTH) level was elevated to higher than 1,250 pg/ml. The compound heterozygous mutations c.772C>T/c.562C>T in STAR gene were identified via genetic testing. The literature review resulted in identification of 47 patients with non-classic LCAH from 36 families. The mutational analysis showed that c.562C>T mutation was prevalent in patients with non-classic LCAH, accounting for 37.2% of the total mutant alleles, which could reflect the founder effect on the non-classic LCAH population. In total, 28 46,XY patients were reported, including 22 (78.5%) cases with complete male external genitalia and six (21.5%) cases with different degrees of hypospadias.ConclusionThe clinical phenotypes of non-classic LCAH are highly variable. Routine physical examination, laboratory measurement, genetic testing, and, importantly, enzymatic activity assay may facilitate the early diagnosis of non-classic LCAH. The age of primary adrenal insufficiency (PAI) onset may not be a diagnostic basis for non-classic LCAH, and enzymatic activity assay determination may be more effective.

Chloroquine was once thought to be a promising treatment for COVID-19 but it quickly failed due to its inefficiency and association with increased mortality. Further, comorbidities such as hypertension may have contributed this failure. The safety and toxicity of chloroquine at doses required for treating SARS-CoV-2 infection in hypertensive patients remain unknown. Herein, to investigate these effects, we performed a safety evaluation of chloroquine at the approved dose (63 mg/kg) and at a high dose (126 mg/kg) in hypertensive rats. We found that chloroquine increased the mortality of hypertensive rats to 18.2% and 100%, respectively, after 7 days. During the chloroquine exposure period, the bodyweight, feed, and water consumption of hypertensive rats were decreased significantly. In addition, we show that chloroquine induces prolongation of QTc interval, elevation of LDH and CK, and histopathological damage of the myocardium in hypertensive rats. Ocular toxicity was observed in hypertensive rats in the form of hemorrhage in the eyes and retinal damage. Furthermore, we also observed intestinal toxicity in hypertensive rats, which presented as thinning intestinal walls with hemorrhagic contents, and histopathological changes of the jejunum. Hepatotoxicity was also evidenced by elevated ALT, and vacuolization of hepatocytes was also observed. Nephrotoxicity was observed only in high dose chloroquine-treated hypertensive rats, presenting as alterations of urinalysis and renal function. Immune alterations were also found in high-dose chloroquine-treated hypertensive rats with elevation of serum IL-10, IL-1β and GRO, and moderate damage to the spleen. In summary, this study partially explains the reason for the failure of chloroquine as a COVID-19 therapy, and underlines the importance of safety evaluation and medical supervision of chloroquine to avoid patient harm, especially to those with hypertension.

BackgroundTransurethral resection of the bladder tumor with or without adjuvant intravesical instillation (IVI) has been the standard treatment for non-muscle-invasive bladder cancer (NMIBC), whereas a high percentage of patients still experience local tumor recurrence and disease progression after receiving the standard treatment modalities. Unfortunately, current relevant prediction models for determining the recurrent and progression risk of NMIBC patients are far from impeccable.MethodsClinicopathological characteristics and follow-up information were retrospectively collected from two tertiary medical centers between October 2018 and June 2021. The least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were used to screen potential risk factors affecting recurrence-free survival (RFS) of patients. A nomogram model was established, and the patients were risk-stratified based on the model scores. Both internal and external validation were performed by sampling the model with 1,000 bootstrap resamples.ResultsThe study included 299 patient data obtained from the Affiliated Hospital of Xuzhou Medical University and 117 patient data obtained from the First Affiliated Hospital of Guangxi Medical University. Univariate regression analysis suggested that urine red blood cell count and different tumor invasion locations might be potential predictors of RFS. LASSO-Cox regression confirmed that prior recurrence status, times of IVI, and systemic immune-inflammation index (SII) were independent factors for predicting RFS. The area under the curve for predicting 1-, 2-, and 3-year RFS was 0.835, 0.833, and 0.871, respectively. Based on the risk stratification, patients at high risk of recurrence and progression could be accurately identified. A user-friendly risk calculator based on the model is deposited at https://dl0710.shinyapps.io/nmibc_rfs/.ConclusionInternal and external validation analyses showed that our model had excellent predictive discriminatory ability and stability. The risk calculator can be used for individualized assessment of survival risk in NMIBC patients and can assist in guiding clinical decision-making.

Heavy oil exploitation needs efficient viscosity reducers to reduce viscosity, and polyether carboxylate viscosity reducers have a significant viscosity reduction effect on heavy oil. Previous work has studied the effect of different side chain lengths on this viscosity reducer, and now a series of polyether carboxylate viscosity reducers, including APAD, APASD, APAS, APA, and AP5AD (the name of the viscosity reducer is determined by the name of the desired monomer), with different electrical properties have been synthesized to investigate the effect of their different electrical properties on viscosity reduction performance. Through the performance tests of surface tension, contact angle, emulsification, viscosity reduction, and foaming, it was found that APAD viscosity reducers had the best viscosity reduction performance, reducing the viscosity of heavy oil to 81 mPa·s with a viscosity reduction rate of 98.34%, and the worst viscosity reduction rate of other viscosity reducers also reached 97%. Additionally, APAD viscosity reducers have the highest emulsification rate, and the emulsion formed with heavy oil is also the most stable. The net charge of APAD was calculated from the molar ratio of the monomers and the total mass to minimize the net charge. While the net charge of other surfactants was higher. It shows that the amount of the surfactant’s net charge affects the surfactant’s viscosity reduction effect, and the smaller the net charge of the surfactant itself, the better the viscosity reduction effect.

Junctional adhesion molecules (JAMs) are cell-cell adhesion molecules of the immunoglobulin superfamily and are involved in the regulation of diverse atherosclerosis-related processes such as endothelial barrier maintenance, leucocytes transendothelial migration, and angiogenesis. To combine and further broaden related results, this review concluded the recent progress in the roles of JAMs and predicted future studies of JAMs in the development of atherosclerosis.

Objective:We aimed to establish nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with primary urachal carcinoma (UrC).MethodsInformation on patients diagnosed with UrC from 1975 to 2018 was collected from the Surveillance, Epidemiology, and End Results (SEER) Program Research Data. The independent prognostic factors were determined using univariate and multivariate Cox regression. Backward variable elimination according to the Akaike information criterion (AIC) identified the most accurate and parsimonious model. Nomograms were built based on regression coefficients. The C-index, calibration plot, Brier score, integrated discrimination improvement (IDI), area under the receiver operating curve (AUC), and decision curve analysis (DCA) curve were used to evaluate the efficiency of models.ResultsIn total, 236 patients obtained from SEER were divided randomly into training and validation cohorts in a 70:30 ratio (166 and 70 patients, respectively). In the training cohort, multivariate Cox regression analysis indicated that pTNM/Sheldon/Mayo staging systems (included respectively), age, and tumor grade were independent prognostic factors for OS. A similar result was also found in CSS. While other variables, such as radiotherapy and chemotherapy, did not identify significant correlations. In predicting OS and CSS at 3- and 5- years, the nomograms based on pTNM showed superior discriminative and calibration capabilities in comparison to multiple statistical tools. The C-index values for the training cohort were 0.770 for OS and 0.806 for CSS, and similar outcomes were shown in further internal validation (C-index 0.693 for OS and 0.719 for CSS). We also discovered that the link between age at diagnosis and survival follows a U-shaped curve, indicating that the risk of poor prognosis decreases first and then increases with age.ConclusionThe efficacy of pTNM in predicting the prognosis of patients with UrC was greater than that of the Sheldon and Mayo staging system. Therefore, we recommend pTNM as the preferred system to stage UrC. The novel constructed nomograms based on pTNM, age, and tumor grade showed high accuracy and specificity and could be applied clinically to predict the prognosis of patients with UrC.

BackgroundThe contribution of hepatitis B virus (HBV) and hepatitis C virus (HCV) to primary liver cancer (PLC) and their association with cancer aggressiveness remains uncertain in China, a country with half of global PLC. We aimed to characterize this using data from four representative medical centers.MethodsIn total, 15,801 PLC patients were enrolled from the centers distributed in Easter5n, Southern, Northern, and Western China from 2003 to 2020. Of those, 7585 with curative surgery were involved in survival analysis. A nomogram was constructed using preoperative parameters to predict postoperative survival.ResultsHepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma, and combined hepatocellular cholangiocarcinoma accounted for 93.0%, 4.3%, and 1.6% in PLC, respectively. The seropositivities of HBV and HCV were 84.4% and 3.2% in HCC, respectively. The seropositivity of anti-HCV antibody was significantly higher in HBV-negative than in HBV-positive HCC patients (13.2% vs. 1.1%). Compared to HCV-positive HCC (HCV-HCC), HBV-positive HCC (HBV-HCC) was associated with 12-year earlier onset, higher proportions of males, high α-fetoprotein, large tumor size, advanced Barcelona Clinic Liver Cancer (BCLC) stage, and vascular tumor thrombus. The proportions of HCC and HBV seropositivity increased, whereas that of anti-HCV decreased, from 2003 to 2020. Postoperative five-year survival rate was 73.5%, 64.1%, 34.9%, and 19.7% in HCC at BCLC stage 0, A, B, and C, respectively. The multivariate Cox regression analysis showed that HBV seropositivity, incomplete tumor capsule, vascular tumor thrombus, tumor diameter (≥3 cm), advanced BCLC stage (B+C), α-fetoprotein (≥20ng/ml), and direct bilirubin (>8µmol/L) contributed independently to shorter overall survival (OS); whereas post-operative radiofrequency ablation and second resection independently improved OS in HCC. HCV-HCC had a more favorable prognosis than did HBV-HCC (Log-rank test, P

BackgroundThe gut microbiome is important for host nutrition and metabolism. Whether the gut microbiome under normal diet regulate human height remains to be addressed. Our study explored the possible relationship between gut microbiota, its metabolic products and the pathogenesis of idiopathic short stature disease (ISS) by comparing the gut microbiota between children with ISS and of normal height, and also the short-chain fatty acids (SCFAs) produced by the gut microbiota.MethodsThe subjects of this study were 32 prepubescent children aged 4-8 years. The fecal microbial structure of the subjects was analyzed by 16S rRNA high-throughput sequencing technology. The concentrations of SCFAs in feces were determined by gas chromatography-mass spectrometry.ResultsThe richness of gut microbiota in ISS group was decreased, and the composition of gut microbiota was significantly different between ISS group and control group. The relative abundance of nine species including family Ruminococcaceae and genera Faecalibacterium and Eubacterium, in ISS group was significantly lower than that in control group (P

Objective:Distant metastasis other than non-regional lymph nodes and lung (i.e., M1b stage) significantly contributes to the poor survival prognosis of patients with germ cell testicular cancer (GCTC). The aim of this study was to develop a machine learning (ML) algorithm model to predict the risk of patients with GCTC developing the M1b stage, which can be used to assist in early intervention of patients.MethodsThe clinical and pathological data of patients with GCTC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Combing the patient's characteristic variables, we applied six machine learning (ML) algorithms to develop the predictive models, including logistic regression(LR), eXtreme Gradient Boosting (XGBoost), light Gradient Boosting Machine (lightGBM), random forest (RF), multilayer perceptron (MLP), and k-nearest neighbor (kNN). Model performances were evaluated by 10-fold cross-receiver operating characteristic (ROC) curves, which calculated the area under the curve (AUC) of models for predictive accuracy. A total of 54 patients from our own center (October 2006 to June 2021) were collected as the external validation cohort.ResultsA total of 4,323 patients eligible for inclusion were screened for enrollment from the SEER database, of which 178 (4.12%) developing M1b stage. Multivariate logistic regression showed that lymph node dissection (LND), T stage, N stage, lung metastases, and distant lymph node metastases were the independent predictors of developing M1b stage risk. The models based on both the XGBoost and RF algorithms showed stable and efficient prediction performance in the training and external validation groups.ConclusionS-stage is not an independent factor for predicting the risk of developing the M1b stage of patients with GCTC. The ML models based on both XGBoost and RF algorithms have high predictive effectiveness and may be used to predict the risk of developing the M1b stage of patients with GCTC, which is of promising value in clinical decision-making. Models still need to be tested with a larger sample of real-world data.

Obtaining solutions to optimal transportation (OT) problems is typically intractable when marginal spaces are continuous. Recent research has focused on approximating continuous solutions with discretization methods based on i.i.d. sampling, and this has shown convergence as the sample size increases. However, obtaining OT solutions with large sample sizes requires intensive computation effort, which can be prohibitive in practice. In this paper, we propose an algorithm for calculating discretizations with a given number of weighted points for marginal distributions by minimizing the (entropy-regularized) Wasserstein distance and providing bounds on the performance. The results suggest that our plans are comparable to those obtained with much larger numbers of i.i.d. samples and are more efficient than existing alternatives. Moreover, we propose a local, parallelizable version of such discretizations for applications, which we demonstrate by approximating adorable images.