Research application of session-RPE in monitoring the training load of elite endurance athletes.

Purpose: TRIMP and sRPE are both representative indicators of training load(TL), and the correlation between two has been widely demonstrated across various sports. The aim of this study was to investigate the reliability of sRPE-TRIMP correlation across different intensities/duration of training in cross-country skiing, and whether sRPE can serve as an validity supplement to TRIMP data in cases of lost heart rate data. Method: 10 athletes were used as the experimental objects. The intensity, duration and RPE of 273 different types of training sessions were collected, and statistical methods were used for data analysis. Results: 1. There was a significant correlation between sRPE and TRIMP (r = 0.68, p < 0.05), but the correlation differs among the LIT, MIT and HIT groups (r = 0.70, 0.46, r = 0.31, p < 0.05) 2. sRPE-TRIMP correlation among three different time duration in the LIT group (0-60 min, 60-120 min and 120-180 min), are all highly significant (r = 0.70, 0.67, 0.69, p < 0.05) and the LRsRPE-TRIMP of 3 duration have no significant differences (chow test, p > 0.05). 3. The difference in actual training duration between samples was the main reason for the difference in the application effect of sRPE, because the actual training duration ratio of LIT was 89.7 ± 16.4%; MIT, 98.5 ± 6.2%; and HIT, 94.4 ± 13.5%. Conclusion: 1. The linear relationship between sRPE and TRIMP (LRsRPE-TRIMP) is more significant in LIT compared to that in MIT and HIT. 2. Variations in the duration of LIT sessions do not affect the consistency of the relationship between sRPE and TRIMP. 3. Discrepancies between actual and planned training durations directly impact the significance of the LRsRPE-TRIMP.

The association between telomere length and blood lipids: a bidirectional two-sample Mendelian randomization study.

Background: Observational studies suggest an association between telomere length (TL) and blood lipid (BL) levels. Nevertheless, the causal connections between these two traits remain unclear. We aimed to elucidate whether genetically predicted TL is associated with BL levels via Mendelian randomization (MR) and vice versa. Methods: We obtained genetic instruments associated with TL, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-1 (ApoA-1) and apolipoprotein B (ApoB) from large-scale genome-wide association studies (GWASs). The causal relationships between TL and BL were investigated via bidirectional MR, multivariable MR and mediation analysis methods. The inverse variance weighted (IVW) method was employed as the principal methodology, complemented by several other estimators to enhance the robustness of the analysis. Results: In the forward MR analyses, we identified significant positive correlation between genetically predicted TL and the levels of TG (ß=0.04, 95% confidence interval [CI]: 0.01 to 0.06, p = 0.003). In the reverse MR analysis, TG (ß=0.02, 95% CI: 0.01 to 0.03, p = 0.004), LDL-C (ß=0.03, 95% CI: 0.01 to 0.04, p = 0.001) and ApoB (ß=0.03, 95% CI: 0.01 to 0.04, p = 9.71×10-5) were significantly positively associated with TL, although this relationship was not observed in the multivariate MR analysis. The mediation analysis via two-step MR showed no significant mediation effects acting through obesity-related phenotypes in analysis of TL with TG, while the effect of LDL-C on TL was partially mediated by body mass index (BMI) in the reverse direction, with mediated proportion of 12.83% (95% CI: 0.62% to 25.04%). Conclusions: Our study indicated that longer TL were associated with higher TG levels, while conversely, higher TG, LDL-C, and ApoB levels predicted longer TL, with BMI partially mediating these effects. Our findings present valuable insights into the development of preventive strategies and interventions that specifically target TL-related aging and age-related diseases.

Towards a Green Equal City: Measuring and matching the supply-demand of green exposure in urban center.

Exposure to green environments is crucial for human health. However, urbanization has reduced the contact of urban residents with natural environments, causing a mismatch between the supply and demand for green exposure. Research in this field is hindered by the lack of long-term, reliable data sources and methodologies, leading to insufficient consideration of temporal variations in green exposure. This study presented a comprehensive methodology for assessing green exposure at a fine scale utilizing satellite images for urban tree canopy identification. We conducted a case study in the core area of Beijing from 2010 to 2020 and examined the effects of urban renewal and alleviation efforts. The results revealed a slight decrease in green exposure for the elderly over the decade, with minimal changes in equity. In contrast, green exposure for children has increased, with increasing inequality. Moreover, urban renewal has improved green exposure for nearly half of the low-supply blocks. However, a significant mismatch was observed between supply and demand for blocks with increased demand but limited supply. This study enhances the assessment of green exposure and provides guidance for planning and constructing a "Green Equal City".

Indirect Estimation of Heavy Metal Contamination in Rice Soil Using Spectral Techniques.

The rapid growth of industrialization and urbanization in China has led to an increase in soil heavy metal pollution, which poses a serious threat to ecosystem safety and human health. The advancement of spectral technology offers a way to rapidly and non-destructively monitor soil heavy metal content. In order to explore the potential of rice leaf spectra to indirectly estimate soil heavy metal content. We collected farmland soil samples and measured rice leaf spectra in Xushe Town, Yixing City, Jiangsu Province, China. In the laboratory, the heavy metals Cd and As were determined. In order to establish an estimation model between the pre-processed spectra and the soil heavy metals Cd and As content, a genetic algorithm (GA) was used to optimise the partial least squares regression (PLSR). The model's accuracy was evaluated and the best estimation model was obtained. The results showed that spectral pre-processing techniques can extract hidden information from the spectra. The first-order derivative of absorbance was more effective in extracting spectral sensitive information from rice leaf spectra. The GA-PLSR model selects only about 10% of the bands and has better accuracy in spectral modeling than the PLSR model. The spectral reflectance of rice leaves has the capacity to estimate Cd content in the soil (relative percent difference [RPD] = 2.09) and a good capacity to estimate As content in the soil (RPD = 2.97). Therefore, the content of the heavy metals Cd and As in the soil can be estimated indirectly from the spectral data of rice leaves. This study provides a reference for future remote sensing monitoring of soil heavy metal pollution in farmland that is quantitative, dynamic, and non-destructive over a large area.

Enrichment methods of N-linked glycopeptides from human serum or plasma: A mini-review.

Human diseases often correlate with changes in protein glycosylation, which can be observed in serum or plasma samples. N-glycosylation, the most common form, can provide potential biomarkers for disease prognosis and diagnosis. However, glycoproteins constitute a relatively small proportion of the total proteins in human serum and plasma compared to the non-glycosylated protein albumin, which constitutes the majority. The detection of microheterogeneity and low glycan abundance presents a challenge. Mass spectrometry facilitates glycoproteomics research, yet it faces challenges due to interference from abundant plasma proteins. Therefore, methods have emerged to enrich N-glycans and N-linked glycopeptides using glycan affinity, chemical properties, stationary phase chemical coupling, bioorthogonal techniques, and other alternatives. This review focuses on N-glycans and N-glycopeptides enrichment in human serum or plasma, emphasizing methods and applications. Although not exhaustive, it aims to elucidate principles and showcase the utility and limitations of glycoproteome characterization.

A miRNA-7704/IL2RB/AKT feedback loop regulates tumorigenesis and chemoresistance in ovarian cancer.

Ovarian cancer is one of the most common gynecological tumors worldwide. Despite the availability of multiple treatments for ovarian cancer, its resistance to chemotherapy remains a significant challenge. miRNAs play crucial roles in the initiation and progression of cancer by affecting processes such as differentiation, proliferation, and chemoresistance. According to microarray and qPCR analyses, miR-7704 is significantly downregulated in cisplatin-resistant cells compared to parental cells. In this study, we found that miR-7704 inhibited the proliferation and promoted cisplatin sensitivity of ovarian cancer cells in vitro and in vivo. Moreover, ectopic expression of miR-7704 had the same effect as IL2RB knockdown. Further mechanistic studies revealed that miR-7704 played an inhibitory role by regulating IL2RB expression to inactivate the AKT signaling pathway. Furthermore, IL2RB reversed the miR-7704 mediated resistance to cisplatin in ovarian cancer. Based on these findings, miR-7704 and IL2RB show the potential as novel therapeutic targets for ovarian cancer.

Effect of Tai Chi vs Aerobic Exercise on Blood Pressure in Patients With Prehypertension: A Randomized Clinical Trial.

Importance: Prehypertension increases the risk of developing hypertension and other cardiovascular diseases. Early and effective intervention for patients with prehypertension is highly important. Objective: To assess the efficacy of Tai Chi vs aerobic exercise in patients with prehypertension. Design, Setting, and Participants: This prospective, single-blinded randomized clinical trial was conducted between July 25, 2019, and January 24, 2022, at 2 tertiary public hospitals in China. Participants included 342 adults aged 18 to 65 years with prehypertension, defined as systolic blood pressure (SBP) of 120 to 139 mm Hg and/or diastolic BP (DBP) of 80 to 89 mm Hg. Interventions: Participants were randomized in a 1:1 ratio to a Tai Chi group (n = 173) or an aerobic exercise group (n = 169). Both groups performed four 60-minute supervised sessions per week for 12 months. Main Outcomes and Measures: The primary outcome was SBP at 12 months obtained in the office setting. Secondary outcomes included SBP at 6 months and DBP at 6 and 12 months obtained in the office setting and 24-hour ambulatory BP at 12 months. Results: Of the 1189 patients screened, 342 (mean [SD] age, 49.3 [11.9] years; 166 men [48.5%] and 176 women [51.5%]) were randomized to 1 of 2 intervention groups: 173 to Tai Chi and 169 to aerobic exercise. At 12 months, the change in office SBP was significantly different between groups by -2.40 (95% CI, -4.39 to -0.41) mm Hg (P = .02), with a mean (SD) change of -7.01 (10.12) mm Hg in the Tai Chi group vs -4.61 (8.47) mm Hg in the aerobic exercise group. The analysis of office SBP at 6 months yielded similar results (-2.31 [95% CI, -3.94 to -0.67] mm Hg; P = .006). Additionally, 24-hour ambulatory SBP (-2.16 [95% CI, -3.84 to -0.47] mm Hg; P = .01) and nighttime ambulatory SBP (-4.08 [95% CI, -6.59 to -1.57] mm Hg; P = .002) were significantly reduced in the Tai Chi group compared with the aerobic exercise group. Conclusions and Relevance: In this study including patients with prehypertension, a 12-month Tai Chi intervention was more effective than aerobic exercise in reducing SBP. These findings suggest that Tai Chi may help promote the prevention of cardiovascular disease in populations with prehypertension. Trial Registration: Chinese Clinical Trial Registry Identifier: ChiCTR1900024368.

Identification of a Group of Therapeutic Targets and Prognostic Biomarker for Triple Negative Breast Cancer.

INTRODUCTION: Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Mining differentially expressed genes of TNBC is helpful to explore new therapeutic targets. This study aimed to investigate diagnostic biomarker genes in TNBC compared to normal tissue. Additionally, we explored the functions and prognostic value of these key genes as well as potential targeted drugs that could affect these genes. METHODS: Differential gene expression analysis was conducted using the R software with data from the Gene Expression Omnibus (GEO) database. Then, the identified differentially expressed genes (DEGs) were used to construct a protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The mRNA expression levels of key genes were analyzed using the UALCAN database with data from The Cancer Genome Atlas (TCGA). Enrichment and survival analyses were performed using R software. In addition, potential compounds showing sensitivity to key genes were identified by gene set cancer analysis (GSCA). RESULTS: Compared with normal tissues, a total of 203 DEGs were upregulated in TNBC. These DEGs participated in various biological processes including nuclear division, microtubule binding, cell cycle, and the p53 signaling pathway. Through the PPI network analysis, ten key genes were identified, among which four genes showed significant correlation with poor progression-free interval (PFI) in patients with TNBC. Moreover, the four survival-related genes were found to act as sensitive therapeutic targets. CONCLUSION: The identified four key genes were considered new biomarkers for diagnosis and prognosis and also potential therapeutic targets for TNBC.

The Emerging Function and Promise of tRNA-Derived Small RNAs in Cancer.

Fragments derived from tRNA, called tRNA-derived small RNAs (tsRNAs), have attracted widespread attention in the past decade. tsRNAs are widespread in prokaryotic and eukaryotic transcriptome, which contains two main types, tRNA-derived fragments (tRFs) and tRNA-derived stress-inducing RNA (tiRNAs), derived from the precursor tRNAs or mature tRNAs. According to differences in the cleavage position, tRFs can be divided into tRF-1, tRF-2, tRF-3, tRF-5, and i-tRF, whereas tiRNAs can be divided into 5'-tiRNA and 3'-tiRNA. Studies have found that tRFs and tiRNAs are abnormally expressed in a variety of human malignant tumors, promote or inhibit the proliferation and apoptosis of cancer cells by regulating the expression of oncogene, and play an important role in the aggressive metastasis and progression of tumors. This article reviews the biological origins of various tsRNAs, introduces their functions and new concepts of related mechanisms, and focuses on the molecular mechanisms of tsRNAs in cancer, including breast cancer, prostate cancer, colorectal cancer, lung cancer, b-cell lymphoma, and chronic lymphoma cell leukemia. Lastly, this article puts forward some unresolved problems and future research prospects.

Copper homeostasis and cuproptosis in atherosclerosis: metabolism, mechanisms and potential therapeutic strategies.

Copper is an essential micronutrient that plays a pivotal role in numerous physiological processes in virtually all cell types. Nevertheless, the dysregulation of copper homeostasis, whether towards excess or deficiency, can lead to pathological alterations, such as atherosclerosis. With the advent of the concept of copper-induced cell death, termed cuproptosis, researchers have increasingly focused on the potential role of copper dyshomeostasis in atherosclerosis. In this review, we provide a broad overview of cellular and systemic copper metabolism. We then summarize the evidence linking copper dyshomeostasis to atherosclerosis and elucidate the potential mechanisms underlying atherosclerosis development in terms of both copper excess and copper deficiency. Furthermore, we discuss the evidence for and mechanisms of cuproptosis, discuss its interactions with other modes of cell death, and highlight the role of cuproptosis-related mitochondrial dysfunction in atherosclerosis. Finally, we explore the therapeutic strategy of targeting this novel form of cell death, aiming to provide some insights for the management of atherosclerosis.

Simulating behavior of perfluorooctane sulfonate (PFOS) in the mainstream of a river system with sluice regulations.

Perfluorooctane sulfonate (PFOS) is a persistent, anionic and ubiquitous contaminant that undergoes long-range transport within the environment. Its behavior has attracted wide-range academic and regulatory attention. In this article, a mass balance model was employed to simulate PFOS concentrations in the mainstream of Haihe River water system, encompassing sluices and artificial rivers. The dynamic simulation of PFOS concentrations in both sediment and freshwater took into account fluctuations in PFOS emissions, water levels and water discharge. Furthermore, the study delved into exploring the impacts of sluices and artificial rivers on the behavior of PFOS. The simulated concentrations of PFOS in steady state agreed with the measured concentrations in surveys carried out in Nov. 2019, July 2020, Oct. 2020, and June 2021. Every year, approximately 24 kg PFOS was discharged into the Bohai Sea with Chaobai New River being the largest contributor for 44 %. Moreover, the transport of PFOS in the original rivers is likely to be restricted by sluices and replaced by artificial rivers. Monte Carlo analysis showed that model predictions of PFOS concentrations in sediment were subject to greater uncertainty than those in freshwater as the former is impacted by more parameters, such as density of sediment. This study provides a scientific basis for the local government to manage and control PFOS.

Biomagnification and health risks of perflfluoroalkyl acids (PFAAs) in seafood from the Yangtze river estuary of China.

Bioaccumulation and human health risk assessment of Perfluoroalkyl acids (PFAAs) is important for pollutant hazard assessment. In this study, 26 aquatic organisms were collected from the Yangtze River estuary, the PFAAs concentrations in organisms were detected by liquid chromatography-mass spectrometry, and the trophic levels of organisms were constructed using nitrogen isotope analysis. The results showed that Perfluorobutane sulfonate (PFBS) was predominant in organisms with the mean concentration of 6.43 ± 8.21 ng/g ww. The biomagnification of organisms along the food chain was widespread, and the biomagnification factor (BMF) of perfluorooctane sulfonic (PFOS) was the most prominent. Trophic magnifcation factors (TMFs) of PFAAs were estimated in the marine food web, and TMFs >1 were observed in Perfluorodecanoic acid (PFDA), Perfluoroundecanoic acid (PFUnDA), Perfluorododecanoic acid (PFDoDA), and PFOS, indicating the biomagnifcation effects of these 4 individual PFAAs in organisms at Yangtze River estuary. The estimated daily intake (EDI) of PFBS was highest in adolescents aged 6-18 years, with EDIs of 18.9 ng/kg·bw/day for males and 14.0 ng/kg·bw/day for females. The hazard ratio (HR) of PFAAs reported in different age and gender groups were lower than 1.

Deep Learning-Based H-Score Quantification of Immunohistochemistry-Stained Images.

Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB), resulting in a brown coloration, whereas hematoxylin serves as a blue counterstain for cell nuclei. The protein expression level is quantified through the H-score, calculated from DAB staining intensity within the target cell region. Traditionally, this process requires evaluation by 2 expert pathologists, which is both time consuming and subjective. To enhance the efficiency and accuracy of this process, we have developed an automatic algorithm for quantifying the H-score of IHC images. To characterize protein expression in specific cell regions, a deep learning model for region recognition was trained based on hematoxylin staining only, achieving pixel accuracy for each class ranging from 0.92 to 0.99. Within the desired area, the algorithm categorizes DAB intensity of each pixel as negative, weak, moderate, or strong staining and calculates the final H-score based on the percentage of each intensity category. Overall, this algorithm takes an IHC image as input and directly outputs the H-score within a few seconds, significantly enhancing the speed of IHC image analysis. This automated tool provides H-score quantification with precision and consistency comparable to experienced pathologists but at a significantly reduced cost during IHC diagnostic workups. It holds significant potential to advance biomedical research reliant on IHC staining for protein expression quantification.

Legacy and alternative per-and polyfluoroalkyl substances (PFASs) in the Bohai Bay Rim: Occurrence, partitioning behavior, risk assessment, and emission scenario analysis.

The use of alternative per- and polyfluoroalkyl substances (PFASs) has been practiced because of the restrictions on legacy PFASs. However, knowledge gaps exist on the ecological risks of alternatives and relationships between restrictions and emissions. This study systematically analyzed the occurrence characteristics, water-sediment partitioning behaviors, ecological risks, and emissions of legacy and alternative PFASs in the Bohai Bay Rim (BBR). The mean concentration of total PFASs was 46.105 ng/L in surface water and 6.125 ng/g dry weight (dw) in sediments. As an alternative for perfluorooctanoic acid (PFOA), hexafluoropropylene oxide dimer acid (GenX) had a concentration second only to PFOA in surface water. In sediments, perfluorobutyric acid (PFBA) and GenX were the two predominant contaminants. In the water-sediment partitioning system, GenX, 9-chlorohexadecafluoro-3-oxanone-1-sulfonic acid (F-53B), and 11-chloroeicosafluoro-3-oxaundecane-1-sulfonic acid (8:2 Cl-PFESA) tended to be enriched towards sediments. The species sensitivity distribution (SSD) models revealed the low ecological risks of PFASs and their alternatives in the BBR. Moreover, predicted no-effected concentrations (PNECs) indicated that short-chain alternatives like PFBA and perfluorobutane sulfonate (PFBS) were safer for aquatic ecosystems, while caution should be exercised when using GenX and F-53B. Due to the incremental replacement of PFOA by GenX, cumulative emissions of 1317.96 kg PFOA and 667.22 kg GenX were estimated during 2004-2022, in which PFOA emissions were reduced by 59.2 % due to restrictions implemented since 2016. If more stringent restrictions are implemented from 2023 to 2030, PFOA emissions will further decrease by 85.0 %, but GenX emissions will increase by an additional 21.3 %. Simultaneously, GenX concentrations in surface water are forecasted to surge by 2.02 to 2.45 times in 2023. This study deepens the understanding of PFAS alternatives and assists authorities in developing policies to administer PFAS alternatives.

pan-MHC and cross-Species Prediction of T Cell Receptor-Antigen Binding.

Profiling the binding of T cell receptors (TCRs) of T cells to antigenic peptides presented by MHC proteins is one of the most important unsolved problems in modern immunology. Experimental methods to probe TCR-antigen interactions are slow, labor-intensive, costly, and yield moderate throughput. To address this problem, we developed pMTnet-omni, an Artificial Intelligence (AI) system based on hybrid protein sequence and structure information, to predict the pairing of TCRs of αß T cells with peptide-MHC complexes (pMHCs). pMTnet-omni is capable of handling peptides presented by both class I and II pMHCs, and capable of handling both human and mouse TCR-pMHC pairs, through information sharing enabled this hybrid design. pMTnet-omni achieves a high overall Area Under the Curve of Receiver Operator Characteristics (AUROC) of 0.888, which surpasses competing tools by a large margin. We showed that pMTnet-omni can distinguish binding affinity of TCRs with similar sequences. Across a range of datasets from various biological contexts, pMTnet-omni characterized the longitudinal evolution and spatial heterogeneity of TCR-pMHC interactions and their functional impact. We successfully developed a biomarker based on pMTnet-omni for predicting immune-related adverse events of immune checkpoint inhibitor (ICI) treatment in a cohort of 57 ICI-treated patients. pMTnet-omni represents a major advance towards developing a clinically usable AI system for TCR-pMHC pairing prediction that can aid the design and implementation of TCR-based immunotherapeutics.

Development and Validation of a Prediction Model for Venous Thrombus Embolism (VTE) in Patients With Colorectal Cancer.

Cancer patients are at high risk of developing venous thromboembolism (VTE). The risk of VTE could be mitigated with the administration of prophylactic anticoagulants. Therefore, risk assessment models would be a useful tool in order to identify those patients who are at higher risk and will be benefited more by prophylactic anticoagulants. This study retrospectively examined 528 newly diagnosed colorectal cancer patients from January 2019 to January 2021. Specified logistic regression models were employed to screen the factors and establish prediction tools based on nomograms according to the final included variables. Discrimination, calibration, and clinical applicability were used to assess the performance of screening tools. In addition, internal verifications were conducted through 10-fold cross-verification, leave-one-out cross-validation, and Bootstrap verification. Four risk factors, closely related to the occurrence of VTE in colorectal cancer patients, were identified after univariate and multivariate logistic regression, including age, body mass index, activated partial thromboplastin time, and D-Dimer value. Besides, the risk assessment model named ABAD was built on the basis, displaying good discriminations and calibrations. The area under the curve was 0.705 (95% confidence interval [CI], 0.644 to 0.766). According to Hosmer-Lemeshow goodness-of-fit test, a good agreement between the predicted and observed VTE events in patients with newly-diagnosed gastrointestinal cancer was observed for χ2 = 6.864, P = .551. Internal validation was applied with a C-index of 0.669 in the 10-fold cross-verification, 0.658 in the leave-one-out cross verification and 0.684 in the bootstrap verification. We developed a prediction model called ABAD for newly diagnosed colorectal cancer patients, which can be used to predict the risk of VTE. After evaluation and internal verification, we believe that ABAD exhibited high predictive performance and availability and could be recommended.

Promoting proliferation and tumorigenesis of breast cancer: KCND2's significance as a prognostic factor.

In recent years, the potassium voltage-gated channel subfamily D (KCND) channels, particularly KCND2 (also known as Kv4.2), have been suggested to play a role in a variety of cancers, but their role in breast cancer has not yet been revealed. We analyzed RNA sequencing data from The Cancer Genome Atlas database and the Genotype-Tissue Expression database to investigate the differential expression of KCND2 in breast cancer and normal breast tissue. In addition, we leveraged GO and KEGG analysis techniques to gain a better understanding of the potential functional enrichment of 500 genes related to KCND2. Our findings were validated using collected tissue samples and clinical data from hospitals showed that KCND2 is a crucial independent factor in the prognosis of breast cancer patients. The higher the expression of KCND2, the shorter the survival time of breast cancer patients. Colony formation assay confirmed that KCND2 promotes the proliferation of breast cancer cells, whereas transwell assay and wound healing assay verified that KCND2 promoted breast cancer invasion and migration. In addition, 5-Ethynyl-2'-deoxyuridine (EdU) and flow cytometry revealed that KCND2 affected the cycle changes of breast cancer cells and contributed to the G1/S phase transition of breast cancer cells. Overall, our study demonstrates that KCND2 holds a promising potential as a significant target for breast cancer diagnosis and therapy.

Multimedia fate of sulfamethoxazole (SMX) in a water-scarce city by coupling fugacity model and HYDRUS-1D model.

Increased concentrations of pharmaceutical and personal care products (PPCPs) have raised concerns about their impact on the ecological system and human health. To understand the environmental impact of PPCPs, we evaluated the fate of a typical PPCP of sulfamethoxazole (SMX) in a water-scarce city of Tianjin during 2013-2020 using a coupled model based on the dynamic fugacity model and HYDRUS-1D model. The results showed that the coupled model successfully simulated the reported SMX concentrations in the main fate media of water and soils, which accounted for 46.4 % and 53.0 % with equilibrium concentrations of 135-165 ng/L and 0.4-0.5 ng/g, respectively. The cross-media transfer flux results showed that advection was the prime input path for SMX in water, while degradation was the dominant output path. Wastewater irrigation and degradation were the main transfer processes of SMX in the soil. Moreover, human activities (i.e., emission loads) and climate (i.e., temperature and precipitation) change can significantly affect the concentrations and transfer rate of SMX in the media. These findings provide basic data and methods for the risk assessment of SMX in water-scarce regions.

Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images.

Polyploidy, the duplication of the entire genome within a single cell, is a significant characteristic of cells in many tissues, including the liver. The quantification of hepatic ploidy typically relies on flow cytometry and immunofluorescence (IF) imaging, which are not widely available in clinical settings due to high financial and time costs. To improve accessibility for clinical samples, we developed a computational algorithm to quantify hepatic ploidy using hematoxylin-eosin (H&E) histopathology images, which are commonly obtained during routine clinical practice. Our algorithm uses a deep learning model to first segment and classify different types of cell nuclei in H&E images. It then determines cellular ploidy based on the relative distance between identified hepatocyte nuclei and determines nuclear ploidy using a fitted Gaussian mixture model. The algorithm can establish the total number of hepatocytes and their detailed ploidy information in a region of interest (ROI) on H&E images. This is the first successful attempt to automate ploidy analysis on H&E images. Our algorithm is expected to serve as an important tool for studying the role of polyploidy in human liver disease.

Role of emodin in atherosclerosis and other cardiovascular diseases: Pharmacological effects, mechanisms, and potential therapeutic target as a phytochemical.

The morbidity and mortality of cardiovascular diseases (CVDs) are increasing in recent years, and atherosclerosis (AS), a major CVD, becomes a disorder that afflicts human beings severely, especially the elders. AS is recognized as the primary cause and pathological basis of some other CVDs. The active constituents of Chinese herbal medicines have garnered increasing interest in recent researches owing to their influence on AS and other CVDs. Emodin (1,3,8-trihydroxy-6-methylanthraquinone) is a naturally occurring anthraquinone derivative found in some Chinese herbal medicines such as Rhei radix et rhizome, Polygoni cuspidati rhizoma et radix and Polygoni multiflori root. In this paper, we first review the latest researches about emodin's pharmacology, metabolism and toxicity. Meanwhile, it has been shown to be effective in treating CVDs caused by AS in dozens of previous studies. Therefore, we systematically reviewed the mechanisms by which emodin treats AS. In summary, these mechanisms include anti-inflammatory activity, lipid metabolism regulation, anti-oxidative stress, anti-apoptosis and vascular protection. The mechanisms of emodin in other CVDs are also discussed, such as vasodilation, inhibition of myocardial fibrosis, inhibition of cardiac valve calcification and antiviral properties. We have further summarized the potential clinical applications of emodin. Through this review, we hope to provide guidance for clinical and preclinical drug development.