Distribution and bioaccumulation of trace elements in two Cyprinidae fish species in the Indus river, Pakistan, including the impact of hydraulic structure on macroinvertebrates' biodiversity.

The concentration of trace elements (chromium, lead, zinc, copper, manganese, and iron) was determined in water, sediment and tissues of two Cyprinidae fish species - Labeo rohita and Tor putitora - collected from the eight sampling stations of Indus River in 2022 for four successive seasons (autumn, winter, spring, summer), and also study the present condition of macroinvertebrates after the construction of hydraulic structure. The obtained results of trace element concentrations in the Indus River were higher than the acceptable drinking water standards by WHO. The nitrate concentration ranges from 5.2 to 59.6 mg l-1, turbidity ranges from 3.00 to 63.9 NTU, total suspended solids and ammonium ions are below the detection limit (<0.05). In the liver, highest dry wt trace elements (µg/g) such as Cr (4.32), Pb (7.07), Zn (58.26), Cu (8.38), Mn (50.27), and Fe (83.9) for the Labeo rohita; and Tor Putitora has significantly greater accumulated concentration (Cr, Pb, Zn, Cu, Mn, Fe) in muscle and liver than did Labeo rohita species. Additionally, lower number of macroinvertebrates were recorded during the monsoonal season than pre-monsoon and post-monsoon. Local communities surrounded by polluted environments are more probably to consume more fish and expose them to higher concentrations of toxic trace elements (lead and copper). The findings also provide a basis for broader ecological management of the Indus River, which significantly influenced human beings and socioeconomic disasters, particularly in the local community.

Spatiotemporal Variability of Asymmetric Daytime and Night-Time Warming and Its Effects on Vegetation in the Yellow River Basin from 1982 to 2015.

Temperatures from 1982 to 2015 have exhibited an asymmetric warming pattern between day and night throughout the Yellow River Basin. The response to this asymmetric warming can be linked to vegetation growth as quantified by the NDVI (Normalized Difference Vegetation Index). In this study, the time series trends of the maximum temperature (Tmax) and the minimum temperature (Tmin) and their spatial patterns in the growing season (April-October) of the Yellow River Basin from 1982 to 2015 were analyzed. We evaluated how vegetation NDVI had responded to daytime and night-time warming, based on NDVI and meteorological parameters (precipitation and temperature) over the period 1982-2015. We found: (1) a persistent increase in the growing season Tmax and Tmin in 1982-2015 as confirmed by using the Mann-Kendall (M-K) non-parametric test method (p < 0.01), where the rate of increase of Tmin was 1.25 times that of Tmax, and thus the diurnal warming was asymmetric during 1982-2015; (2) the partial correlation between Tmax and NDVI was significantly positive only for cultivated plants, shrubs, and desert, which means daytime warming may increase arid and semi-arid vegetation's growth and coverage, and cultivated plants' growth and yield. The partial correlation between Tmin and NDVI of all vegetation types except broadleaf forest is very significant (p < 0.01) and, therefore, it has more impacts vegetation across the whole basin. This study demonstrates a methodogy for studying regional responses of vegetation to climate extremes under global climate change.

MiR-503 inhibited cell proliferation of human breast cancer cells by suppressing CCND1 expression.

Breast cancer is one of the most common malignancies and a major cause of cancer-related mortality all over the world. A growing body of reports revealed that microRNAs play essential roles in the progression of cancers. Aberrant expression of miR-503 has been reported in several kinds of cancer. The aim of the current study was to elucidate the role of miR-503 in the pathogenesis of breast cancer. In the present study, our results suggested that miR-503 expression was markedly downregulated in breast cancer tissues and cells. Overexpression of miR-503 in breast cancer cell lines reduced cell proliferation through inducing G0/G1 cell cycle arrest by targeting CCND1. Together, our findings provide new knowledge regarding the role of miR-503 in the progression of breast cancer and indicate the role of miR-503 as a tumor suppressor microRNA (miRNA) in breast cancer.

Advancing NSCLC pathological subtype prediction with interpretable machine learning: a comprehensive radiomics-based approach.

Objective: This research aims to develop and assess the performance of interpretable machine learning models for diagnosing three histological subtypes of non-small cell lung cancer (NSCLC) utilizing CT imaging data. Methods: A retrospective cohort of 317 patients diagnosed with NSCLC was included in the study. These individuals were randomly segregated into two groups: a training set comprising 222 patients and a validation set with 95 patients, adhering to a 7:3 ratio. A comprehensive extraction yielded 1,834 radiomic features. For feature selection, statistical methodologies such as the Mann-Whitney U test, Spearman's rank correlation, and one-way logistic regression were employed. To address data imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was utilized. The study designed three distinct models to predict adenocarcinoma (ADC), squamous cell carcinoma (SCC), and large cell carcinoma (LCC). Six different classifiers, namely Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, eXtreme Gradient Boosting (XGB), and LightGBM, were deployed for model training. Model performance was gauged through accuracy metrics and the area under the receiver operating characteristic (ROC) curves (AUC). To interpret the diagnostic process, the Shapley Additive Explanations (SHAP) approach was applied. Results: For the ADC, SCC, and LCC groups, 9, 12, and 8 key radiomic features were selected, respectively. In terms of model performance, the XGB model demonstrated superior performance in predicting SCC and LCC, with AUC values of 0.789 and 0.848, respectively. For ADC prediction, the Random Forest model excelled, showcasing an AUC of 0.748. Conclusion: The constructed machine learning models, leveraging CT imaging, exhibited robust predictive capabilities for SCC, LCC, and ADC subtypes of NSCLC. These interpretable models serve as substantial support for clinical decision-making processes.

Enhancing prognostic prediction in hepatocellular carcinoma post-TACE: a machine learning approach integrating radiomics and clinical features.

Objective: This study aimed to investigate the use of radiomics features and clinical information by four machine learning algorithms for predicting the prognosis of patients with hepatocellular carcinoma (HCC) who have been treated with transarterial chemoembolization (TACE). Methods: A total of 105 patients with HCC treated with TACE from 2002 to 2012 were enrolled retrospectively and randomly divided into two cohorts for training (n = 74) and validation (n = 31) according to a ratio of 7:3. The Spearman rank, random forest, and univariate Cox regression were used to select the optimal radiomics features. Univariate Cox regression was used to select clinical features. Four machine learning algorithms were used to develop the models: random survival forest, eXtreme gradient boosting (XGBoost), gradient boosting, and the Cox proportional hazard regression model. The area under the curve (AUC) and C-index were devoted to assessing the performance of the models in predicting HCC prognosis. Results: A total of 1,834 radiomics features were extracted from the computed tomography images of each patient. The clinical risk factors for HCC prognosis were age at diagnosis, TNM stage, and metastasis, which were analyzed using univariate Cox regression. In various models, the efficacy of the combined models generally surpassed that of the radiomics and clinical models. Among four machine learning algorithms, XGBoost exhibited the best performance in combined models, achieving an AUC of 0.979 in the training set and 0.750 in the testing set, demonstrating its strong prognostic prediction capability. Conclusion: The superior performance of the XGBoost-based combined model underscores its potential as a powerful tool for enhancing the precision of prognostic assessments for patients with HCC.

Dendritic quinary PtRhMoCoFe high-entropy alloy as a robust immunosensing nanoplatform for ultrasensitive detection of biomarker.

Recently, high-entropy alloys have superior physicochemical properties as compared to conventional alloys for their glamorous "cocktail effect". Nevertheless, they are scarcely applied to electrochemical immunoassays until now. Herein, uniform PtRhMoCoFe high-entropy alloyed nanodendrites (HEANDs) were synthesized by a wet-chemical co-reduction method, where glucose and oleylamine behaved as the co-reducing agents. Then, a series of characterizations were conducted to illustrate the synergistic effect among multiple metals and fascinating structural characteristics of PtRhMoCoFe HEANDs. The obtained high-entropy alloy was adopted to build a electrochemical label-free biosensor for ultrasensitive bioassay of biomarker cTnI. In the optimized analytical system, the resultant sensor exhibited a dynamic linear range of 0.0001-200 ng mL-1 and a low detection limit of 0.0095 pg mL-1 (S/N = 3). Eventually, this sensing platform was further explored in serum samples with satisfied recovery (102.0 %). This research renders some constructive insights for synthesis of high-entropy alloys and their expanded applications in bioassays and bio-devices.

Ferroptosis: From Basic Research to Clinical Therapeutics in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common and highly heterogeneous malignancies worldwide. Despite the rapid development of multidisciplinary treatment and personalized precision medicine strategies, the overall survival of HCC patients remains poor. The limited survival benefit may be attributed to difficulty in early diagnosis, the high recurrence rate and high tumor heterogeneity. Ferroptosis, a novel mode of cell death driven by iron-dependent lipid peroxidation, has been implicated in the development and therapeutic response of various tumors, including HCC. In this review, we discuss the regulatory network of ferroptosis, describe the crosstalk between ferroptosis and HCC-related signaling pathways, and elucidate the potential role of ferroptosis in various treatment modalities for HCC, such as systemic therapy, radiotherapy, immunotherapy, interventional therapy and nanotherapy, and applications in the diagnosis and prognosis of HCC, to provide a theoretical basis for the diagnosis and treatment of HCC to effectively improve the survival of HCC patients.

Spatiotemporal changes in snow depth and the influence factors in China from 1979 to 2019.

Snow depth is an important parameter to characterize the characteristics of snow cover, and it is also one of the most sensitive response factors to regional climate change. However, the extent of snow depth variability and its driving mechanisms are still unknown in China. Therefore, in this study, we used the regression analysis, root-mean-square error analysis, anomalous year analysis, and correlation analysis methods to explore the spatiotemporal variation characteristics of snow depth in China from 1979 to 2019 based on the reanalysis snow depth dataset. The results show that (1) the snow distribution in China is obviously spatially heterogeneous, and the southeastern, western, and southern regions of the Qinghai-Tibet Plateau, northern Xinjiang, and northeastern China have high values of snow depth; (2) the high-value regions are also the sensitive regions for anomalous variations in snow depth in China; (3) in the past 41 years, the interannual variability of snow depth in China has shown a significantly decreasing trend, and the linear tendency of snow depth is - 0.093 cm/10 a (p < 0.01) and the snow depth in four seasons showed a decreasing trend (p < 0.05); and (4) the driving factors of snow heterogeneity are dissimilar in different regions and seasons. In temperate zones, average air temperature is the main factor affecting snow depth in cold temperature, mid temperature, and warm temperature zones; the maximum air temperature is the main factor affecting snow depth in mid temperate and warm temperate zones. Both the minimum air temperature and the average land-surface temperature are important factors affecting the snow depth in the cold temperate, mid temperate and warm temperate zones, and all passed the significance test of 0.01.

Long noncoding RNA HAND2-AS1: A crucial regulator of malignancy.

Long non-coding RNAs (LncRNAs) are single-stranded RNAs over 200 nucleotides in length that have no protein-coding function and have long been considered non-functional by-products of transcription. Recent studies have shown that dysregulation of lncRNAs may be involved in the malignant biological behavior of tumors. Targeted regulation of lncRNAs has become a research focus of anti-tumor treatment. LncRNAs heart and neural crest derivatives expressed 2 antisense RNA 1 (HAND2-AS1) was down-regulated in various tumors and can be used as a critical tumor regulator to modulate tumor cells proliferation, apoptosis, metastasis, invasion, metabolism and drug resistance. Additionally, aberrantly expressed HAND2-AS1 was closely related to the clinical pathological characteristics of cancer patients and serve as a promising tumor diagnostic and prognostic biomarker. This article aims to review the roles of HAND2-AS1 in tumorigenesis and development, as well as the underlying molecular mechanisms and clinical significance.

Contribution of local and surrounding anthropogenic emissions to a particulate matter pollution episode in Zhengzhou, Henan, China.

In this study, we simulated the spatial and temporal processes of a particulate matter (PM) pollution episode from December 10-29, 2019, in Zhengzhou, the provincial capital of Henan, China, which has a large population and severe PM pollution. As winter is the high incidence period of particulate pollution, winter statistical data were selected from the pollutant observation stations in the study area. During this period, the highest concentrations of PM2.5 (atmospheric PM with a diameter of less than 2.5 µm) and PM10 (atmospheric PM with a diameter of less than 10 µm) peaked at 283 µg m-3 and 316 µg m-3, respectively. The contribution rates of local and surrounding regional emissions within Henan (emissions from the regions to the south, northwest, and northeast of Zhengzhou) to PM concentrations in Zhengzhou were quantitatively analyzed based on the regional Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). Model evaluation showed that the WRF/Chem can accurately simulate the spatial and temporal variations in the PM concentrations in Zhengzhou. We found that the anthropogenic emissions south of Zhengzhou were the main causes of high PM concentrations during the studied episode, with contribution rates of 14.39% and 16.34% to PM2.5 and PM10, respectively. The contributions of anthropogenic emissions from Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.94% and 7.29%, respectively. The contributions of anthropogenic emissions from the area northeast of Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.42% and 7.18%, respectively. These two areas had similar contributions to PM pollution in Zhengzhou. The area northeast of Zhengzhou had the lowest contributions to the PM2.5 and PM10 concentrations in Zhengzhou (5.96% and 5.40%, respectively).

Research progress of circulating non-coding RNA in diagnosis and treatment of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a highly malignant tumor that carries a significant risk of morbidity and mortality. This type of cancer is prevalent in Asia due to the widespread presence of risk factors. Unfortunately, HCC often goes undetected until it has reached an advanced stage, making early detection and treatment critical for better outcomes. Alpha-fetoprotein (AFP) is commonly used in clinical practice for diagnosing HCC, but its sensitivity and specificity are limited. While surgery and liver transplantation are the main radical treatments, drug therapy and local interventions are better options for patients with advanced HCC. Accurately assessing treatment efficacy and adjusting plans in a timely manner can significantly improve the prognosis of HCC. Non-coding RNA gene transcription products cannot participate in protein production, but they can regulate gene expression and protein function through the regulation of transcription and translation processes. These non-coding RNAs have been found to be associated with tumor development in various types of tumors. Noncoding RNA released by tumor or blood cells can circulate in the blood and serve as a biomarker for diagnosis, prognosis, and efficacy assessment. This article explores the unique role of circulating noncoding RNA in HCC from various perspectives.

IFT20 Confers Paclitaxel Resistance by Triggering ß-arrestin-1 to Modulate ASK1 Signaling in Breast Cancer.

ABSTRACT: System paclitaxel-based chemotherapy is the first-line treatment regimen of defense against breast cancer, but inherent or acquired chemotherapy resistance remains a major obstacle in breast cancer therapy. Elucidating the molecular mechanism of chemoresistance is essential to improve the outcome of patients with breast cancer. Here, we demonstrate that intraflagellar transport 20 (IFT20) is positively associated with shorter relapse-free survival in patients with system paclitaxel-based chemotherapy. High-expressed IFT20 in breast cancer cells increases resistance to cell death upon paclitaxel treatment; in contrast, IFT20 knockdown enhances apoptosis in breast cancer cells in response to paclitaxel. Mechanistically, IFT20 triggers ß-arrestin-1 to bind with apoptosis signal-regulating kinase 1 (ASK1) and promotes the ubiquitination of ASK1 degradation, leading to attenuating ASK1 signaling and its downstream JNK cascades, which helps cells to escape from cell death during paclitaxel treatment. Our results reveal that IFT20 drives paclitaxel resistance through modulating ASK1 signaling and identifies IFT20 as a potential molecular biomarker for predicting the response to paclitaxel therapeutic in breast cancer. IMPLICATIONS: IFT20 drives paclitaxel resistance through modulating ASK1 signaling and IFT20 may act as a potential molecular biomarker for predicting the response to paclitaxel therapeutic in breast cancer.

Roles and Molecular Mechanisms of Biomarkers in Hepatocellular Carcinoma with Microvascular Invasion: A Review.

Hepatocellular carcinoma (HCC) being a leading cause of cancer-related death, has high associated mortality and recurrence rates. It has been of great necessity and urgency to find effective HCC diagnosis and treatment measures. Studies have shown that microvascular invasion (MVI) is an independent risk factor for poor prognosis after hepatectomy. The abnormal expression of biomacromolecules such as circ-RNAs, lncRNAs, STIP1, and PD-L1 in HCC patients is strongly correlated with MVI. Deregulation of several markers mentioned in this review affects the proliferation, invasion, metastasis, EMT, and anti-apoptotic processes of HCC cells through multiple complex mechanisms. Therefore, these biomarkers may have an important clinical role and serve as promising interventional targets for HCC. In this review, we provide a comprehensive overview on the functions and regulatory mechanisms of MVI-related biomarkers in HCC.

Liver fibrosis and MAFLD: the exploration of multi-drug combination therapy strategies.

In recent years, the prevalence of metabolic-associated fatty liver disease (MAFLD) has reached pandemic proportions as a leading cause of liver fibrosis worldwide. However, the stage of liver fibrosis is associated with an increased risk of severe liver-related and cardiovascular events and is the strongest predictor of mortality in MAFLD patients. More and more people believe that MAFLD is a multifactorial disease with multiple pathways are involved in promoting the progression of liver fibrosis. Numerous drug targets and drugs have been explored for various anti-fibrosis pathways. The treatment of single medicines is brutal to obtain satisfactory results, so the strategies of multi-drug combination therapies have attracted increasing attention. In this review, we discuss the mechanism of MAFLD-related liver fibrosis and its regression, summarize the current intervention and treatment methods for this disease, and focus on the analysis of drug combination strategies for MAFLD and its subsequent liver fibrosis in recent years to explore safer and more effective multi-drug combination therapy strategies.

Reprogramming of central carbon metabolism in hepatocellular carcinoma.

In multicellular organisms, nutrient uptake and its metabolism are subject to stringent regulation to maintain cellular integrity and prevent aberrant cell proliferation. However, the altered signaling pathways and gene expression disorders in hepatocellular carcinoma (HCC) induce the transformation of metabolic patterns. The reprogrammed metabolic pattern not only conferred HCC cells viability in nutrient-deficient environments, but also contributed to the formation of a unique immune surveillance barrier. Furthermore, in this metabolic pattern, the accumulation of a large number of oxidation products in cells also activates tumor-related signaling pathways. Therefore, the exploration of underlying molecular mechanisms of the metabolic switch will help to improve therapeutic strategies for HCC. We systematically reviewed the landmark events and current research breakthroughs in the study of glucometabolic reprogramming in HCC. Focusing on the central carbon metabolism, the internal energy conversion in HCC and its cancerous mechanisms were fully explained. Furthermore, we also discussed the HCC-specific acellular regulation, metabolic switch of cancer stem cells, oxidative stress adaptation and the formation of immunosuppressive microenvironment, hoping to provide insights for future basic and clinical research.

Glucometabolic reprogramming: From trigger to therapeutic target in hepatocellular carcinoma.

Glucose, the central macronutrient, releases energy as ATP through carbon bond oxidation and supports various physiological functions of living organisms. Hepatocarcinogenesis relies on the bioenergetic advantage conferred by glucometabolic reprogramming. The exploitation of reformed metabolism induces a uniquely inert environment conducive to survival and renders the hepatocellular carcinoma (HCC) cells the extraordinary ability to thrive even in the nutrient-poor tumor microenvironment. The rewired metabolism also confers a defensive barrier which protects the HCC cells from environmental stress and immune surveillance. Additionally, targeted interventions against key players of HCC metabolic and signaling pathways provide promising prospects for tumor therapy. The active search for novel drugs based on innovative mutation targets is warranted in the future for effectively treating advanced HCC and the preoperative downstage. This article aims to review the regulatory mechanisms and therapeutic value of glucometabolic reprogramming on the disease progression of HCC, to gain insights into basic and clinical research.

Contribution of anthropogenic CO2 in China to global radiative forcing and its offset by the ecosystem during 2000-2015.

As the world's largest developing country, quantifying China's CO2 contribution to global warming is important for assessing the climate effects of anthropogenic and natural factors. We used global CO2 assimilation data from 2000 to 2015 and a carbon-climate parameterized scheme to analyze anthropogenic carbon emissions and their climatic effects while considering the climate effects of the terrestrial ecosystem carbon sink. Three results are notable: (1) From 2000 to 2015, global anthropogenic emissions increased from 2.48 to 3.45 mol m-2 , and net emission (sum of anthropogenic and natural emissions) rose from 1.24 to 2.51 mol m-2 ; China's contribution of anthropogenic emissions to global anthropogenic emission was 34.78% and to net emission 39.65%. (2) By 2015, radiative forcing (RF) caused by CO2 absorption in the global terrestrial ecosystem was -0.18 Wm-2 , and this offset accounts for 30.96% of the warming effect of global anthropogenic carbon emissions; in China, RF caused by the terrestrial ecosystem was -0.04 Wm-2 , and this offset accounts for 20.27% of the warming effect of China's anthropogenic carbon emissions. (3) Using CO2 assimilation data and sectoral inventory data, China's contribution of carbon emissions to global RF was 10.02% and 9.73%, respectively, and China's contribution of net RF to global RF was 7.93%. Our findings highlight the importance of ecosystems on mitigating climate warming.

Exosomal Non-Coding RNAs: Regulatory and Therapeutic Target of Hepatocellular Carcinoma.

Exosomes are small extracellular vesicles secreted by most somatic cells, which can carry a variety of biologically active substances to participate in intercellular communication and regulate the pathophysiological process of recipient cells. Recent studies have confirmed that non-coding RNAs (ncRNAs) carried by tumor cell/non-tumor cell-derived exosomes have the function of regulating the cancerous derivation of target cells and remodeling the tumor microenvironment (TME). In addition, due to the unique low immunogenicity and high stability, exosomes can be used as natural vehicles for the delivery of therapeutic ncRNAs in vivo. This article aims to review the potential regulatory mechanism and the therapeutic value of exosomal ncRNAs in hepatocellular carcinoma (HCC), in order to provide promising targets for early diagnosis and precise therapy of HCC.

LncRNA DiGeorge syndrome critical region gene 5: A crucial regulator in malignant tumors.

Long non-coding RNA (lncRNA), a subgroup of ncRNA with a length of more than 200 nt without protein coding function, has been recognized by the academia for its mediating effects of dysregulated expression on the tumorigenesis and development of a variety of tumors. LncRNA DiGeorge syndrome critical region gene 5 (DGCR5), originally found to induce DiGeorge syndrome, has been confirmed to be extremely dysregulated in multiple tumors, which mediates the malignant phenotypes of hepatocellular carcinoma, pancreatic cancer, lung cancer, etc. through the regulation of Wnt/ß-catenin, MEK/ERK1/2 and other cancerous signaling pathways as a molecular sponge. Researches on the cancerous derivation-related pathways involved in DGCR5 can provide potential molecular intervention targets for tumor precision treatment. Moreover, liquid biopsy based on the detection of DGCR5 in body fluids is also expected to provide a non-invasive evaluation method for the early diagnosis and prognostic evaluation of malignant tumors.

Exosomes in hepatocellular carcinoma microenvironment and their potential clinical application value.

Hepatocellular carcinoma (HCC) has become a challenging disease in the world today. Due to the limitations on the current diagnosis and treatment as well as its high metastatic ability and high recurrence rate, HCC gradually becomes the second deadliest tumor. Exosomes are one of the types of cell-derived vesicles and can carry intracellular materials such as genetic materials, lipids, and proteins. In recent years, it has been verified that exosomes are linked to numerous physiological and pathological processes, including HCC. However, how exosomes affect HCC progression remains largely unknown. In this review, the exosome-mediated cellular material transfer between cells of different types in the HCC microenvironment and their effects on the behaviors and functions of recipient cells are studied. Furthermore, we also addressed the underlying molecular mechanisms. We believe that new light on the diagnosis of this cancer as well as its treatment strategies will be shed after a collation of literature in this area.