Characterization and utilization potential of typical molybdenum tailings in Shaanxi Province, China.

Shaanxi Province is located in the most important molybdenum ore district in the world, but a lot of molybdenum tailings have been released, polluting the environment and wasting resources seriously. Taking eleven tailing samples collected at the main molybdenum tailings ponds in Shaanxi Province as the research object, the physical, chemical, and mineralogical characteristics were studied through scanning electron microscope, X-ray fluorescence, X-ray diffraction, inductively coupled plasma mass spectrometer, and others. The ecological risk and utilization potential of molybdenum tailings were investigated through leaching test, geo-accumulation index, potential ecological risk assessment, and other methods. The results demonstrated that the main chemical and mineralogical composition of various molybdenum tailings in Shaanxi Province is similar, and the predominant mineral composition is muscovite, quartz, microcline, and calcite. The potential ecological risk of heavy metals in six molybdenum tailings is high, while Pb and Cd are the main pollution risk elements. Molybdenum tailings contain considerable amounts of critical minerals with huge potential economic value, and molybdenum tailings with high environmental hazards could be converted into a possible source for critical minerals by recovering the critical minerals and repurposing the secondary tailings as an additive or cement substitute. This study provides an innovative idea for the pollution treatment of molybdenum tailings and indicates the prospect of molybdenum tailings as a secondary source for critical minerals.

FoxO1 silencing in Atp7b-/- neural stem cells attenuates high copper-induced apoptosis via regulation of autophagy.

Wilson disease (WD) is a severely autosomal genetic disorder triggered by dysregulated copper metabolism. Autophagy and apoptosis share common modulators that process cellular death. Emerging evidences suggest that Forkhead Box O1 over-expression (FoxO1-OE) aggravates abnormal autophagy and apoptosis to induce neuronal injury. However, the underlying mechanisms remain undetermined. Herein, the aim of this study was to investigate how regulating FoxO1 affects cellular autophagy and apoptosis to attenuate neuronal injury in a well-established WD cell model, the high concentration copper sulfate (CuSO4, HC)-triggered Atp7b-/- (Knockout, KO) neural stem cell (NSC) lines. The FoxO1-OE plasmid, or siRNA-FoxO1 (siFoxO1) plasmid, or empty vector plasmid was stably transfected with recombinant lentiviral vectors into HC-induced Atp7b-/- NSCs. Toxic effects of excess deposited copper on wild-type (WT), Atp7b-/- WD mouse hippocampal NSCs were tested by Cell Counting Kit-8 (CCK-8). Subsequently, the FoxO1 expression was evaluated by immunofluorescence (IF) assay, western blot (WB) and quantitative real-time polymerase chain reaction (qRT-PCR) analysis. Meanwhile, the cell autophagy and apoptosis were evaluated by flow cytometry (FC), TUNEL staining, 2,7-dichlorofluorescein diacetate (DCFH-DA), JC-1, WB, and qRT-PCR. The current study demonstrated a strong rise in FoxO1 levels in HC-treated Atp7b-/- NSCs, accompanied with dysregulated autophagy and hyperactive apoptosis. Also, it was observed that cell viability was significantly decreased with the over-expressed FoxO1 in HC-treated Atp7b-/- WD model. As intended, silencing FoxO1 effectively inhibited abnormal autophagy in HC-treated Atp7b-/- NSCs, as depicted by a decline in LC3II/I, Beclin-1, ATG3, ATG7, ATG13, and ATG16, whereas simultaneously increasing P62. In addition, silencing FoxO1 suppressed apoptosis via diminishing oxidative stress (OS), and mitochondrial dysfunction in HC-induced Atp7b-/- NSCs. Collectively, these results clearly demonstrate the silencing FoxO1 has the neuroprotective role of suppressing aberrant cellular autophagy and apoptosis, which efficiently attenuates neuronal injury in WD.

Nano-based drug delivery systems for active ingredients from traditional Chinese medicine: Harnessing the power of nanotechnology.

Introduction: Traditional Chinese medicine (TCM) is gaining worldwide popularity as a complementary and alternative medicine. The isolation and characterization of active ingredients from TCM has become optional strategies for drug development. In order to overcome the inherent limitations of these natural products such as poor water solubility and low bioavailability, the combination of nanotechnology with TCM has been explored. Taking advantage of the benefits offered by the nanoscale, various drug delivery systems have been designed to enhance the efficacy of TCM in the treatment and prevention of diseases. Methods: The manuscript aims to present years of research dedicated to the application of nanotechnology in the field of TCM. Results: The manuscript discusses the formulation, characteristics and therapeutic effects of nano-TCM. Additionally, the formation of carrier-free nanomedicines through self-assembly between active ingredients of TCM is summarized. Finally, the paper discusses the safety behind the application of nano-TCM and proposes potential research directions. Discussion: Despite some achievements, the safety of nano-TCM still need special attention. Furthermore, exploring the substance basis of TCM formulas from the perspective of nanotechnology may provide direction for elucidating the scientific intension of TCM formulas.

Vaginal microbial profile of cervical cancer patients receiving chemoradiotherapy: the potential involvement of Lactobacillus iners in recurrence.

The vaginal microbiome is an immune defense against reproductive diseases and can serve as an important biomarker for cervical cancer. However, the intrinsic relationship between the recurrence and the vaginal microbiome in patients with cervical cancer before and after concurrent chemoradiotherapy is poorly understood. Here, we analyzed 125 vaginal microbial profiles from a patient cohort of stage IB-IVB cervical cancer using 16S metagenomic sequencing and deciphered the microbial composition and functional characteristics of the recurrent and non-recurrent both before and after chemoradiotherapy. We demonstrated that the abundance of beneficial bacteria and stability of the microbial community in the vagina decreased in the recurrence group, implying the unique characteristics of the vaginal microbiome for recurrent cervical cancer. Moreover, using machine learning, we identified Lactobacillus iners as the most important biomarker, combined with age and other biomarkers (such as Ndongobacter massiliensis, Corynebacterium pyruviciproducens ATCC BAA-1742, and Prevotella buccalis), and could predict cancer recurrence phenotype before chemoradiotherapy. This study prospectively employed rigorous bioinformatics analysis and highlights the critical role of vaginal microbiota in post-treatment cervical cancer recurrence, identifying promising biomarkers with prognostic significance in the context of concurrent chemoradiotherapy for cervical cancer. The role of L. iners in determining chemoradiation resistance in cervical cancer warrants further detailed investigation. Our results expand our understanding of cervical cancer recurrence and help develop better strategies for prognosis prediction and personalized therapy.

Advances in Bioinspired Artificial Systems Enabling Biomarker-Driven Therapy.

Bioinspired molecular engineering strategies have emerged as powerful tools that significantly enhance the development of novel therapeutics, improving efficacy, specificity, and safety in disease treatment. Recent advancements have focused on identifying and utilizing disease-associated biomarkers to optimize drug activity and address challenges inherent in traditional therapeutics, such as frequent drug administrations, poor patient adherence, and increased risk of adverse effects. In this review, we provide a comprehensive overview of the latest developments in bioinspired artificial systems (BAS) that use molecular engineering to tailor therapeutic responses to drugs in the presence of disease-specific biomarkers. We examine the transition from open-loop systems, which rely on external cues, to closed-loop feedback systems capable of autonomous self-regulation in response to disease-associated biomarkers. We detail various BAS modalities designed to achieve biomarker-driven therapy, including activatable prodrug molecules, smart drug delivery platforms, autonomous artificial cells, and synthetic receptor-based cell therapies, elucidating their operational principles and practical in vivo applications. Finally, we discuss the current challenges and future perspectives in the advancement of BAS-enabled technology and envision that ongoing advancements toward more programmable and customizable BAS-based therapeutics will significantly enhance precision medicine.

Analysis of risk factors for fatty liver disease in children with Wilson's disease.

BACKGROUND AND AIMS: Many children with Wilson's disease are complicated with dyslipidemia. The aim of this study was to investigate the risk factors for the development of fatty liver disease (FLD) in children with Wilson's disease. METHODS: We evaluated sex, age, weight, the disease course, treatment course, clinical classification, alanine transaminase (ALT), aspartate transaminase, γ-glutamyl transpeptidase, total biliary acid, triglyceride, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, homocysteine, uric acid, fibrinogen (FBG), creatinine, procollagen III N-terminal propeptide, laminin, hyaluronic acid, type IV collagen, and performed receiver operating characteristic curve analysis to investigate the forecast value of individual biochemical predictors and combined predictive indicators to evaluate FLD in Wilson's disease. RESULTS: The multivariate logistic regression analysis revealed that ALT [odds ratio (OR), 1.011; 95% confidence interval (CI), 1.004-1.02; P  = 0.006], uric acid (OR, 1.01; 95% CI, 1.002-1.018; P  = 0.017), FBG (OR, 3.668; 95% CI, 1.145-13.71; P  = 0.037), creatinine (OR, 0.872; 95% CI, 0.81-0.925; P  < 0.001), and laminin (OR, 1.01; 95% CI, 1.002-1.018; P  = 0.017) acted as independent risk factors in Wilson's disease complicated with FLD. The receiver operating characteristic curves for combined predictive indicators demonstrated an area under the curve values of 0.872, which was found to be a significant predictors for FLD in Wilson's disease. CONCLUSIONS: We screened out the most important risk factors, namely ALT, uric acid, creatinine, FBG, and laminin for Wilson's disease complicated with FLD. The joint prediction achieved is crucial for identifying children with Wilson's disease complicated with FLD.

Constructing a Prognostic Model of Uterine Corpus Endometrial Carcinoma and Predicting Drug-Sensitivity Responses Using Programmed Cell Death-Related Pathways.

Background: Uterine Corpus Endometrial Carcinoma (UCEC) is the most common type of cancer that develops in the uterus, specifically originating from the endometrium, the inner lining of the uterus. Programmed cell death (PCD) is a highly regulated process that eliminates damaged, aged, or unwanted cells in the body. Dysregulation of PCD pathways can contribute to the formation and progression of various cancers, including UCEC. Methods: Fourteen PCD pathways (autophagy-dependent cell death, alkaliptosis, apoptosis, cuproptosis, entotic cell death, ferroptosis, immunogenic cell death, lysosome-dependent cell death, MPT-driven necrosis, necroptosis, netotic cell death, oxeiptosis, parthanatos, and pyroptosis) were involved in building a prognostic signature. The model was trained and tested using data from the TCGA-UCEC and validated with the GSE119041 dataset. Results: A 12-gene PCD signature (DRAM1, ELAPOR1, MAPT, TRIM58, UCHL1, CDKN2A, CYFIP2, AKT2, LINC00618, TTPA, TRIM46, and NOS2) was established and validated in an independent dataset. UCEC patients with a high PCD score (PCDS) exhibited worse prognosis. Furthermore, PCDS was found to be associated with immune related cells and key tumor microenvironment components through multiple methods. It was observed that UCEC patients with a high PCD score may not benefit from immunotherapy, but some chemo drugs like Bortezomib may be useful. Conclusion: In conclusion, a novel PCD model was established by comprehensively analyzing diverse cell death patterns. This model accurately predicts the clinical prognosis and drug sensitivity of UCEC. The findings suggest that the PCD signature can serve as a valuable tool in assessing prognosis and guiding treatment decisions for UCEC patients.

Serum biomarkers in patients with drug-resistant epilepsy: a proteomics-based analysis.

Objective: To investigate the serum biomarkers in patients with drug-resistant epilepsy (DRE). Methods: A total of 9 DRE patients and 9 controls were enrolled. Serum from DRE patients was prospectively collected and analyzed for potential serum biomarkers using TMT18-labeled proteomics. After fine quality control, bioinformatics analysis was conducted to find differentially expressed proteins. Pathway enrichment analysis identified some biological features shared by differential proteins. Protein-protein interaction (PPI) network analysis was further performed to discover the core proteins. Results: A total of 117 serum differential proteins were found in our study, of which 44 were revised upwards and 73 downwards. The up-regulated proteins mainly include UGGT2, PDIA4, SEMG1, KIAA1191, CCT7 etc. and the down-regulated proteins mainly include ROR1, NIF3L1, ITIH4, CFP, COL11A2 etc. Pathway enrichment analysis identified that the upregulated proteins were mainly enriched in processes such as immune response, extracellular exosome, serine-type endopeptidase activity and complement and coagulation cascades, and the down-regulated proteins were enriched in signal transduction, extracellular exosome, zinc/calcium ion binding and metabolic pathways. PPI network analysis revealed that the core proteins nodes include PRDX6, CAT, PRDX2, SOD1, PARK7, GSR, TXN, ANXA1, HINT1, and S100A8 etc. Conclusion: The discovery of these differential proteins enriched our understanding of serum biomarkers in patients with DRE and potentially provides guidance for future targeted therapy.

Global insights into endophytic bacterial communities of terrestrial plants: Exploring the potential applications of endophytic microbiota in sustainable agriculture.

Endophytic microorganisms are indispensable symbionts during plant growth and development and often serve functions such as growth promotion and stress resistance in plants. Therefore, an increasing number of researchers have applied endophytes for multifaceted phytoremediation (e.g., organic pollutants and heavy metals) in recent years. With the availability of next-generation sequencing technologies, an increasing number of studies have shifted the focus from culturable bacteria to total communities. However, information on the composition, structure, and function of bacterial endophytic communities is still not widely synthesized. To explore the general patterns of variation in bacterial communities between plant niches, we reanalyzed data from 1499 samples in 30 individual studies from different continents and provided comprehensive insights. A group of bacterial genera were commonly found in most plant roots and shoots. Our analysis revealed distinct variations in the diversity, composition, structure, and function of endophytic bacterial communities between plant roots and shoots. These variations underscore the sophisticated mechanisms by which plants engage with their endophytic microbiota, optimizing these interactions to bolster growth, health, and resilience against stress. Highlighting the strategic role of endophytic bacteria in promoting sustainable agricultural practices and environmental stewardship, our study not only offers global insights into the endophytic bacterial communities of terrestrial plants but also underscores the untapped potential of these communities as invaluable resources for future research.

A novel mitochondrial unfolded protein response-related risk signature to predict prognosis, immunotherapy and sorafenib sensitivity in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common cause of cancer-associated death worldwide. The mitochondrial unfolded protein response (UPRmt) not only maintains mitochondrial integrity but also regulates cancer progression and drug resistance. However, no study has used the UPRmt to construct a prognostic signature for HCC. This work aimed to establish a novel signature for predicting patient prognosis, immune cell infiltration, immunotherapy, and chemotherapy response based on UPRmt-related genes (MRGs). Transcriptional profiles and clinical information were obtained from the TCGA and ICGC databases. Cox regression and LASSO regression analyses were applied to select prognostic genes and develop a risk model. The TIMER algorithm was used to investigate immunocytic infiltration in the high- and low-risk subgroups. Here, two distinct clusters were identified with different prognoses, immune cell infiltration statuses, drug sensitivities, and response to immunotherapy. A risk score consisting of seven MRGs (HSPD1, LONP1, SSBP1, MRPS5, YME1L1, HDAC1 and HDAC2) was developed to accurately and independently predict the prognosis of HCC patients. Additionally, the expression of core MRGs was confirmed by immunohistochemistry (IHC) staining, single-cell RNA sequencing, and spatial transcriptome analyses. Notably, the expression of prognostic MRGs was significantly correlated with sorafenib sensitivity in HCC and markedly downregulated in sorafenib-treated HepG2 and Huh7 cells. Furthermore, the knockdown of LONP1 decreased the proliferation, invasion, and migration of HepG2 cells, suggesting that upregulated LONP1 expression contributed to the malignant behaviors of HCC cells. To our knowledge, this is the first study to investigate the consensus clustering algorithm, prognostic potential, immune microenvironment infiltration and drug sensitivity based on the expression of MRGs in HCC. In summary, the UPRmt-related classification and prognostic signature could assist in determining the prognosis and personalized therapy of HCC patients from the perspectives of predictive, preventative and personalized medicine.

Atractylodes macrocephala III suppresses EMT in cervical cancer by regulating IGF2BP3 through ETV5.

Atractylodes macrocephala III (ATL III), with anti-inflammatory and antitumor effects, is the main compound of Atractylodes macrocephala. Whether ATL III has an effect on cervical cancer and the specific mechanism are still unclear. Here, we investigated the effects of ATL III on cervical cancer cells at different concentrations and found that ATL III downregulates insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3), which was found to be highly expressed in cervical cancer tissue by RNA-Seq. In this study, we found that ATL III promotes apoptosis and regulates epithelial-mesenchymal transition (EMT) in cervical cancer cells (HeLa and SiHa cells) and that IGF2BP3 is a common target gene of ATL III in HeLa and SiHa cells. The expression level of IGF2BP3 in cervical cancer cells was proportional to their migration and invasion abilities. This was verified by transfection of cells with a small interfering RNA and an IGF2BP3 overexpression plasmid. After ATL III treatment, the migration and invasion abilities of cervical cancer cells were obviously reduced, but these effects were attenuated after overexpression of IGF2BP3. In addition, the transcription factor IGF2BP3 was predicted by the JASPAR system. After intersection with our sequencing results, we verified the promotional effect of ETV5 (ETS translocation variant 5) on IGF2BP3 and found that ALT III inhibited ETV5. In general, our research showed that ATL III inhibits the migration and invasion of cervical cancer cells by regulating IGF2BP3 through ETV5.

Transcription factors-related molecular subtypes and risk prognostic model: exploring the immunogenicity landscape and potential drug targets in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, with a high mortality rate and poor prognosis. Mutated or dysregulated transcription factors (TFs) are significantly associated with carcinogenesis. The aim of this study was to develop a TF-related prognostic risk model to predict the prognosis and guide the treatment of HCC patients. METHODS: RNA sequencing data were obtained from the TCGA database. The ICGC and GEO databases were used as validation datasets. The consensus clustering algorithm was used to classify the molecular subtypes of TFs. Kaplan‒Meier survival analysis and receiver operating characteristic (ROC) analysis were applied to evaluate the prognostic value of the model. The immunogenic landscape differences of molecular subtypes were evaluated by the TIMER and xCell algorithms. Autodock analysis was used to predict possible binding sites of trametinib to TFs. RT‒PCR was used to verify the effect of trametinib on the expression of core TFs. RESULTS: According to the differential expression of TFs, HCC samples were divided into two clusters (C1 and C2). The survival time, signaling pathways, abundance of immune cell infiltration and responses to chemotherapy and immunotherapy were significantly different between C1 and C2. Nine TFs with potential prognostic value, including HMGB2, ESR1, HMGA1, MYBL2, TCF19, E2F1, FOXM1, CENPA and ZIC2, were identified by Cox regression analysis. HCC patients in the high-risk group had a poor prognosis compared with those in the low-risk group (p < 0.001). Moreover, the area under the ROC curve (AUC) values of the 1-year, 2-year and 3-year survival rates were 0.792, 0.71 and 0.695, respectively. The risk model was validated in the ICGC database. Notably, trametinib sensitivity was highly correlated with the expression of core TFs, and molecular docking predicted the possible binding sites of trametinib with these TFs. More importantly, the expression of core TFs was downregulated under trametinib treatment. CONCLUSIONS: A prognostic signature with 9 TFs performed well in predicting the survival rate and chemotherapy/immunotherapy effect of HCC patients. Trimetinib has potential application value in HCC by targeting TFs.

Short-term effectiveness of single-dose intranasal spray COVID-19 vaccine against symptomatic SARS-CoV-2 Omicron infection in healthcare workers: a prospective cohort study.

Background: The pivotal phase 3 efficacy clinical trial has demonstrated that a two-dose regimen of dNS1-RBD (Beijing Wantai Biological Pharmacy Enterprise, Beijing, China) is well-tolerated and provides wide protection against SARS-CoV-2 infection. However, the effectiveness of a single-dose regimen is still unknown. We aimed to estimate the effectiveness of one-dose of dNS1-RBD against symptomatic Omicron infections in real-world conditions. Methods: This prospective cohort study was conducted during an Omicron outbreak among healthcare workers in Xiamen, China, from December 22, 2022 to January 16, 2023. Participants chose to receive single-dose of dNS1-RBD or remain unvaccinated based on personal preference. Healthcare workers daily validated their SARS-CoV-2 infection status, using either RT-PCR or rapid antigen test. A survey questionnaire was conducted to gather information on acute symptoms from individuals infected with SARS-CoV-2. The primary outcome was the symptomatic SARS-CoV-2 infections after enrollment in the dNS1-RBD recipients or the control group among all participants and by prior COVID-19 vaccination status. Findings: On December 22, 2022, a total of 1391 eligible participants without a history of prior SARS-CoV-2 infection were enrolled. Among them, 550 received single-dose of dNS1-RBD, while 841 remained unvaccinated. In the total cohort, the range of follow-up time was 1∼26 days. During the study period, a total of 880 symptomatic SARS-CoV-2 infections were identified in the total cohort. The adjusted vaccine effectiveness against symptomatic SARS-CoV-2 infections and the infections requiring medical attention were 19.0% (95% CI: 6.7, 29.7, P = 0.004) and 59.4% (95% CI: 25.1, 78.0, P = 0.004) in the total cohort, 11.6% (95% CI: -2.4, 23.7, P = 0.100) and 55.3% (95% CI: 15.3, 76.4, P = 0.014) in the participants with inactivated COVID-19 vaccination history, as well as 87.0% (95% CI: 72.6, 93.9, P < 0.001) and 84.2% (95% CI: -41.8, 98.2, P = 0.099) in the naïve participants, respectively. Interpretation: When administered as a booster to individuals with a history of inactivated COVID-19 vaccination, a single-dose of dNS1-RBD provides protection against infections requiring medical attention at least in the short-term after vaccination. The data also showed that a single-dose of dNS1-RBD is protective against symptomatic SARS-CoV-2 infections as a primary immunization for individuals without prior exposure, but due to the limited sample size of naïve participants, further research with a larger sample size is needed to make a solid conclusion. Funding: Xiamen Science and Technology Bureau 2022 General Science and Technology Plan Project and the Bill & Melinda Gates Foundation.

Pharmacokinetics, Pharmacodynamics, and Safety of Single Dose HSK7653 Tablets in Chinese Subjects with Normal or Impaired Renal Function.

OBJECTIVE: HSK7653 is a novel, ultralong-acting dipeptidyl peptidase-4 (DPP-4) inhibitor, promising for type 2 diabetes mellitus with a dosing regimen of once every 2 weeks. This trial investigates the pharmacokinetics (PKs), pharmacodynamics (PDs),and safety of HSK7653 in outpatients with normal or impaired renal function. METHODS: This is a multicenter, open-label, nonrandomized, parallel-controlled phase I clinical study that investigates the pharmacokinetic profiles of HSK7653 after a single oral administration in 42 subjects with mild (n = 8), moderate (n = 10), severe renal impairment (n = 10), and end-stage renal disease (without dialysis, n = 5) compared with matched control subjects with normal renal function (n = 9). Safety was evaluated throughout the study, and the pharmacodynamic effects were assessed on the basis of a DPP-4 inhibition rate. RESULTS: HSK7653 exposure levels including the maximum plasma concentration (Cmax), area under the plasma concentration-time curve from zero to last time of quantifiable concentration (AUC0-t), and area under the plasma concentration-time curve from zero to infinity (AUC0-inf) showed no significant differences related to the severity of renal impairment. Renal clearance (CLR) showed a certain downtrend along with the severity of renal impairment. The CLR of the group with severe renal impairment and the group with end-stage renal disease were basically similar. The DPP-4 inhibition rate-time curve graph was similar among the renal function groups. All groups had favorable safety, and no serious adverse events occurred. CONCLUSIONS: HSK7653 is a potent oral DPP-4 inhibitor with a long plasma half-life, supporting a dosing regimen of once every 2 weeks. Impaired renal function does not appear to impact the pharmacokinetic and pharmacodynamic properties of HSK7653 after a single administration in Chinese subjects. HSK7653 is also well tolerated without an increase in adverse events with increasing renal impairment. These results indicate that dose adjustment of HSK7653 may not be required in patients with renal impairment. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05497297.

Genetic architecture of ecological divergence between Oryza rufipogon and Oryza nivara.

Ecological divergence due to habitat difference plays a prominent role in the formation of new species, but the genetic architecture during ecological speciation and the mechanism underlying phenotypic divergence remain less understood. Two wild ancestors of rice (Oryza rufipogon and Oryza nivara) are a progenitor-derivative species pair with ecological divergence and provide a unique system for studying ecological adaptation/speciation. Here, we constructed a high-resolution linkage map and conducted a quantitative trait locus (QTL) analysis of 19 phenotypic traits using an F2 population generated from a cross between the two Oryza species. We identified 113 QTLs associated with interspecific divergence of 16 quantitative traits, with effect sizes ranging from 1.61% to 34.1% in terms of the percentage of variation explained (PVE). The distribution of effect sizes of QTLs followed a negative exponential, suggesting that a few genes of large effect and many genes of small effect were responsible for the phenotypic divergence. We observed 18 clusters of QTLs (QTL hotspots) on 11 chromosomes, significantly more than that expected by chance, demonstrating the importance of coinheritance of loci/genes in ecological adaptation/speciation. Analysis of effect direction and v-test statistics revealed that interspecific differentiation of most traits was driven by divergent natural selection, supporting the argument that ecological adaptation/speciation would proceed rapidly under coordinated selection on multiple traits. Our findings provide new insights into the understanding of genetic architecture of ecological adaptation and speciation in plants and help effective manipulation of specific genes or gene cluster in rice breeding.

Spatial distribution characteristics, risk assessment and management strategies of tailings ponds in China.

The tailings ponds (TPS) stemming from mineral resource exploitation are becoming a global challenge due to their high hazards and pollution to the surrounding area. However, previous studies on China's tailings ponds have either focused on a single or few areas, or the number of tailings ponds varies greatly. A systematic assessment of the number, distribution characteristics, potential risks and management strategies of the tailings pond in China is lacking. This study obtained the latest list of tailings ponds in China up to the end of 2022 based on official information and assessed their spatial distribution characteristics, environmental risk and management strategies simultaneously. The results demonstrated that the distribution of TPS in China is relatively clustered and multiple factors affected the spatial distribution of TPS in China, which were concentrated in areas with low economic and population density, convenient transportation, and a developed water system. The risk assessment suggested that 1803 TPS had large or significant environmental risks, which were mainly distributed in Yunnan, Hunan, Shaanxi and Jiangxi provinces. To solve the problem of tailings ponds from the source, the key point of tailings pond management in China should be adjusted from the prevention of pollution or dam break accidents to the full resource utilization of tailings. In summary, this study will provide a scientific basis for the risk control of TPS and an innovative idea for the management of other solid waste.

Apoptosis-related prognostic biomarkers and potential targets for acute kidney injury based on machine learning algorithm and in vivo experiments.

Acute kidney injury (AKI) is a common critical illness in hospitalized patients, characterized by a rapid decline in kidney function over a short period, which can seriously endanger the patient's life. Currently, there is a lack of precise and universal AKI diagnostic biomarkers in clinical practice. In this study, weighted gene coexpression network analysis (WGCNA), differential expression analysis, univariate and multivariate logistic regression analyses, receiver operating characteristic (ROC) curves, and immune cell infiltration were performed to identify apoptosis-related biomarkers that can be used for AKI diagnosis. Three core apoptosis-related genes (ARGs), CBFB, EGF and COL1A1, were identified as AKI biomarkers. More importantly, an apoptosis-related signature containing three hub ARGs was validated as a diagnostic model. The hub genes exhibited good correlations with glomerular filtration rate (GFR) and serum creatinine (SCr) in the Nephroseq kidney disease database. Additionally, CIBERSORT immune infiltration analysis indicated that these core ARGs may affect immune cell recruitment and infiltration in AKI patients. Subsequently, we investigated the alteration of the expression levels of three core ARGs in AKI samples using single-cell RNA sequencing analysis and analyzed the cell types that mainly expressed these ARGs. More importantly, the expression of core ARGs was validated in folic acid- and cisplatin-induced AKI mouse models. In summary, our study identified three diagnostic biomarkers for AKI, explored the roles of ARGs in AKI progression and provided new ideas for the clinical diagnosis and treatment of AKI.

Identification of lncRNA-miRNA-mRNA Networks in the Lenticular Nucleus Region of the Brain Contributes to Hepatolenticular Degeneration Pathogenesis and Therapy.

Long non-coding RNAs (lncRNAs) are a recently discovered group of non-coding RNAs that play a crucial role in the regulation of various human diseases, especially in the study of nervous system diseases which has garnered significant attention. However, there is limited knowledge on the identification and function of lncRNAs in hepatolenticular degeneration (HLD). The objective of this study was to identify novel lncRNAs and determine their involvement in the networks associated with HLD. We conducted a comprehensive analysis of RNA sequencing (RNA-seq) data, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and computational biology to identify novel lncRNAs and explore their potential mechanisms in HLD. We identified 212 differently expressed lncRNAs, with 98 upregulated and 114 downregulated. Additionally, 32 differently expressed mRNAs were found, with 15 upregulated and 17 downregulated. We obtained a total of 1131 pairs of co-expressed lncRNAs and mRNAs by Pearson correlation test and prediction and annotation of the lncRNA-targeted miRNA-mRNA network. The differential lncRNAs identified in this study were found to be involved in various biological functions and signaling pathways. These include translational initiation, motor learning, locomotors behavior, dioxygenase activity, integral component of postsynaptic membrane, neuroactive ligand-receptor interaction, nuclear factor-kappa B (NF-κB) signaling pathway, cholinergic synapse, sphingolipid signaling pathway, and Parkinson's disease signaling pathway, as revealed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Six lncRNAs, including XR_001782921.1 (P < 0.01), XR_ 001780581.1 (P < 0.01), ENSMUST_00000207119 (P < 0.01), XR_865512.2 (P < 0.01), TCONS_00005916 (P < 0.01), and TCONS_00020683 (P < 0.01), showed significant differences in expression levels between the model group and normal group by RT-qPCR. Among these, four lncRNAs (TCONS_00020683, XR_865512.2, XR_001780581.1, and ENSMUST00000207119) displayed a high degree of conservation. This study provides a unique perspective for the pathogenesis and therapy of HLD by constructing the lncRNA-miRNA-mRNA network. This insight provides a foundation for future exploration in this field.