Prediction of heavy metal ion distribution and Pb and Zn ion concentrations in the tailing pond area.

The pollution caused by tailings ponds has resulted in ecological damage, with soil contamination significantly impacting the daily lives of residents in the vicinity of mining areas and the future development of mining areas. This study assesses the transport status of heavy metal pollution in tailings areas and predicts its impact on future pollution levels. This study focused on lead-zinc tailing ponds, exploring the spatial and chemical distribution characteristics of heavy metals based on the distributions of Pb, Zn, As, Cu, Cr, Cd, Hg, and Ge ions. The concentrations of the major heavy metal ions Pb and Zn in tailings ponds were predicted via the exponential smoothing method. ① The total accumulation of Pb and Zn in the mine tailings ranges from 936.74~1212.61 mg/kg and 1611.85~2191.47 mg/kg, much greater than the total accumulation of the remaining six heavy metals. The total accumulation of associated heavy metal Cu was high, and the lowest total heavy metals were Hg and Ge at only 0.19 mg/kg and 1.05 mg/kg. ② The analyses of soil heavy metal chemical forms reveal that the heavy metals Pb and Zn had the highest exchangeable state content and state ratio and the strongest transport activity in the industrial plaza and village soils. Pb and Zn are the heavy metals with the greatest eco-environmental impacts in the mining area. ③ The predicted results show that the soil concentrations of the heavy metals Pb and Zn around the tailings area in 2026 are 1.335 and 1.191 times the predicted time starting values. The concentrations of the heavy metals Pb and Zn at the starting point of the forecast are already 3.34 and 3.02 times the upper limits of the environmental standard (according to environmental standards for gravelly grey calcium soils). These results have significant implications for heavy metal pollution risk management.

An Internet-Based Developmental Home Care Support Program Improved Maternal Psychological Symptoms and Infant Growth: A Randomized Controlled Trial.

OBJECTIVE: To examine the effects of an internet-based Developmental Home Care Support program (DHCSP) to reduce maternal psychological symptoms and improve preterm infants' physical growth outcomes. METHODS: A randomized controlled trial was conducted. The mother-infant dyads (nm = 34, np = 40) were randomly assigned to either the DHCSP intervention group or the control group. Data were collected at discharge (T0), 1-month corrected age (T1), and 2-month follow-up (T2), including mothers' postpartum depressive and posttraumatic stress disorder (PTSD) symptoms and mother-proxy infants' body length, weight, and head circumference. RESULTS: There were no significant differences in sociodemographic characteristics between the 2 groups at T0, except for mothers' age and monthly household income (both P = .01). Mothers in the DHCSP group reported significantly higher decreases in depression symptoms (ß = -2.24; 95% confidence interval [CI], -4.31 to -0.16, P = .03), and their preterm infants showed significantly more increases in body length (ß = 2.09; 95% CI, 0.30-3.87, P = .02) than the control participants at T2. The 2 groups did not show significant differences in mothers' PTSD symptoms or infants' body weight and head circumference. CONCLUSION: The internet-based DHCSP intervention was effective in improving mothers' depressive symptoms and infants' body length.

Association between breastfeeding duration and neurodevelopment in Chinese children aged 2 to 3 years.

OBJECTIVE: The aim of this study was to explore the relationship between breastfeeding duration and neurodevelopment in children aged 2 to 3 years in a Chinese population. METHODS: This study was based on a cross-sectional survey. The data were from the National Nutrition and Health Systematic Survey for children in China which was conducted from 2019 to 2020. Characteristics of parents and children and the breastfeeding duration were obtained using interview-administered questionnaires. Children's neuropsychological development was assessed by a trained child health care physician using the Child Psychological Development Scale. A multivariable linear regression model was used to analyze the association between breastfeeding duration and neuropsychological development. RESULTS: A total 1290 children aged 2-3 years were included in the present analysis. In multivariable linear regression models, after adjustment for potential confounders, children who were breastfed for 7-12 months had a 3.59-point increase in gross motor development (ß = 3.59; 95 % confidence interval [CI]: 1.23 to 6.34), a 3.73-point increase in fine motor development (ß = 3.73; 95 % CI: 1.09 to 6.47), and a 2.87-point in language development (ß = 2.87; 95 % CI: 1.12 to 5.31) compared with those who were never breastfed. Children who were breastfed for > 12 months had a 3.77-point increase in fine motor development (ß = 3.77; 95 % CI: 0.98 to 6.86) compared with those who were never breastfed. CONCLUSIONS: Longer breastfeeding duration was associated with increased gross motor, fine motor, and language scores in our study population. Mothers in China should be encouraged to initiate and continue breastfeeding.

The molecular regulated mechanism of METTL3 and FTO in lipid metabolism of Hu sheep.

BACKGROUND: Balanced lipid metabolism can improve the growth performance and meat quality of livestock. The m6A methylation-related genes METTL3 and FTO play important roles in animal lipid metabolism; however, the mechanism through which they regulate lipid metabolism in sheep is unclear. RESULTS: We established lipid deposition models of hepatocytes and preadipocytes in Hu sheep. In the hepatocyte lipid deposition model, the genes expression levels of FABP4, Accα, ATGL and METTL3, METTL14, and FTO-were significantly up-regulated after lipid deposition (P < 0.05). Transcriptomic and metabolomic analyses showed that lipid deposition had a significant effect on MAPK, steroid biosynthesis, and glycerophospholipid metabolism pathway in hepatocytes. The m6A methylation level decreased but the difference was not significant after METTL3 interference, and the expression levels of FABP4 and ATGL increased significantly (P < 0.05); the m6A methylation level significantly increased following METTL3 overexpression, and LPL and ATGL expression levels significantly decreased (P < 0.05), indicating that overexpression of METTL3 inhibited the expression of lipid deposition-related genes in a m6A-dependent manner. The m6A methylation level was significantly increased, ATGL expression was significantly decreased (P < 0.05), and LPL, FABP4, and Accα expression was not significantly changed following FTO interference (P > 0.05); the m6A methylation level was significantly decreased after FTO overexpression, and LPL, FABP4, and ATGL expression was significantly increased (P < 0.05), indicating that FTO overexpression increased the expression of lipid deposition-related genes in a m6A-dependent manner. Transcriptomic and metabolomic analyses showed that m6A methylation modification mainly regulated lipid metabolism through triglyceride metabolism, adipocytokine signaling, MAPK signaling, and fat digestion and absorption in hepatocytes. In the lipid deposition model of preadipocytes, the regulation of gene expression is the same as that in hepatocytes. CONCLUSIONS: METTL3 significantly inhibited the expression of lipid deposition-related genes, whereas FTO overexpression promoted lipid deposition. Our study provides a theoretical basis and reference for accurately regulating animal lipid deposition by mastering METTL3 and FTO genes to promote high-quality animal husbandry.

Constructing Asymmetric Fe-Nb Diatomic Sites to Enhance ORR Activity and Durability.

Iron-nitrogen-carbon (Fe-N-C) materials have been identified as a promising class of platinum (Pt)-free catalysts for the oxygen reduction reaction (ORR). However, the dissolution and oxidation of Fe atoms severely restrict their long-term stability and performance. Modulating the active microstructure of Fe-N-C is a feasible strategy to enhance the ORR activity and stability. Compared with common 3d transition metals (Co, Ni, etc.), the 4d transition metal atom Nb has fewer d electrons and more unoccupied orbitals, which could potentially forge a more robust interaction with the Fe site to optimize the binding energy of the oxygen-containing intermediates while maintaining stability. Herein, an asymmetric Fe-Nb diatomic site catalyst (FeNb/c-SNC) was synthesized, which exhibited superior ORR performance and stability compared with those of Fe single-atom catalysts (SACs). The strong interaction within the Fe-Nb diatomic sites optimized the desorption energy of key intermediates (*OH), so that the adsorption energy of Fe-*OH approaches the apex of the volcano plot, thus exhibiting optimal ORR activity. More importantly, introducing Nb atoms could effectively strengthen the Fe-N bonding and suppress Fe demetalation, causing an outstanding stability. The zinc-air battery (ZAB) and hydroxide exchange membrane fuel cell (HEMFC) equipped with our FeNb/c-SNC could deliver high peak power densities of 314 mW cm-2 and 1.18 W cm-2, respectively. Notably, the stable operation time for ZAB and HEMFC increased by 9.1 and 5.8 times compared to Fe SACs, respectively. This research offers further insights into developing stable Fe-based atomic-level catalytic materials for the energy conversion process.

Development and application of an intelligent nitrogen removal diagnosis and optimization framework for WWTPs: Low-carbon and stable operation.

Optimizing nitrogen removal is crucial for ensuring the efficient operation of wastewater treatment plants (WWTPs), but it is susceptible to variations in influent conditions and operational parameter constraints, and conflicts with the energy-saving and carbon emission reduction goals. To address these issues, this study proposes a hybrid framework integrating process simulation, machine learning, and multi-objective genetic algorithms for nitrogen removal diagnosis and optimization, aiming to predict the total nitrogen in effluent, diagnose nitrogen over-limit risks, and optimize the control strategies. Taking a full-scale WWTP as a case study, a process time-lag simulation-enhanced machine learning model (PTLS-ML) was developed, achieving R2 values of 0.94 and 0.79 for the training and testing sets, respectively. The proposed model successfully identified the potential reasons of nitrogen over-limit risks under different influent conditions and operational parameters, and accordingly provided optimization suggestions. In addition, the multi-objective optimization (MOO) algorithms analysis further demonstrated that maintaining 4-6 mg/L total nitrogen concentration in effluent by adjusting process operational parameters can effectively balance multiple objectives (i.e., effluent water quality, operating costs, and greenhouse gas emissions), achieving coordinated optimization. This framework can serve as a reference for stable operation, energy-saving, and emission reduction in the nitrogen removal of WWTPs.

Novel genetic variants in the NLRP3 inflammasome-related PANX1 and APP genes predict survival of patients with hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND: The nod-like receptor protein 3 (NLRP3) is one of the most characterized inflammasomes involved in the pathogenesis of several cancers, including hepatocellular carcinoma (HCC). However, the effects of genetic variants in the NLRP3 inflammasome-related genes on survival of hepatitis B virus (HBV)-related HCC patients are unclear. METHODS: We performed multivariable Cox proportional hazards regression analysis to evaluate associations between 299 single-nucleotide polymorphisms (SNPs) in 16 NLRP3 inflammasome-related genes and overall survival (OS) of 866 patients with HBV-related HCC. We further performed expression quantitative trait loci (eQTL) analysis using the data from the GTEx project and 1000 Genomes projects, and performed differential expression analysis using the TCGA dataset to explore possible molecular mechanisms underlying the observed associations. RESULTS: We found that two functional SNPs (PANX1 rs3020013 A > G and APP rs9976425 C > T) were significantly associated with HBV-related HCC OS with the adjusted hazard ratio (HR) of 0.83 [95% confidence interval (CI) = 0.73-0.95, P = 0.008], and 1.26 (95% CI = 1.02-1.55, P = 0.033), respectively. Moreover, the eQTL analysis revealed that the rs3020013 G allele was correlated with decreased mRNA expression levels of PANX1 in both normal liver tissues (P = 0.044) and whole blood (P < 0.001) in the GTEx dataset, and PANX1 mRNA expression levels were significantly higher in HCC samples and associated with a poorer survival of HCC patients. However, we did not observe such correlations for APP rs9976425. CONCLUSIONS: These results indicated that SNPs in the NLRP3 inflammasome-related genes may serve as potential biomarkers for HBV-related HCC survival, once replicated by additional larger studies.

Delta-like noncanonical notch ligand 2 regulates the proliferation and differentiation of sheep myoblasts through the Wnt/ß-catenin signaling pathway.

This study delved into the role of delta-like noncanonical notch ligand 2 (DLK2) in the cell cycle, proliferation, apoptosis, and differentiation of myoblasts, as well as its interaction with the classical Wnt/ß-catenin signaling pathway in regulating myoblast function. The research revealed that upregulation of DLK2 in myoblasts during the proliferation phase enhanced myoblast proliferation, facilitated cell cycle progression, and reduced apoptosis. Conversely, downregulation of DLK2 expression using siRNA during the differentiation phase promoted myoblast hypertrophy and fusion, suppressed the expression of muscle fiber degradation factors, and expedited the differentiation process. DLK2 regulates myoblasts function by influencing the expression of various factors associated with the Wnt/ß-catenin signaling pathway, including CTNNB1, FZD1, FZD6, RSPO1, RSPO4, WNT4, WNT5A, and adenomatous polyposis coli. In essence, DLK2, with the involvement of the Wnt/ß-catenin signaling pathway, plays a crucial regulatory role in the cell cycle, proliferation, apoptosis, and differentiation of myoblasts.

Cellulose-citric acid-chitosan@metal sulfide nanocomposites: Methyl orange dye removal and antibacterial activity.

In this study, to develop efficient adsorbents in removing water pollution, new cellulose-citric acid-chitosan@metal sulfide nanocomposites (CL-CA-CS@NiS and CL-CA-CS@CuS) were synthesized by one-pot reaction at mild conditions and characterized using X-ray powder diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscope (SEM), Energy Dispersive X-ray (EDX) and Brunauer-Emmett-Teller (BET) isotherm. The results of characterization techniques confirm that the desired compounds have been successfully synthesized. The as-prepared composites were applied for the removal of methyl orange (MO) dye from aqueous solutions using a batch technique, and the effect of key factors such as initial pH, shaking time, MO concentration, temperature and adsorbent dose were investigated and discussed. Adsorption results exhibited positive impact of temperature, shaking time and adsorbent dose on the MO removal percent. The MO removal percent has been increased over a wide range of pH from 2 (27.6 %) to 6 (98.8 %). Also, almost being constant over a wide range of MO concentration (10-70 mg/L). The results demonstrated that the maximum removal percentage of MO dye (98.9 % and 93.4 % using CL-CA-CS@NiS and CL-CA-CS@CuS, respectively) was achieved under the conditions of pH 6, shaking time of 120 min, adsorbent dose of 0.02 g, MO concentration of 70 mg/L and temperature of 35 °C. The pseudo-second-order (PSO) and Langmuir models demonstrated the best fit to the kinetic and equilibrium data. Also, the thermodynamic results showed that the MO removal process is endothermic and spontaneous in nature. The MO adsorption can be happened by different electrostatic attraction, n-π and π-π stacking and also hydrogen bonding interaction. In addition, antibacterial activity of CL-CA-CS@NiS and CL-CA-CS@CuS nanocomposites exhibited a superior efficiency against S. aureus.

Identification of the conductivity type of single-walled carbon nanotubes via dual-modulation dielectric force microscopy.

The conductivity type is one of the most fundamental transport properties of semiconductors, which is usually identified by fabricating the field-effect transistor, the Hall-effect device, etc. However, it is challenging to obtain an Ohmic contact if the sample is down to nanometer-scale because of the small size and intrinsic heterogeneity. Noncontact dielectric force microscopy (DFM) can identify the conductivity type of the sample by applying a DC gate voltage to the tip, which is effective in tuning the accumulation or depletion of charge carriers. Here, we further developed a dual-modulation DFM, which simplified the conductivity type identification from multiple scan times under different DC gate voltages to a single scan under an AC gate voltage. Taking single-walled carbon nanotubes as testing samples, the semiconducting-type sample exhibits a more significant charge carrier accumulation/depletion under each half-period of the AC gate voltage than the metallic-type sample due to the stronger rectification effect. The charge carrier accumulation or depletion of the p-type sample is opposite to that of the n-type sample at the same half-period of the AC gate voltage because of the reversed charge carrier type.

In Situ-Grown Ultrathin Catalyst Layers for Improving both Proton Exchange Membrane Fuel Cell and Anion Exchange Membrane Fuel Cell Performances.

The mass transport and ion conductivity in the catalyst layer are important for fuel cell performances. Here, we report an in situ-grown ultrathin catalyst layer (UTCL) to reduce the oxygen mass transport and a surface ionomer-coated gas diffusion layer method to reduce the ion conducting resistance. A significantly reduced catalyst layer thickness (ca. 1 µm) is achieved, and coupled with the ionomer introduction method, the ultrathin catalyst layer is in good contact with the membrane, resulting in high ion conductivity and high Pt utilization. This ultrathin catalyst layer is suitable for both proton exchange membrane fuel cells and anion exchange membrane fuel cells, giving peak power densities of 2.24 and 1.11 W cm-2, respectively, which represent an increase of more than 30% compared with the membrane electrode assembly (MEA) fabricated by using traditional Pt/C power catalysts. Electrochemical impedance spectra and limiting current tests demonstrate the reduced charge transfer, mass transfer, and ohmic resistances in the ultrathin catalyst layer membrane electrode assembly, resulting in the promoted fuel cell performances.

Incorporating ions during thermal processing tailors the microstructure and practical features of rice starch/anthocyanin binary system.

Understanding the interplay among salt ions, anthocyanin and starch within food matrices under thermal conditions is important for the development of starch-based foods with demanded quality attributes. However, how salt ions presence influences the microstructure and properties of starch/anthocyanin binary system remains largely unclear. Herein, indica rice starch (IRS) and rice anthocyanin (RA) were used to construct an IRS-RA binary system, with thermal treatment under different concentrations of Na+ (10-40 mM) and types of salt ions (Na+ and Ca2+). The incorporation of salt ions induced the formation of a porous gel matrix, and destroyed the hydrogen bond between starch and anthocyanin through electrostatic interactions, reducing the storage modulus and radius of gyration of the binary system, and increasing the relative crystallinity (from 1.08 % to 1.51 % (20 mM Na+) and 1.69 % (20 mM Ca+)) of the IRS-RA binary system at 90 °C. Also, the DPPH radical scavenging ability of the binary system at 90 °C was enhanced upon incorporating salt ions (0.93 for Na+ condition and 0.94 for Ca2+ condition at 20 mM ion concentration). It is noteworthy that Ca2+ inclusion had more significant effects than the case for Na+ presence, presumably due to the increased charge density.

Research on the bearing creep characteristics and constitutive model of gangue filling body.

The creep characteristics and potential deformation patterns of gangue backfill material are crucial in backfill mining operations. This study utilizes crushed gangue from the Gangue Yard in Fuxin City as the research material. An in-house designed, large-scale, triaxial gangue compaction test system was used. Triaxial compaction creep tests were conducted on gangue materials with varying particle size distributions. Analysis was performed based on different particle sizes, stresses, and confinement pressures. The study investigates the creep characteristics of the gangue under different conditions and explores the underlying causes. It reveals the relationship between the creep deformation of gangue materials and the passage of time. Mathematical methods are applied to develop a triaxial compaction creep power law model for gangue backfill materials. Finally, the creep results are fitted using an empirical formula approach.

Lectin microarray based glycan profiling of exosomes for dynamic monitoring of colorectal cancer progression.

BACKGROUND: Exosomes, as emerging biomarkers in liquid biopsies in recent years, offer profound insights into cancer diagnostics due to their unique molecular signatures. The glycosylation profiles of exosomes have emerged as potential biomarkers, offering a novel and less invasive method for cancer diagnosis and monitoring. Colorectal cancer (CRC) represents a substantial global health challenge and burden. Thus there is a great need for the aberrant glycosylation patterns on the surface of CRC cell-derived exosomes, proposing them as potential biomarkers for tumor characterization. RESULTS: The interactions of 27 lectins with exosomes from three CRC cell lines (SW480, SW620, HCT116) and one normal colon epithelial cell line (NCM460) have been analyzed by the lectin microarray. The result indicates that Ulex Europaeus Agglutinin I (UEA-I) exhibits high affinity and specificity towards exosomes derived from SW480 cells. The expression of glycosylation related genes within cells has been analyzed by high-throughput quantitative polymerase chain reaction (HT-qPCR). The experimental result of HT-qPCR is consistent with that of lectin microarray. Moreover, the limit of detection (LOD) of UEA-I microarray is calculated to be as low as 2.7 × 105 extracellular vehicles (EVs) mL-1 (three times standard deviation (3σ) of blank sample). The UEA-I microarray has been successfully utilized to dynamically monitor the progression of tumors in mice-bearing SW480 CRC subtype, applicable in tumor sizes ranging from 2 mm to 20 mm in diameter. SIGNIFICANCE: The results reveal that glycan expression pattern of exosome is linked to specific CRC subtypes, and regulated by glycosyltransferase and glycosidase genes of mother cells. Our findings illuminate the potential of glycosylation molecules on the surface of exosomes as reliable biomarkers for diagnosis of tumor at early stage and monitoring of cancer progression.

Development and validation of a lung metastases-predicting nomogram for intermediate- to high-risk differentiated thyroid carcinoma patients.

Aim: This research aimed to construct a clinical model for forecasting the likelihood of lung metastases in differentiated thyroid carcinoma (DTC) with intermediate- to high-risk.Methods: In this study, 375 DTC patients at intermediate to high risk were included. They were randomly divided into a training set (70%) and a validation set (30%). A nomogram was created using the training group and then validated in the validation set using calibration, decision curve analysis (DCA) and receiver operating characteristic (ROC) curve.Results: The calibration curves demonstrated excellent consistency between the predicted and the actual probability. ROC analysis showed that the area under the curve in the training cohort was 0.865 and 0.845 in the validation cohort. Also, the DCA curve indicated that this nomogram had good clinical utility.Conclusion: A user-friendly nomogram was constructed to predict the lung metastases probability with a high net benefit.

[Box: see text].

A multimodal generative AI copilot for human pathology.

Computational pathology1,2 has witnessed considerable progress in the development of both task-specific predictive models and task-agnostic self-supervised vision encoders3,4. However, despite the explosive growth of generative artificial intelligence (AI), there have been few studies on building general-purpose multimodal AI assistants and copilots5 tailored to pathology. Here we present PathChat, a vision-language generalist AI assistant for human pathology. We built PathChat by adapting a foundational vision encoder for pathology, combining it with a pretrained large language model and fine-tuning the whole system on over 456,000 diverse visual-language instructions consisting of 999,202 question and answer turns. We compare PathChat with several multimodal vision-language AI assistants and GPT-4V, which powers the commercially available multimodal general-purpose AI assistant ChatGPT-4 (ref. 6). PathChat achieved state-of-the-art performance on multiple-choice diagnostic questions from cases with diverse tissue origins and disease models. Furthermore, using open-ended questions and human expert evaluation, we found that overall PathChat produced more accurate and pathologist-preferable responses to diverse queries related to pathology. As an interactive vision-language AI copilot that can flexibly handle both visual and natural language inputs, PathChat may potentially find impactful applications in pathology education, research and human-in-the-loop clinical decision-making.

Spatiotemporal Analysis of HIV/AIDS Incidence in China From 2009 to 2019 and Its Association With Socioeconomic Factors: Geospatial Study.

BACKGROUND: The Joint United Nations Program on HIV/AIDS (UNAIDS) has set the "95-95-95" targets to ensure that 95% of all people living with HIV will know their HIV status, 95% of all people living with HIV will receive sustained antiretroviral therapy (ART), and 95% of all people receiving ART will achieve viral suppression (<1000 copies/mL). However, few countries have currently achieved these targets, posing challenges to the realization of the UNAIDS goal to eliminate the global HIV/AIDS epidemic by 2030. The Chinese government has implemented corresponding policies for HIV/AIDS prevention and control; however, it still faces the challenge of a large number of HIV/AIDS cases. Existing research predominantly focuses on the study of a particular region or population in China, and there is relatively limited research on the macro-level analysis of the spatiotemporal distribution of HIV/AIDS across China and its association with socioeconomic factors. OBJECTIVE: This study seeks to identify the impact of these factors on the spatiotemporal distribution of HIV/AIDS incidence in China, aiming to provide scientific recommendations for future policy development. METHODS: This study employed ArcGIS 10.2 (Esri) for spatial analysis, encompassing measures such as the imbalance index, geographical concentration index, spatial autocorrelation analysis (Moran I), and hot spot analysis (Getis-Ord Gi*). These methods were used to unveil the spatiotemporal distribution characteristics of HIV/AIDS incidence in 31 provinces of China from 2009 to 2019. Geographical Detector was used for ecological detection, risk area detection, factor detection, and interaction detection. The analysis focused on 9 selected socioeconomic indicators to further investigate the influence of socioeconomic factors on HIV/AIDS incidence in China. RESULTS: The spatiotemporal distribution analysis of HIV/AIDS incidence in China from 2009 to 2019 revealed distinct patterns. The spatial distribution type of HIV/AIDS incidence in China was random in 2009-2010. However, from 2011 to 2019, the distribution pattern evolved toward a clustered arrangement, with the degree of clustering increasing each year. Notably, from 2012 onwards, there was a significant and rapid growth in the aggregation of cold and hot spot clusters of HIV/AIDS incidence in China, stabilizing only by the year 2016. An analysis of the impact of socioeconomic factors on HIV/AIDS incidence in China highlighted the "urbanization rate" and "urban basic medical insurance fund expenditure" as the primary factors influencing the spatial distribution of HIV/AIDS incidence. Additionally, among social factors, indicators related to medical resources exerted a crucial influence on HIV/AIDS incidence. CONCLUSIONS: From 2009 to 2019, HIV/AIDS incidence in China was influenced by various socioeconomic factors. In the future, it is imperative to optimize the combination of different socioeconomic indicators based on regional incidence patterns. This optimization will facilitate the formulation of corresponding policies to address the challenges posed by the HIV/AIDS epidemic.

Integration analysis of transcriptome and proteome profiles brings new insights of somatic embryogenesis of two eucalyptus species.

BACKGROUND: Somatic embryogenesis (SE) is recognized as a promising technology for plant vegetative propagation. Although previous studies have identified some key regulators involved in the SE process in plant, our knowledge about the molecular changes in the SE process and key regulators associated with high embryogenic potential is still poor, especially in the important fiber and energy source tree - eucalyptus. RESULTS: In this study, we analyzed the transcriptome and proteome profiles of E. camaldulensis (with high embryogenic potential) and E. grandis x urophylla (with low embryogenic potential) in SE process: callus induction and development. A total of 12,121 differentially expressed genes (DEGs) and 3,922 differentially expressed proteins (DEPs) were identified in the SE of the two eucalyptus species. Integration analysis identified 1,353 (131 to 546) DEGs/DEPs shared by the two eucalyptus species in the SE process, including 142, 13 and 186 DEGs/DEPs commonly upregulated in the callus induction, maturation and development, respectively. Further, we found that the trihelix transcription factor ASR3 isoform X2 was commonly upregulated in the callus induction of the two eucalyptus species. The SOX30 and WRKY40 TFs were specifically upregulated in the callus induction of E. camaldulensis. Three TFs (bHLH62, bHLH35 isoform X2, RAP2-1) were specifically downregulated in the callus induction of E. grandis x urophylla. WGCNA identified 125 and 26 genes/proteins with high correlation (Pearson correlation > 0.8 or < -0.8) with ASR3 TF in the SE of E. camaldulensis and E. grandis x urophylla, respectively. The potential target gene expression patterns of ASR3 TF were then validated using qRT-PCR in the material. CONCLUSIONS: This is the first time to integrate multiple omics technologies to study the SE of eucalyptus. The findings will enhance our understanding of molecular regulation mechanisms of SE in eucalyptus. The output will also benefit the eucalyptus breeding program.

Association between serum chloride and in-hospital mortality in congestive heart failure with diabetes: Data from the MIMIC-IV database.

Background: Congestive heart failure (CHF) demonstrates a heightened prevalence in individuals with diabetes mellitus within Intensive Care Units. The occurrence of abnormal chloride levels is frequently observed in critically ill patients, yet its clinical significance remains subject to debate. This study endeavors to explore the relationship between serum chloride levels and in-hospital mortality among patients affected by both congestive heart failure and diabetes. Methods: A retrospective cohort study was conducted, utilizing data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database, focusing on adult patients in the United States. The impact of serum chloride levels upon ICU admission on in-hospital mortality was analyzed using multivariable logistic regression models, generalized additive models and subgroup analysis. Results: The study encompassed 7,063 patients with coexisting diabetes and congestive heart failure. The fully adjusted model revealed an inverse association between serum chloride levels and in-hospital mortality. As a tertile variable (Q3 vs Q1), the odds ratio (OR) was 0.73 with a 95% confidence interval (CI) of 0.54-0.98 (p = 0.039). As a continuous variable, per 1 mmol/L increment, the OR (95% CI) was 0.97 (0.96-0.99, p = 0.01). The relationship between serum chloride and in-hospital mortality demonstrated linearity (non-linear p = 0.958). Stratified analyses further validated the robustness of this correlation. Conclusions: Serum chloride levels exhibited a negative association with in-hospital mortality in patients with both congestive heart failure and diabetes. Nevertheless, prospective, randomized, controlled studies are warranted to corroborate and validate the findings presented in this investigation.

Analysis of 3D pathology samples using weakly supervised AI.

Human tissue, which is inherently three-dimensional (3D), is traditionally examined through standard-of-care histopathology as limited two-dimensional (2D) cross-sections that can insufficiently represent the tissue due to sampling bias. To holistically characterize histomorphology, 3D imaging modalities have been developed, but clinical translation is hampered by complex manual evaluation and lack of computational platforms to distill clinical insights from large, high-resolution datasets. We present TriPath, a deep-learning platform for processing tissue volumes and efficiently predicting clinical outcomes based on 3D morphological features. Recurrence risk-stratification models were trained on prostate cancer specimens imaged with open-top light-sheet microscopy or microcomputed tomography. By comprehensively capturing 3D morphologies, 3D volume-based prognostication achieves superior performance to traditional 2D slice-based approaches, including clinical/histopathological baselines from six certified genitourinary pathologists. Incorporating greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, further emphasizing the value of capturing larger extents of heterogeneous morphology.