Molecular insights into kaempferol derivatives as potential inhibitors for CDK2 in colon cancer: pharmacophore modeling, docking, and dynamic analysis.

Cyclin-dependent kinase 2 (CDK2) has been recognized as one of the crucial factors in cell cycle regulation and has been proposed as a potential target for cancer therapies, particularly for colorectal cancer (CRC). Due to the increased incidence rate of CRC and challenges associated with existing treatment options, there is a need for efficient and selective anti-cancer compounds. The current work aims to explore the ability of novel kaempferol derivatives as CDK2 inhibitors by performing conceptual pharmacophore modeling, molecular docking, and molecular dynamic analysis. Kaempferol and its derivatives were obtained from PubChem, and the optimized 3D structures of the compounds were generated using Maestro Ligprep. Subsequently, a pharmacophore model was developed to identify compounds with high fitness values, resulting in the selection of several kaempferol derivatives for further study. We evaluated the ADMET properties of these compounds to assess their therapeutic potential. Molecular docking was conducted using Maestro and BIOVIA Discovery Studio version 4.0 to predict the binding affinities of the compounds to CDK2. The top candidates were subjected to MM-GBSA analysis to predict their binding free energies. Molecular dynamics simulations using GROMACS were performed to assess the thermodynamic stability of the ligand-protein complexes. The results revealed several kaempferol derivatives with high predicted binding affinities to CDK2 and favorable ADMET properties. Specifically, compounds 5281642, 5318980, and 14427423 demonstrated binding free energies of -30.26, -38.66, and -34.2 kcal/mol, respectively. Molecular dynamics simulations indicated that these ligand-protein complexes remained stable throughout the simulation period, with RMSD values remaining below 2 Å. In conclusion, the identified kaempferol derivatives show potential as CDK2 inhibitors based on computational predictions and demonstrate stability in molecular dynamics simulations, suggesting their future application in CRC treatment by targeting CDK2. These computational findings encourage further experimental validation and development of kaempferol derivatives as anti-cancer agents.

Study on Selenium Assimilation and Transformation in Radish Sprouts Cultivated Using Maillard Reaction Products.

The organic selenium (Se), particularly in the form of selenoamino acids, in non-edible sections or by-products of Se-enriched plants, has the potential to generate Maillard reaction products (MRPs) during thermal treatment or fermentation. To elucidate the recycling process of organic selenium in foods and improve the utilization rate of Se, the biotransformation of organic selenium was studied by the cultivation of edible radish sprouts with Se-MPRs. Maillard reactions were simulated using selenoamino acids (SeAAs; selenomethionine and methylselenocysteine) and reducing sugars (glucose and fructose) for preparing Se-MRPs. The structures of the possible dehydrated Se-MRPs were analyzed using a HPLC-ESI-MS/MS system based on their fragmentation patterns and Se isotopic characteristics. Se absorption by the radish sprouts cultivated using Se-MRPs was estimated by the corresponding Se in the SeAAs and the total Se contents. The capabilities of SeAA transformation and total Se assimilation by the sprouts were related to the substrate composition during the Se-Maillard reaction. A particular Se-MRP (selenomethionine + fructose) increased SeAAs transformation by 33.8% compared to selenomethionine. However, glucose and fructose seemed to inhibit the transformation of the Se-MRPs to SeAAs by 10.0 to 59.1% compared to purified Se-MRPs. These results provide key references for the efficient utilization of organic Se in the cultivation of Se-enriched sprouts.

Constructing the cGAMP-Aluminum Nanoparticles as a Vaccine Adjuvant-Delivery System (VADS) for Developing the Efficient Pulmonary COVID-19 Subunit Vaccines.

The cGAMP-aluminum nanoparticles (CAN) are engineered as a vaccine adjuvant-delivery system to carry mixed RBD (receptor-binding domain) of the original severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its new variant for developing bivalent pulmonary coronavirus disease 2019 (COVID-19) vaccines (biRBD-CAN). High phosphophilicity/adsorptivity made intrapulmonary CAN instantly form the pulmonary ingredient-coated CAN (piCAN) to possess biomimetic features enhancing biocompatibility. In vitro biRBD-CAN sparked APCs (antigen-presenting cells) to mature and make extra reactive oxygen species, engendered lysosome escape effects and enhanced proteasome activities. Through activating the intracellular stimulator of interferon genes (STING) and nucleotide-binding domain and leucine-rich repeat and pyrin domain containing proteins 3 (NALP3) inflammasome pathways to exert synergy between cGAMP and AN, biRBD-CAN stimulated APCs to secret cytokines favoring mixed Th1/Th2 immunoresponses. Mice bearing twice intrapulmonary biRBD-CAN produced high levels of mucosal antibodies, the long-lasting systemic antibodies, and potent cytotoxic T lymphocytes which efficiently erased cells displaying cognate epitopes. Notably, biRBD-CAN existed in mouse lungs and different lymph nodes for at least 48 h, unveiling their sustained immunostimulatory activity as the main mechanism underlying the long-lasting immunity and memory. Hamsters bearing twice intrapulmonary biRBD-CAN developed high resistance to pseudoviral challenges performed using different recombinant strains including the ones with distinct SARS-CoV-2-spike mutations. Thus, biRBD-CAN as a broad-spectrum pulmonary COVID-19 vaccine candidate may provide a tool for controlling the emerging SARS-CoV-2 variants.

Stochastic processes drive the dynamic assembly of bacterial communities in Salix matsudana afforested soils.

Introduction: This study investigates the dynamic shifts in soil bacterial communities within a Salix matsudana afforested ecosystem transitioning from agricultural land. Understanding the temporal variability in bacterial diversity and community structures is crucial for informing forest management and conservation strategies, particularly in regions undergoing afforestation. Methods: We employed high-throughput sequencing across three distinct months (August, September, and October) to analyze the temporal variability in bacterial community composition and diversity. Network analysis was utilized to identify keystone species and assess community stability under varying environmental conditions, including fluctuations in temperature and precipitation. Results: We uncover significant temporal variability in bacterial diversity and community structures, which are closely tied to fluctuations in temperature and precipitation. Our findings reveal the abundance of the dominant bacterial phyla, such as Actinobacteria and Proteobacteria, which did not change overall, highlighting the stability and resilience of the microbial community across seasonal transitions. Notably, the increasing similarity in community composition from August to October indicates a reduction in species turnover, likely driven by more homogeneous environmental conditions. Through comprehensive network analysis, we identify the pivotal role of keystone species, particularly the human pathogen Nocardia, in maintaining community stability under reduced soil moisture. The observed variations in community connectivity underscore the microbial community's resilience and adaptability to seasonal shifts, with higher stability in August and October contrasting with the instability observed in September. Discussion: These results underscore the complex interplay between stochastic and deterministic processes in bacterial community assembly, significantly shaped by prevailing environmental conditions. The insights gained from this research have far-reaching implications for forestry management and conservation strategies, particularly in regions undergoing similar afforestation efforts.

Genome-wide analysis of the ERF Family in Stephania japonica provides insights into the regulatory role in Cepharanthine biosynthesis.

Introduction: Cepharanthine (CEP), a bisbenzylisoquinoline alkaloid (bisBIA) extracted from Stephania japonica, has received significant attention for its anti-coronavirus properties. While ethylene response factors (ERFs) have been reported to regulate the biosynthesis of various alkaloids, their role in regulating CEP biosynthesis remains unexplored. Methods: Genome-wide analysis of the ERF genes was performed with bioinformatics technology, and the expression patterns of different tissues, were analyzed by transcriptome sequencing analysis and real-time quantitative PCR verification. The nuclear-localized ERF gene cluster was shown to directly bind to the promoters of several CEP-associated genes, as demonstrated by yeast one-hybrid assays and subcellular localization assays. Results: In this work, 59 SjERF genes were identified in the S. japonica genome and further categorized into ten subfamilies. Notably, a SjERF gene cluster containing three SjERF genes was found on chromosome 2. Yeast one-hybrid assays confirmed that the SjERF gene cluster can directly bind to the promoters of several CEP-associated genes, suggesting their crucial role in CEP metabolism. The SjERFs cluster-YFP fusion proteins were observed exclusively in the nuclei of Nicotiana benthamiana leaves. Tissue expression profiling revealed that 13 SjERFs exhibit high expression levels in the root, and the qRT-PCR results of six SjERFs were consistent with the RNA-Seq data. Furthermore, a co-expression network analysis demonstrated that 24 SjERFs were highly positively correlated with the contents of various alkaloids and expression levels of CEP biosynthetic genes. Conclusion: This study provides the first systematic identification and analysis of ERF transcription factors in the S.japonica genome, laying the foundation for the future functional research of SjERFs transcription factors.

Nanoplastics exposure-induced mitochondrial dysfunction contributes to disrupted stem cell differentiation in human cerebral organoids.

Nanoplastics are ubiquitous in our daily lives, raising concerns about their potential impact on the human brain. Many studies reported that nanoplastics permeate the blood-brain barrier and influence cellular processes in mouse models. However, the neurotoxic effects of ingesting nanoplastics on human brain remain poorly understood. Here, we treated cerebral organoids with polystyrene nanoplastics to model the effects of nanoplastic exposure on human brain. Importantly, we found that mitochondria might be the significant organelles affected by polystyrene nanoplastics using immunostaing and RNA-seq analysis. Subsequently, we observed the increased cell death and decreased cell differentiation in our cerebral organoids. In conclusion, our findings shed insights on the mechanisms underlying the toxicity of nanoplastics on human brain organoids, providing an evaluation system in detection potential environmental toxicity on human brain.

Identification of novel drug targets for osteoarthritis by integrating genetics and proteomes from blood.

BACKGROUND: Osteoarthritis (OA) is a degenerative osteoarticular disease, involving genetic predisposition. How the risk variants confer the risk of OA through their effects on proteins remains largely unknown. Therefore, we aimed to discover new and effective drug targets for OA and its subtypes. METHODS: A proteome-wide association study (PWAS) was performed based on OA and its subtypes genome-wide association studies (GWAS) summary datasets and the protein quantitative trait loci (pQTL) data. Subsequently, Mendelian randomization (MR) and colocalization analysis was conducted to estimate the associations between protein and OA risk. The replication analysis was performed in an independent dataset of human plasma pQTL data. RESULTS: The abundance of seven proteins was causally related to OA, two proteins to knee OA and six proteins to hip OA, respectively. We replicated 2 of these proteins using an independent pQTL dataset. With the further support of colocalization, and higher ECM1 level was causally associated with a higher risk of OA and hip OA. Higher PCSK1 level was causally associated with a lower risk of OA. And higher levels of ITIH1, EFEMP1, and ERLEC1 were associated with decreased risk of hip OA. CONCLUSION: Our study provides new insights into the genetic component of protein abundance in OA and a promising therapeutic target for future drug development.

Effect of low-purine diet on the serum uric acid of gout patients in different clinical subtypes: a prospective cohort study.

BACKGROUND: The pathogenic causes of primary gout include urate overproduction and/or renal or extra-renal urate underexcretion. The aim of this study was to evaluate the association of gout subtypes with the response to low-purine diet (LPD). METHODS: This is a single-center prospective clinical study. Gout patients visiting from 2019 to 2022, from Shandong Gout Clinic Center at the Affiliated Hospital of Qingdao University, China, assigned to three groups according to clinical subtypes, were enrolled and all treated with 2-week low-purine diet. General characteristics, serum uric acid (sUA) and other clinical biochemical variables before and after the diet were evaluated. RESULTS: A total of 626 gout patients (age 41.20 ± 13.41 years, male 98.0%) were included. Of these, 69 (11.0%) were overproduction type, 428 (68.37%) were underexcretion type, and 129 (20.61%) were combined type. Overall, there was a substantial decrease in sUA after a 2-week LPD (p < 0.001). In addition, systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), serum alanine aminotransferase (ALT), serum aspartate aminotransferase (AST), serum triglycerides (TG), serum total cholesterol (TC), blood urea nitrogen (BUN) and serum creatinine (Scr) levels were lower than those at baseline (p < 0.05). On the other hand, there were significant differences in the reduction of sUA among different types, the rank order being overproduction type (- 88.81 ± 63.01 µmol/L) > combined type (- 65.22 ± 44.13 µmol/L) > underexcretion type (- 57.32 ± 61.19 µmol/L). After adjusting for age, BMI and baseline sUA and eGFR, there were still significant differences in the decline of serum uric acid among different types. Higher baseline sUA (95%CI - 0.285, - 0.191; p < 0.001) and BUN (95%CI - 6.751, - 0.602; p < 0.001) were correlated with greater decrease of sUA. CONCLUSIONS: Our findings support the protective role of low-purine diet on sUA levels in gout patients, especially overproduction type. Furthermore, LPD could exert a beneficial effect on gout patients' blood pressure, BMI, blood lipid, BUN and Scr levels. Trial registration Registered with ChiCTR, No. ChiCTR1900022981 at 06/05/2019.

Concordance of Ultrasound and Dual-Energy CT in Diagnosing Gouty Arthritis in the Knee Joint: A Retrospective Observational Study.

RATIONALE AND OBJECTIVES: To assess the consistency between ultrasound and dual-energy computed tomography (DECT) for the diagnosis of gout in the knee joint. MATERIALS AND METHODS: The ultrasound and DECT images of 176 knee joints from 167 patients diagnosed with gout at the Gout Specialty Clinic of Qingdao University Affiliated Hospital from February 2022 to December 2023 were retrospectively analyzed. The knee joint was segmented into five anatomical regions: intra-articular, anterior, posterior, medial, and lateral. The location of monosodium urate (MSU) crystal deposition was recorded. Tophi were classified as hypoechogenic, isoechogenic, hyperechogenic, or strongly echogenic. The Kappa test was used to assess the consistency between the two examination methods in different regions of the knee joint. The McNemar chi-square test was utilized to conduct a differential analysis between the DECT and ultrasound results. The chi-square test was used to assess differences in the rate of tophi detection with different echogenicities by DECT. Pearson's correlation coefficient was used to assess the correlation between MSU crystal deposition volume and clinically relevant indicators. RESULTS: Double contour (61.4%) was the most common intra-articular ultrasound sign. In the extra-articular region, MSU crystals were commonly deposited in and around the popliteal groove region (ultrasound: 52.3%; DECT: 60.0%). Corresponding MSU deposits on DECT were found in 7 of 54 joints with aggregates detected on ultrasound, and in 15 of 108 joints with DC. Tophi with hyperechogenicity or strong echogenicity were more likely to be detected on DECT than those with hypoechoic or isoechoic features (84.3% and 90.9% vs. 55.1% and 27.8%, respectively). For the assessment of MSU deposits, ultrasound showed an overall higher positive rate than DECT (81.1% vs. 72.2%), with poor consistency between the two examinations (κ = 0.177). In distinct anatomical regions, ultrasound and DECT showed high consistency in the medial (κ = 0.651) and lateral (κ = 0.705) views, with no significant difference. The intra-articular (κ = 0.316) and anterior (κ = 0.346) regions exhibited only fair consistency, with statistically significant diagnostic differences. When exclusively assessing cases with tophi, ultrasound and DECT demonstrated similar consistency in the medial, lateral and anterior views (κ = 0.633, 0.712, and 0.400, respectively), with statistically significant differences. In the intra-articular region, the consistency was reduced (κ = 0.237), and the differences were statistically significant. CONCLUSION: Ultrasound and DECT are effective methods to detect MSU deposition in gout of the knee. However, the consistency between the two techniques varies in different anatomical locations. Clinical assessment should be tailored based on the specific anatomical position. DECT is advantageous for the evaluation of intra-articular MSU deposits, while ultrasound is more sensitive for the early detection of scattered MSU deposits.

Biochar combined with humic acid improves the soil environment and regulate microbial communities in apple replant soil.

Apple replant disease (ARD) negatively affects plant growth and reduces yields in replanted orchards. In this study, biochar and humic acid were applied to apple replant soil. We aimed to investigate whether biochar and humic acid could promote plant growth and alleviate apple replant disease by reducing the growth of harmful soil microorganisms, changing soil microbial community structure, and improving the soil environment. This experiment included five treatments: apple replant soil (CK), apple replant soil with methyl bromide fumigation (FM), replant soil with biochar addition (2 %), replant soil with humic acid addition (1.5 ‰), and replant soil with biochar combined with humic acid. Seedling biomass, the activity of antioxidant enzymes in the leaves and roots, and soil environmental variables were measured. Microbial community composition and structure were analyzed using ITS gene sequencing. Biochar and humic acid significantly reduced the abundance of Fusarium and promoted the recovery of replant soil microbial communities. Biochar and humic acid also increased the soil enzymes activity (urease, invertase, neutral phosphatase, and catalase), the plant height, fresh weight, dry weight, the activity of antioxidant enzymes (superoxide dismutase, peroxidase, and catalase), and root indexes of apple seedlings increased in replant soil. In sum, We can use biochar combined with humic acid to alleviate apple replant disease.

Treatment of Parkinson's disease model with human umbilical cord mesenchymal stem cell-derived exosomes loaded with BDNF.

AIMS: Parkinson's disease (PD) is a common neurodegenerative disease that has received widespread attention; however, current clinical treatments can only relieve its symptoms, and do not effectively protect dopaminergic neurons. The purpose of the present study was to investigate the therapeutic effects of human umbilical cord mesenchymal stem cell-derived exosomes loaded with brain-derived neurotrophic factor (BDNF-EXO) on PD models and to explore the underlying mechanisms of these effects. MAIN METHODS: 6-Hydroxydopamine was used to establish in vivo and in vitro PD models. Western blotting, flow cytometry, and immunofluorescence were used to detect the effects of BDNF-EXO on apoptosis and ferroptosis in SH-SY5Y cells. The in vivo biological distribution of BDNF-EXO was detected using a small animal imaging system, and dopaminergic neuron improvements in brain tissue were detected using western blotting, immunofluorescence, immunohistochemistry, and Nissl and Prussian blue staining. KEY FINDINGS: BDNF-EXO effectively suppressed 6-hydroxydopamine-induced apoptosis and ferroptosis in SH-SY5Y cells. Following intravenous administration, BDNF-EXO crossed the blood-brain barrier to reach afflicted brain regions in mice, leading to a notable enhancement in neuronal survival. Furthermore, BDNF-EXO modulated microtubule-associated protein 2 and phosphorylated tau expression, thereby promoting neuronal cytoskeletal stability. Additionally, BDNF-EXO bolstered cellular antioxidant defense mechanisms through the activation of the nuclear factor erythroid 2-related factor 2 signaling pathway, thereby conferring neuroprotection against damage. SIGNIFICANCE: The novel drug delivery system, BDNF-EXO, had substantial therapeutic effects in both in vivo and in vitro PD models, and may represent a new treatment strategy for PD.

Ultrasound Controllable Release of Proteolysis Targeting Chimeras for Triple-Negative Breast Cancer Treatment.

Triple-negative breast cancer (TNBC) is a special subtype of breast cancer, which is highly aggressive and incurable. Here, we proposed an ultrasound activatable bromodomain-containing protein 4 (BRD4) proteolysis targeting chimera (PROTAC) release strategy for the first time for precisely controlled protein degradation in preclinical TNBC model. Through combination of PROTAC and ultrasound-targeted microbubble destruction (UTMD) technology, the present strategy also aims to concurrently solve the major limitations of poor loading capacity of microbubbles and undesirable targeting and membrane permeability of PROTAC. PROTAC (ARV-825)-encapsulated microbubbles, ARV-MBs, were developed for the efficacious treatment of TNBC in vitro and in vivo. The microbubbles we synthesized showed ultrasound-responsive drug release ability, which could effectively promote the penetration of PROTAC into tumor site and tumor cell. Under ultrasound, ARV-MBs could play an effective antitumor effect by potentiating the ubiquitination and degradation of BRD4 in tumor. The current study may provide a new idea for promoting clinical translation of drug-loaded microbubbles and PROTAC, and offer a new efficacious therapeutic modality for TNBC.

Boosting physical performance in SD rats through brain-targeted delivery of caffeine-loaded transferrin liposomes.

This study aimed to explore the impact of caffeine (CAF) encapsulated in transferrin-modified, sterically-stabilized liposomes (Tf-SSL) on the physical performance of rats, specifically forelimb grip strength, running, and swimming. The brain-targeted drug delivery system, Tf-SSL, was used for the administration of caffeine. 168 male Sprague-Dawley (SD) rats were randomly assigned to different groups, including swimming, running, running wheel, and strength groups. Each group was further subdivided into high, medium, and low dose free caffeine (HCAF, MCAF, LCAF) and Tf-SSL CAF groups, along with a control group (CON). The strength, swimming, and running groups underwent training for four weeks, three times per week. The running wheel group was placed in rearing cages for a one-week adaptation period. After the final training session, the resistance, swimming, running, and running wheel exercise capacities of the rats were tested. The rats were administered treatment via tail vein injection, while the blank CON group received 0.9 % saline solution without treatment throughout the entire process. The results demonstrated a Tf-SSL CAF group encapsulation rate of 70.58 ± 5.14 %. Increasing the concentration of supplemented caffeine led to enhanced forelimb grip strength in rats, with significant differences observed in HCAF alone group, medium-dose Tf-SSL CAF (MTf-SSL CAF), and high-dose Tf-SSL CAF (HTf-SSL CAF) groups compared to the CON group. In the running and swimming experiments, higher caffeine supplementation concentrations correlated with increased running and swimming time to exhaustion, and the MTf-SSL CAF group showed longer running and swimming time compared to the HCAF alone group. The results of rat striatal dopamine levels indicated that increased caffeine supplementation concentrations led to higher dopamine secretion, with significantly different striatal concentrations in the HCAF group, MTf-SSL CAF group, and HTf-SSL CAF group compared to the CON group. The running wheel experiment revealed that rats in the medium- and high-dose Tf-SSL CAF groups exhibited greater 6-h running distances than the HCAF group and CON group. In conclusion, caffeine supplementation improved the physical performance of rats, with the high concentration CAF group outperforming the low and medium concentration groups. Furthermore, Tf-SSL CAF demonstrated superior physical enhancement compared to caffeine supplementation alone.

Analysis of risk factors affecting postoperative neurological recovery in patients with cervical spine fracture in ankylosing spondylitis.

Ankylosing spondylitis (AS) is a chronic progressive inflammatory disease that mainly affects the spine and involves the sacroiliac and peripheral joints. Low-energy trauma can often lead to spinal fractures and spinal cord injuries (SCIs), the treatment of AS is challenging. The prognosis of neurological function in patients with AS cervical fracture and SCI is a major problem that must sought clinician attention on urgent basis. A total of 106 patients with AS cervical fractures who underwent surgical treatment at Shanghai Changzheng Hospital between August 2009 and 2021 were included in this study. All the patients were divided into 2 groups (improved group and the control group) based on their neurological function improvement at 1 year mark after the surgery. The baseline characteristics, perioperative factors, and procedural outcomes of all the patients including injury type, AS drug treatment, the injured segment, ossified anterior longitudinal ligament injury, spinal hypersignal, decompression time window, operation duration, blood loss, preoperative and postoperative American Spinal Injury Association (ASIA) score were recorded and analyzed. Among the 106 patients, 79 demonstrated improved neurological function at 1 year mark after the surgery. Binary univariate logistic regression analysis revealed significant differences in injury type (P = .018), ossified anterior longitudinal ligament injury (P = .01), operation duration (P = .002), spinal hypersignal (P = .001), preoperative ASIA score (P < .001), and prior AS drug treatment (P = .012). No significant differences were observed in the other variables (P > .05). Binary multivariate logistic regression analysis identified spinal hypersignal (OR = 37.185, P = .028), preoperative ASIA score (OR = 0.16, P = .012) and previous AS drug treatment (OR = 0.296, P = .049) as factors associated with postoperative neurological function improvement. The preoperative ASIA score and previous drug treatment of AS were identified as protective factors affecting the improvement of neurological functions in patients with AS cervical fracture after surgery. Preoperative T2-weighted spinal hypersignal was identified as an independent risk factor affecting the improvement of neurological function recovery in patients with AS cervical fracture after the surgery.

Optimized Random Forest Method for 3D Evaluation of Coalbed Methane Content Using Geophysical Logging Data.

Accurate evaluation of coalbed methane (CBM) content is crucial for effective exploration and development. Traditional gas content measurement methods based on laboratory analysis of drill core samples are costly, whereas geophysical logging methods offer a cost-effective alternative by providing continuous high-resolution profiles of rock layer physical properties. However, the relationship between CBM content and geophysical logging data is complex and nonlinear, necessitating an advanced prediction method. This study focuses on the No. 3 coal seam in the Shizhuang South Block of the Qinshui Basin, utilizing geophysical logging data and 148 sets of laboratory core samples. We employed the Random Forest (RF) method optimized with a simulated annealing-genetic algorithm (SA-GA) to develop the SA-GA-RF model for evaluating CBM content. The model's performance was validated using test data and new CBM well data, and it was applied to calculate the vertical gas content profiles of No. 3 coal seam across 128 wells. The SA-GA-RF model demonstrated an average relative error of 13.13% in the test data set, outperforming Backpropagation Neural Network (BPNN), Least Squares Support Vector Machine (LSSVM), Extreme Learning Machine (ELM), and multivariate regression (MR) methods. The model also exhibited strong generalizability in new wells and improved model-building efficiency compared to traditional cross-validation grid search methods. The construction of a three-dimensional CBM content model, incorporating well coordinates and elevation data, allowed for detailed identification of high gas content areas and layers. This three-dimensional model offers a more precise characterization than traditional two-dimensional isopleth maps, providing valuable insights for CBM exploration, reserve evaluation, and production optimization.

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort.

OBJECTIVE: Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS: We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS: In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION: This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Seasonal variations affect the ecosystem functioning and microbial assembly processes in plantation forest soils.

While afforestation mitigates climate concerns, the impact of afforestation on ecological assembly processes and multiple soil functions (multifunctionality) in afforested areas remains unclear. The Xiong'an New Area plantation forests (Pinus and Sophora forests) in North China were selected to examine the effects of plantation types across four distinct seasons on soil microbiomes. Three functional categories (nutrient stocks, organic matter decomposition, and microbial functional genes) of multifunctionality and the average (net) multifunctionality were quantified. All these categories are directly related to soil functions. The results showed that net soil multifunctionality as a broad function did not change seasonally, unlike other narrow functional categories. Bacterial communities were deterministically (variable selection and homogenous selection) structured, whereas the stochastic process of dispersal limitation was mainly responsible for the assembly and turnover of fungal and protist communities. In Pinus forests, winter initiates a sudden shift from deterministic to stochastic processes in bacterial community assembly, accompanied by decreased Shannon diversity and heightened nutrient cycling (nutrient stocks and organic matter decomposition). This indicates the potential vulnerability of deterministic assembly to seasonal fluctuations, particularly in environments rich in nutrients. The results predicted that protist community composition was uniquely structured with C-related functional activities relative to bacterial and fungal ß-diversity variations, which were mostly explained by seasonal variations. Our study highlighted the importance of the protist phagocytosis process on soil microbial interactions through the predicted impact of protist α-diversity on microbial cooccurrence network parameters. This association might be driven by the high abundance of protist consumers as the main predators of bacterial and fungal lineages in our sampling plots. Our findings reveal that the complexity of microbial co-occurrence interactions was considerably higher in spring, perhaps attributing thermal variability and increased resource availability within spring that foster microbial diversity and network complexity. This study contributes to local ecosystem prospects to model the behavior of soil biota seasonally and their implied effects on soil functioning and microbial assembly processes, which will benefit global-scale afforestation programs by promoting novel, precise, and rational plantation forests for future environmental sustainability and self-sufficiency.

Hyperechoic spots in the renal medulla as a potential indicator of early gouty nephropathy.

INTRODUCTION: To explore the causes and clinical significance of hyperechoic renal medulla observed by ultrasonography in patients with primary gout. METHODS: This study included 2107 patients with primary gout treated in the Gout Clinic of our hospital from 2016 to 2022. The clinical data and biochemical data of these patients were collected and analyzed. According to the presence or absence of punctate hyper-echogenicity in the renal medulla on ultrasound examination, the patients were divided into the hyperechoic medulla (HM) and the normal hypoechoic medulla (NM) groups, and the HM group was further divided into the partial HM (P-HM) and fulfilled-HM (F-HM) subgroups according to the distribution range of hyper-echogenicity. RESULTS: Among the 2107 patients with primary gout, 380 had hyperechoic renal medulla on renal ultrasound, including 106 patients with F-HM and 274 with P-HM. There were significant differences in the gout duration, urate arthropathies number, serum urate (SU) level, clinical tophi number, blood urea nitrogen (BUN), sCr, and eGFR between the HM and NM groups or between the F-HM and P-HM subgroups (P < 0.05). Multivariate regression analysis showed that the presence of hyperechoic medulla was positively correlated with gout duration, urate arthropathy number, gout attack frequency, SU, and sCr. The number of clinical tophi and sCr were closely related to F-HM. CONCLUSION: Ultrasound examination showed that a high medulla echo in patients with gout was often related to renal function damage. P-HM may be a transitory condition between NM and F-HM in patients with gout.

F for Fantastic: Fostering Stability and Efficiency in Perovskite Solar Cells via Comb-Like Perfluoroalkyl-g-Polyethylenimine Additive.

Additive engineering has emerged as a promising strategy to address the inherent instability challenges of perovskite solar cells (PSCs) in the pursuit of commercial viability. However, achieving multifunctionality using a singular additive remains a considerable challenge. In this study, a novel comb-like multifunctional perfluoroalkyl-g-polyethylenimmonium iodide (FPEI·HI) as additives to the PbI2 precursor solution to facilitate the formation of high-quality and water-resistant perovskite films is presented. FPEI·HI establishes robust interactions with both formamidinium iodide (FAI) and PbI2, mediated by hydrogen bonding and Lewis acid-base interactions. These interactions play a pivotal role in simultaneously passivating negative and positive charged defects within the perovskite structure. Furthermore, the inclusion of perfluoroalkyl chains serves as resilience against moisture intrusion. As a consequence of these effects, a notably high device efficiency of 24.29% is achieved, demonstrating comprehensive improvement in various photovoltaic parameters compared to the control device (22.51%). Notably, unencapsulated devices exhibit remarkable stability in high-humidity environments, retaining 90% of their initial efficiency even after 2500 h of storage. This work underscores the efficacy of FPEI·HI as a critical enabler for enhancing the stability and efficiency of perovskite solar cells, marking a significant stride toward their commercialization.

An Eye Movement Classification Method based on Cascade Forest.

Eye tracking technology has become increasingly important in scientific research and practical applications. In the field of eye tracking research, analysis of eye movement data is crucial, particularly for classifying raw eye movement data into eye movement events. Current classification methods exhibit considerable variation in adaptability across different participants, and it is necessary to address the issues of class imbalance and data scarcity in eye movement classification. In the current study, we introduce a novel eye movement classification method based on cascade forest (EMCCF), which comprises two modules: (1) a feature extraction module that employs a multi-scale time window method to extract features from raw eye movement data; (2) a classification module that innovatively employs a layered ensemble architecture, integrating the cascade forest structure with ensemble learning principles, specifically for eye movement classification. Consequently, EMCCF not only enhanced the accuracy and efficiency of eye movement classification but also represents an advancement in applying ensemble learning techniques within this domain. Furthermore, experimental results indicated that EMCCF outperformed existing deep learning-based classification models in several metrics and demonstrated robust performance across different datasets and participants.