Machine learning in predicting pathological complete response to neoadjuvant chemoradiotherapy in rectal cancer using MRI: A systematic review and meta-analysis.

OBJECTIVES: To evaluate the performance of machine learning models in predicting treatment response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using computed tomography (CT) and magnetic resonance imaging (MRI). METHODS: We searched PubMed, Embase, Cochrane Library, and Web of Science for studies published before January 2023. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to assess the methodological quality of the included studies, random-effects models were used to calculate sensitivity and specificity, I2 values were used for heterogeneity measurements, and subgroup analyses were carried out to detect potential sources of heterogeneity. RESULTS: A total of 1690 patients from 24 studies were included. The meta-analysis calculated a pooled area under the curve (AUC) of 0.92 (95%CI-0.89-0.94), pooled sensitivity of 0.81 (95%CI-0.73-0.88), and pooled specificity of 0.88 (95%CI-0.82-0.92). We investigated 4 studies that mainly contributed to heterogeneity. After performing meta-analysis again excluding these 4 studies, the heterogeneity was significantly reduced. In subgroup analysis, the pooled AUC of the deep learning model was 0.95 and was 0.88 for the traditional statistical model; the pooled AUC of studies that used diffusion-weighted imaging (DWI) was 0.90, and was 0.92 in studies that did not use DWI; the pooled AUC of studies conducted in China was 0.94, and was 0.83 in studies conducted in other countries. CONCLUSIONS: Machine learning has promising potential in predicting tumor response to nCRT in patients with locally advanced rectal cancer. Together with clinical information, machine-learning based models may bring us closer toward precision medicine. ADVANCES IN KNOWLEDGE: Compared to traditional machine learning models, deep learning-based studies are able to obtain higher AUC, although they are less predominant and more heterogeneous. Together with clinical information, machine-learning based models may bring us closer toward precision medicine.

A Virus-Inspired Inhalable Liponanogel Induces Potent Antitumor Immunity and Regression in Metastatic Lung Tumors.

Pulmonary delivery of immunostimulatory agents such as poly(I:C) to activate double-stranded RNA sensors MDA5 and RIG-I within lung-resident antigen-presenting cells is a potential strategy to enhance antitumor immunity by promoting type I interferon secretion. However, following pulmonary delivery, poly(I:C) suffers from rapid degradation and poor endosomal escape, thus limiting its potency. Inspired by the structure of a virus that utilizes internal viral proteins to tune the loading and cytosolic delivery of viral nucleic acids, we developed a liponanogel (LNG)-based platform to overcome the delivery challenges of poly(I:C). The LNG consisted of an anionic polymer hyaluronic acid-based nanogel core coated by a lipid shell, which served as a protective layer to stabilize the nanogel core in the lungs. The nanogel core was protonated within acidic endosomes to enhance the endosomal membrane permeability and cytosolic delivery of poly(I:C). After pulmonary delivery, LNG-poly(I:C) induced 13.7-fold more IFNß than poly(I:C) alone and 2-fold more than poly(I:C) loaded in the state-of-art lipid nanoparticles (LNP-poly(I:C)). Moreover, LNG-poly(I:C) induced more potent CD8+ T cell immunity and stronger therapeutic effects than LNP-poly(I:C). The combination of LNG-poly(I:C) and PD-L1 targeting led to regression of established lung metastases. Due to the ease of manufacturing and the high biocompatibility of LNG, pulmonary delivery of LNG may be broadly applicable to the treatment of different lung tumors and may spur the development of innovative strategies for cancer immunotherapy.

A Pump-Free Strategy for the Controllable Generation of Alginate Microgels as Cellular Microcarriers.

Microgels are advanced scaffolds for tissue engineering due to their proper biodegradability, good biocompatibility, and high specific surface area for effective oxygen and nutrient transfer. However, most of the current monodispersed microgel fabrication systems rely heavily on various precision pumps, which highly increase the cost and complexity of their downstream application. In this work, we developed a simple and facile system for the controllable generation of uniform alginate microgels by integrating a gas-shearing strategy into a glass microfluidic device. Importantly, the cell-laden microgels can be rapidly prepared in a pump-free manner under an all-aqueous environment. The three-dimensional cultured green fluorescent protein-human A549 cells in alginate microgels exhibited enhanced stemness and drug resistance compared to those under two-dimensional conditions. The pancreatic cancer organoids in alginate microgels exhibited some of the key features of pancreatic cancer. The proposed microgels showed decent monodispersity, biocompatibility, and versatility, providing great opportunities in various biomedical applications such as microcarrier fabricating, organoid engineering, and high-throughput drug screening.

A rapid and simple non-radioactive assay for measuring uptake by solute carrier transporters.

Introduction: Solute carrier (SLC) transport proteins play a crucial role in maintaining cellular nutrient and metabolite homeostasis and are implicated in various human diseases, making them potential targets for therapeutic interventions. However, the study of SLCs has been limited due to the lack of suitable tools, particularly cell-based substrate uptake assays, necessary for understanding their biological functions and for drug discovery purposes. Methods: In this study, a cell-based uptake assay was developed using a stable isotope-labeled compound as the substrate for SLCs, with detection facilitated by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This assay aimed to address the limitations of existing assays, such as reliance on hazardous radiolabeled substrates and limited availability of fluorescent biosensors. Results: The developed assay was successfully applied to detect substrate uptakes by two specific SLCs: L-type amino acid transporter 1 (LAT1) and sodium taurocholate co-transporting polypeptide (NTCP). Importantly, the assay demonstrated comparable results to the radioactive method, indicating its reliability and accuracy. Furthermore, the assay was utilized to screen for novel inhibitors of NTCP, leading to the identification of a potential NTCP inhibitor compound. Discussion: The findings highlight the utility of the developed cell-based uptake assay as a rapid, simple, and environmentally friendly tool for investigating SLCs' biological roles and for drug discovery purposes. This assay offers a safer alternative to traditional methods and has the potential to contribute significantly to advancing our understanding of SLC function and identifying therapeutic agents targeting SLC-mediated pathways.

Visual Tracking in Amblyopia: A Continuous Psychophysical Approach.

Purpose: This study aimed to explore the underlying mechanisms of the observed visuomotor deficit in amblyopia. Methods: Twenty-four amblyopic (25.8 ± 3.8 years; 15 males) and 22 normal participants (25.8 ± 2.1 years; 8 males) took part in the study. The participants were instructed to continuously track a randomly moving Gaussian target on a computer screen using a mouse. In experiment 1, the participants performed the tracking task at six different target sizes. In experiments 2 and 3, they were asked to track a target with the contrast adjusted to individual's threshold. The tracking performance was represented by the kernel function calculated as the cross-correlation between the target and mouse displacements. The peak, latency, and width of the kernel were extracted and compared between the two groups. Results: In experiment 1, target size had a significant effect on the kernel peak (F(1.649, 46.170) = 200.958, P = 4.420 × 10-22). At the smallest target size, the peak in the amblyopic group was significantly lower than that in the normal group (0.089 ± 0.023 vs. 0.107 ± 0.020, t(28) = -2.390, P = 0.024) and correlated with the contrast sensitivity function (r = 0.739, P = 0.002) in the amblyopic eyes. In experiments 2 and 3, with equally visible stimuli, there were still differences in the kernel between the two groups (all Ps < 0.05). Conclusions: When stimulus visibility was compensated, amblyopic participants still showed significantly poorer tracking performance.

Biomonitoring urinary pesticide metabolites in preschool children by supported liquid extraction and ultra-high performance liquid chromatography-tandem mass spectrometry and their association with oxidative stress.

Investigating pesticide exposure and oxidative stress in preschool children is essential for elucidating the determinants of environmental health in early life, with human biomonitoring of urinary pesticide metabolites serving as a critical strategy for achieving this objective. This study demonstrated biomonitoring of 2 phenoxyacetic acid herbicides, 2 organophosphorus pesticide metabolites, and 4 pyrethroid pesticide metabolites in 159 preschool children and evaluated their association with oxidative stress biomarker 8-hydroxydeoxyguanosine. An enzymatic deconjugation process was used to release urinary pesticide metabolites, which were then extracted and enriched by supported liquid extraction, and quantified by ultra-high performance liquid chromatography-tandem mass spectrometry with internal standard calibration. Dichloromethane: methyl tert­butyl ether (1:1, v/v) was optimized as the solvent for supported liquid extraction, and we validated the method for linear range, recovery, matrix effect and method detection limit. Method detection limit of the pesticide metabolites ranged from 0.01 µg/L to 0.04 µg/L, with satisfactory recoveries ranging from 70.5 % to 95.5 %. 2,4,5-Trichlorophenoxyacetic acid was not detected, whereas the other seven pesticide metabolites were detected with frequencies ranging from 10.1 % to 100 %. The concentration of urinary pesticide metabolites did not significantly differ between boys and girls, with the median concentrations being 9.39 µg/L for boys and 4.90 µg/L for girls, respectively. Spearman correlation analysis indicated that significant positive correlations among urinary metabolites. Bayesian kernel machine regression revealed a significant positive association between urinary pesticide metabolites and 8-hydroxydeoxyguanosine. Para-nitrophenol was the pesticide metabolite that contributed significantly to the elevated level of oxidative stress.

Enhanced interactions among gut mycobiomes with the deterioration of glycemic control.

BACKGROUND: The gut mycobiome is closely linked to health and disease; however, its role in the progression of type 2 diabetes mellitus (T2DM) remains obscure. Here, a multi-omics approach was employed to explore the role of intestinal fungi in the deterioration of glycemic control. METHODS: 350 participants without hypoglycemic therapies were invited for a standard oral glucose tolerance test to determine their status of glycemic control. The gut mycobiome was identified through internal transcribed spacer sequencing, host genetics were determined by genotyping array, and plasma metabolites were measured with untargeted liquid chromatography mass spectrometry. FINDINGS: The richness of fungi was higher, whereas its dissimilarity was markedly lower, in participants with T2DM. Moreover, the diversity and composition of fungi were closely associated with insulin sensitivity and pancreatic ß-cell functions. With the exacerbation of glycemic control, the co-occurrence network among fungus taxa became increasingly complex, and the complexity of the interaction network was inversely associated with insulin sensitivity. Mendelian randomization analysis further demonstrated that the Archaeorhizomycetes class, Fusarium genus, and Neoascochyta genus were causally linked to impaired glucose metabolism. Furthermore, integrative analysis with metabolomics showed that increased 4-hydroxy-2-oxoglutaric acid, ketoleucine, lysophosphatidylcholine (20:3/0:0), and N-lactoyl-phenylalanine, but decreased lysophosphatidylcholine (O-18:2), functioned as key molecules linking the adverse effect of Fusarium genus on insulin sensitivity. CONCLUSIONS: Our study uncovers a strong association between disturbance in gut fungi and the progression of T2DM and highlights the potential of targeting the gut mycobiome for the management of T2DM. FUNDINGS: This study was supported by MOST and NSFC of China.

SMG5 Inhibition Restrains Hepatocellular Carcinoma Growth and Enhances Sorafenib Sensitivity.

Hepatocellular carcinoma (HCC) has a pathogenesis that remains elusive with restricted therapeutic strategies and efficacy. This study aimed to investigate the role of SMG5, a crucial component in nonsense-mediated mRNA decay (NMD) that degrades mRNA containing a premature termination codon (PTC), in HCC pathogenesis and therapeutic resistance. We demonstrated an elevated expression of SMG5 in HCC and scrutinized its potential as a therapeutic target. Our findings revealed that SMG5 knockdown not only inhibited the migration, invasion, and proliferation of HCC cells but also influenced sorafenib resistance. Differential gene expression analysis between the control and SMG5 knockdown groups showed an upregulation of MAT1A in the latter. High expression of MAT1A, a catalyst for S-adenosylmethionine (SAM) production, as suggested by TCGA data, was indicative of a better prognosis for HCC. Further, an enzyme-linked immunosorbent assay showed a higher concentration of SAM in SMG5 knockdown cell supernatants. Furthermore, we found that exogenous SAM supplementation enhanced the sensitivity of HCC cells to sorafenib alongside changes in the expression of Bax and Bcl 2, apoptosis-related proteins. Our findings underscore the important role of SMG5 in HCC development and its involvement in sorafenib resistance, highlighting it as a potential target for HCC treatment.

Associations between genomic aberrations, increased nuchal translucency, and pregnancy outcomes: a comprehensive analysis of 2,272 singleton pregnancies in women under 35.

Objectives: Regarding increased nuchal translucency (NT), the cutoff values used are heterogeneous in clinical practice, this study aims to assess the efficacy of prenatal detection for chromosomal abnormalities and pregnancy outcomes in fetuses with varying NT thicknesses, in order to provide data that supports informed prenatal diagnosis and genetic counseling for such cases. Methods: We included 2,272 pregnant women under 35 with singleton pregnancies who underwent invasive prenatal diagnosis between 2014 and 2022. The cohort comprised 2,010 fetuses with increased NT (≥2.5 mm) and 262 fetuses with normal NT but exhibiting a single soft marker. Prenatal diagnoses were supported by chromosomal microarray (CMA) and copy number variation sequencing (CNV-seq) analyses. Results: The detection rates of numerical chromosomal abnormalities were 15.4% (309/2,010) and 17.3% (297/1,717) in the NT ≥2.5 and ≥ 3.0 groups, respectively. Pathogenic/likely pathogenic CNV incidence increased with NT thickness (χ2 = 8.60, p < 0.05), peaking at 8.7% (22/254) in the NT 4.5-5.4 mm group. Structural defects were found in 18.4% of fetuses with NT values between 2.5 mm and 2.9 mm. Chromosomal abnormality rates in the isolated increased NT groups of 2.5-2.9 mm and 3.0-3.4 mm were 6.7% (16/239) and 10.0% (47/470), respectively, with no statistical significance (χ2 = 2.14, p > 0.05). Fetuses with NT thickness between 2.5 and 2.9 mm combined with the presence of soft markers or non-lethal structural abnormalities exhibited a significantly higher chromosomal abnormality risk (19.0%) compared to fetuses with isolated increased NT ranging from 3.5 to 4.4 mm (13.0%). Pregnancy termination rates increased with NT thickness (χ2 = 435.18, p < 0.0001), ranging from 12.0% (30/249) in the NT 2.5-2.9 mm group to 87.0% (141/162) in the NT ≥ 6.5 mm group. Conclusion: CMA or CNV-seq exhibited good performance in identifying genomic aberrations in pregnancies with increased NT thickness. NT ranging from 2.5 mm to 2.9 mm elevated the risk of fetal chromosomal abnormalities, particularly when combined with other soft markers.

Prevalence and outcomes of atrial fibrillation in patients suffering prostate cancer: a national analysis in the United States.

Purpose: Although the adverse effects of atrial fibrillation (AF) on cancers have been well reported, the relationship between the AF and the adverse outcomes in prostate cancer (PC) remains inconclusive. This study aimed to explore the prevalence of AF and evaluate the relationship between AF and clinical outcomes in PC patients. Methods: Patients diagnosed with PC between 2008 and 2017 were identified from the National Inpatient Sample database. The trends in AF prevalence were compared among PC patients and their subgroups. Multivariable regression models were used to assess the associations between AF and in-hospital mortality, length of hospital stay, total cost, and other clinical outcomes. Results: 256,239 PC hospitalizations were identified; 41,356 (83.8%) had no AF and 214,883 (16.2%) had AF. AF prevalence increased from 14.0% in 2008 to 20.1% in 2017 (P < .001). In-hospital mortality in PC inpatients with AF increased from 5.1% in 2008 to 8.1% in 2017 (P < .001). AF was associated with adverse clinical outcomes, such as in-hospital mortality, congestive heart failure, pulmonary circulation disorders, renal failure, fluid and electrolyte disorders, cardiogenic shock, higher total cost, and longer length of hospital stay. Conclusions: The prevalence of AF among inpatients with PC increased from 2008 to 2017. AF was associated with poor prognosis and higher health resource utilization. Better management strategies for patients with comorbid PC and AF, particularly in older individuals, are required.

Tetrabromobisphenol-A/S and their derivatives in surface particulates from workshop floors of three representative e-waste recycling sites in China.

Surface particulates collected from the workshop floors of three major e-waste recycling sites (Taizhou, Qingyuan, and Guiyu) in China were analyzed for tetrabromobisphenol A/S (TBBPA/S) and their derivatives to investigate the environmental pollution caused by e-waste recycling activities. Mean concentrations of total TBBPA/S analogs in surface particulates were 31,471-116,059 ng/g dry weight (dw). TBBPA, TBBPA-BGE, and TBBPA-BDBPE were the most frequently detected in particulates with average concentration ranges of 17,929-78,406, 5,601-15,842, and 5,929-21,383 ng/g dw, respectively. Meanwhile, TBBPA, TBBPA-BGE, and TBBPA-BDBPE were the most abundant TBBPA/S analogs, accounting for around 96% of the total. The composition profiles of TBBPA/S analogs differed significantly among three e-waste sites. Similarly, principal component analysis uncovered different pollution patterns among different sites. The discrepancy in the profiles of TBBPA/S analogs largely relied on the e-waste types recycled in different areas. E-waste recycling led to the release of TBBPA/S analogs, and TBBPA/S analogs produced differentiation during migration from source (surface particulates) to nearby soil. More researches are necessary to find a definite relationship between pollution status and e-waste types and study differentiation behavior of TBBPA/S analogs in migration and diffusion from source to environmental medium.

[Non-targeted metabolomics of spleen and liver metabolism in mice treated with Pruni Semen processed with different methods].

Ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was employed to investigate the impacts of Pruni Semen processed with different methods(raw and fried) on the liver and spleen metabolism in mice. A total of 24 male mice were randomly assigned to three groups: raw Pruni Semen group, fried Pruni Semen group, and control(deionized water) group. Mice in the three groups were orally administrated with 0.01 g·mL~(-1) Pruni Semen decoction or deionized water for one week. After that, the liver and spleen tissues were collected, and liquid chromatography-mass spectrometry(LC-MS)-based metabolomic analysis was carried out to investigate the impact of Pruni Semen on the liver and spleen metabolism in mice. Compared with thte control group, the raw Pruni Semen group showed up-regulation of 11 metabolites and down-regulation of 57 metabolites in the spleen(P<0.05), as well as up-regulation of 15 metabolites and down-regulation of 58 metabolites in the liver(P<0.05). The fried Pruni Semen group showed up-regulation of 31 metabolites and down-regulation of 10 metabolites in the spleen(P<0.05), along with up-regulation of 26 metabolites and down-regulation of 61 metabolites in the liver(P<0.05). The differential metabolites identified in the raw Pruni Semen group were primarily associated with alanine, aspartate, and glutamate metabolism, purine metabolism, amino sugar and nucleotide sugar metabolism, and D-glutamine and D-glutamate metabolism. The differential metabolites identified in the fried Pruni Semen group predominantly involved riboflavin metabolism, amino sugar and nucleotide sugar metabolism, purine metabolism, alanine, aspartate, and glutamate metabolism, D-glutamine and D-glutamate metabolism, and glutathione metabolism. The findings suggest that both raw and fried Pruni Semen have the potential to modulate the metabolism of the liver and spleen in mice by influencing the glutamine and glutamate metabolism.

XELOX (capecitabine plus oxaliplatin) plus bevacizumab (anti-VEGF-A antibody) with or without adoptive cell immunotherapy in the treatment of patients with previously untreated metastatic colorectal cancer: a multicenter, open-label, randomized, controlled, phase 3 trial.

Fluoropyrimidine-based combination chemotherapy plus targeted therapy is the standard initial treatment for unresectable metastatic colorectal cancer (mCRC), but the prognosis remains poor. This phase 3 trial (ClinicalTrials.gov: NCT03950154) assessed the efficacy and adverse events (AEs) of the combination of PD-1 blockade-activated DC-CIK (PD1-T) cells with XELOX plus bevacizumab as a first-line therapy in patients with mCRC. A total of 202 participants were enrolled and randomly assigned in a 1:1 ratio to receive either first-line XELOX plus bevacizumab (the control group, n = 102) or the same regimen plus autologous PD1-T cell immunotherapy (the immunotherapy group, n = 100) every 21 days for up to 6 cycles, followed by maintenance treatment with capecitabine and bevacizumab. The main endpoint of the trial was progression-free survival (PFS). The median follow-up was 19.5 months. Median PFS was 14.8 months (95% CI, 11.6-18.0) for the immunotherapy group compared with 9.9 months (8.0-11.8) for the control group (hazard ratio [HR], 0.60 [95% CI, 0.40-0.88]; p = 0.009). Median overall survival (OS) was not reached for the immunotherapy group and 25.6 months (95% CI, 18.3-32.8) for the control group (HR, 0.57 [95% CI, 0.33-0.98]; p = 0.043). Grade 3 or higher AEs occurred in 20.0% of patients in the immunotherapy group and 23.5% in the control groups, with no toxicity-associated deaths reported. The addition of PD1-T cells to first-line XELOX plus bevacizumab demonstrates significant clinical improvement of PFS and OS with well tolerability in patients with previously untreated mCRC.

Exploring the Risk Factors for Deep Vein Thrombosis after Percutaneous Nephrolithotomy.

BACKGROUND: Deep vein thrombosis (DVT), a frequent complication following percutaneous nephrolithotomy (PCNL), may lead to severe conditions like pulmonary embolism. Current knowledge on postoperative DVT risk factors is, however, limited. The aim of our study was to investigate the risk of DVT after PCNL. METHODS: A retrospective study was conducted on patients who underwent PCNL from March 2020 to March 2023 at our institution. Patient demographics and clinical data, including, DVT-specific information, preoperative labs, and surgical details, was evaluated. RESULTS: One hundred patients were included. Thirty-two (20 males, 12 females, mean age 52.5 ± 7.4 years) developed lower limb DVT post-surgery, while the remaining 68 (48 males, 20 females, mean age 51.1 ± 5.5 years) had no DVT symptoms. Analysis revealed significant correlations between hyperlipidemia, operating time, postoperative bed rest duration, D-dimer level on the first day after surgery, Caprini risk assessment model (RAM) score, and DVT risk. D-dimer on the first day after percutaneous nephrolithotomy, postoperative bed rest time and Caprini RAM scores were independent risk factors for DVT after PCNL. Sex, age, hypertension status, diabetes status and smoking and drinking habits were not significantly associated with DVT risk. CONCLUSIONS: D-dimer on the first day after PCNL, postoperative bed rest time and Caprini RAM scores were independent risk factors for DVT after PCNL.

BiMPADR: A Deep Learning Framework for Predicting Adverse Drug Reactions in New Drugs.

Detecting the unintended adverse reactions of drugs (ADRs) is a crucial concern in pharmacological research. The experimental validation of drug-ADR associations often entails expensive and time-consuming investigations. Thus, a computational model to predict ADRs from known associations is essential for enhanced efficiency and cost-effectiveness. Here, we propose BiMPADR, a novel model that integrates drug gene expression into adverse reaction features using a message passing neural network on a bipartite graph of drugs and adverse reactions, leveraging publicly available data. By combining the computed adverse reaction features with the structural fingerprints of drugs, we predict the association between drugs and adverse reactions. Our models obtained high AUC (area under the receiver operating characteristic curve) values ranging from 0.861 to 0.907 in an external drug validation dataset under differential experiment conditions. The case study on multiple BET inhibitors also demonstrated the high accuracy of our predictions, and our model's exploration of potential adverse reactions for HWD-870 has contributed to its research and development for market approval. In summary, our method would provide a promising tool for ADR prediction and drug safety assessment in drug discovery and development.

Analyzing spatio-temporal changes and trade-offs/synergies of gross ecosystem product based on water-energy-food nexus.

The value of the ecosystem's ultimate goods and services for human welfare and long-term economic and social development is known as the gross ecosystem product (GEP). For the study of GEP accounting, the suggested water-energy-food (WEF) nexus offers a fresh viewpoint. This work aims to build a GEP accounting index system based on WEF, investigate its spatio-temporal evolution characteristics, and assess trade-offs and synergies between and within the water, energy, and food subsystems. Using the Three Gorges Reservoir area (TGRA) as an illustration, the findings revealed that, firstly, the comprehensive benefit of GEP based on WEF showed an upward trend in TGRA. Still, it was worth noting that the total production of the food ecosystem decreased. Secondly, the GEP based on WEF in five periods showed a spatial pattern of "high east and west, low middle." Thirdly, the Pearson correlation coefficient indicated that the GEP trade-off relationships based on WEF were dominant in TGRA, with the strongest trade-offs between AQV, SCV, APV, and LEV. In addition, in bivariate local spatial autocorrelation, the value of the six ecosystem service function relationships was dominated by the trade-off relationship, and the distribution of trade-offs and synergies showed significant heterogeneity at the county scale in the TGRA. Finally, hot spot analysis showed that the hot spots of the gross water and energy ecosystem products were scattered in the tail area of the study area. In contrast, the hot spots of the gross food ecosystem product were concentrated in the belly region. The findings of this study provided a basis for the scientific formulation of territorial spatial pattern optimization for water, energy, and agricultural resources in the TGRA and can more accurately reflect the status of the ecological environment and changes of WEF over time. Moreover, this paper also gives full play to the growth advantages of shipping and aquatic products, implements effective soil erosion prevention and control measures, and establishes water-saving mechanisms and other measures in terms of water resources. Subregional plans for industrial structure and strengthening of waste gas and wastewater treatment facilities regarding energy resources are developed. Implement the cultivated land protection system and promote the superiority of crop varieties and other measures in terms of food resources.

Oleuropein alleviates myocardial ischemia-reperfusion injury by suppressing oxidative stress and excessive autophagy via TLR4/MAPK signaling pathway.

BACKGROUND: Myocardial ischemia/reperfusion injury (MIRI) is an important complication of reperfusion therapy, and has a lack of effective prevention and treatment methods. Oleuropein (OP) is a natural strong antioxidant with many protective effects on cardiovascular diseases, but its protective effect on MIRI has not yet been studied in depth. METHODS: Tert-Butyl hydroperoxide (tBHP) was used to establish an in vitro oxidative stress model. Cell viability was detected by 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) and lactate dehydrogenase (LDH). Flow cytometry and fluorescence assays were performed for evaluating the ROS levels and mitochondrial membrane potential (MMP). Immunofluorescence analysis detected the NRF2 nuclear translocation and autophagy indicators. Further, Western blotting and quantitative real-time PCR were performed to evaluate the expression levels of proteins and mRNAs. Molecular docking, CETSA, and molecular interaction analysis explored the binding between OP and TLR4. The protective effects of OP in vivo were determined using a preclinical MIRI rat model. RESULTS: OP protected against tBHP-treated injury, reduced ROS levels and reversed the damaged MMP. Mechanistically, OP activated NRF2-related antioxidant pathways, inhibited autophagy and attenuated the TLR4/MAPK signaling pathway in tBHP-treated H9C2 cells with a high binding affinity to TLR4 (KD = 37.5 µM). The TLR4 inhibitor TAK242 showed a similar effect as OP. In vivo, OP could alleviate cardiac ischemia/reperfusion injury and it ameliorated adverse cardiac remodeling. Consistent with in vitro studies, OP inhibited TLR4/MAPK and autophagy pathway and activated NRF2-dependent antioxidant pathways in vivo. CONCLUSION: This study shows that OP binds to TLR4 to regulate oxidative stress and autophagy for protecting damaged cardiomyocytes, supporting that OP can be a potential therapeutic agent for MIRI.

A comprehensive benchmark of graph-based genetic variant genotyping algorithms on plant genomes for creating an accurate ensemble pipeline.

BACKGROUND: Although sequencing technologies have boosted the measurement of the genomic diversity of plant crops, it remains challenging to accurately genotype millions of genetic variants, especially structural variations, with only short reads. In recent years, many graph-based variation genotyping methods have been developed to address this issue and tested for human genomes. However, their performance in plant genomes remains largely elusive. Furthermore, pipelines integrating the advantages of current genotyping methods might be required, considering the different complexity of plant genomes. RESULTS: Here we comprehensively evaluate eight such genotypers in different scenarios in terms of variant type and size, sequencing parameters, genomic context, and complexity, as well as graph size, using both simulated and real data sets from representative plant genomes. Our evaluation reveals that there are still great challenges to applying existing methods to plants, such as excessive repeats and variants or high resource consumption. Therefore, we propose a pipeline called Ensemble Variant Genotyper (EVG) that can achieve better genotyping performance in almost all experimental scenarios and comparably higher genotyping recall and precision even using 5× reads. Furthermore, we demonstrate that EVG is more robust with an increasing number of graphed genomes, especially for insertions and deletions. CONCLUSIONS: Our study will provide new insights into the development and application of graph-based genotyping algorithms. We conclude that EVG provides an accurate, unbiased, and cost-effective way for genotyping both small and large variations and will be potentially used in population-scale genotyping for large, repetitive, and heterozygous plant genomes.

Artificial intelligence powered advancements in upper extremity joint MRI: A review.

Magnetic resonance imaging (MRI) is an indispensable medical imaging examination technique in musculoskeletal medicine. Modern MRI techniques achieve superior high-quality multiplanar imaging of soft tissue and skeletal pathologies without the harmful effects of ionizing radiation. Some current limitations of MRI include long acquisition times, artifacts, and noise. In addition, it is often challenging to distinguish abutting or closely applied soft tissue structures with similar signal characteristics. In the past decade, Artificial Intelligence (AI) has been widely employed in musculoskeletal MRI to help reduce the image acquisition time and improve image quality. Apart from being able to reduce medical costs, AI can assist clinicians in diagnosing diseases more accurately. This will effectively help formulate appropriate treatment plans and ultimately improve patient care. This review article intends to summarize AI's current research and application in musculoskeletal MRI, particularly the advancement of DL in identifying the structure and lesions of upper extremity joints in MRI images.

Unveiling the Impact of Hemodynamics on Endothelial Inflammation-Mediated Hepatocellular Carcinoma Metastasis Using a Biomimetic Vascular Flow Model.

Hepatocellular carcinoma (HCC) hematogenous dissemination is a leading cause of HCC-related deaths. The inflammatory facilitates this process by promoting the adhesion and invasion of tumor cells in the circulatory system. But the contribution of hemodynamics to this process remains poorly understood due to the lack of a suitable vascular flow model for investigation. This study develops a vascular flow model to examine the impact of hemodynamics on endothelial inflammation-mediated HCC metastasis. This work finds the increasing shear stress will reduce the recruitment of HCC cells by disturbing adhesion forces between endothelium and HCC cells. However, this reduction will be restored by the inflammation. When applying high FSS (4-6 dyn cm-2) to the inflammatory endothelium, there will be a 4.8-fold increase in HCC cell adhesions compared to normal condition. Nevertheless, the increase fold of cell adhesions is inapparent, around 1.5-fold, with low and medium FSS. This effect can be attributed to the FSS-induced upregulation of ICAM-1 and VCAM-1 of the inflammatory endothelium, which serve to strengthen cell binding forces. These findings indicate that hemodynamics plays a key role in HCC metastasis during endothelial inflammation by regulating the expression of adhesion-related factors.