The causal relationship between rheumatoid arthritis and bronchiectasis: a bidirectional Mendelian randomization study.

Background: Several observational studies suggested an association between rheumatoid arthritis (RA) and bronchiectasis. Nevertheless, the presence of a causal relationship between these conditions is yet to be determined. This study aimed to investigate whether genetically predicted RA is associated with the risk of bronchiectasis and vice versa. Methods: We obtained RA genome-wide association study (GWAS) data from FinnGen consortium, and bronchiectasis GWAS data from IEU Open GWAS project. Univariate Mendelian randomization (MR) analysis was performed using inverse variance weighted (IVW) estimation as the main method. Furthermore, bidirectional and replication MR analysis, multivariate MR (MVMR), Mediation analysis, and sensitivity analyses were conducted to validate the findings. Results: In the UVMR analysis, the IVW results revealed that RA had an increased risk of bronchiectasis (OR = 1.18, 95% CI = 1.10-1.27; p = 2.34 × 10-6). In the reverse MR analysis, no evidence of a causal effect of bronchiectasis on the risk of RA was detected. Conversely, in the replication MR analysis, RA remained associated with an increased risk of bronchiectasis. Estimates remained consistent in MVMR analyses after adjusting for the prescription of non-steroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids. Immunosuppressants were found to mediate 58% of the effect of the RA on bronchiectasis. Sensitivity analyses confirmed the stability of these associations. Conclusion: This study demonstrated a positive causal relationship between RA and an increased risk of bronchiectasis, offering insights for the early prevention of bronchiectasis in RA patients and shedding new light on the potential role of immunosuppressants as mediators in promoting the effects of RA on bronchiectasis.

Integration analysis of miRNA-mRNA pairs between two contrasting genotypes reveals the molecular mechanism of jujube (Ziziphus jujuba Mill.) response to high-temperature stress.

With global warming, high temperature (HT) has become one of the most common abiotic stresses resulting in significant crop yield losses, especially for jujube (Ziziphus jujuba Mill.), an important temperate economic crop cultivated worldwide. This study aims to explore the coping mechanism of jujube to HT stress at the transcriptional and post-transcriptional levels, including identifying differentially expressed miRNAs and mRNAs as well as elucidating the critical pathways involved. High-throughput sequencing analyses of miRNA and mRNA were performed on jujube leaves, which were collected from "Fucumi" (heat-tolerant) and "Junzao" (heat-sensitive) cultivars subjected to HT stress (42 °C) for 0, 1, 3, 5, and 7 days, respectively. The results showed that 45 known miRNAs, 482 novel miRNAs, and 13,884 differentially expressed mRNAs (DEMs) were identified. Among them, integrated analysis of miRNA target genes prediction and mRNA-seq obtained 1306 differentially expressed miRNAs-mRNAs pairs, including 484, 769, and 865 DEMIs-DEMs pairs discovered in "Fucuimi", "Junzao" and two genotypes comparative groups, respectively. Furthermore, functional enrichment analysis of 1306 DEMs revealed that plant-pathogen interaction, starch and sucrose metabolism, spliceosome, and plant hormone signal transduction were crucial pathways in jujube leaves response to HT stress. The constructed miRNA-mRNA network, composed of 20 DEMIs and 33 DEMs, displayed significant differently expressions between these two genotypes. This study further proved the regulatory role of miRNAs in the response to HT stress in plants and will provide a theoretical foundation for the innovation and cultivation of heat-tolerant varieties.

Topology Control of Covalent Organic Frameworks with Interlaced Unsaturated 2D and Saturated 3D Units for Boosting Electrocatalytic Hydrogen Peroxide Production.

Modulating the electronic state of multicomponent covalent organic framework (COF) electrocatalysts is crucial for enhancing catalytic activity. However, the effect of dimensionality on their physicochemical functionalities is still lacking. Herein, we report an interlaced unsaturated 2D and saturated 3D strategy to develop multicomponent-regulated COFs with tunable gradient dimensionality for high selectivity and activity electrocatalysis. Compared with the two-component 2D and 3D model COFs, the 2D/3D framework interlaced COFs with locally irregular dimensions and electronic structures are more practical in optimizing the intrinsic electrode surface reaction and mass transfer. Remarkably, the unsaturated 2D-inserted 3D TAE-COF regulates the adsorption mode of OOH* species to supply a favorable dynamic pathway for the H2O2 process, thereby achieving an excellent production rate of 8.50 mol gcat-1 h-1. Moreover, utilizing theoretical calculation and in situ ATR-FTIR experiment, we found that the central carbon atom of the tetraphenyl-based unit (site-1 and site-6) are potential active sites. This strategy of operating the adsorption ability of reactants with dimensionality-interconnected building blocks provides an idea for designing durable and efficient electrocatalysts.

Action Programmed Nanoantibiotics with pH-Induced Collapse and Negative-Charged-Surface-Induced Deformation against Antibiotic-Resistant Bacterial Peritonitis.

The incorporation of well-designed antibiotic nanocarriers, along with an antibiotic adjuvant effect, in combination with various antibiotics, offers an opportunity to combat drug-resistant strains. However, precise control over morphology and encapsulated payload release can significantly impact their antibacterial efficacy and synergistic effects when used alongside antibiotics. Here, this study focuses on developing lipopeptide-based nanoantibiotics, which demonstrate an antibiotic adjuvant effect by inducing pH-induced collapse and negative-charged-surface-induced deformation. This enhances the disruption of the bacterial outer membrane and facilitates drug penetration, effectively boosting the antimicrobial activity against drug-resistant strains. The modulation regulations of the lipopeptide nanocarriers with modular design are governed by the authors. The nanoantibiotics, made from lipopeptide and ciprofloxacin (Cip), have a drug loading efficiency of over 80%. The combination with Cip results in a significantly low fractional inhibitory concentration index of 0.375 and a remarkable reduction in the minimum inhibitory concentration of Cip against multidrug-resistant (MDR) Escherichia coli (clinical isolated strains) by up to 32-fold. The survival rate of MDR E. coli peritonitis treated with nanoantibiotics is significantly higher, reaching over 87%, compared to only 25% for Cip and no survival for the control group. Meanwhile, the nanoantibiotic shows no obvious toxicity to major organs.

Downregulation of enhancer RNA AC003092.1 is associated with poor prognosis in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) is the most common histological type of renal cancer, enhancer RNA plays a significant role in tumor growth, however, it has been less studied in renal cancer. The aim of this study was to investigate the role of eRNA AC003092.1 in KIRC. Clinical and RNA expression data were downloaded from a TCGA database, and performed bioinformatics analysis, including expression level analysis, survival analysis, clinical correlation analysis, immune correlation analysis. We further confirmed the expression level of AC003092.1 between normal and tumor cell, predicted the biological role of AC003092.1 in KIRC, and performed cell proliferation and wound healing assays, followed by GSEA enrichment analysis and western blot to detect the proteins of the enriched pathway. Bioinformatics results showed that AC003092.1 expression was elevated in tumor tissues, and knockdown of AC003092.1 expression inhibited cell proliferation and migration. GSEA and western blot results showed that knockdown AC003092.1 expression alleviated the extracellular matrix (ECM) process in KIRC cell lines. Our study provides evidence that AC003092.1 play an important role in KIRC, and AC003092.1 may promote tumor cell progression by affecting the ECM process during tumor development.

Influence of Cold Wave Diversities on Thermal Stress and Thermal Fatigue Life of Asphalt Mixture.

Apart from low-temperature cracking, asphalt pavement may also suffer from thermal fatigue cracking. To clarify the impact of cold waves on the thermal fatigue performance of asphalt mixtures, the typical atmospheric temperature characteristics of different regions in China from 2012 to 2019 were analyzed, and the frequency of cold waves in these regions was determined. The viscoelastic parameters of an asphalt mixture are determined through an indirect tensile relaxation test. The thermal stress of the asphalt mixture is simulated and analyzed by using the finite element method. The effect of cold waves on the thermal fatigue life of the asphalt mixture was evaluated. The results show that the frequency of cold waves is different from region to region in China, and the cold waves mainly occurred from October of one year to February of the next year. Northeast China has the most frequency and the largest temperature drop amplitude, followed by North China. The maximum thermal stress increases with the decrease in temperature drop and initial temperature and is unrelated to the duration of cold waves. The thermal stress calculated based on the atmospheric thermal boundary is higher than the value using the road surface temperature. The thermal fatigue lives of asphalt mixtures in North China and Northeast China are very short, while the thermal fatigue life of the mixture in Central China is the longest. To meet the requirement of thermal fatigue damage caused by cold waves during the designed service stage, the recommended threshold for thermal stress is 0.39-0.77 MPa.

Adsorption Behavior of Co2+, Ni2+, Sr2+, Cs+, and I- by Corrosion Products α-FeOOH from Typical Metal Tanks.

Throughout the nuclear power production process, the disposal of radioactive waste has consistently raised concerns about environmental safety. When the metal tanks used for waste disposal are corroded, radionuclides seep into the groundwater environment and eventually into the biosphere, causing significant damage to the environment. Hence, investigating the adsorption behavior of radionuclides on the corrosion products of metal tanks used for waste disposal is an essential component of safety and evaluation protocols at disposal sites. In order to understand the adsorption behavior of important radionuclides 60Co, 59Ni, 90Sr, 135Cs and 129I on α-FeOOH, the influences of different pH values, contact time, temperature and ion concentration on the adsorption rate were studied. The adsorption mechanism was also discussed. It was revealed that the adsorption of key nuclides onto α-FeOOH is significantly influenced by both pH and temperature. This change in surface charge corresponds to alterations in the morphology of nuclide ions within the system, subsequently impacting the adsorption efficiency. Sodium ions (Na+) and chlorate ions (ClO3-) compete for coordination with nuclide ions, thereby exerting an additional influence on the adsorption process. The XPS analysis results demonstrate the formation of an internal coordination bond (Ni-O bond) between Ni2+ and iron oxide, which is adsorbed onto α-FeOOH.

Efficacy and safety of Shenmai injection for acute ischemic stroke: a systematic review and meta-analysis.

Background: Ischemic stroke is a serious and sudden cerebrovascular condition that significantly affects individual's health and imposes a substantial economic burden on medical management. Despite its widespread use in China, there is still a lack of reliable evidence regarding the efficacy of Shenmai injection (SMI) in acute ischemic stroke (AIS). We aimed to comprehensively assess the effectiveness and safety of SMI in treating AIS through a systematic review and meta-analysis. Methods: Randomized controlled studies (RCTs) investigating the efficacy of SMI in treating AIS were searched for in eight databases from the inception of each database till January 2024. We utilized the ROB 2.0 to assess the risk of bias. A meta-analysis was conducted using Review Manager 5.4, while sensitivity analyses and publication bias assessments were conducted using Stata 16.1. Results: A total of 17 studies involving 1,603 AIS patients were included in our meta-analysis. Our results showed that SMI plus conventional treatments (CTs) was more effective than CTs alone in improving the total effective rate (RR 1.22, 95% CI: 1.14 to 1.30, p < 0.00001), the Barthel index (BI) (MD 12.18, 95% CI: 10.30 to 14.06, p < 0.00001), and reducing the National Institute of Health Stroke Scale Score (NIHSS) score (MD -3.05, 95% CI: 3.85 to -2.24, p < 0.00001) and Modified Rankin Scale (mRS) (MD -0.68, 95% CI: 0.86 to-0.49, p < 0.00001). In addition, SMI combination therapy was better than CTs alone in decreasing the levels of IL-6, IL-18, and hs-CRP. SMI therapy also enhanced the cerebral hemorheology of patients by reducing levels of fibrinogen and plasma viscosity. However, there was no significant difference in the incidence of adverse events, including elevated transaminase, rash, nausea, bleeding, urticaria, headache, vomiting, chest tightness, and facial flushes. Moreover, no serious adverse effects or life-threatening events were reported. Conclusion: Our study shows that combining SMI with CTs effectively enhances the neurological function of patients with acute cerebral infarction. However, our findings should be interpreted considering the significant heterogeneity and suboptimal quality of the analyzed trials. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024504675, Identifier PROSPERO, CRD42024504675.

Simultaneously enhancement of methane production and active phosphorus transformation by sludge-based biochar during high solids anaerobic co-digestion of dewatered sludge and food waste: Performance and mechanism.

Biochar has been proved to improve methane production in high solids anaerobic co-digestion (HS-AcoD) of dewatered sludge (DS) and food waste (FW), but its potential mechanism for simultaneous methane production and phosphorus (P) transformation has not been sufficiently revealed. Results showed that the optimal preparation temperature and dosage of sludge-based biochar were selected as 300 °C and 0.075 g·g-1, respectively. Under this optimized condition, the methane production of the semi-continuous reactor increased by 54%, and the active phosphorus increased by 18%. The functional microorganisms, such as Methanosarcina, hydrogen-producing, sulfate-reducing, and iron-reducing bacteria, were increased. Metabolic pathways associated with sulfate reduction and methanogenesis, especially hydrogenotrophic methanogenesis, were enhanced, which in turn promoted methanogenesis and phosphorus transformation and release. This study provides theoretical support for simultaneously recovery of carbon and phosphorus resources from DS and FW using biochar.

Identification of Multiple Diseases in Apple Leaf Based on Optimized Lightweight Convolutional Neural Network.

In this study, our aim is to find an effective method to solve the problem of disease similarity caused by multiple diseases occurring on the same leaf. This study proposes the use of an optimized RegNet model to identify seven common apple leaf diseases. We conducted comparisons and analyses on the impact of various factors, such as training methods, data expansion methods, optimizer selection, image background, and other factors, on model performance. The findings suggest that utilizing offline expansion and transfer learning to fine-tune all layer parameters can enhance the model's classification performance, while complex image backgrounds significantly influence model performance. Additionally, the optimized RegNet network model demonstrates good generalization ability for both datasets, achieving testing accuracies of 93.85% and 99.23%, respectively. These results highlight the potential of the optimized RegNet network model to achieve high-precision identification of different diseases on the same apple leaf under complex field backgrounds. This will be of great significance for intelligent disease identification in apple orchards in the future.

Exploration into the Mechanism of Yiyi Baijiang Decoction Attenuating Chronic Pelvic Inflammation Based on Network Pharmacology and Experimental Verification.

Patients with chronic pelvic inflammation (CPI) experience irregular menstrual, ectopic pregnancy, and infertility. Yiyi Baijiang Decoction attenuates CPI in patients with uncovered mechanisms. CPI therapeutic targets intersected with those of Yiyi Baijiang Decoction, followed by importing into STRING to obtain protein-target interaction. "Drug-component-disease-target" interaction was constructed by Cytoscape. mRNA and protein levels were detected by real-time quantitative PCR (RT-qPCR) and western blot. Yiyi Baijiang Decoction contained 199 active ingredients. There were 1071 drug targets for Yiyi Baijiang Decoction and 1622 therapeutic targets for CPI. The GO functional enrichment analysis revealed 3445 biological processes, and the KEGG pathway enrichment analysis screened 67 signal pathways. Decreased ALB, increased protein kinase B (AKT1), interleukin (IL)-6, vascular endothelial growth factor A (VEGFA), and phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K/AKT)-extracellular-regulated protein kinases (ERK)1/2 activation in CPI mice were abolished by Yiyi Baijiang Decoction. Yiyi Baijiang Decoction attenuates CPI by inactivating PI3K/AKT and ERK1/2 and regulating ALB, VEGFA, AKT1, and IL-6.

Crystal structure optimization of copper oxides for the benzyl alcohol oxidation reaction.

In this work, experimental and theoretical analyses reveal that different types of Cu wires significantly change the adsorption properties of reactant molecules and the benzyl alcohol oxidation reaction performance. In particular, CuO nanowires in situ grown on Cu foam exhibit the best performance with a low potential of 1.39 V at a current density of 200 mA cm-2, high selectivity to benzoic acid production, and good operational stability.

Mechanisms underlying neutrophils adhesion to triple-negative breast cancer cells via CD11b-ICAM1 in promoting breast cancer progression.

BACKGROUND: Triple-negative breast cancer (TNBC) is recognized as the most aggressive and immunologically infiltrated subtype of breast cancer. A high circulating neutrophil-to-lymphocyte ratio (NLR) is strongly linked to a poor prognosis among patients with breast cancer, emphasizing the critical role of neutrophils. Although the involvement of neutrophils in tumor metastasis is well documented, their interactions with primary tumors and tumor cells are not yet fully understood. METHODS: Clinical data were analyzed to investigate the role of neutrophils in breast cancer. In vivo mouse model and in vitro co-culture system were used for mechanism researches. Blocking experiments were further performed to identify therapeutic agents against TNBC. RESULTS: TNBC cells secreted GM-CSF to sustain the survival of mature neutrophils and upregulated CD11b expression. Through CD11b, neutrophils specifically binded to ICAM1 on TNBC cells, facilitating adhesion. Transcriptomic sequencing combined with human and murine functional experiments revealed that neutrophils, through direct CD11b-ICAM1 interactions, activated the MAPK signaling pathway in TNBC cells, thereby enhancing tumor cell invasion and migration. Atorvastatin effectively inhibited ICAM1 expression in tumor cells, and tumor cells with ICAM1 knockout or treated with atorvastatin were unresponsive to neutrophil activation. The MAPK pathway and MMP9 expression were significantly inhibited in the tumor tissues of TNBC patients treated with atorvastatin. CONCLUSIONS: Targeting CD11b-ICAM1 with atorvastatin represented a potential clinical approach to reduce the malignant characteristics of TNBC.

Unexpected decrease in necrotizing enterocolitis morbidity during the COVID-19 pandemic-A single-centre retrospective study.

Background: The impact of the coronavirus disease 2019 (COVID-19) pandemic on neonatal necrotizing enterocolitis (NEC) is not well characterised. This cross-sectional study evaluated the potential effects of pandemic-related measures on NEC morbidity in premature infants in a neonatal ward during the COVID-19 pandemic. Methods: This was a retrospective study conducted in a tertiary neonatal ward in eastern and central China over 6 consecutive years (2017, 2018, 2019, 2020, 2021 and 2022). The medical records of 189 premature infants with stage II or III NEC were reviewed for clinical manifestations and aetiologies. The data were analysed and compared between the prepandemic period (2017, 2018, and 2019) and the pandemic period (2020, 2021 and 2022). Results: A total of 9,903 infants with gestational age (GA) < 37 weeks were enrolled, including 5,382 in the prepandemic period and 4,521 in the pandemic period. A reduction in stage II or III NEC morbidity was observed in infants with GA < 37 weeks, with an average annual morbidity of 2.29% (123/5,382) (95% CI, 1.89%-2.68%) in the prepandemic period and 1.46% (66/4,521) (95% CI, 1.11%-1.81%) in the pandemic period. NEC morbidity showed resurgent characteristics in 2021. When prepandemic coinfections were excluded, most cases of NEC with bloodstream infections in the prepandemic period were attributable to Gram-negative bacteria (27/32, 84.38%), mainly Klebsiella pneumoniae, while in the pandemic period they were attributable to Gram-positive bacteria (10/18, 55.56%), mainly Staphylococcus aureus. Antimicrobial susceptibility testing revealed that Klebsiella pneumoniae was 100% sensitive to meropenem, imipenem, ciprofloxacin and levofloxacin and 100% resistant to ampicillin. Staphylococcus capitis was 100% sensitive to vancomycin, linezolid, tetracycline, cotrimoxazole and cefoxitin and 100% resistant to penicillin and benzathine. Conclusions: COVID-19 pandemic-related interventions can reduce the morbidity of NEC and change the pathogen spectrum in patients with bloodstream infections. We need to understand the exact factors leading to these changes.

Depleting profibrotic macrophages using bioactivated in vivo assembly peptides ameliorates kidney fibrosis.

Managing renal fibrosis is challenging owing to the complex cell signaling redundancy in diseased kidneys. Renal fibrosis involves an immune response dominated by macrophages, which activates myofibroblasts in fibrotic niches. However, macrophages exhibit high heterogeneity, hindering their potential as therapeutic cell targets. Herein, we aimed to eliminate specific macrophage subsets that drive the profibrotic immune response in the kidney both temporally and spatially. We identified the major profibrotic macrophage subset (Fn1+Spp1+Arg1+) in the kidney and then constructed a 12-mer glycopeptide that was designated as bioactivated in vivo assembly PK (BIVA-PK) to deplete these cells. BIVA-PK specifically binds to and is internalized by profibrotic macrophages. By inducing macrophage cell death, BIVA-PK reshaped the renal microenvironment and suppressed profibrotic immune responses. The robust efficacy of BIVA-PK in ameliorating renal fibrosis and preserving kidney function highlights the value of targeting macrophage subsets as a potential therapy for patients with CKD.

The anti-hyperplasia effect of polysaccharide from Prunella vulgaris L. on mammary gland hyperplasia in rats through regulation of the AKT-FOXO3a signaling pathway and intestinal flora.

BACKGROUND: Prunella vulgaris L., a medicinal and edible homologous plant, is often used to treat conditions such as breast hyperplasia, thyroid enlargement and lymphatic tuberculosis. Research has demonstrated that it is particularly effective in the treatment of mammary gland hyperplasia (MGH). However, the material basis and mechanism of its efficacy are still unclear. RESULTS: Our results showed that in rats with MGH, polysaccharide from Prunella vulgaris L. (PVP) led to a reduction in the levels of estradiol, prolactin and malondialdehyde, while simultaneously increasing the concentrations of progesterone (P), superoxide dismutase (SOD), manganese superoxide dismutase (MnSOD) and catalase (CAT) in the serum. In addition, results obtained from 16S rRNA sequencing demonstrated that PVP had the capacity to increase the richness and diversity of the intestinal microbiota in MGH rats, as well as modify the structure of the microbiota. Correlation analysis revealed that the levels of P, SOD, MnSOD and CAT were positively associated with Allobaculum, Romboutsia, Faecalibaculum and Clostridium, while negatively correlated with Turicibacter. CONCLUSIONS: The mechanism of PVP in treating MGH might be through inhibiting the phosphorylation of the AKT-FOXO3a signaling pathway and then activating the expression of downstream antioxidant enzymes, such as MnSOD and CAT. At the same time, PVP could restore intestinal flora homeostasis in rats with MGH by regulating the flora changes of Allobaculum, Romboutsia, Clostridium and Faecalibaculum, thereby reducing oxidative stress in rats with MGH. © 2024 Society of Chemical Industry.

Development of a non-intercepting weak beam current measurement electronics for Heavy Ion Accelerator Facility in Lanzhou.

Non-destructive measurements of low-intensity charged particle beams are particularly challenging for beam diagnostics. At the Heavy Ion Accelerator Facility in Lanzhou (HIRFL), beams with weak currents below 1 µA are often provided for experiments. The detection of such low beam current is below the threshold of typical standard beam current transformers. Therefore, a low-intensity monitoring system is developed by using a sensitive capacitive pick-up (PU) and low-noise electronics. This device measures beam currents by digitally analyzing the amplitude of the PU signals using a homodyne detection scheme. During lab tests, the amplitude nonlinearity is <0.5% in the operational range of 1 nA-45 µA and the amplitude resolution is 0.94 nA. At present, four measurement systems for low beam currents are installed at HIRFL for the monitoring of standard operating conditions with low beam currents below 1 µA. After an absolute calibration with a Faraday cup, it can be used for accurate beam intensity measurement with a current resolution of about 1 nA.

Development of a logic regression-based approach for the discovery of host- and niche-informative biomarkers in Escherichia coli and their application for microbial source tracking.

Microbial source tracking leverages a wide range of approaches designed to trace the origins of fecal contamination in aquatic environments. Although source tracking methods are typically employed within the laboratory setting, computational techniques can be leveraged to advance microbial source tracking methodology. Herein, we present a logic regression-based supervised learning approach for the discovery of source-informative genetic markers within intergenic regions across the Escherichia coli genome that can be used for source tracking. With just single intergenic loci, logic regression was able to identify highly source-specific (i.e., exceeding 97.00%) biomarkers for a wide range of host and niche sources, with sensitivities reaching as high as 30.00%-50.00% for certain source categories, including pig, sheep, mouse, and wastewater, depending on the specific intergenic locus analyzed. Restricting the source range to reflect the most prominent zoonotic sources of E. coli transmission (i.e., bovine, chicken, human, and pig) allowed for the generation of informative biomarkers for all host categories, with specificities of at least 90.00% and sensitivities between 12.50% and 70.00%, using the sequence data from key intergenic regions, including emrKY-evgAS, ibsB-(mdtABCD-baeSR), ompC-rcsDB, and yedS-yedR, that appear to be involved in antibiotic resistance. Remarkably, we were able to use this approach to classify 48 out of 113 river water E. coli isolates collected in Northwestern Sweden as either beaver, human, or reindeer in origin with a high degree of consensus-thus highlighting the potential of logic regression modeling as a novel approach for augmenting current source tracking efforts.IMPORTANCEThe presence of microbial contaminants, particularly from fecal sources, within water poses a serious risk to public health. The health and economic burden of waterborne pathogens can be substantial-as such, the ability to detect and identify the sources of fecal contamination in environmental waters is crucial for the control of waterborne diseases. This can be accomplished through microbial source tracking, which involves the use of various laboratory techniques to trace the origins of microbial pollution in the environment. Building on current source tracking methodology, we describe a novel workflow that uses logic regression, a supervised machine learning method, to discover genetic markers in Escherichia coli, a common fecal indicator bacterium, that can be used for source tracking efforts. Importantly, our research provides an example of how the rise in prominence of machine learning algorithms can be applied to improve upon current microbial source tracking methodology.

[A design of interactive review for computer aided diagnosis of pulmonary nodules based on active learning].

Automatic detection of pulmonary nodule based on computer tomography (CT) images can significantly improve the diagnosis and treatment of lung cancer. However, there is a lack of effective interactive tools to record the marked results of radiologists in real time and feed them back to the algorithm model for iterative optimization. This paper designed and developed an online interactive review system supporting the assisted diagnosis of lung nodules in CT images. Lung nodules were detected by the preset model and presented to doctors, who marked or corrected the lung nodules detected by the system with their professional knowledge, and then iteratively optimized the AI model with active learning strategy according to the marked results of radiologists to continuously improve the accuracy of the model. The subset 5-9 dataset of the lung nodule analysis 2016(LUNA16) was used for iteration experiments. The precision, F1-score and MioU indexes were steadily improved with the increase of the number of iterations, and the precision increased from 0.213 9 to 0.565 6. The results in this paper show that the system not only uses deep segmentation model to assist radiologists, but also optimizes the model by using radiologists' feedback information to the maximum extent, iteratively improving the accuracy of the model and better assisting radiologists.

Diagnosis and management of inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic and relapsing immune-mediated disease of the gastrointestinal tract with a gradually increasing global incidence and prevalence. A prolonged course of IBD leads to a decline in patient quality of life and the creation of a substantial economic burden on society. Owing to the lack of specific diagnostic markers, the diagnosis of IBD still needs a gold standard based on a combination of clinical manifestations, imaging, laboratory, and endoscopic results. Accordingly, the current goals of IBD treatment are to alleviate clinical symptoms and reduce recurrence rates. Therefore, it is imperative to develop a standard set of procedures to diagnose and treat IBD. In this review, we summarize prominent and emerging studies, outline classical and contemporary approaches to diagnosing and managing IBD, and integrate multiple guidelines. Furthermore, we propose the possibility of establishing an early and comprehensive diagnostic workflow and personalized management strategy in the future. We aim to enhance the quality and standardization of diagnostic and treatment procedures for IBD.