Stratified analysis of risk factors affecting vasovagal reactions in first-time whole blood donors: a regional multi-center donor hemovigilance data study.

BACKGROUND AND OBJECTIVES: Vasovagal reactions (VVR) are the most common adverse reactions in blood donation. This study aimed to provide and analyze the data of the regional hemovigilance system in Chongqing, China from 2020 to 2022, report the prevalence and explore the risk factors of VVR. MATERIALS AND METHODS: R software (version 4.2.3) was used for all statistical analyses. Frequency and composition rates were used to describe the data of total donation , as well as data on the different types of ADR. The Chi-square test was used to analyze risk factors for VVR and inter-group comparisons of VVR stratified by gender (female/male), age (18-22; 23-29; 30-39; 40-49; 50-60) and season(Spring (Mar.-May.); Summer (Jun.-Aug.); Autumn (sep.-Nov.); Winter (Dec.-Feb.)). RESULTS: The reported incidence rate of VVR was 8.69‰ during whole blood donations and 1.02‰ during platelet-apheresis donations.The stratified analysis revealed that female donors aged 18-22 years old and 30-39 years old were reported to have lower VVR rates than male donors, oppositely, higher in females in 50-60 years old. Statistically significant differences in the incidence rate of VVR were observed between winter and summer, and between winter and spring in 18-49 years old. No seasonal variation was found in 50-60 years old. CONCLUSIONS: The reported incidence rate of VVR related to blood donation was very low and varied from those calculated by other haemovigilance systems. The higher prevalence of VVR in young, first-time donors, college students, donating in mobile vehicles, males and in spring. Among first-time donors, the prevalence of VVR was higher in males than in females; and stratified analysis revealed there were seasonal variation and gender differences within a same age group.

Influences of released humic acids during thermal hydrolysis on sludge anaerobic digestion: New insights from the molecular weight of humic acids.

Humic acids (HAs) would be excessively released during thermal hydrolysis pretreatment (THP) and deeply disturb anaerobic digestion (AD) of waste activated sludge (WAS). The molecular weights of HAs could affect HAs entering microbial cells, binding with digestive enzymes and participating in electron transfer, thereby determining its influences on sludge AD. Results in this study confirmed the different influences of HAs from diverse sources on sludge AD indeed had significant correlations with their molecular weights. The presence of commercial HAs (SAHA) inhibited methane production by 53.3% at 0.5 g/L while HAs extracted from raw sludge (WNHA) increased methane production by 20.5% at the same concentration, which attribute to the comprehensive impacts from their differences in functional group compositions and molecular weights. Moreover, comparing to WNHA, the HAs extracted from thermally hydrolyzed sludge (THHA) showed unchanged functional group compositions but reduced methane generation facilitation to 5.1%, which only be due to its decreased molecular weights. In-depth research indicated that HAs influences on enzymes were closely relative to its molecular weight. HAs with greater molecular weights presented more significant inhibition to extracellular enzymes while micromolecular HAs affected intracellular enzymes more. Furthermore, macromolecular HAs promoted sludge solubilization and acidification but hindered hydrolysis and methanogenesis, whereas micromolecular HAs promoted acidification but inhibited methanogenesis. This study underscored the importance of changes in molecular weight of HAs during sludge THP, offering insights into previous discrepancies in reports on HAs effects on sludge AD.

Processing imbalanced medical data at the data level with assisted-reproduction data as an example.

OBJECTIVE: Data imbalance is a pervasive issue in medical data mining, often leading to biased and unreliable predictive models. This study aims to address the urgent need for effective strategies to mitigate the impact of data imbalance on classification models. We focus on quantifying the effects of different imbalance degrees and sample sizes on model performance, identifying optimal cut-off values, and evaluating the efficacy of various methods to enhance model accuracy in highly imbalanced and small sample size scenarios. METHODS: We collected medical records of patients receiving assisted reproductive treatment in a reproductive medicine center. Random forest was used to screen the key variables for the prediction target. Various datasets with different imbalance degrees and sample sizes were constructed to compare the classification performance of logistic regression models. Metrics such as AUC, G-mean, F1-Score, Accuracy, Recall, and Precision were used for evaluation. Four imbalance treatment methods (SMOTE, ADASYN, OSS, and CNN) were applied to datasets with low positive rates and small sample sizes to assess their effectiveness. RESULTS: The logistic model's performance was low when the positive rate was below 10% but stabilized beyond this threshold. Similarly, sample sizes below 1200 yielded poor results, with improvement seen above this threshold. For robustness, the optimal cut-offs for positive rate and sample size were identified as 15% and 1500, respectively. SMOTE and ADASYN oversampling significantly improved classification performance in datasets with low positive rates and small sample sizes. CONCLUSIONS: The study identifies a positive rate of 15% and a sample size of 1500 as optimal cut-offs for stable logistic model performance. For datasets with low positive rates and small sample sizes, SMOTE and ADASYN are recommended to improve balance and model accuracy.

Application and mechanistic insights of a washing/microwave/ultrasonic ternary pretreatment for enhancing barite flotation in waste drilling fluids.

A quantity of recoverable barite exists in high-density waste drilling fluid. Based on the inefficiencies and complexities of existing recycling methods, a novel pre-treatment approach which includes clean-breaking, high-speed washing, ultrasonic dispersion, and microwave heating and a new depressant (Gellan Gum) was proposed. The floatability, separation efficiency and mechanism were discussed by SEM, adsorption capacity, zeta potential measurements and contact angle tests. The results of reverse flotation experiments results indicated that secondary water washing proves highly effective in enriching a significant quantity of barite solid phase. Subsequent microwave-ultrasonic and flotation can obtain barite of high quality with recovery and density reaching 81.5% and 4.238 g/cm3, respectively. It can be utilized directly in the preparation of drilling fluid. Mechanism studies shown that the per-treatments substantially enhances the barite grade while effectively eliminating low-density solid phases adhering to the barite surface, thus exposing additional contact points between the constituents so as to improve flotation separation. This new recovery scheme has environmental advantages and great reference value for the separation of barite within high-density waste drilling fluids.

Prognostic factors of patients with human epidermal growth factor receptor 2-positive breast cancer following neoadjuvant therapy: Development and validation of a predictive nomogram.

OBJECTIVE: Human epidermal growth factor receptor 2 (HER2)-positive breast cancer exhibits an aggressive phenotype and poor prognosis. The application of neoadjuvant therapy (NAT) in patients with breast cancer can significantly reduce the risks of disease recurrence and improve survival. By integrating different clinicopathological factors, nomograms are valuable tools for prognosis prediction. This study aimed to assess the prognostic value of clinicopathological factors in patients with HER2-positive breast cancer and construct a nomogram for outcome prediction. METHODS: We retrospectively analyzed the clinicopathological data from 374 patients with breast cancer admitted to the Fourth Hospital of Hebei Medical University between January 2009 and December 2017, who were diagnosed with invasive breast cancer through preoperative core needle biopsy pathology, underwent surgical resection after NAT, and were HER2-positive. Patients were randomly divided into a training and validation set at a ratio of 7:3. Univariate and multivariate survival analyses were performed using Kaplan-Meier and Cox proportional hazards regression models. Results of the multivariate analysis were used to create nomograms predicting 3-, 5-, and 8-year overall survival (OS) rates. Calibration curves were plotted to test concordance between the predicted and actual risks. Harrell C-index and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discriminability of the nomogram prediction model. RESULTS: All included patients were women, with a mean age of 50 ± 10.4 years (range: 26-72 years). In the training set, both univariate and multivariate analyses identified residual cancer burden (RCB) class, tumor-infiltrating lymphocytes(TILs), and clinical stage as independent prognostic factors for OS, and these factors were combined to construct a nomogram. The calibration curves demonstrated good concordance between the predicted and actual risks, and the C-index of the nomogram was 0.882 (95 % CI 0.863-0.901). The 3-, 5-, and 8-year areas under the ROC curve (AUCs) were 0.909, 0.893, and 0.918, respectively, indicating good accuracy of the nomogram. The calibration curves also demonstrated good concordance in the validation set, with a C-index of 0.850 (95 % CI 0.804-0.896) and 3-, 5-, and 8-year AUCs of 0.909, 0.815, and 0.834, respectively, which also indicated good accuracy. CONCLUSION: The nomogram prediction model accurately predicted the prognostic status of post-NAT patients with breast cancer and was more accurate than clinical stage and RCB class. Therefore, it can serve as a reliable guide for selecting clinical treatment measures for breast cancer.

Bisphenol mixtures, metal mixtures and type 2 diabetes mellitus: Insights from metabolite profiling.

BACKGROUND: Little is known about the combined effect of bisphenol mixtures and metal mixtures on type 2 diabetes mellitus (T2DM) risk, and the mediating roles of metabolites. METHODS: The study included 606 pairs of T2DM cases and controls matched by age and sex, and information of participants was collected through questionnaires and laboratory tests. Serum bisphenol and plasma metal concentrations were measured using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. Widely targeted metabolomics was employed to obtain the serum metabolomic profiles. Conditional logistic regression models were used to assess the single associations of bisphenols and metals with T2DM risk after multivariable adjustment. Additionally, the joint effects of bisphenol mixtures and metal mixtures were examined using quantile-based g-computation (QG-C) models. Furthermore, differential metabolites associated with T2DM were identified, and mediation analyses were performed to explore the role of metabolites in the associations of bisphenols and metals with T2DM risk. RESULTS: The results showed bisphenol mixtures were associated with an increased T2DM risk, with bisphenol A (BPA) identified as the primary contributor. While the association between metal mixtures and T2DM remained inconclusive, cobalt (Co), iron (Fe), and zinc (Zn) showed the highest weight indices for T2DM risk. A total of 154 differential metabolites were screened between the T2DM cases and controls. Mediation analyses indicated that 9 metabolites mediated the association between BPA and T2DM, while L-valine mediated the association between Zn and T2DM risk. CONCLUSIONS: The study indicated that BPA, Co, Fe, and Zn were the primary contributors to increased T2DM risk, and metabolites played a mediating role in the associations of BPA and Zn with the risk of T2DM. Our findings contribute to a better understanding of the mechanisms underlying the associations of bisphenols and metals with T2DM.

Effect of different extraction methods on the lipid composition and antioxidant activity of Ziziphi spinosae semens oil.

Chinese sour jujube is an important fruit for both medicine and food and effects various biological activities. Although the Chinese sour jujube seed (Ziziphi spinosae semen) is rich in oil, its lipid profiles is significantly affected by the extraction process. However, no studies to date have comprehensively analysed the lipid composition and bioactivity of Ziziphi spinosae semen oil processed using different methods. In this study, we compared the effects of commonly-used pressed, ultrasonic-assisted, and Soxhlet extraction methods on the lipid composition, characteristics, and antioxidant properties of Ziziphi spinosae semen oil. Nineteen subclasses and 390 lipid molecular species were identified, of which 24 lipid molecular species could potentially be used as biomarkers for different processing methods. Correlation analysis revealed that 57 lipids were significantly correlated with the antioxidant capacity (r > 0.9 and P < 0.05). These results indicate that Ziziphi spinosae semen oil is rich in bioactive lipids. These data greatly expand our understanding of the bioactive lipids of Ziziphi spinosae semen oil. Additionally, it could provide useful information for Ziziphi spinosae semen oil applications in functional products or the food industry and new insights into the effects of active vegetable oil processing.

Life cycle assessment of biochar for sustainable agricultural application: A review.

Biochar application is an effective strategy to address Agro-climatic challenges. However, the agro-environmental impacts of different biochar technology models are lacking of systematic summaries and reviews. Therefore, this paper comprehensively reviews recent developments derived from published literature, delving into the economic implications and environmental benefits of three distinct process namely technologies-pyrolysis, gasification, and hydrothermal carbonization. This paper specifically focuses on the agricultural life cycle assessment (LCA) methodology, and the influence of biochar preparation technologies and products on energy consumption and agricultural carbon emissions. LCA analysis shows that process and feedstock pose a predominant role on the properties and production rate of biochar, while gasification technology exhibits excellent economic attributes compared to the other two technologies. Biochar applications in agricultural has the beneficial effect of sequestering carbon and reducing emissions, especially in the area of mitigating the carbon footprint of farmland. However, the complexity of the composition of the prepared feedstock and the mismatch between the biochar properties and the application scenarios are considered as potential sources of risks. Notably, mechanism of carbon sequestration and emission reduction by soil microorganisms and agro-environmental sequestration by biochar application remains unclear, calling for in-depth studies. We review novel aspects that have not been covered by previous reviews by comparing the technical, economic, and environmental benefits of pyrolysis, gasification, and hydrothermal carbonization systematically. Overall, this study will provide a valuable framework to environmental implications of biochar preparation, application, and life cycle assessments.

Genomic and Phenotypic Analysis of bla KPC-2 Associated Carbapenem Resistance in Klebsiella aerogenes: Insights into Clonal Spread and Resistance Mechanisms Across Hospital Departments in Beijing.

Purpose: This study conducted an phenotypic and whole-genome sequencing analysis with Klebsiella aerogenes to elucidate its clinical epidemiological characteristics, antimicrobial resistance (AMR) phenotype, biofilm formation ability and hemolytic activity testing, AMR genes and phylogenetic relationships, so as to provide a further understanding of the intra-hospital strain transmission. Methods: Samples were collected from a hospital in Beijing between 2020 and 2022. All strains underwent bacterial identification, antimicrobial susceptibility testing (AST) using the VITEK-2 compact system. Biofilm formation ability and hemolytic activity were tested. Second-generation sequencing was applied to all strains, with those carrying the bla KPC gene were selected for third-generation sequencing. Whole-genome analysis identified resistance genes, plasmid types, MLST typing, and phylogenetic relationships. Plasmids were assembled to detect plasmid structures and AMR gene location. Results: Among the 42 K. aerogenes isolates, 21 were carbapenem-resistant K. aerogenes (CRKA). All strains exhibited strong biofilm formation and no hemolytic activity. Most were sourced from sputum (83.3%). CRKA demonstrated extensive resistance to antibiotics, particularly ß-lactamase inhibitors and Cefotetan. This resistance pattern was closely associated with the presence of an IncFII(pHN7A8) plasmid, which carried multiple resistance genes, including bla KPC-2, bla CTX-M-65, bla TEM-1, rmtB and a large number of mobile elements. The majority of CRKA strains clustered within the same branch of the phylogenetic tree, exhibiting minimal single nucleotide polymorphism (0-13 SNPs) differences, and they shared the same sequence type (ST292), resistance genes, and plasmids, originating from different departments, suggesting clonal transmission among the hospital. Conclusion: Our research reveals that the clonal transmission of CRKA occurs across various departments within the hospital. The widespread resistance observed in CRKA, attributed to the presence of bla KPC and ESBLs genes, underscores the need for heightened vigilance to prevent the further dissemination of CRKA within the hospital and, potentially, throughout the wider community.

Characterization of a Salmonella enterica serovar Typhimurium lineage with rough colony morphology and multidrug resistance.

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a major cause of salmonellosis, and the emergence of multidrug-resistant pathovariants has become a growing concern. Here, we investigate a distinct rough colony variant exhibiting a strong biofilm-forming ability isolated in China. Whole-genome sequencing on 2,212 Chinese isolates and 1,739 publicly available genomes reveals the population structure and evolutionary history of the rough colony variants. Characterized by macro, red, dry, and rough (mrdar) colonies, these variants demonstrate enhanced biofilm formation at 28 °C and 37 °C compared to typical rdar colonies. The mrdar variants exhibit extensive multidrug resistance, with significantly higher resistance to at least five classes of antimicrobial agents compared to non-mrdar variants. This resistance is primarily conferred by an IncHI2 plasmid harboring 19 antimicrobial resistance genes. Phylogenomic analysis divides the global collections into six lineages. The majority of mrdar variants belong to sublineage L6.5, which originated from Chinese smooth colony strains and possibly emerged circa 1977. Among the mrdar variants, upregulation of the csgDEFG operons is observed, probably due to a distinct point mutation (-44G > T) in the csgD gene promoter. Pangenome and genome-wide association analyses identify 87 specific accessory genes and 72 distinct single nucleotide polymorphisms associated with the mrdar morphotype.

Anaerobic dynamic membrane bioreactor for the co-digestion of toilet blackwater and kitchen waste.

Anaerobic co-digestion using an anaerobic dynamic membrane bioreactor (AnDMBR) can separate the sludge retention time and hydraulic retention time, retaining the biomass for efficient degradation and the use of less expensive large pore-size membrane materials and more sustainable dynamic membranes (DMs). Therefore, anaerobic co-digestion of toilet blackwater (BW) and kitchen waste (KW) using an AnDMBR was hypothesized to increase the potential for co-digestion. Here, the efficiency and stability of AnDMBR in anaerobic co-digestion of toilet BW and KW were investigated. DM morphology and structural characteristics, filtration properties, and composition, as well as membrane contamination and membrane regeneration mechanisms, were investigated. Average daily biogas yields of the reactor in two membrane cycles before and after cleaning were 788.67 and 746.09 ml/g volatile solids, with average methane content of 66.64% and 67.27% and average COD removal efficiencies of 82.03% and 80.96%, respectively. The results showed that the bioreactor obtained good performance and stability. During the stabilization phase of the DM operation, the flux was maintained between 43.65 and 65.15 L/m2/h. DM was mainly composed of organic and inorganic elements. Off-line cleaning facilitated DM regulation and regeneration, restoring new Anaerobic morphology and structure. PRACTITIONER POINTS: High efficiency co-digestion of BW and KW was realized in the DMBR system. Average daily biogas yields before and after membrane cleaning were 788.67 and 746.09 ml/g volatile solids. Off-line cleaning facilitated DM regulation and regeneration as well as system stability. The flux was maintained between 43.65 and 65.15 L/m2/h during operation.

Re-establishing immune tolerance in multiple sclerosis: focusing on novel mechanisms of mesenchymal stem cell regulation of Th17/Treg balance.

The T-helper 17 (Th17) cell and regulatory T cell (Treg) axis plays a crucial role in the development of multiple sclerosis (MS), which is regarded as an immune imbalance between pro-inflammatory cytokines and the maintenance of immune tolerance. Mesenchymal stem cell (MSC)-mediated therapies have received increasing attention in MS research. In MS and its animal model experimental autoimmune encephalomyelitis, MSC injection was shown to alter the differentiation of CD4+T cells. This alteration occurred by inducing anergy and reduction in the number of Th17 cells, stimulating the polarization of antigen-specific Treg to reverse the imbalance of the Th17/Treg axis, reducing the inflammatory cascade response and demyelination, and restoring an overall state of immune tolerance. In this review, we summarize the mechanisms by which MSCs regulate the balance between Th17 cells and Tregs, including extracellular vesicles, mitochondrial transfer, metabolic reprogramming, and autophagy. We aimed to identify new targets for MS treatment using cellular therapy by analyzing MSC-mediated Th17-to-Treg polarization.

O-Glycosyltransferase Gene BnaC09.OGT Involved in Regulation of Unsaturated Fatty Acid Biosynthesis for Enhancing Osmotic Stress Tolerance in Brassica napus L.

Osmotic stress is a major threaten to the growth and yield stability of Brassica napus. Post-translational modification with O-linked ß-N-acetylglucosamine (O-GlcNAc) is ubiquitous in plants, and participates in a variety of signal transduction and metabolic regulation. However, studies on the role of O-GlcNAc transferase (OGT) in osmotic stress tolerance of plants are limited. In previous study, a O-glycosyltransferase, named BnaC09.OGT, was identified from the B. napus variety 'Zhongshuang 11' by yeast one hybrid with promoter of BnaA01.GPAT9. It was found that BnaC09.OGT localized in both nucleus and cytoplasm. The spatiotemporal expression pattern of BnaC09.OGT exhibited tissue specificity in developmental seed, especially in 15 days after pollination. In view of osmotic stress inducing, the BnaC09.OGT overexpression and knockout transgenic lines were constructed for biological function study. Phenotypic analysis of BnaC09.OGT overexpression seedlings demonstrated that BnaC09.OGT could enhance osmotic stress tolerance than WT and knockout lines in euphylla stage under 15% PEG6000 treatment after 7 days. In addition, compared with WT and knockout lines, overexpression of BnaC09.OGT had significantly higher activities of antioxidant enzymes (SOD and POD), higher content of soluble saccharide, and while significantly less content of malondialdehyde, proline and anthocyanidin under 15% PEG6000 treatment after 7 days. On the other hand, the unsaturated fatty acid content of BnaC09.OGT overexpression was significantly higher than that of WT and knockout lines, so it is speculated that the BnaC09.OGT could increase unsaturated fatty acid biosynthesis for osmotic stress tolerance by promoting the expression of BnaA01.GPAT9 in glycerolipid biosynthesis. In summary, the above results revealed that the function of BnaC09.OGT provides new insight for the analysis of the pathway of O-glycosylation in regulating osmotic stress tolerance in B. napus.

Artificial intelligence for assisted HER2 immunohistochemistry evaluation of breast cancer: A systematic review and meta-analysis.

Accurate assessment of HER2 expression in tumor tissue is crucial for determining HER2-targeted treatment options. Nevertheless, pathologists' assessments of HER2 status are less objective than automated, computer-based evaluations. Artificial Intelligence (AI) promises enhanced accuracy and reproducibility in HER2 interpretation. This study aimed to systematically evaluate current AI algorithms for HER2 immunohistochemical diagnosis, offering insights to guide the development of more adaptable algorithms in response to evolving HER2 assessment practices. A comprehensive data search of the PubMed, Embase, Cochrane, and Web of Science databases was conducted using a combination of subject terms and free text. A total of 4994 computational pathology articles published from inception to September 2023 identifying HER2 expression in breast cancer were retrieved. After applying predefined inclusion and exclusion criteria, seven studies were selected. These seven studies comprised 6867 HER2 identification tasks, with two studies employing the HER2-CONNECT algorithm, two using the CNN algorithm, one with the multi-class logistic regression algorithm, and two using the HER2 4B5 algorithm. AI's sensitivity and specificity for distinguishing HER2 0/1+ were 0.98 [0.92-0.99] and 0.92 [0.80-0.97] respectively. For distinguishing HER2 2+, the sensitivity and specificity were 0.78 [0.50-0.92] and 0.98 [0.93-0.99], respectively. For HER2 3+ distinction, AI exhibited a sensitivity of 0.99 [0.98-1.00] and specificity of 0.99 [0.97-1.00]. Furthermore, due to the lack of HER2-targeted therapies for HER2-negative patients in the past, pathologists may have neglected to distinguish between HER2 0 and 1+, leaving room for improvement in the performance of artificial intelligence (AI) in this differentiation. AI excels in automating the assessment of HER2 immunohistochemistry, showing promising results despite slight variations in performance across different HER2 status. While incorporating AI algorithms into the pathology workflow for HER2 assessment poses challenges in standardization, application patterns, and ethical considerations, ongoing advancements suggest its potential as a widely effective tool for pathologists in clinical practice in the near future.

Single-cell multi-omic and spatial profiling of human kidneys implicates the fibrotic microenvironment in kidney disease progression.

Kidneys are intricate three-dimensional structures in the body, yet the spatial and molecular principles of kidney health and disease remain inadequately understood. We generated high-quality datasets for 81 samples, including single-cell, single-nuclear, spot-level (Visium) and single-cell resolution (CosMx) spatial-RNA expression and single-nuclear open chromatin, capturing cells from healthy, diabetic and hypertensive diseased human kidneys. Combining these data, we identify cell types and map them to their locations within the tissue. Unbiased deconvolution of the spatial data identifies the following four distinct microenvironments: glomerular, immune, tubule and fibrotic. We describe the complex organization of microenvironments in health and disease and find that the fibrotic microenvironment is able to molecularly classify human kidneys and offers an improved prognosis compared to traditional histopathology. We provide a comprehensive spatially resolved molecular roadmap of the human kidney and the fibrotic process, demonstrating the clinical utility of spatial transcriptomics.

Genetic Engineering for Enhancing Sugarcane Tolerance to Biotic and Abiotic Stresses.

Sugarcane, a vital cash crop, contributes significantly to the world's sugar supply and raw materials for biofuel production, playing a significant role in the global sugar industry. However, sustainable productivity is severely hampered by biotic and abiotic stressors. Genetic engineering has been used to transfer useful genes into sugarcane plants to improve desirable traits and has emerged as a basic and applied research method to maintain growth and productivity under different adverse environmental conditions. However, the use of transgenic approaches remains contentious and requires rigorous experimental methods to address biosafety challenges. Clustered regularly interspaced short palindromic repeat (CRISPR) mediated genome editing technology is growing rapidly and may revolutionize sugarcane production. This review aims to explore innovative genetic engineering techniques and their successful application in developing sugarcane cultivars with enhanced resistance to biotic and abiotic stresses to produce superior sugarcane cultivars.

Inhibition of the ATP synthase increases sensitivity of Escherichia coli carrying mcr-1 to polymyxin B.

Bacterial infections caused by multidrug-resistant (MDR) gram-negative strains carrying the mobile colistin resistance gene mcr-1 are serious threats to world public health due to the lack of effective treatments. Inhibition of the ATP synthase makes bacteria such as Staphylococcus aureus and Klebsiella pneumoniae more sensitive to polymyxin. This provides new strategies for treating infections caused by polymyxins-resistant bacteria carrying mcr-1. Six mcr-1-positive strains were isolated from clinical samples, and all were identified as Escherichia coli. Here we investigated several ATP synthase inhibitors, N,N'-dicyclohexylcarbodiimide (DCCD), resveratrol, and piceatannol, for their antibacterial effects against the mcr-1-positive strains combined with polymyxin B (POL). Checkerboard assay, time-kill assay, biofilm inhibition and eradication assay indicated the significant synergistic effect of ATP synthase inhibitors/POL combination in vitro. Meanwhile, mouse infection model experiment was also performed, showing a 5 log10 reduction of the pathogen after treatment with the resveratrol/POL combination. Moreover, adding adenosine disodium triphosphate (Na2ATP) could inhibit the antibacterial effect of the ATP synthase inhibitors/POL combination. In conclusion, our study confirmed that inhibition of ATP production could increase the susceptibility of bacteria carrying mcr-1 to polymyxins. This provides a new strategy against polymyxins-resistant bacteria infection.

Predicting personalized cumulative live birth rate after a complete in vitro fertilization cycle: an analysis of 32,306 treatment cycles in China.

BACKGROUND: The cumulative live birth rate (CLBR) has been regarded as a key measure of in vitro fertilization (IVF) success after a complete treatment cycle. Women undergoing IVF face great psychological pressure and financial burden. A predictive model to estimate CLBR is needed in clinical practice for patient counselling and shaping expectations. METHODS: This retrospective study included 32,306 complete cycles derived from 29,023 couples undergoing IVF treatment from 2014 to 2020 at a university-affiliated fertility center in China. Three predictive models of CLBR were developed based on three phases of a complete cycle: pre-treatment, post-stimulation, and post-treatment. The non-linear relationship was treated with restricted cubic splines. Subjects from 2014 to 2018 were randomly divided into a training set and a test set at a ratio of 7:3 for model derivation and internal validation, while subjects from 2019 to 2020 were used for temporal validation. RESULTS: Predictors of pre-treatment model included female age (non-linear relationship), antral follicle count (non-linear relationship), body mass index, number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, tubal factor, male factor, and scarred uterus. Predictors of post-stimulation model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. Predictors of post-treatment model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), cumulative Day-3 embryos live-birth capacity (non-linear relationship), number of previous IVF attempts, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. The C index of the three models were 0.7559, 0.7744, and 0.8270, respectively. All models were well calibrated (p = 0.687, p = 0.468, p = 0.549). In internal validation, the C index of the three models were 0.7422, 0.7722, 0.8234, respectively; and the calibration P values were all greater than 0.05. In temporal validation, the C index were 0.7430, 0.7722, 0.8234 respectively; however, the calibration P values were less than 0.05. CONCLUSIONS: This study provides three IVF models to predict CLBR according to information from different treatment stage, and these models have been converted into an online calculator ( https://h5.eheren.com/hcyc/pc/index.html#/home ). Internal validation and temporal validation verified the good discrimination of the predictive models. However, temporal validation suggested low accuracy of the predictive models, which might be attributed to time-associated amelioration of IVF practice.

Improve-RRBS: a novel tool to correct the 3' trimming of reduced representation sequencing reads.

Motivation: Reduced Representation Bisulfite Sequencing (RRBS) is a popular approach to determine DNA methylation of the CpG-rich regions of the genome. However, we observed that false positive differentially methylated sites (DMS) are also identified using the standard computational analysis. Results: During RRBS library preparation the MspI digested DNA undergo end-repair by a cytosine at the 3' end of the fragments. After sequencing, Trim Galore cuts these end-repaired nucleotides. However, Trim Galore fails to detect end-repair when it overlaps with the 3' end of the sequencing reads. We found that these non-trimmed cytosines bias methylation calling, thus, can identify DMS erroneously. To circumvent this problem, we developed improve-RRBS, which efficiently identifies and hides these cytosines from methylation calling with a false positive rate of maximum 0.5%. To test improve-RRBS, we investigated four datasets from four laboratories and two different species. We found non-trimmed 3' cytosines in all datasets analyzed and as much as >50% of false positive DMS under certain conditions. By applying improve-RRBS, these DMS completely disappeared from all comparisons. Availability and implementation: Improve-RRBS is a freely available python package https://pypi.org/project/iRRBS/ or https://github.com/fothia/improve-RRBS to be implemented in RRBS pipelines.

Far-field superresolution of thermal sources by double homodyne or double array homodyne detection.

We propose two schemes for estimating the separation of two thermal sources via double homodyne and double array homodyne detection considering the joint measurement of conjugate quadratures of the image plane field.By using the Cramér-Rao bound, we demonstrate that the two schemes can estimate the separation well below the Rayleigh limit and have an advantage over direct imaging when the average photon number per source exceeds five.For arbitrary source strengths, double homodyne detection is superior to homodyne detection when the separation is above 25/4 σ/N s , σ is the beam width, Ns is the average photon number per source.A larger separation can be estimated better via double array homodyne detection with the superiority of flexible operation compared with other schemes. High-speed and high-efficiency detection enables the measurement schemes with potential practical applications in fluorescence microscopy, astronomy and quantum imaging.