Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research.

OBJECTIVE: Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening. METHODS: This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms. RESULTS AND CONCLUSIONS: The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

Spatially Distributed Cytokinins: Metabolism, Signaling, and Transport.

Cytokinins are a type of mobile phytohormone that regulate plant growth, development, and environmental adaptability. The major cytokinin species include isopentenyl adenine (iP), trans-zeatin (tZ), cis-zeatin (cZ), and dihydrozeatin (DZ). The spatial distributions of different cytokinin species in different organelles, cells, tissues, and organs are primarily shaped by biosynthesis via isopentenyltransferases (IPT), cytochrome P450 monooxygenase, and 5'-ribonucleotide phosphohydrolase, and by conjugation or catabolism via glycosyltransferase or cytokinin oxidase/dehydrogenase (CKX). Cytokinins bind to histidine receptor kinases (HKs) in the endoplasmic reticulum (ER) or plasma membrane (PM) and relay signals to response regulators (RRs) in the nucleus by shuttle proteins known as histidine phosphotransfer proteins (HPs). The movements of cytokinins from sites of biosynthesis to signal perception sites usually require long-distance, intercellular, and intracellular transport. In the past decade, ATP-binding cassette (ABC) transporters, purine permeases (PUP), AZA-GUANINE RESISTANT (AZG) transporters, equilibrative nucleoside transporters (ENT), and Sugars Will Eventually be Exported Transporters (SWEET) have been characterized as involved in cytokinin transport processes. This review begins by introducing the spatial distributions of various cytokinins and the subcellular localizations of the proteins involved in cytokinin metabolism and signaling. Highlights focus on an inventory of the characterized transporters involved in cytokinin compartmentalization, including long-distance, intercellular, and intracellular transport, and the regulation of spatial distributions of cytokinins by environmental cues. Future directions for cytokinin research are also discussed.

Prompt Tuning in Biomedical Relation Extraction.

Biomedical relation extraction (RE) is critical in constructing high-quality knowledge graphs and databases as well as supporting many downstream text mining applications. This paper explores prompt tuning on biomedical RE and its few-shot scenarios, aiming to propose a simple yet effective model for this specific task. Prompt tuning reformulates natural language processing (NLP) downstream tasks into masked language problems by embedding specific text prompts into the original input, facilitating the adaption of pre-trained language models (PLMs) to better address these tasks. This study presents a customized prompt tuning model designed explicitly for biomedical RE, including its applicability in few-shot learning contexts. The model's performance was rigorously assessed using the chemical-protein relation (CHEMPROT) dataset from BioCreative VI and the drug-drug interaction (DDI) dataset from SemEval-2013, showcasing its superior performance over conventional fine-tuned PLMs across both datasets, encompassing few-shot scenarios. This observation underscores the effectiveness of prompt tuning in enhancing the capabilities of conventional PLMs, though the extent of enhancement may vary by specific model. Additionally, the model demonstrated a harmonious balance between simplicity and efficiency, matching state-of-the-art performance without needing external knowledge or extra computational resources. The pivotal contribution of our study is the development of a suitably designed prompt tuning model, highlighting prompt tuning's effectiveness in biomedical RE. It offers a robust, efficient approach to the field's challenges and represents a significant advancement in extracting complex relations from biomedical texts. Supplementary Information: The online version contains supplementary material available at 10.1007/s41666-024-00162-9.

Enhancing Early Detection of Cognitive Decline in the Elderly: A Comparative Study Utilizing Large Language Models in Clinical Notes.

Background: Large language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement. Methods: This study, conducted at Mass General Brigham in Boston, MA, analyzed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We used a randomly annotated sample of 4,949 note sections, filtered with keywords related to cognitive functions, for model development. For testing, a random annotated sample of 1,996 note sections without keyword filtering was utilized. We developed prompts for two LLMs, Llama 2 and GPT-4, on HIPAA-compliant cloud-computing platforms using multiple approaches (e.g., both hard and soft prompting and error analysis-based instructions) to select the optimal LLM-based method. Baseline models included a hierarchical attention-based neural network and XGBoost. Subsequently, we constructed an ensemble of the three models using a majority vote approach. Results: GPT-4 demonstrated superior accuracy and efficiency compared to Llama 2, but did not outperform traditional models. The ensemble model outperformed the individual models, achieving a precision of 90.3%, a recall of 94.2%, and an F1-score of 92.2%. Notably, the ensemble model showed a significant improvement in precision, increasing from a range of 70%-79% to above 90%, compared to the best-performing single model. Error analysis revealed that 63 samples were incorrectly predicted by at least one model; however, only 2 cases (3.2%) were mutual errors across all models, indicating diverse error profiles among them. Conclusions: LLMs and traditional machine learning models trained using local EHR data exhibited diverse error profiles. The ensemble of these models was found to be complementary, enhancing diagnostic performance. Future research should investigate integrating LLMs with smaller, localized models and incorporating medical data and domain knowledge to enhance performance on specific tasks.

Spatial-Temporal Mapping Reveals the Golgi as the Major Processing Site for the Pathogenic Swedish APP Mutation: Familial APP Mutant Shifts the Major APP Processing Site.

Alzheimer's disease is associated with increased levels of amyloid beta (Aß) generated by sequential intracellular cleavage of amyloid precursor protein (APP) by membrane-bound secretases. However, the spatial and temporal APP cleavage events along the trafficking pathways are poorly defined. Here, we use the Retention Using Selective Hooks (RUSH) to compare in real time the anterograde trafficking and temporal cleavage events of wild-type APP (APPwt) with the pathogenic Swedish APP (APPswe) and the disease-protective Icelandic APP (APPice). The analyses revealed differences in the trafficking profiles and processing between APPwt and the APP familial mutations. While APPwt was predominantly processed by the ß-secretase, BACE1, following Golgi transport to the early endosomes, the transit of APPswe through the Golgi was prolonged and associated with enhanced amyloidogenic APP processing and Aß secretion. A 20°C block in cargo exit from the Golgi confirmed ß- and γ-secretase processing of APPswe in the Golgi. Inhibition of the ß-secretase, BACE1, restored APPswe anterograde trafficking profile to that of APPwt. APPice was transported rapidly through the Golgi to the early endosomes with low levels of Aß production. This study has revealed different intracellular locations for the preferential cleavage of APPwt and APPswe and Aß production, and the Golgi as the major processing site for APPswe, findings relevant to understand the molecular basis of Alzheimer's disease.

Genetic prediction of modifiable lifestyle factors for erectile dysfunction.

Background: The causal relationship between certain lifestyle factors and erectile dysfunction (ED) is still uncertain. Aim: The study sought to investigate the causal effect of 9 life factors on ED through 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR). Methods: Genetic instruments to proxy 9 risk factors were identified by genome-wide association studies. The genome-wide association studies estimated the connection of these genetic variants with ED risk (n = 223 805). We conducted SVMR, inverse variance-weighting, Cochran's Q, weighted median, MR-Egger, MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier), and MVMR analyses to explore the total and direct relationship between life factors and ED. Outcomes: The primary outcome was defined as self or physician-reported ED, or using oral ED medication, or a history of surgery related to ED. Results: In SVMR analyses, suggestive associations with increased the risk of ED were noted for ever smoked (odds ratio [OR], 5.894; 95% confidence interval [CI], 0.469 to 3.079; P = .008), alcohol consumption (OR, 1.495; 95% CI, 0.044 to 0.760; P = .028) and body mass index (BMI) (OR, 1.177; 95% CI, 0.057 to 0.268; P = .003). Earlier age at first intercourse was significantly related to reduced ED risk (OR, 0.659; 95% CI, -0.592 to -0.244; P = 2.5 × 10-6). No strong evidence was found for the effect of coffee intake, time spent driving, physical activity, and leisure sedentary behaviors on the incidence of ED (All P > .05). The result of MVMR analysis for BMI (OR, 1.13; 95% CI, 1.01 to 1.25; P = .045) and earlier age at first intercourse (OR, 0.77; 95% CI, 0.56 to 0.99; P = .018) provided suggestive evidence for the direct impact on ED, while no causal factor was detected for alcoholic drinks per week and ever smoked. Clinical implications: This study provides evidence for the impact of certain modifiable lifestyle factors on the development of ED. Strengths and limitations: We performed both SVMR and MVMR to strengthen the causal relationship between exposures and outcomes. However, the population in this study was limited to European ancestry. Conclusion: Ever smoked, alcoholic drinks per week, BMI, and age first had sexual intercourse were causally related to ED, while the potential connection between coffee intake, physical activity, recreational sedentary habits, and increased risk of ED needs to be further confirmed.

A comprehensive transformer-based approach for high-accuracy gas adsorption predictions in metal-organic frameworks.

Gas separation is crucial for industrial production and environmental protection, with metal-organic frameworks (MOFs) offering a promising solution due to their tunable structural properties and chemical compositions. Traditional simulation approaches, such as molecular dynamics, are complex and computationally demanding. Although feature engineering-based machine learning methods perform better, they are susceptible to overfitting because of limited labeled data. Furthermore, these methods are typically designed for single tasks, such as predicting gas adsorption capacity under specific conditions, which restricts the utilization of comprehensive datasets including all adsorption capacities. To address these challenges, we propose Uni-MOF, an innovative framework for large-scale, three-dimensional MOF representation learning, designed for multi-purpose gas prediction. Specifically, Uni-MOF serves as a versatile gas adsorption estimator for MOF materials, employing pure three-dimensional representations learned from over 631,000 collected MOF and COF structures. Our experimental results show that Uni-MOF can automatically extract structural representations and predict adsorption capacities under various operating conditions using a single model. For simulated data, Uni-MOF exhibits remarkably high predictive accuracy across all datasets. Additionally, the values predicted by Uni-MOF correspond with the outcomes of adsorption experiments. Furthermore, Uni-MOF demonstrates considerable potential for broad applicability in predicting a wide array of other properties.

Role of hydrocolloid dressing in preventing face pressure ulcers from non-invasive ventilation and facilitating postoperative wound healing in maxillofacial surgery: A meta-analysis.

Facial pressure ulcers from non-invasive ventilation (NIV) and challenges in wound healing post-maxillofacial surgery are significant concerns in clinical care. This meta-analysis aimed to evaluate the effectiveness of hydrocolloid dressings in these contexts. From a pool of 1135 articles, 8 studies met the inclusion criteria. Hydrocolloid dressings demonstrated a significant reduction in facial pressure ulcers for NIV patients, with lower REEDA scores 1-week postapplication (standardized mean difference [SMD] = -16.7, 95% confidence interval [CI]: -24.26 to -9.15, p < 0.01). In maxillofacial surgery, patients treated with hydrocolloid dressings exhibited improved wound healing and reduced scar formation, evidenced by lower Manchester Scar Scale scores 3 months post-surgery (SMD = -15.46, 95% CI: -20.28 to -10.64, p < 0.01). These findings suggest that hydrocolloid dressings are effective in both preventing NIV-related facial pressure ulcers and enhancing wound healing in maxillofacial surgery.

Chickpea: Its Origin, Distribution, Nutrition, Benefits, Breeding, and Symbiotic Relationship with Mesorhizobium Species.

Chickpea (Cicer arietinum L.), encompassing the desi and kabuli varieties, is a beloved pulse crop globally. Its cultivation spans over fifty countries, from the Indian subcontinent and southern Europe to the Middle East, North Africa, the Americas, Australia, and China. With a rich composition of carbohydrates and protein, constituting 80% of its dry seed mass, chickpea is also touted for its numerous health benefits, earning it the title of a 'functional food'. In the past two decades, research has extensively explored the rhizobial diversity associated with chickpea and its breeding in various countries across Europe, Asia, and Oceania, aiming to understand its impact on the sustainable yield and quality of chickpea crops. To date, four notable species of Mesorhizobium-M. ciceri, M. mediterraneum, M. muleiense, and M. wenxiniae-have been reported, originally isolated from chickpea root nodules. Other species, such as M. amorphae, M. loti, M. tianshanense, M. oportunistum, M. abyssinicae, and M. shonense, have been identified as potential symbionts of chickpea, possibly acquiring symbiotic genes through lateral gene transfer. While M. ciceri and M. mediterraneum are widely distributed and studied across chickpea-growing regions, they remain absent in China, where M. muleiense and M. wenxiniae are the sole rhizobial species associated with chickpea. The geographic distribution of chickpea rhizobia is believed to be influenced by factors such as genetic characteristics, competitiveness, evolutionary adaptation to local soil conditions, and compatibility with native soil microbes. Inoculating chickpea with suitable rhizobial strains is crucial when introducing the crop to new regions lacking indigenous chickpea rhizobia. The introduction of a novel chickpea variety, coupled with the effective use of rhizobia for inoculation, offers the potential not only to boost the yield and seed quality of chickpeas, but also to enhance crop productivity within rotation and intercropped systems involving chickpea and other crops. Consequently, this advancement holds the promise to drive forward the cause of sustainable agriculture on a global scale.

Abscisic acid root-to-shoot translocation by transporter AtABCG25 mediates stomatal movements in Arabidopsis.

The phytohormone abscisic acid (ABA) plays a central role in regulating stomatal movements under drought conditions. The root-derived peptide CLAVATA3/EMBRYO SURROUNDING REGION-RELATED 25 (CLE25) moves from the root to shoot for activating ABA biosynthesis under drought conditions. However, the root-to-shoot translocation of root-derived ABA and its regulation of stomatal movements in the shoot remain to be clarified. Here, we reveal that the ABA transporter ATP-binding cassette subfamily G member 25 (AtABCG25) mediates root-to-shoot translocation of ABA and ABA-glucosyl ester (ABA-GE) in Arabidopsis (Arabidopsis thaliana). Isotope-labeled ABA tracer experiments and hormone quantification in xylem sap showed that the root-to-shoot translocation of ABA and ABA-GE was substantially impaired in the atabcg25 mutant under nondrought and drought conditions. However, the contents of ABA and ABA-GE in the leaves were lower in the atabcg25 mutant than in the wild type (WT) under nondrought but similar under drought conditions. Consistently, the stomatal closure was suppressed in the atabcg25 mutant under nondrought but not under drought conditions. The transporter activity assays showed that AtABCG25 directly exported ABA and ABA-GE in planta and in yeast (Saccharomyces cerevisiae) cells. Thus, we proposed a working model in which root-derived ABA transported by AtABCG25 via xylem mediates stomatal movements in the shoot under nondrought conditions but might exhibit little effect on stomatal movements under drought conditions. These findings extend the functions of AtABCG25 and provide insights into the long-distance translocation of ABA and its role in stomatal movements.

The chromatin remodeler ERCC6 and the histone chaperone NAP1 are involved in apurinic/apyrimidinic endonuclease-mediated DNA repair.

During base excision repair (BER), the apurinic or apyrimidinic (AP) site serves as an intermediate product following base excision. In plants, APE-redox protein (ARP) represents the major AP site of cleavage activity. Despite the well-established understanding that the nucleosomal structure acts as a barrier to various DNA-templated processes, the regulatory mechanisms underlying BER at the chromatin level remain elusive, especially in plants. In this study, we identified plant chromatin remodeler Excision Repair Cross-Complementing protein group 6 (ERCC6) and histone chaperone Nucleosome Assembly Protein 1 (NAP1) as interacting proteins with ARP. The catalytic ATPase domain of ERCC6 facilitates its interaction with both ARP and NAP1. Additionally, ERCC6 and NAP1 synergistically contribute to nucleosome sliding and exposure of hindered endonuclease cleavage sites. Loss-of-function mutations in Arabidopsis (Arabidopsis thaliana) ERCC6 or NAP1 resulted in arp-dependent plant hypersensitivity to 5-fluorouracil (5-FU), a toxic agent inducing BER, and the accumulation of AP sites. Furthermore, similar protein interactions are also found in yeast cells, suggesting a conserved recruitment mechanism employed by the AP endonuclease to overcome chromatin barriers during BER progression.

Characterization and optimization of 5´ untranslated region containing poly-adenine tracts in Kluyveromyces marxianus using machine-learning model.

BACKGROUND: The 5´ untranslated region (5´ UTR) plays a key role in regulating translation efficiency and mRNA stability, making it a favored target in genetic engineering and synthetic biology. A common feature found in the 5´ UTR is the poly-adenine (poly(A)) tract. However, the effect of 5´ UTR poly(A) on protein production remains controversial. Machine-learning models are powerful tools for explaining the complex contributions of features, but models incorporating features of 5´ UTR poly(A) are currently lacking. Thus, our goal is to construct such a model, using natural 5´ UTRs from Kluyveromyces marxianus, a promising cell factory for producing heterologous proteins. RESULTS: We constructed a mini-library consisting of 207 5´ UTRs harboring poly(A) and 34 5´ UTRs without poly(A) from K. marxianus. The effects of each 5´ UTR on the production of a GFP reporter were evaluated individually in vivo, and the resulting protein abundance spanned an approximately 450-fold range throughout. The data were used to train a multi-layer perceptron neural network (MLP-NN) model that incorporated the length and position of poly(A) as features. The model exhibited good performance in predicting protein abundance (average R2 = 0.7290). The model suggests that the length of poly(A) is negatively correlated with protein production, whereas poly(A) located between 10 and 30 nt upstream of the start codon (AUG) exhibits a weak positive effect on protein abundance. Using the model as guidance, the deletion or reduction of poly(A) upstream of 30 nt preceding AUG tended to improve the production of GFP and a feruloyl esterase. Deletions of poly(A) showed inconsistent effects on mRNA levels, suggesting that poly(A) represses protein production either with or without reducing mRNA levels. CONCLUSION: The effects of poly(A) on protein production depend on its length and position. Integrating poly(A) features into machine-learning models improves simulation accuracy. Deleting or reducing poly(A) upstream of 30 nt preceding AUG tends to enhance protein production. This optimization strategy can be applied to enhance the yield of K. marxianus and other microbial cell factories.

AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models.

OBJECTIVES: We aim to build a generalizable information extraction system leveraging large language models to extract granular eligibility criteria information for diverse diseases from free text clinical trial protocol documents. We investigate the model's capability to extract criteria entities along with contextual attributes including values, temporality, and modifiers and present the strengths and limitations of this system. MATERIALS AND METHODS: The clinical trial data were acquired from https://ClinicalTrials.gov/. We developed a system, AutoCriteria, which comprises the following modules: preprocessing, knowledge ingestion, prompt modeling based on GPT, postprocessing, and interim evaluation. The final system evaluation was performed, both quantitatively and qualitatively, on 180 manually annotated trials encompassing 9 diseases. RESULTS: AutoCriteria achieves an overall F1 score of 89.42 across all 9 diseases in extracting the criteria entities, with the highest being 95.44 for nonalcoholic steatohepatitis and the lowest of 84.10 for breast cancer. Its overall accuracy is 78.95% in identifying all contextual information across all diseases. Our thematic analysis indicated accurate logic interpretation of criteria as one of the strengths and overlooking/neglecting the main criteria as one of the weaknesses of AutoCriteria. DISCUSSION: AutoCriteria demonstrates strong potential to extract granular eligibility criteria information from trial documents without requiring manual annotations. The prompts developed for AutoCriteria generalize well across different disease areas. Our evaluation suggests that the system handles complex scenarios including multiple arm conditions and logics. CONCLUSION: AutoCriteria currently encompasses a diverse range of diseases and holds potential to extend to more in the future. This signifies a generalizable and scalable solution, poised to address the complexities of clinical trial application in real-world settings.

Teriflunomide Promotes Blood-Brain Barrier Integrity by Upregulating Claudin-1 via the Wnt/ß-catenin Signaling Pathway in Multiple Sclerosis.

The blood-brain barrier (BBB) and tight junction (TJ) proteins maintain the homeostasis of the central nervous system (CNS). The dysfunction of BBB allows peripheral T cells infiltration into CNS and contributes to the pathophysiology of multiple sclerosis (MS). Teriflunomide is an approved drug for the treatment of MS by suppressing lymphocytes proliferation. However, whether teriflunomide has a protective effect on BBB in MS is not understood. We found that teriflunomide restored the injured BBB in the EAE model. Furthermore, teriflunomide treatment over 6 months improved BBB permeability and reduced peripheral leakage of CNS proteins in MS patients. Teriflunomide increased human brain microvascular endothelial cell (HBMEC) viability and promoted BBB integrity in an in vitro cell model. The TJ protein claudin-1 was upregulated by teriflunomide and responsible for the protective effect on BBB. Furthermore, RNA sequencing revealed that the Wnt signaling pathway was affected by teriflunomide. The activation of Wnt signaling pathway increased claudin-1 expression and reduced BBB damage in cell model and EAE rats. Our study demonstrated that teriflunomide upregulated the expression of the tight junction protein claudin-1 in endothelial cells and promoted the integrity of BBB through Wnt signaling pathway.

Quasi-Solid-State All-V2 O5 Battery.

Solid-state symmetrical battery represents a promising paradigm for future battery technology. However, its development is hindered by the deficiency of high-performance bipolar electrodes and compatible solid electrolytes. Herein, a quasi-solid-state all-V2 O5 battery constructed by a binder-free carbon fabric-V2 O5 nanowires@graphene (CVOG) bipolar electrode and a softly cross-linked polyethylene oxide-based solid polymer electrolyte (SPE) is reported. The synergetic effect of nano-structuring of V2 O5 , hierarchical conductive network, and graphene wrapping endows the CVOG electrode with boosted reaction kinetics and suppressed vanadium dissolution. The cathodic and anodic reactions of CVOG are decoupled by electrochemical analysis, conceiving the feasibility of constructing all-V2 O5 full battery. In manifesting the solid-state all-V2 O5 battery, the robust and elastic SPE exhibits high ionic conductivity, tight/self-adaptable electrolyte-electrode contact, and a low charge-transfer barrier. The resultant solid-state full battery exhibits a high reversible capacity of 158 mAh g-1 at 0.1 C, good capacity retention of over 61% from 0.1 C to 2 C, and remarkable cycling stability of 77% capacity retention after 1000 cycles at 1 C, which surpass other solid-state symmetrical batteries. Hence, this work provides a practice of high-performance solid-state batteries with symmetrical configuration and is constructive for next-generation battery technology.

Low risk of erectile dysfunction after nontransecting bulbar urethroplasty for urethral stricture: a systematic review and meta-analysis.

BACKGROUND: Sexual function after urethroplasty may be a concern for patients, but there are still some controversies regarding the consequences of nontransecting bulbar urethroplasty (ntBU) in terms of erectile dysfunction (ED). AIM: This meta-analysis aimed to compare the efficacy and safety of ntBU with that of transecting bulbar urethroplasty (tBU). METHODS: The PubMed, Web of Science, Cochrane, and Embase databases were searched and reviewed up to October 31, 2022. Quality evaluation was performed using the Newcastle-Ottawa scale system and Cochrane tools for the nonrandomized and randomized studies, respectively. Baseline characteristics, preoperative information, and postoperative outcomes were collected. OUTCOMES: Outcomes included success rate, ED, overall complication, and maximum urinary flow. RESULTS: Thirteen studies comprising 1683 patients met the inclusion criteria, with 596 and 1087 patients undergoing ntBU and tBU, respectively. The results revealed that compared with the tBU group, the patients who underwent ntBU had a significantly lower incidence of ED, while there were no significant differences in the other perioperative outcomes. In subgroup analysis, the nontransecting anastomotic urethroplasty group had a lower incidence of ED than excision and primary anastomosis, and other perioperative outcomes were similar between the 2 groups. CLINICAL IMPLICATIONS: The results of the study may help clinicians choose procedures that protect sexual function in the treatment of urethral stricture. STRENGTHS AND LIMITATIONS: The strength of this study is that it is, to our knowledge, the first meta-analysis to evaluate the efficacy and safety of ntBU. A limitation is that most of the included studies were retrospective cohort studies. CONCLUSION: ntBU preserves the high efficacy of its transecting counterpart while reducing postoperative ED.

Diverse Bradyrhizobium spp. with Similar Symbiosis Genes Nodulate Peanut in Different Regions of China: Characterization of Symbiovar sv. Arachis.

A total of 219 rhizobial strains isolated from peanut grown in soils from six peanut croplands in Zhengyang county, Henan Province, were typed by PCR-RFLP of IGS sequences. Their phylogenetic relationships were refined on representative strains using sequence analyses of 16S rRNA genes, housekeeping genes (atpD, recA, glnII) and symbiosis genes (nodA, nodC and nifH). The 219 rhizobial isolates were classified into 13 IGS types, and twenty representatives were defined within eight Bradyrhizobium genospecies: B. guangdongense covering 5 IGS types (75.2% of total isolates), B. guangzhouense (2 IGS types, 2.7% total isolates), B. zhengyangense (1 IGS type, 11.3% total isolates) and five novel genospecies (5 IGS types, 0.9 to 3.2% total isolates). All representative strains had identical nodA, nodC and nifH sequences except for one nifH sequence. With this one exception, these sequences were identical to those of the type strains of Bradyrhizobium species and several Bradyrhizobium genospecies isolated from peanut in different regions of China. The nodC sequences of all strains showed < 67% similarity to the closest strains on the Genbank database indicating that they are representative of a novel Bradyrhiobium symbiovar. This study has shown that (1) diverse Bradyrhizobium spp. with similar symbiosis genes nodulate peanut in different regions of China. (2) Horizontal transfer of genes involved in nodulating peanut is common between Bradyrhizobium species in soils used to grow the crop in China. (3) The strains studied here are representative of a novel Bradyrhizobium symbiovar that nodulates peanut in China. We propose the name sv. arachis for this novel symbiovar indicating that the strains were isolated from Arachis hypogaea. Results here have practical implications in relation to the selection of rhizobial inoculants for peanut in China.

Long-term live cell imaging during differentiation of human iPSC-derived neurons.

Live-cell imaging is crucial to appreciate the dynamics and the complexity of cellular interaction processes. However, live-cell imaging of human neurons is challenging due to neuronal sensitivity. Here, we describe a long-term live-cell imaging protocol for neurons derived from human induced pluripotent stem cells. By using an IncuCyte live-cell imaging system, we have obtained information on neuronal dynamics during the different stages of neurogenesis. The protocol has also been developed to monitor the dynamics of the neuronal intracellular organelles. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

Epirubicin and gait apraxia: a real-world data analysis of the FDA Adverse Event Reporting System database.

Introduction: Epirubicin is widely used in many malignancies with good efficacy and tolerability. However, investigations about adverse events (AEs) using real-world information are still insufficient. Methods: We extracted Epirubicin-related reports submitted between the first quarter of 2014 and first quarter of 2023 from FAERS database. Four algorithms were utilized to evaluate whether there was a significant correlation between Epirubicin and AEs. Results: After de-duplicating, a total of 3919 cases were extracted. Among the 3919 cases, we identified 1472 AEs, 253 of which were found to be adverse drug reactions (ADRs) associated with Epirubicin. We analysed the occurrence of Epirubicin-induced ADRs and found several unexpected significant ADRs, such as hepatic artery stenosis, hepatic artery occlusion, intestinal atresia and so on. Interestingly, we found gait apraxia, a neurological condition, was also significantly associated with Epirubicin. To our knowledge, there haven't studies that have reported an association between gait disorders and the usage of epirubicin. Discussion: Our study identified new unexpected significant ADRs related to Epirubicin, providing new perspectives to the clinical use of Epirubicin.

The Effect of Different Rhizobial Symbionts on the Composition and Diversity of Rhizosphere Microorganisms of Chickpea in Different Soils.

BACKGROUND: Chickpea (Cicer arietinum L.) is currently the third most important legume crop in the world. It could form root nodules with its symbiotic rhizobia in soils and perform bio-nitrogen fixation. Mesorhizobium ciceri is a prevalent species in the world, except China, where Mesorhizobium muleiense is the main species associated with chickpea. There were significant differences in the competitive ability between M. ciceri and M. muleiense in sterilized and unsterilized soils collected from Xinjiang, China, where chickpea has been grown long term. In unsterilized soils, M. muleiense was more competitive than M. ciceri, while in sterilized soils, the opposite was the case. In addition, the competitive ability of M. ciceri in soils of new areas of chickpea cultivation was significantly higher than that of M. muleiense. It was speculated that there might be some biological factors in Xinjiang soils of China that could differentially affect the competitive nodulation of these two chickpea rhizobia. To address this question, we compared the composition and diversity of microorganisms in the rhizosphere of chickpea inoculated separately with the above two rhizobial species in soils from old and new chickpea-producing regions. RESULTS: Chickpea rhizosphere microbial diversity and composition varied in different areas and were affected significantly due to rhizobial inoculation. In general, eight dominant phyla with 34 dominant genera and 10 dominant phyla with 47 dominant genera were detected in the rhizosphere of chickpea grown in soils of Xinjiang and of the new zones, respectively, with the inoculated rhizobia. Proteobacteria and Actinobacteria were dominant at the phylum level in the rhizosphere of all soils. Pseudomonas appeared significantly enriched after inoculation with M. muleiense in soils from Xinjiang, a phenomenon not found in the new areas of chickpea cultivation, demonstrating that Pseudomonas might be the key biological factor affecting the competitive colonization of M. muleiense and M. ciceri there. CONCLUSIONS: Different chickpea rhizobial inoculations of M. muleiense and M. ciceri affected the rhizosphere microbial composition in different sampling soils from different chickpea planting areas. Through high throughput sequencing and statistical analysis, it could be found that Pseudomonas might be the key microorganism influencing the competitive nodulation of different chickpea rhizobia in different soils, as it is the dominant non-rhizobia community in Xinjiang rhizosphere soils, but not in other areas.