Dehydrogenation Coupling and [3 + 2] Cycloaddition of Indolizines with Allenes in the Presence of Piezoelectric Materials under Ball Milling Conditions.

A wide range of indolizines with allenes proceeded smoothly under mechanochemical-induced conditions via [3 + 2] annulation process, affording various substituted pyrrolo[2,1,5-cd]indolizines with good yield. The reaction efficiency was greatly improved by using a piezoelectric material as the charge transfer catalyst. The photophysical properties of the resulting pyrrolo[2,1,5-cd]indolizine was characterized.

Stable Lithium Oxygen Batteries Enabled by Solvent-diluent Interaction in N,N-dimethylacetamide-based Electrolytes.

In the pursuit of next-generation ultrahigh-energy-density Li-O2 batteries, it is imperative to develop an electrolyte with stability against the strong oxidation environments. N,N-dimethylacetamide (DMA) is a recognized solvent known for its robust resistance to the highly reactive reduced oxygen species, yet its application in Li-O2 batteries has been constrained due to its poor compatibility with the Li metal anode. In this study, a rationally selected hydrofluoroether diluent, methyl nonafluorobutyl ether (M3), has been introduced into the DMA-based electrolyte to construct a localized high concentration electrolyte. The stable -CH3 and C-F bonds within the M3 structure could not only augment the fundamental properties of the electrolyte but also fortify its resilience against attacks from O2- and 1O2. Additionally, the strong electron-withdrawing groups (-F) presented in the M3 diluent could facilitate coordination with the electron-donating groups (-CH3) in the DMA solvent. This intermolecular interaction promotes more alignment of Li+-anions with a small amount of M3 addition, leading to the construction of an anion-derived inorganic-rich SEI that enhances the stability of the Li anode. As a result, the Li-O2 batteries with the DMA/M3 electrolyte exhibit superior cycling performance at both 30 °C (359th) and -10 °C (120th).

Impact and potential value of immunosenescence on solid gastrointestinal tumors.

Solid gastrointestinal tumors often respond poorly to immunotherapy for the complex tumor microenvironment (TME), which is exacerbated by immune system alterations. Immunosenescence is the process of increased diversification of immune genes due to aging and other factors, leading to a decrease in the recognition function of the immune system. This process involves immune organs, immune cells, and the senescence-associated secretory phenotype (SASP). The most fundamental change is DNA damage, resulting in TME remodeling. The main manifestations are worsening inflammation, increased immunosuppressive SASP production, decreased immune cell antitumor activity, and the accumulation of tumor-associated fibroblasts and myeloid-derived suppressor cells, making antitumor therapy less effective. Senotherapy strategies to remove senescent cells and block key senescence processes can have synergistic effects with other treatments. This review focuses on immunoenescence and its impact on the solid TME. We characterize the immunosenescent TME and discuss future directions for antitumor therapies targeting senescence.

Human papilloma virus (HPV)-related information acquisition and seeking behavior among infected women: A single center cross-sectional survey in Shanghai, China.

Lacking of adequate knowledge is an obstacle to effective prevention of cervical cancer, yet factors that affect the information acquisition and seeking behavior as well as the information communication process are not well studied. We assessed information acquisition and seeking behavior, as well as perceived barriers of doctor-patient communication regarding human papilloma virus (HPV)-related information of infected women. Among 437 participants, 405 (93%) expressed demands for HPV-related information, while only a small proportion (100/437, 22.9%) actively sought information and felt obstacles comprehending. Web-based channels were most frequently utilized and medical personnel were the most trusted information source. Patients' satisfaction was significantly correlated with doctor's patience (r = 0.581, p < 0.001) and emotional caring (r = 0.555, p < 0.001). Compared to patients not actively seeking information, those actively seeking information were more likely to be single (p = 0.005), had higher education (p = 0.009) and monthly individual-level income (p = 0.023), and was more likely to undergo regular cervical cancer screening (p = 0.003), and were already or willing to be vaccinated (p = 0.008). The actively seeking information group also achieved higher scores in HPV knowledge test (p = 0.007). Public health interventions targeting HPV-infected women using specifically designed educational materials may influence information seeking behavior, increase HPV literacy and knowledge, which could potentially increase HPV vaccine uptake and cervical cancer screening rate.

Predictive value of neutrophil-to-lymphocyte ratio in coronary chronic total occlusion patients.

BACKGROUND: The neutrophil to lymphocyte ratio (NLR) has been reported as a novel predictor for atherosclerosis and cardiovascular outcomes. This study aimed to determine the effects of NLR on long-term clinical outcomes of chronic total occlusion (CTO) patients. METHODS: A total of 670 patients with CTO who met the inclusion criteria were included at the end of the follow-up period. Patients were divided into tertiles according to their baseline NLR levels at admission: low (n = 223), intermediate (n = 223), and high (n = 224). The incidence of major adverse cardiac events (MACEs) during the follow-up period, including all-cause death, nonfatal myocardial infarction (MI), or ischemia-driven revascularization, were compared among the three groups. RESULTS: Major adverse cardiac events were observed in 27 patients (12.1%) in the low tertile, 40 (17.9%) in the intermediate tertile, and 61 (27.2%) in the high NLR tertile (P < 0.001). Kaplan-Meier analysis demonstrated a significantly higher incidence of MACE, ischemia-driven coronary revascularization, non-fatal MI, and mortality in patients within the high tertile than those in the low and intermediate groups (all P < 0.001). Multivariable COX regression analysis showed that the high tertile of baseline NLR level showed a strong association with the risk of MACE (hazard ratio [HR] = 2.21; 95% confidence interval [CI]: 1.21-4.03; P = 0.009), ischemia-driven coronary revascularization (HR = 3.19; 95% CI: 1.56-6.52; P = 0.001), MI (HR = 2.61; 95% CI: 1.35-5.03; P = 0.043) and mortality (HR = 3.78; 95% CI: 1.65-8.77; P = 0.001). CONCLUSION: Our findings suggest that NLR is an inexpensive and readily available biomarker that can independently predict cardiovascular risk in patients with CTO.

The Role of Implementation Climate in Moderating Educator Use of Evidence-Based Practices and Outcomes for Autistic Students.

Ensuring effective use of evidence-based practice (EBP) for autism in schools is imperative due to the significantly increasing number of autistic students receiving school services each year. High-quality EBP use has proven challenging in schools. Research indicates implementation climate, or how EBP are supported, rewarded, and valued, and EBP resources are related to successful implementation. However, limited understanding of system-level contextual factors that impact EBP implementation for school-based providers makes development of appropriate implementation supports challenging. Understanding these factors is crucial for selecting and tailoring implementation strategies to support EBP scale up. In this observational study, California school-based providers (n = 1084) completed surveys related to implementation climate, leadership, autism experience and EBP implementation (use, competence, knowledge). Student outcomes included state level academic and behavioral indicators. Using an implementation science framework (Aarons et al., in Administration and Policy in Mental Health and Mental Health Services Research 38:4-23, 2011) and multilevel modeling, we examined the relationship between EBP Implementation and student outcomes and the moderation effects of provider and district level factors. Higher implementation climate predicted better EBP implementation outcomes, and proved more impactful when provider hands-on autism experience was low. Greater EBP resources predicted a higher percentage of students who met math standards only when district poverty level was high. Our findings suggested moderating effects on EBP implementation from both provider and system level factors. Implementation climate and resources may be especially key in addressing equity issues related to high poverty schools in which teachers often have less autism experience.

A comprehensive exploration of hydrogel applications in multi-stage skin wound healing.

Hydrogels, as an emerging biomaterial, have found extensive use in the healing of wounds due to their distinctive physicochemical structure and functional properties. Moreover, hydrogels can be made to match a range of therapeutic requirements for materials used in wound healing through specific functional modifications. This review provides a step-by-step explanation of the processes involved in cutaneous wound healing, including hemostasis, inflammation, proliferation, and reconstitution, along with an investigation of the factors that impact these processes. Furthermore, a thorough analysis is conducted on the various stages of the wound healing process at which functional hydrogels are implemented, including hemostasis, anti-infection measures, encouraging regeneration, scar reduction, and wound monitoring. Next, the latest progress of multifunctional hydrogels for wound healing and the methods to achieve these functions are discussed in depth and categorized for elucidation. Finally, perspectives and challenges associated with the clinical applications of multifunctional hydrogels are discussed.

Insufficient Plasma Melatonin and Its Association With Neuropsychiatric Impairments in Patients With T2DM.

Purpose: Type 2 diabetes mellitus (T2DM) is associated with multiple neuropsychiatric impairments, including cognitive dysfunction, and melatonin (MLT) plays a crucial role in maintaining normal neuropsychiatric functions. This study is aimed at investigating the change in plasma MLT levels and its association with neuropsychiatric impairments in T2DM patients. Methods: One hundred twenty-six T2DM patients were recruited, and their demographics and clinical data were collected. Apart from the plasma glycated hemoglobin (HbA1c) levels and other routine metabolic indicators, the plasma concentrations of MLT, C-reactive protein (CRP), Interleukin 6 (IL-6), soluble myeloid triggered receptor 1 (sTREM 1), and receptor 2 (sTREM 2) were measured. Moreover, the executive function and depressive tendency were evaluated via the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) and the Epidemiological Research Center Depression Scale (CES-D), respectively. Result: Compared with the low HbA1c group, the T2DM patients in the high HbA1c group presented lower plasma MLT levels but higher plasma concentrations of inflammatory biomarker levels, together with higher scores in the BRIEF-A and CES-D scales. Moreover, results of the Pearson correlation test showed that the plasma MLT levels were negatively correlated with the BRIEF-A and CES-D scores, as well as plasma concentrations of HbA1c and inflammatory indications, indicating that MLT may mediate their neuroinflammation and neuropsychiatric impairments. Furthermore, the ROC curve results indicated that plasma MLT levels have a predictive effect on executive impairment and depressive status in T2DM patients. Conclusion: MLT levels decreased in patients with T2DM and were associated with neuropsychiatric impairments and inflammatory status, and MLT might be developed as a therapeutic agent and predictive indicator for T2DM-associated executive impairment and depression status.

Bimetallic PtAu-Decorated SnO2 Nanospheres Exhibiting Enhanced Gas Sensitivity for Ppb-Level Acetone Detection.

Acetone is a biomarker found in the expired air of patients suffering from diabetes. Therefore, early and accurate detection of its concentration in the breath of such patients is extremely important. We prepared Tin(IV) oxide (SnO2) nanospheres via hydrothermal treatment and then decorated them with bimetallic PtAu nanoparticles (NPs) employing the approach of in situ reduction. The topology, elemental composition, as well as crystal structure of the prepared materials were studied via field emission scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, and X-ray diffraction. The findings revealed that bimetallic PtAu-decorated SnO2 nanospheres (PtAu/SnO2) were effectively synthesized as well as PtAu NPs evenly deposited onto the surface of the SnO2 nanospheres. Pure SnO2 nanospheres and PtAu/SnO2 sensors were prepared, and their acetone gas sensitivity was explored. The findings demonstrated that in comparison to pristine SnO2 nanosphere sensors, the sensors based on PtAu/SnO2 displayed superior sensitivity to acetone of 0.166-100 ppm at 300 °C, providing a low theoretical limit of detection equal to 158 ppm. Moreover, the PtAu/SnO2 sensors showed excellent gas response (Ra/Rg = 492.3 to 100 ppm), along with fast response and recovery (14 s/13 s to 10 ppm), good linearity of correlation, excellent repeatability, long-term stability, and satisfactory selectivity at 300 °C. This improved gas sensitivity was because of the electron sensitization of the Pt NPs, the chemical sensitization of the Au NPs, as well as the synergistic effects of bimetallic PtAu. The PtAu/SnO2 sensors have considerable potential for the early diagnosis and screening of diabetes.

PEARL-Catalyzed Peptide Bond Formation after Chain Reversal by Ureido-Forming Condensation Domains.

A subset of nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs) are encoded in their biosynthetic gene clusters (BGCs) with enzymes annotated as lantibiotic dehydratases. The functions of these putative lantibiotic dehydratases remain unknown. Here, we characterize an NRPS-PKS BGC with a putative lantibiotic dehydratase from the bacterium Stackebrandtia nassauensis (sna). Heterologous expression revealed several metabolites produced by the BGC, and the omission of selected biosynthetic enzymes revealed the biosynthetic pathway toward these compounds. The final product is a bisarginyl ureidopeptide with an enone electrophile. The putative lantibiotic dehydratase catalyzes peptide bond formation to a Thr that extends the peptide scaffold opposite to the NRPS and PKS biosynthetic direction. The condensation domain of the NRPS SnaA catalyzes the formation of a ureido group, and bioinformatics analysis revealed a distinct active site signature EHHXXHDG of ureido-generating condensation (Curea) domains. This work demonstrates that the annotated lantibiotic dehydratase serves as a separate amide bond-forming machinery in addition to the NRPS, and that the lantibiotic dehydratase enzyme family possesses diverse catalytic activities in the biosynthesis of both ribosomal and nonribosomal natural products.

The alteration and role of glycoconjugates in Alzheimer's disease.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by abnormal protein deposition. With an alarming 30 million people affected worldwide, AD poses a significant public health concern. While inhibiting key enzymes such as ß-site amyloid precursor protein-cleaving enzyme 1 and γ-secretase or enhancing amyloid-ß clearance, has been considered the reasonable strategy for AD treatment, their efficacy has been compromised by ineffectiveness. Furthermore, our understanding of AD pathogenesis remains incomplete. Normal aging is associated with a decline in glucose uptake in the brain, a process exacerbated in patients with AD, leading to significant impairment of a critical post-translational modification: glycosylation. Glycosylation, a finely regulated mechanism of intracellular secondary protein processing, plays a pivotal role in regulating essential functions such as synaptogenesis, neurogenesis, axon guidance, as well as learning and memory within the central nervous system. Advanced glycomic analysis has unveiled that abnormal glycosylation of key AD-related proteins closely correlates with the onset and progression of the disease. In this context, we aimed to delve into the intricate role and underlying mechanisms of glycosylation in the etiopathology and pathogenesis of AD. By highlighting the potential of targeting glycosylation as a promising and alternative therapeutic avenue for managing AD, we strive to contribute to the advancement of treatment strategies for this debilitating condition.

Magnetic lanthanide sensor with self-ratiometric time-resolved luminescence for accurate detection of epithelial cancerous exosomes.

Fluorescence-based LB (liquid biopsy) offers a rapid means of detecting cancer non-invasively. However, the widespread issue of sample loss during purification steps will diminish the accuracy of detection results. Therefore, in this study, we introduce a magnetic lanthanide sensor (MLS) designed for sensitive detection of the characteristic protein, epithelial cell adhesion molecule (EpCAM), on epithelial tumor exosomes. By leveraging the inherent multi-peak emission and time-resolved properties of the sole-component lanthanide element, combined with the self-ratiometric strategy, MLS can overcome limitations imposed by manual operation and/or sample complexity, thereby providing more stable and reliable output results. Specifically, terbium-doped NaYF4 nanoparticles (NaYF4:Tb) and deformable aptamers terminated with BHQ1 were sequentially introduced onto superparamagnetic silica-decorated Fe3O4 nanoparticles. Prior to target binding, emission from NaYF4:Tb at 543 nm was partially quenched due to the fluorescence resonance energy transfer (FRET) from NaYF4:Tb to BHQ1. Upon target binding, changes in the secondary structure of aptamers led to the fluorescence intensity increasing since the deconfinement of distance-dependent FRET effect. The characteristic emission of NaYF4:Tb at 543 nm was then utilized as the detection signal (I1), while the less changed emission at 583 nm served as the reference signal (I2), further reporting the self-ratiometric values of I1 and I2 (I1/I2) to illustrate the epithelial cancerous features of exosomes while ignoring possible sample loss. Consequently, over a wide range of exosome concentrations (2.28 × 102-2.28 × 108 particles per mL), the I1/I2 ratio exhibited a linear increase with exosome concentration [Y(I1/I2) = 0.166 lg (Nexosomes) + 3.0269, R2 = 0.9915], achieving a theoretical detection limit as low as 24 particles per mL. Additionally, MLS effectively distinguished epithelial cancer samples from healthy samples, showcasing significant potential for clinical diagnosis.

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy.

BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have developed prediction model for post-stroke epilepsy (PSE), their accuracy remains insufficient, and their applicability to different populations is uncertain. With the rapid advancement of computer technology, machine learning (ML) offers new opportunities for creating more accurate prediction models. However, the potential of ML in predicting PSE is still not well understood. The purpose of this study was to develop prediction models for PSE among ischemic stroke patients. METHODS: Patients with ischemic stroke from two stroke centers were included in this retrospective cohort study. At the baseline level, 33 input variables were considered candidate features. The 2-year PSE prediction models in the derivation cohort were built using six ML algorithms. The predictive performance of these machine learning models required further appraisal and comparison with the reference model using the conventional triage classification information. The Shapley additive explanation (SHAP), based on fair profit allocation among many stakeholders according to their contributions, is used to interpret the predicted outcomes of the naive Bayes (NB) model. RESULTS: A total of 1977 patients were included to build the predictive model for PSE. The Boruta method identified NIHSS score, hospital length of stay, D-dimer level, and cortical involvement as the optimal features, with the receiver operating characteristic curves ranging from 0.709 to 0.849. An additional 870 patients were used to validate the ML and reference models. The NB model achieved the best performance among the PSE prediction models with an area under the receiver operating curve of 0.757. At the 20 % absolute risk threshold, the NB model also provided a sensitivity of 0.739 and a specificity of 0.720. The reference model had poor sensitivities of only 0.15 despite achieving a helpful AUC of 0.732. Furthermore, the SHAP method analysis demonstrated that a higher NIHSS score, longer hospital length of stay, higher D-dimer level, and cortical involvement were positive predictors of epilepsy after ischemic stroke. CONCLUSIONS: Our study confirmed the feasibility of applying the ML method to use easy-to-obtain variables for accurate prediction of PSE and provided improved strategies and effective resource allocation for high-risk patients. In addition, the SHAP method could improve model transparency and make it easier for clinicians to grasp the prediction model's reliability.

A comprehensive prediction system for silkworm acute toxicity assessment of environmental and in-silico pesticides.

The excessive application and loss of pesticides poses a great risk to the ecosystem, and the environmental safety assessment of pesticides is time-consuming and expensive using traditional animal toxicity tests. In this work, a pesticide acute toxicity dataset was created for silkworm integrating extensive experiments and various common pesticide formulations considering the sensitivity of silkworm to adverse environment, its economic value in China, and a gap in machine learning (ML) research on the toxicity prediction of this species, which addressed the previous limitation of only being able to predict toxicity classification without specific toxicity values. A new comprehensive voting model (CVR) was developed based on ML, combined with three regression algorithms, namely, Bayesian Ridge (BR), K Neighbors Regressor (KNN), Random Forest Regressor (RF) to accurately calculate lethal concentration 50 % (LC50). Three conformal models were successfully constructed, marking the first combination of conformal models with confidence intervals to predict silkworm toxicity. Further, the mechanism by analyzing structural alerts was summarized, and identified 25 warning structures, 24 positive compounds and 14 negative compounds. Importantly, a novel comprehensive prediction system was constructed that can provide LC50 and confidence intervals, structural alerts analysis, lipid-water partition coefficient (LogP) and similarity analysis, which can comprehensively evaluate the ecological toxicity risk of substances to make up for the incomplete toxicity data of new pesticides. The validity and generalization of the CVR model were verified by an external validation set. In addition, five new, low-toxic and green pesticide alternatives were designed through 50,000 cycles. Moreover, our software and ST Profiler can provide low-cost information access to accelerate environmental risk assessment, which can predict not only a single chemical, but also batches of chemicals, simply by inputting the SMILES / CAS / (Chinese / English) name of chemicals.

Matching Patients to Clinical Trials using LLaMA 2 Embeddings and Siamese Neural Network.

Patient recruitment is a key desideratum for the success of a clinical trial that entails identifying eligible patients that match the selection criteria for the trial. However, the complexity of criteria information and heterogeneity of patient data render manual analysis a burdensome and time-consuming task. In an attempt to automate patient recruitment, this work proposes a Siamese Neural Network-based model, namely Siamese-PTM. Siamese-PTM employs the pretrained LLaMA 2 model to derive contextual representations of the EHR and criteria inputs and jointly encodes them using two weight-sharing identical subnetworks. We evaluate Siamese-PTM on structured and unstructured EHR to analyze their predictive informativeness as standalone and collective feature sets. We explore a variety of deep models for Siamese-PTM's encoders and compare their performance against the Single-encoder counterparts. We develop a baseline rule-based classifier, compared to which Siamese-PTM improved performance by 40%. Furthermore, visualization of Siamese-PTM's learned embedding space reinforces its predictive robustness.

Spin occupancy regulation of the Pt d-orbital for a robust low-Pt catalyst towards oxygen reduction.

Disentangling the limitations of O-O bond activation and OH* site-blocking effects on Pt sites is key to improving the intrinsic activity and stability of low-Pt catalysts for the oxygen reduction reaction (ORR). Herein, we integrate of PtFe alloy nanocrystals on a single-atom Fe-N-C substrate (PtFe@FeSAs-N-C) and further construct a ferromagnetic platform to investigate the regulation behavior of the spin occupancy state of the Pt d-orbital in the ORR. PtFe@FeSAs-N-C delivers a mass activity of 0.75 A mgPt-1 at 0.9 V and a peak power density of 1240 mW cm-2 in the fuel-cell, outperforming the commercial Pt/C catalyst, and a mass activity retention of 97%, with no noticeable current drop at 0.6 V for more than 220 h, is attained. Operando spectroelectrochemistry decodes the orbital interaction mechanism between the active center and reaction intermediates. The Pt dz2 orbital occupation state is regulated to t2g6eg3 by spin-charge injection, suppressing the OH* site-blocking effect and effectively inhibiting H2O2 production. This work provides valuable insights into designing high-performance and low-Pt catalysts via spintronics-level engineering.

Identification and transcriptome analysis of a photosynthesis deficient mutant of Populus davidiana Dode.

Photosynthesis is the main source of energy for plants to sustain growth and development. Abnormalities in photosynthesis may cause defects in plant development. The elaborate regulatory mechanism underlying photosynthesis remains unclear. In this study, we identified a natural mutant from the Greater Khingan Mountains and named it as "1-T". This mutant had variegated leaf with irregular distribution of yellow and green. Chlorophyll contents and photosynthetic capacity of 1-T were significantly reduced compared to other poplar genotypes. Furthermore, a transcriptome analysis revealed 3269 differentially expressed genes (DEGs) in 1-T. The products of the DEGs were enriched in photosystem I and photosystem II. Three motifs were significantly enriched in the promoters of these DEGs. Yeast one-hybrid, Electrophoretic mobility shift assays and tobacco transient transformation experiments indicated that PdGLKs may bind to the three motifs. Further analysis indicated that these photosystem related genes were also significantly down-regulated in PdGLK-RNAi poplars. Therefore, we preliminarily concluded that the down-regulation of PdGLKs in 1-T may affect the expression of photosystem-related genes, resulting in abnormal photosystem development and thus affecting the growth and development. Our results provide new insights into the molecular mechanism of photosynthesis regulating plant growth.

RefAI: a GPT-powered retrieval-augmented generative tool for biomedical literature recommendation and summarization.

OBJECTIVES: Precise literature recommendation and summarization are crucial for biomedical professionals. While the latest iteration of generative pretrained transformer (GPT) incorporates 2 distinct modes-real-time search and pretrained model utilization-it encounters challenges in dealing with these tasks. Specifically, the real-time search can pinpoint some relevant articles but occasionally provides fabricated papers, whereas the pretrained model excels in generating well-structured summaries but struggles to cite specific sources. In response, this study introduces RefAI, an innovative retrieval-augmented generative tool designed to synergize the strengths of large language models (LLMs) while overcoming their limitations. MATERIALS AND METHODS: RefAI utilized PubMed for systematic literature retrieval, employed a novel multivariable algorithm for article recommendation, and leveraged GPT-4 turbo for summarization. Ten queries under 2 prevalent topics ("cancer immunotherapy and target therapy" and "LLMs in medicine") were chosen as use cases and 3 established counterparts (ChatGPT-4, ScholarAI, and Gemini) as our baselines. The evaluation was conducted by 10 domain experts through standard statistical analyses for performance comparison. RESULTS: The overall performance of RefAI surpassed that of the baselines across 5 evaluated dimensions-relevance and quality for literature recommendation, accuracy, comprehensiveness, and reference integration for summarization, with the majority exhibiting statistically significant improvements (P-values <.05). DISCUSSION: RefAI demonstrated substantial improvements in literature recommendation and summarization over existing tools, addressing issues like fabricated papers, metadata inaccuracies, restricted recommendations, and poor reference integration. CONCLUSION: By augmenting LLM with external resources and a novel ranking algorithm, RefAI is uniquely capable of recommending high-quality literature and generating well-structured summaries, holding the potential to meet the critical needs of biomedical professionals in navigating and synthesizing vast amounts of scientific literature.

Evolutionary genomics of two diploid goat grass species belonging to the section Sitopsis of Aegilops, Aegilops longissima, and Aegilops sharonensis.

Aegilops longissima and Ae. sharonensis, being classified into the Sitopsis section of genus Aegilops, are distinct species both taxonomically and ecologically. Nevertheless, earlier observations indicate that the two species are not reproductively isolated to full extent and can inter-bred upon secondary contact. However, the genomic underpinnings of the morpho-ecological differentiation between the two foci species remained unexplored. Here, we resequenced 31 representative accessions of the two species and conducted in-depth comparative genomic analyses. We demonstrate recurrent and ongoing natural hybridizations between Ae. longissima and Ae. sharonensis, and depict features of genome composition of the resultant hybrids at both individual and population levels. We also delineate genomic regions and candidate genes potentially underpinning the differential morphological and edaphic adaptations of the two species. Intriguingly, a binary morphology was observed in the hybrids, suggesting existence of highly diverged genomic regions that remain uneroded by the admixtures. Together, our results provide new insights into the molding effects of interspecific hybridization on genome composition and mechanisms preventing merge of the two species.

Microdeletion on Xq27.1 in a Chinese VACTERL-Like Family with Kidney and Anal Anomalies.

Objective: VATER/VACTERL-like association is associated with adverse pregnancy outcomes. Genetic evidence of this disorder is sporadic. In this study, we aimed to provide genetic insights to improve the diagnosis of VACTERL. Methods: We have described a Chinese family in which four members were affected by renal defects or agenesis, anal atresia, and anovaginal fistula, which is consistent with the diagnosis of a VACTERL-like association. Pedigree and genetic analyses were conducted using genome and exome sequencing. Results: Segregation analysis revealed the presence of a recessive X-linked microdeletion in two living affected individuals, harboring a 196-380 kb microdeletion on Xq27.1, which was identified by familial exome sequencing. Genome sequencing was performed on the affected male, confirming a -196 kb microdeletion in Xq27.1, which included a 28% loss of the CDR-1 gene. Four family members were included in the co-segregation analysis, and only VACTERL-like cases with microdeletions were reported in X27.1. Conclusion: These results suggest that the 196-380 kb microdeletion in Xq27.1 could be a possible cause of the VATER/VACTERL-like association. However, further genetic and functional analyses are required to confirm or rule out genetic background as the definitive cause of the VACTERL association.