Early identification of stroke through deep learning with multi-modal human speech and movement data.

JOURNAL/nrgr/04.03/01300535-202501000-00031/figure1/v/2024-05-14T021156Z/r/image-tiff Early identification and treatment of stroke can greatly improve patient outcomes and quality of life. Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale (CPSS) and the Face Arm Speech Test (FAST) are commonly used for stroke screening, accurate administration is dependent on specialized training. In this study, we proposed a novel multimodal deep learning approach, based on the FAST, for assessing suspected stroke patients exhibiting symptoms such as limb weakness, facial paresis, and speech disorders in acute settings. We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements, facial expressions, and speech tests based on the FAST. We compared the constructed deep learning model, which was designed to process multi-modal datasets, with six prior models that achieved good action classification performance, including the I3D, SlowFast, X3D, TPN, TimeSformer, and MViT. We found that the findings of our deep learning model had a higher clinical value compared with the other approaches. Moreover, the multi-modal model outperformed its single-module variants, highlighting the benefit of utilizing multiple types of patient data, such as action videos and speech audio. These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke, thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

Impact of insulin resistance on IVF/ICSI outcomes in women with polycystic ovary syndrome: A systematic review and meta-analysis.

OBJECTIVE: To evaluate the effect of insulin resistance (IR) on in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) outcomes in patients with polycystic ovary syndrome (PCOS). STUDY DESIGN: PubMed, Google Scholar,Web of Science, Embase, Scopus and the Cochrane Library were searched to identify relevant studies. A total of 6,137 PCOS women undergoing IVF/ICSI with or without IR were included in the systematic review and meta-analysis. RESULTS: The systematic review and meta-analysis included twelve observational studies that were free from inherent bias. When comparing PCOS women undergoing IVF/ICSI, the IR and non-IR groups did not show significant differences in oocytes retrieved (WMD = -0.63, 95 % CI: -2.37 to 1.12, P = 0. 483), fertilization rate (WMD = 1.01, 95 % CI: -0.66 to 2.67, P = 0.236; OR = 0.97, 95 % CI: 0.79 to 1.19, P = 0.783), and live birth rate (OR = 1.02, 95 % CI: 0.78 to 1.33, P = 0.892). However, the group with IR had a lower number of MII oocytes (WMD = -1.07, 95 % CI: -1.54 to -0.59, P < 0.001), total embryos (WMD = -1.37, 95 % CI: -1. 78 to -0.95, P < 0.001), and clinical pregnancy rate (OR = 0.77, 95 % CI: 0.59 to 0.99, P = 0.042), as well as a higher miscarriage rate (OR = 1.11, 95 % CI: 1.02 to 1.22, P = 0.017) compared to the non-IR group. CONCLUSION: In women with PCOS, IR had a negative impact on IVF/ICSI outcomes. To obtain more favourable empirical support, larger studies are necessary.

Patterns and correlates of potential range shifts of bat species in China in the context of climate change.

Climate change may diminish biodiversity; thus, it is urgent to predict how species' ranges may shift in the future by integrating multiple factors involving more taxa. Bats are particularly sensitive to climate change due to their high surface-to-volume ratio. However, few studies have considered geographic variables associated with roost availability and even fewer have linked the distributions of bats to their thermoregulation and energy regulation traits. We used species distribution models to predict the potential distributions of 12 bat species in China under current and future greenhouse gas emission scenarios (SSP1-2.6 and SSP5-8.5) and examined factors that could affect species' range shifts, including climatic, geographic, habitat, and human activity variables and wing surface-to-mass ratio (S-MR). The results suggest that Ia io, Rhinolophus ferrumequinum, and Rhinolophus rex should be given the highest priority for conservation in future climate conservation strategies. Most species were predicted to move northward, except for I. io and R. rex, which moved southward. Temperature seasonality, distance to forest, and distance to karst or cave were the main environmental factors affecting the potential distributions of bats. We found significant relationships between S-MR and geographic distribution, current potential distribution, and future potential distribution in the 2050s. Our work highlights the importance of analyzing range shifts of species with multifactorial approaches, especially for species traits related to thermoregulation and energy regulation, to provide targeted conservation strategies.

Patrones y correlaciones de los cambios potenciales en la distribución de las especies de murciélago de China en el contexto del cambio climático Resumen El cambio climático puede disminuir la biodiversidad, por lo que es urgente pronosticar cómo puede cambiar en el futuro la distribución de las especies mediante la integración de múltiples factores que involucren a más taxones. Los murciélagos son particularmente sensibles al cambio climático debido a que tienen una gran proporción superficie­volumen. Sin embargo, hay pocos estudios que han considerado las variables asociadas con la disponibilidad de nidos y son todavía menos los que han conectado la distribución de los murciélagos con sus rasgos de termorregulación y regulación de energía. Usamos modelos de distribución de especies para pronosticar la distribución potencial de doce especies de murciélago en China bajo escenarios actuales y futuros de emisión de gases de efecto invernadero (SSP1­2.6 y SSP5­8.5) y analizamos los factores que podrían afectar el cambio en la distribución de las especies, incluyendo las variables climáticas, geográficas, de hábitat y de actividad humana y la proporción entre la superficie del ala y la masa (P S­M). Los resultados sugieren que Ia io, Rhinolophus ferrumequinum y R. rex deberían ser la mayor prioridad de conservación para las estrategias de conservación climáticas en el futuro. Pronosticamos que la mayoría de las especies se desplazarían al norte, a excepción de I. io y R. rex, que se desplazarían hacia el sur. Los principales factores que afectaron la distribución potencial de los murciélagos fueron la estacionalidad de la temperatura, la distancia al bosque y la distancia a la cueva o al karst. Encontramos una relación significativa entre la P S­M y la distribución geográfica, la distribución potencial actual y la distribución potencial para la década de 2050. Nuestra investigación destaca la importancia del análisis de los cambios de distribución de las especies con enfoques multifactoriales, especialmente para los rasgos de especie relacionados con la termorregulación y la regulación de energía, para proporcionar estrategias de conservación focalizadas.

Effect of ph on migration patterns and degradation pathways of sulfamethazine in soil systems.

Sulfonamide antibiotics (SAs) are widely used antimicrobial agents in livestock and aquaculture, and most of them entering the animal's body will be released into the environment as prodrugs or metabolites, which ultimately affect human health through the food chain. Both acid deposition and salinization of soil may have an impact on the migration and degradation of antibiotics. Sulfamethazine (SM2), a frequently detected compound in agricultural soils, has a migration and transformation process in the environment that is closely dependent on environmental pH. Nevertheless, scarcely any studies have been conducted on the effect of soil pH changes on the environmental behavior of sulfamethazine. We analyzed the migration and degradation mechanisms of SM2 using simulation experiments and ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) techniques. The results showed that acidic conditions limited the vertical migration of sulfadimidine, and SM2 underwent different reaction processes under different pH conditions, including S-C bond breaking, S-N bond hydrolysis, demethylation, six-membered heterocyclic addition, methyl hydroxylation and ring opening. The study of the migration pattern and degradation mechanism of SM2 under different pH conditions can provide a solid theoretical basis for assessing the pollution risk of sulfamethazine degradation products under acid rain and saline conditions, and provide a guideline for remediation of antibiotic contamination, so as to better prevent, control and protect groundwater resources.

Comparative study of urea-15N fate in pure bamboo and bamboo-broadleaf mixed forests.

Objectives: Bamboo is a globally significant plant with ecological, environmental, and economic bene-fits. Choosing suitable native tree species for mixed planting in bamboo forests is an effective measure for achieving both ecological and economic benefits of bamboo forests. However, little is currently known about the impact of bamboo forests on nitrogen cycling and utilization efficiency after mixing with other tree species. Therefore, our study aims to compare the nitrogen cycling in pure bamboo forests with that in mixed forests. Methods: Through field experiments, we investigated pure Qiongzhuea tumidinoda forests and Q. tumidinoda-Phellodendron chinense mixed forests, and utilized 15N tracing technology to explore the fertilization effects and fate of urea-15N in different forest stands. Results: The results demonstrated the following: 1) in both forest stands, bamboo culms account for the highest biomass percentage (42.99%-51.86%), while the leaves exhibited the highest nitrogen concentration and total nitrogen uptake (39.25%-44.52%/29.51%-33.21%, respectively) Additionally, the average nitrogen uptake rate of one-year-old bamboo is higher (0.25 mg kg-1 a-1) compared to other age groups. 2) the urea-15N absorption in mixed forests (1066.51-1141.61 g ha-1, including 949.65-1000.07 g ha-1 for bamboo and 116.86-141.54 g ha-1 for trees) was significantly higher than that in pure forests (663.93-727.62 g ha-1, P<0.05). Additionally, the 15N recovery efficiency of culms, branches, leaves, stumps, and stump roots in mixed forests was significantly higher than that in pure forests, with increases of 43.14%, 69.09%, 36.84%, 51.63%, 69.18%, 34.60%, and 26.89%, respectively. 3) the recovery efficiency of urea-15N in mixed forests (45.81%, comprising 40.43% for bamboo and 5.38% for trees) and the residual urea-15N recovery rate in the 0-60 cm soil layer (23.46%) are significantly higher compared to those in pure forests (28.61%/18.89%). This could be attributed to the nitrogen losses in mixed forests (30.73%, including losses from ammonia volatilization, runoff, leaching, and nitrification-denitrification) being significantly lower than those in pure forests (52.50%). Conclusion: These findings suggest that compared to pure bamboo forests, bamboo in mixed forests exhibits higher nitrogen recovery efficiency, particularly with one-year-old bamboo playing a crucial role.

ICU Nurses' Perception of Sensitive Indicators of Quality of Care for ECMO Patients in Guizhou Province, China: A Cross-Sectional Study.

Purpose: This study aimed to investigate the cognitive evaluation level of ICU nurses in Guizhou Province, China, on the sensitivity indicators of nursing quality for ECMO patients. Patients and Methods: This was a cross-sectional observational study conducted in Guizhou Province, China, from May to July 2023, 259 ICU nurses were surveyed. Objective sampling method was used to select the participants from 10 hospitals in Guizhou Province that carried out ECMO. Data were collected through questionnaire survey. Two researchers checked and recorded Epidata 3.1. SPSS 25.0 was used for statistical analysis of the data, and frequency, mean and component ratio were used for descriptive statistical analysis. The importance rating was used to reflect the degree of nurses' agreement with the indicators. Results: The results of this study showed that 79.1% of the 253 ICU nurses in Guizhou Province, China, had not participated in training and courses related to indicators of quality of care evaluation for ECMO patients. The main way for ICU nurses to acquire knowledge related to indicators of quality of care sensitivity for ECMO patients was departmental training, which accounted for 87.4%. And the other ways, in descending order, were public, the matic lectures or academic conferences, journals and magazines; their evaluation scores of the importance of most of the quality of care sensitivity indicators for ECMO patients was moderate, with the scores ranging from 73 to 150. Among them, the range of importance evaluation scores for each indicator was 4.01 ~ 4.48. Conclusion: The overall cognitive evaluation of ICU nurses in Guizhou Province, China, on most sensitivity indicators of quality of care for ECMO patients was moderate, and there is a general lack of systematic courses and training on the knowledge related to ECMO care quality sensitive indicators.

Optimizing anesthesia strategies to NSCLC patients in VATS procedures: Insights from drug requirements and patient recovery patterns.

Understanding the intricate relationship between cancer clinicopathological features and anesthetics dosage is crucial for optimizing patient outcomes and safety during surgery. This retrospective study investigates this relationship in patients with non-small cell lung cancer (NSCLC) undergoing video-assisted thoracic surgery (VATS). A comprehensive analysis of medical records was undertaken for NSCLC patients who underwent VATS with intravenous compound inhalation general anesthesia. Patients were categorized based on histological, chemotherapy, radiotherapy, and epidural anesthesia factors. Statistical analysis was performed to compare the differences between the groups. The results revealed compelling insights. Specifically, patients with lung adenocarcinoma (LUAD) undergoing VATS exhibited higher dosages of rocuronium bromide and midazolam during general anesthesia, coupled with a shorter post-anesthesia care unit (PACU) stay compared to those with squamous cell carcinoma (sqCL). Furthermore, chemotherapy patients undergoing VATS demonstrated diminished requirements for phenylephrine and remifentanil in contrast to their non-chemotherapy counterparts. Similarly, radiotherapy patients undergoing VATS demonstrated a decreased necessity for rocuronium bromide compared to non-radiotherapy patients. Notably, patients who received epidural anesthesia in combination with general anesthesia manifested reduced hydromorphone requirements and prolonged hospital stays compared to those subjected to general anesthesia alone. In conclusion, the findings from this study indicate several important observations in diverse patient groups undergoing VATS. The higher dosages of rocuronium bromide and midazolam in LUAD patients point to potential differences in drug requirements among varying lung cancer types. Additionally, the observed shorter PACU stay in LUAD patients suggests a potentially expedited recovery process. The reduced anesthetic requirements of phenylephrine and remifentanilin chemotherapy patients indicate distinct responses to anesthesia and pain management. Radiotherapy patients requiring lower doses of rocuronium bromide imply a potential impact of prior radiotherapy on muscle relaxation. Finally, the combination of epidural anesthesia with general anesthesia resulted in reduced hydromorphone requirements and longer hospital stays, suggesting the potential benefits of this combined approach in terms of pain management and postoperative recovery. These findings highlight the importance of tailoring anesthesia strategies for specific patient populations to optimize outcomes in VATS procedures.

Structural basis for recognition of 26RFa by the pyroglutamylated RFamide peptide receptor.

The neuropeptide 26RFa, a member of the RF-amide peptide family, activates the pyroglutamylated RF-amide peptide receptor (QRFPR), a class A GPCR. The 26RFa/QRFPR system plays critical roles in energy homeostasis, making QRFPR an attractive drug target for treating obesity, diabetes, and eating disorders. However, the lack of structural information has hindered our understanding of the peptide recognition and regulatory mechanism of QRFPR, impeding drug design efforts. In this study, we determined the cryo-EM structure of the Gq-coupled QRFPR bound to 26RFa. The structure reveals a unique assembly mode of the extracellular region of the receptor and the N-terminus of the peptide, and elucidates the recognition mechanism of the C-terminal heptapeptide of 26RFa by the transmembrane binding pocket of QRFPR. The study also clarifies the similarities and distinctions in the binding pattern of the RF-amide moiety in five RF-amide peptides and the RY-amide segment in neuropeptide Y. These findings deepen our understanding of the RF-amide peptide recognition, aiding in the rational design of drugs targeting QRFPR and other RF-amide peptide receptors.

Optimizing multicopy chromosomal integration for stable high-performing strains.

The copy number of genes in chromosomes can be modified by chromosomal integration to construct efficient microbial cell factories but the resulting genetic systems are prone to failure or instability from triggering homologous recombination in repetitive DNA sequences. Finding the optimal copy number of each gene in a pathway is also time and labor intensive. To overcome these challenges, we applied a multiple nonrepetitive coding sequence calculator that generates sets of coding DNA sequence (CDS) variants. A machine learning method was developed to calculate the optimal copy number combination of genes in a pathway. We obtained an engineered Yarrowia lipolytica strain for eicosapentaenoic acid biosynthesis in 6 months, producing the highest titer of 27.5 g l-1 in a 50-liter bioreactor. Moreover, the lycopene production in Escherichia coli was also greatly improved. Importantly, all engineered strains of Y. lipolytica, E. coli and Saccharomyces cerevisiae constructed with nonrepetitive CDSs maintained genetic stability.

Investigation of zero-phonon line characteristics in ensemble nitrogen-vacancy centers at 1.6†K-300†K.

The ensemble of nitrogen-vacancy (NV) centers is widely used in quantum information transmission, high-precision magnetic field, and temperature sensing due to their advantages of long-lived state and the ability to be pumped by optical cycling. In this study, we investigate the zero-phonon line behavior of the two charge states of NV centers by measuring the photoluminescence of the NV center at 1.6 K-300 K. The results demonstrate a positional redshift, an increase in line width, and a decrease in fluorescence intensity for the ZPL of NV0 and NV- as the temperature increased. In the range of 10 K to 140 K, the peak shift with high concentrations of NV- revealed an anomaly of bandgap reforming. The peak position undergoes a blueshift and then a redshift as temperature increases. Furthermore, the transformation between NV0 and NV- with temperature changes has been obtained in diamonds with different nitrogen concentrations. This study explored the ZPL characteristics of NV centers in various temperatures, and the findings are significant for the development of high-resolution temperature sensing and high-precision magnetic field sensing in ensemble NV centers.

Dark solitons and their bound states in a nonlinear fiber with second- and fourth-order dispersion.

We study the excitations of dark solitons in a nonlinear optical fiber with the second- and fourth-order dispersion, and find the emergence of striped dark solitons (SDSs) and some multi-dark-soliton bound states. The SDSs can exhibit time-domain oscillating structures on a plane wave, and they have two types: the ones with or without the total phase step, while the multi-dark-soliton bound states exhibit different numbers of amplitude humps. By the modified linear stability analysis, we regard the SDSs as the results of the competition between periodicity and localization, and analytically give their existence condition, oscillation frequency, and propagation stability, which show good agreements with numerical results. We also provide a possible interpretation of the formation of the existing striped bright solitons (SBSs), and find that SBS will become the pure-quartic soliton when its periodicity and localization carry equal weight. Our results provide the theoretical support for the experimental observation of striped solitons in nonlinear fibers, and our method can also guide the discovery of striped solitons in other physical systems.

Optimization of the structure, morphology and luminescent properties of NaYF4 upconversion nanoparticles.

We designed and constructed rare earth doped upconversion nanoparticles ß-Na(Y0.78Yb0.18Er0.04)F4, sensitizing layer encapsulated ß-Na(Y0.9Er0.1)F4@ß-NaYbF4 and inert layer encapsulated ß-Na(Y0.9Er0.1)F4@ß-NaYbF4@ß-NaYF4. Compared with the mononuclear material, the luminescence intensity of the particles encapsulated with double shells in the three main bands of blue, green and red emissions increased by 346, 22, and 54 times respectively. While improving the upconversion luminescence performance, the underlying reasons for this improvement were analyzed in detail. The effects of shell coating on the fluorescence lifetime, thermal stability and energy level transition are discussed. On this basis, the composite film material was constructed by combining the shell coating strategy and the plasma resonance interaction strategy, which further improved the upconversion efficiency. In addition, by combining performance optimized upconversion particles with information coding, we explored its potential as an anti-counterfeiting material.

Target recognition and segmentation in turbid water using data from non-turbid conditions: a unified approach and experimental validation.

Semantic segmentation of targets in underwater images within turbid water environments presents significant challenges, hindered by factors such as environmental variability, difficulties in acquiring datasets, imprecise data annotation, and the poor robustness of conventional methods. This paper addresses this issue by proposing a novel joint method using deep learning to effectively perform semantic segmentation tasks in turbid environments, with the practical case of efficiently collecting polymetallic nodules in deep-sea while minimizing damage to the seabed environment. Our approach includes a novel data expansion technique and a modified U-net based model. Drawing on the underwater image formation model, we introduce noise to clear water images to simulate images captured under varying degrees of turbidity, thus providing an alternative to the required data. Furthermore, traditional U-net-based modified models have shown limitations in enhancing performance in such tasks. Based on the primary factors underlying image degradation, we propose a new model which incorporates an improved dual-channel encoder. Our method significantly advances the fine segmentation of underwater images in turbid media, and experimental validation demonstrates its effectiveness and superiority under different turbidity conditions. The study provides new technical means for deep-sea resource development, holding broad application prospects and scientific value.

Methylation synthetic lethality: Exploiting selective drug targets for cancer therapy.

In cancer, synthetic lethality refers to the drug-induced inactivation of one gene and the inhibition of another in cancer cells by a drug, resulting in the death of only cancer cells; however, this effect is not present in normal cells, leading to targeted killing of cancer cells. Recent intensive epigenetic research has revealed that aberrant epigenetic changes are more frequently observed than gene mutations in certain cancers. Recently, numerous studies have reported various methylation synthetic lethal combinations involving DNA damage repair genes, metabolic pathway genes, and paralogs with significant results in cellular models, some of which have already entered clinical trials with promising results. This review systematically introduces the advantages of methylation synthetic lethality and describes the lethal mechanisms of methylation synthetic lethal combinations that have recently demonstrated success in cellular models. Furthermore, we discuss the future opportunities and challenges of methylation synthetic lethality in targeted anticancer therapies.

Posterior default mode network is associated with the social performance in male children with autism spectrum disorder: A dynamic causal modeling analysis based on triple-network model.

The triple-network model has been widely applied in neuropsychiatric disorders including autism spectrum disorder (ASD). However, the mechanism of causal regulations within the triple-network and their relations with symptoms of ASD remains unclear. 81 male ASD and 80 well matched typically developing control (TDC) were included in this study, recruited from Autism Brain Image Data Exchange-I datasets. Spatial reference-based independent component analysis was used to identify the anterior and posterior part of default-mode network (aDMN and pDMN), salience network (SN), and bilateral executive-control network (ECN) from resting-state functional magnetic resonance imaging data. Spectral dynamic causal model and parametric empirical Bayes with Bayesian model reduction/average were adopted to explore the effective connectivity (EC) within triple-network and the relationship between EC and autism diagnostic observation schedule (ADOS) scores. After adjusting for age and site effect, ASD and TDC groups both showed inhibition patterns. Compared with TDC, ASD group showed weaker self-inhibition in aDMN and pDMN, stronger inhibition in pDMN→aDMN, weaker inhibition in aDMN→LECN, pDMN→SN, LECN→SN, and LECN→RECN. Furthermore, negative relationships between ADOS scores and pDMN self-inhibition strength, as well as with the EC of pDMN→aDMN were observed in ASD group. The present study reveals imbalanced effective connections within triple-networks in ASD children. More attentions should be focused at the pDMN, which modulates the core symptoms of ASD and may serve as an important region for ASD diagnosis and the target region for ASD treatments.

Exploiting ChatGPT for Diagnosing Autism-Associated Language Disorders and Identifying Distinct Features.

Diagnosing language disorders associated with autism is a complex and nuanced challenge, often hindered by the subjective nature and variability of traditional assessment methods. Traditional diagnostic methods not only require intensive human effort but also often result in delayed interventions due to their lack of speed and specificity. In this study, we explored the application of ChatGPT, a state-of-the-art large language model, to overcome these obstacles by enhancing diagnostic accuracy and profiling specific linguistic features indicative of autism. Leveraging ChatGPT's advanced natural language processing capabilities, this research aims to streamline and refine the diagnostic process. Specifically, we compared ChatGPT's performance with that of conventional supervised learning models, including BERT, a model acclaimed for its effectiveness in various natural language processing tasks. We showed that ChatGPT substantially outperformed these models, achieving over 13% improvement in both accuracy and F1-score in a zero-shot learning configuration. This marked enhancement highlights the model's potential as a superior tool for neurological diagnostics. Additionally, we identified ten distinct features of autism-associated language disorders that vary significantly across different experimental scenarios. These features, which included echolalia, pronoun reversal, and atypical language usage, were crucial for accurately diagnosing ASD and customizing treatment plans. Together, our findings advocate for adopting sophisticated AI tools like ChatGPT in clinical settings to assess and diagnose developmental disorders. Our approach not only promises greater diagnostic precision but also aligns with the goals of personalized medicine, potentially transforming the evaluation landscape for autism and similar neurological conditions.

Association between BCL11B gene polymorphisms and age-related hearing loss in the elderly: A case-control study in Qingdao, China.

Age-related hearing loss is a complex disease caused by a combination of genetic and environmental factors, and a study have conducted animal experiments to explore the association between BCL11B heterozygosity and age-related hearing loss. The present study used established genetic models to examine the association between BCL11B gene polymorphisms and age-related hearing loss. A total of 410 older adults from two communities in Qingdao, China, participated in this study. The case group comprised individuals aged ≥ 60 years with age-related hearing loss, and the control group comprised individuals without age-related hearing loss from the same communities. The groups were matched 1:1 for age and sex. The individual characteristics of the participants were analyzed descriptively using the Mann-Whitney U test and the chi-square test. To explore the association between BCL11B gene polymorphisms and age-related hearing loss, conditional logistic regression was performed to construct genetic models for two single-nucleotide-polymorphisms (SNPs) of BCL11B, and haplotype analysis was conducted to construct their haplotype domains. Two SNP sites of the BCL11B gene, four genetic models of rs1152781 (additive, dominant, recessive, and codominant), and five genetic models of rs1152783 (additive, dominant, recessive, codominant, and over dominant) were significantly associated with age-related hearing loss in the models both unadjusted and adjusted for all covariates (P < 0.05). Additionally, a linkage disequilibrium between rs1152781 and rs1152783 was revealed through haplotype analysis. Our study revealed that BCL11B gene polymorphisms were significantly associated with age-related hearing loss.

Predictive value of plasma ephrinB2 levels for amputation risk following endovascular revascularization in peripheral artery disease.

Background: The aim of this study is to investigate the expression levels of ephrinB2 in patients with lower extremity peripheral arterial disease (PAD) and explore its association with the severity of the disease and the risk of amputation after endovascular revascularization. Methods: During the period from March 2021 to March 2023, this study collected blood samples and clinical data from 133 patients diagnosed with lower extremity PAD and 51 healthy volunteer donors. The severity of lower extremity PAD patients was classified using the Rutherford categories. The expression of ephrin-B2 in plasma samples was detected using the Western Blotting. Results: Compared to the control group, the levels of serum ephrinB2 in patients were significantly elevated (p < 0.001). Moreover, the plasma EphrinB2 levels were positively correlated with white blood cell counts (r = 0.204, p = 0.018), neutrophil counts (r = 0.174, p = 0.045), and neutrophil-to-lymphocyte ratio (NLR) (r = 0.223, p = 0.009). Furthermore, the AUCs of plasma ephrinB2 level, NLR, and their combination as predictors for amputation events within 30 months after lower extremity PAD endovascular revascularization were 0.659, 0.730 and 0.811. In the high-ephrinB2 group, the incidence of amputation events within 30 months after endovascular revascularization was higher. Conclusions: Plasma EphrinB2 levels may be linked to lower extremity PAD development, inflammation, and postoperative amputation. Combining EphrinB2 and NLR can improve amputation prediction accuracy after endovascular revascularization in lower extremity PAD patients.