Objective To analyze the characteristics of nystagmus during the Dix-Hallpike and Roll tests in patients with benign paroxysmal positional vertigo (BPPV) using three-dimensional videonystagmography (3D-VNG), in order to to optimize diagnostic and therapeutic strategies of BPPV. Methods A retrospective analysis was conducted on 68 patients with posterior semicircular canal (PSC)-BPPV and 26 patients with horizontal semicircular canal (HSC)-BPPV. Nystagmus data obtained from 3D-VNG were reviewed for all patients, with a focus on the eye movement components during the Dix-Hallpike test in PSC-BPPV patients and the Roll test in HSC-BPPV patients. The direction and reversal rates of the vertical, horizontal, and torsional components were recorded and analyzed. Results All PSC-BPPV patients exhibited highly consistent three-dimensional nystagmus characteristics during the Dix-Hallpike test: vertical nystagmus was uniformly upward, torsional nystagmus was predominantly clockwise in left-side BPPV patients (17/23) and counterclockwise in right-side BPPV patients (44/45), while the horizontal component was mostly directed contralaterally (50/68); upon transitioning from the head-hanging to the sit-up position, vertical nystagmus components in all patients reversed, and torsional and horizontal nystagmus components reversed in approximately 50.0% or more patients. Among HSC-BPPV patients, right-side BPPV patients all showed right-beating (geotropic) horizontal nystagmus with predominantly upward vertical component (16/19), while most left-side BPPV patients showed left-beating horizontal nystagmus (6/7) with predominantly downward vertical component (6/7). During head rotation toward the healthy side, most (25/26) HSC-BPPV patients exhibited a reversal in the horizontal nystagmus direction, reduced intensity compared to the affected side, with a reversal in vertical components in 3 patients, and atypical torsional components. Conclusions 3D-VNG could precisely quantitative analyze three-dimensional features of nystagmus in BPPV patients, improve diagnostic accuracy in canal and side localization, particularly in PSC-BPPV patients.

The diagnosis of hematological disorders is currently established from the combined results of different tests, including those assessing morphology (M), immunophenotype (I), cytogenetics (C), and molecular biology (M) (collectively known as the MICM classification). In this workflow, most of the results are interpreted manually (i.e., by a human, without automation), which is expertise-dependent, labor-intensive, time-consuming, and with inherent interobserver variability. Also, with advances in instruments and technologies, the data is gaining higher dimensionality and throughput, making additional challenges for manual analysis. Recently, artificial intelligence (AI) has emerged as a promising tool in clinical hematology to ensure timely diagnosis, precise risk stratification, and treatment success. In this review, we summarize the current advances, limitations, and challenges of AI models and raise potential strategies for improving their performance in each sector of the MICM pipeline. Finally, we share perspectives, highlight future directions, and call for extensive interdisciplinary cooperation to perfect AI with wise human-level strategies and promote its integration into the clinical workflow.

Lactylation (Kla), a protein post-translational modification characterized by the covalent conjugation of lactyl groups to lysine residues in proteins, is widely present in living organisms. Since its discovery in 2019, it has attracted much attention for its role in regulating major pathological processes such as tumorigenesis, neurodegenerative diseases, and cardiovascular diseases. By mediating core biological processes such as signal transduction, epigenetic regulation, and metabolic homeostasis, lactylation contributes to disease progression. However, the lactylation donor lactyl-CoA has a low intracellular concentration, and the specific enzyme catalyzing lactylation is not yet clear, which has become an urgent issue in lactate research. A groundbreaking study in 2024 found that alanyl-transfer t-RNA synthetase 1/2 (AARS1/2), members of the aminoacyl-tRNA synthetase (aaRS) family, can act as protein lysine lactate transferases, modifying histones and metabolic enzymes directly with lactate as a substrate, without relying on the classical substrate lactyl-CoA, promoting a new stage in lactate research. Although exercise significantly increases lactate levels in the body and can induce changes in lactylation in multiple tissues and cells, the regulation of lactylation by exercise is not entirely consistent with lactate levels. Research has found that high-intensity exercise can induce upregulation of lactate at 37 lysine sites in 25 proteins of adipose tissue, while leading to downregulation of lactate at 27 lysine sites in 22 proteins. The level of lactate is not the only factor regulating lactylation through exercise. We speculate that the lactate transferase AARS1/2 play an important role in the process of lactylation regulated by exercise, and AARS1/2 should also be regulated by exercise. This review introduces the molecular biology characteristics, subcellular localization, and multifaceted biological functions of AARS, including its canonical roles in alanylation and editing, as well as its newly identified lactate transferase activity. We detail the discovery of AARS1/2 as lactylation catalysts and the specific process of them as lactate transferases catalyzing protein lactylation. Furthermore, we discuss the pathophysiological significance of AARS in tumorigenesis, immune dysregulation, and neuropathy, with a focus on exploring the expression regulation and possible mechanisms of AARS through exercise. The expression of AARS in skeletal muscle regulated by exercise is related to exercise time and muscle fiber type; the skeletal muscle AARS2 upregulated by long-term and high-intensity exercise catalyzes the lactylation of key metabolic enzymes such as pyruvate dehydrogenase E1 alpha subunit (PDHA1) and carnitine palmitoyltransferase 2 (CPT2), reducing exercise capacity and providing exercise protection; physiological hypoxia caused by exercise significantly reduces the ubiquitination degradation of AARS2 by inhibiting its hydroxylation, thereby maintaining high levels of AARS2 protein and exerting lactate transferase function; exercise induced lactate production can promote the translocation of AARS1 cytoplasm to the nucleus, exert lactate transferase function upon nuclear entry, regulate histone lactylation, and participate in gene expression regulation; exercise induced lactate production promotes direct interactions between AARS and star molecules such as p53 and cGAS, and is widely involved in the occurrence and development of tumors and immune diseases. Elucidating the regulatory mechanism of exercise on AARS can provide new ideas for improving metabolic diseases and promote health through exercise.

This study identified 8 members including NjBIN2 of the GSK3 family in Nardostachys jatamansi by bioinformatics analysis. Moreover, the phylogenetic tree revealed that the GKS3 family members of N. jatamansi had a close relationship with those of Arabidopsis. RT-qPCR results showed that NjBIN2 presented a tissue-specific expression pattern with the highest expression in roots, suggesting that NjBIN2 played a role in root growth and development. In addition, the application of epibrassinolide or the brassinosteroid(BR) synthesis inhibitor(brassinazole) altered the expression pattern of NjBIN2 and influenced the photomorphogenesis(cotyledon opening) and root development of N. jatamansi, which provided direct evidence about the functions of NjBIN2. In conclusion, this study highlights the roles of BIN2 in regulating the growth and development of N. jatamansi by analyzing the expression pattern and biological function of NjBIN2. It not only enriches the understanding about the regulatory mechanism of the growth and development of N. jatamansi but also provides a theoretical basis and potential gene targets for molecular breeding of N. jatamansi with improved quality in the future.
Brassinosteroids/metabolism* ; Steroids, Heterocyclic/metabolism* ; Gene Expression Regulation, Plant/drug effects* ; Plant Proteins/metabolism* ; Phylogeny ; Nardostachys/metabolism* ; Plant Growth Regulators/pharmacology* ; Plant Roots/drug effects*

Researchers commonly use cyclization recombination enzyme/locus of X-over P1 (Cre/loxP) technology-based conditional gene knockouts of model mice to investigate the functional roles of genes of interest in Sertoli and Leydig cells within the testis. However, the shortcomings of these genetic tools include high costs, lengthy experimental periods, and limited accessibility for researchers. Therefore, exploring alternative gene silencing techniques is of great practical value. In this study, we employed adeno-associated virus (AAV) as a vector for gene silencing in Sertoli and Leydig cells. Our findings demonstrated that AAV serotypes 1, 8, and 9 exhibited high infection efficiency in both types of testis cells. Importantly, we discovered that all three AAV serotypes exhibited exquisite specificity in targeting Sertoli cells via tubular injection while demonstrating remarkable selectivity in targeting Leydig cells via interstitial injection. We achieved cell-specific knockouts of the steroidogenic acute regulatory ( Star ) and luteinizing hormone/human chorionic gonadotropin receptor (Lhcgr) genes in Leydig cells, but not in Sertoli cells, using AAV9-single guide RNA (sgRNA)-mediated gene editing in Rosa26-LSL-Cas9 mice. Knockdown of androgen receptor ( Ar ) gene expression in Sertoli cells of wild-type mice was achieved via tubular injection of AAV9-short hairpin RNA (shRNA)-mediated targeting. Our findings offer technical approaches for investigating gene function in Sertoli and Leydig cells through AAV9-mediated gene silencing.
Animals ; Male ; Leydig Cells/metabolism* ; Mice ; Dependovirus/genetics* ; Sertoli Cells/metabolism* ; Gene Silencing ; Genetic Vectors ; Testis/cytology*

OBJECTIVE: To screen factors affecting the prognosis of chronic myeloid leukemia (CML) patients, and construct a nomogram model for event-free survival (EFS). METHODS: To screen out meaningful variables by univariate and multivariate Cox regression analysis in CML patients, and construct a nomogram model using R software. The nomogram was validated using consistency index (C-index), receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), calibration curve, decision curve analysis (DCA), and risk stratification analysis. RESULTS: This study analyzed data from 116 CML patients. Univariate and multivariate Cox regression analysis demonstrated that age, peripheral blood basophil percentage, BCR-ABL1 ^IS at 3 months, and red blood cell distribution width (RDW) were independent prognostic factors of EFS. Subsequently, a nomogram was constructed based on the above predictors. The C-index of the nomogram was 0.733(95%CI : 0.676-0.790). The AUC values for predicting 1-, 3-, and 5-year EFS rate were 0.765, 0.855, and 0.827, respectively. The results of the calibration curve and DCA curve showed that the predictive model had good consistency, as well as strong clinical utility. The patients were stratified into high-risk group and low-risk group based on the total score of the model, there was a significant difference in EFS between the two groups (P < 0.001). CONCLUSION Age, peripheral blood basophil percentage, BCR-ABL1 ^IS at 3 months, and RDW were associated with the prognosis of CML patients. The nomogram model constructed in this study can accurately predict the prognostic status of CML patients, but its widespread application still requires external and prospective validation.
Nomograms ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/mortality* ; Proportional Hazards Models ; Erythrocyte Indices ; Risk Assessment/methods* ; Fusion Proteins, bcr-abl/genetics* ; Basophils ; Leukocyte Count ; Humans

Bacterial infection is a major threat to global public health, and can cause serious diseases such as bacterial skin infection and foodborne diseases. It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time. In this work, we developed a 4-mercaptophenylboronic acid gold nanoparticles (4-MPBA-AuNPs)-functionalized hydrogel microneedle (MPBA-H-MN) for bacteria detection in skin interstitial fluid. MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min. Surface enhanced Raman spectroscopy (SERS) detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria. Overall, the capture efficiency of this method exceeded 50%. In the concentration range of 1 × 10⁷ to 1 × 10¹⁰ colony-forming units/mL (CFU/mL), the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration. Using random forest (RF)-based machine learning, bacteria were effectively distinguished with an accuracy of 97.87%. In addition, the harmless disposal of used MNs by photothermal ablation was convenient, environmentally friendly, and inexpensive. This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.

OBJECTIVE: To compare the efficacy and safety of intravenous colistin sulfate combined with nebulized inhalation versus intravenous monotherapy for pulmonary infections caused by carbapenem-resistant organism (CRO). METHODS: A multicenter retrospective cohort study was conducted. Clinical data were collected from patients admitted to the intensive care unit (ICU) of 10 tertiary class-A hospitals in Henan Province between July 2021 and May 2023, who received colistin sulfate for CRO pulmonary infections. Data included baseline characteristics, inflammatory markers [white blood cell count (WBC), neutrophil count (NEU), procalcitonin (PCT), C-reactive protein (CRP)], renal function indicators [serum creatinine (SCr), blood urea nitrogen (BUN)], life support measures, anti-infection regimens, clinical efficacy, microbiological clearance rate, and prognostic outcomes. Patients were divided into two groups: intravenous group (colistin sulfate monotherapy via intravenous infusion) and combination group ((intravenous infusion combined with nebulized inhalation of colistin sulfate). Changes in parameters before and after treatment were analyzed. RESULTS: A total of 137 patients with CRO pulmonary infections were enrolled, including 89 in the intravenous group and 48 in the combination group. Baseline characteristics, life support measures, daily colistin dose, and combination regimens (most commonly colistin sulfate plus carbapenems in both groups) showed no significant differences between two groups. The combination group exhibited higher clinical efficacy [77.1% (37/48) vs. 59.6% (52/89)] and microbiological clearance rate [60.4% (29/48) vs. 39.3% (35/89)], both P < 0.05. Pre-treatment inflammatory and renal parameters showed no significant differences between two groups. Post-treatment, the combination group showed significantly lower WBC and CRP [WBC (×10⁹/L): 8.2±0.5 vs. 10.9±0.6, CRP (mg/L): 14.0 (5.7, 26.6) vs. 52.1 (24.4, 109.6), both P < 0.05], whereas NEU, PCT, SCr, and BUN levels showed no significant between two groups. ICU length of stay was shorter in the combination group [days: 16 (10, 25) vs. 21 (14, 29), P < 0.05], although mechanical ventilation duration and total hospitalization showed no significant differences between two groups. CONCLUSIONS Intravenous colistin sulfate combined with nebulized inhalation improved clinical efficacy and microbiological clearance in CRO pulmonary infections with an acceptable safety profile.
Humans ; Colistin/therapeutic use* ; Retrospective Studies ; Administration, Inhalation ; Anti-Bacterial Agents/therapeutic use* ; Carbapenems/pharmacology* ; Male ; Female ; Middle Aged ; Gram-Negative Bacteria/drug effects* ; Aged ; Treatment Outcome ; Respiratory Tract Infections/drug therapy*

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.