Animal experimentation constitutes a critical link between basic research and clinical application, making its research quality and translational efficiency paramount. Although considerable progress has been made in standardizing operational procedures and ethical guidelines, the standardization of outcome evaluation systems has significantly lagged, creating a key bottleneck that constrains the quality of biomedical research and evidence synthesis. This deficiency is manifested by pronounced heterogeneity in outcome selection across similar studies, incomplete methodological reporting, and disparate criteria for result interpretation, which severely impairs the comparability of findings and the evidence integration. To cope with this challenge, this paper systematically introduces a mature methodological tool from clinical research–the core outcome set (COS)–and explores its construction strategies and application potential in the field of animal experimentation. Given the extensive diversity of animal experiments, a pragmatic strategy of "focusing on key areas, implementing phased pilots, and promoting gradual expansion" should be adopted. This approach prioritizes the development of domain-specific COS for disease areas characterized by high research volume, urgent translational needs, and well-established animal models. A multi-source integration pathway for COS development is detailed, comprising systematic literature searches, methodological appraisals, and expert consensus, with the feasibility of leveraging artificial intelligence (AI) to enhance efficiency also being examined. The development and promotion of such COS are not intended to restrict scientific exploration; rather, they aim to establish a new, tiered evaluation paradigm consisting of "core outcomes" (mandatory), "recommended outcomes" (encouraged), and "exploratory outcomes" (optional). This framework is expected not only to enhance research quality through standardization and to adhere to the "3R" principles but also to accelerate the accumulation of high-quality evidence. This, in turn, provides a solid foundation for higher-level evidence synthesis, ultimately facilitating the effective translation of basic research findings into clinical practice and providing an essential methodological framework for scientific advancement in relevant disciplines.

This article reports a rare case of autoinflammatory disease presenting initially with skin induration and swelling after trauma as the initial manifestation, followed by progressive limb weakness. The patient was a middle-aged female who developed skin induration and swelling after trauma, which gradually progressed to limb weakness, dysarthria and bilateral facial paralysis, accompanied by livedo reticularis of the lower extremities, diffuse skin induration of the limbs, and beaded subcutaneous nodules in the right upper limb. The patient had a susceptibility to infection since childhood and a history of chronic livedo reticularis. Skin pathological examination revealed panniculitis. A comprehensive etiological screening for special infections and autoimmune diseases was completed with an unremarkable results, and whole-exome sequencing showed no abnormal findings. Following a multidisciplinary discussion combined with RNA sequencing results, the patient was diagnosed with an autoinflammatory disease, with a suspected type Ⅰ interferonopathy. Treatment with tofacitinib resulted in gradual improvement of clinical symptoms. This case highlights the importance of detailed medical history collection, systematic physical examination and multidisciplinary collaborative diagnosis and treatment, and underscores the pivotal role of molecular diagnosis in the confirmation of rare diseases. It can provide a reference for the clinical diagnosis and management of similar rare cases.

ObjectiveStroke poses a heavy burden due to its high mortality and morbidity rates. Accurate and real-time detection of lesions is pivotal for prompt clinical intervention and favorable prognosis. Electrical impedance tomography (EIT) and microwave tomography (MWT) have emerged as compelling alternatives for stroke screening, owing to their non-ionizing, non-invasive and portable nature. EIT provides information on tissue conductivity, and MWT offers high sensitivity to changes in dielectric properties. However, single-modality imaging is inherently limited, EIT suffers from low sensitivity to deep-seated tissues and severe ill-posedness of inverse problems, whereas MWT is challenged by strong nonlinearity in inverse scattering and susceptibility to modeling errors. Consequently, the clinical utility of standalone EIT or MWT for stroke diagnosis remains constrained by poor spatial resolution and imaging artifacts. To improve the accuracy and robustness of stroke imaging, a dual-modality fusion conditional denoising diffusion probabilistic model (DM-DDPM) was proposed for high-precision dual-modality image reconstruction. MethodsA dual-encoder network with a symmetric architecture and independently trained parameters was constructed to extract heterogeneous features separately from EIT boundary voltage measurements and MWT scattered field signals. Attentional feature fusion (AFF) is employed to integrate complementary information from the two modalities adaptively, generating robust fused priors that suppress redundant noise while preserving key physical characteristics. Subsequently, the fused priors are embedded into a Transformer-based diffusion model via a cross attention mechanism to guide the reverse denoising process. This approach effectively reduces artifacts and enhances the stability of conductivity distribution reconstruction. Time step embedding is introduced to enable the network to perceive the diffusion stage and further improve the accuracy of noise prediction. ResultsSimulated experiments demonstrated that DM-DDPM significantly outperforms single-modality and multi-modality networks under various noise levels. A head model simulation dataset was constructed based on COMSOL Multiphysics, and tests were carried out under 50 dB, 40 dB and 30 dB signal-to-noise ratio levels. At 30 dB, the average relative error (RE) was below 0.20, while the structural similarity index measure (SSIM) and correlation coefficient (CC) remained above 0.90 and 0.89, respectively. Compared with single-modality and multi-modality networks, artifacts were significantly reduced, lesion edges were clearer, and localization was more accurate. The model maintains high reconstruction quality and strong robustness for single, double, and triple lesions simultaneously. Furthermore, physical experiments were conducted using a 16-electrode EIT system and a 16-antenna MWT system with asynchronous data acquisition. These experiments confirmed the feasibility of the method in real-world scenarios and demonstrated that it can robustly reconstruct simulated lesions despite environmental interference and measurement noise, validating its reliability for practical clinical applications. ConclusionThe proposed method effectively combines complementary dual-modality information with a conditional diffusion model. Low accuracy and poor noise resistance in single-modality imaging were effectively addressed, while the noise amplification issue caused by direct multimodal data fusion was avoided. The proposed algorithm exhibits strong anti-noise interference ability and high imaging stability in both simulation and physical experiments. Precise localization of stroke lesions with different quantities was achieved, providing a high-precision, and practical technical support for clinical stroke detection.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

BACKGROUND:At present,osteoarthritis has become a major disease affecting the quality of life of the elderly,and the therapeutic effect is poor,often focusing on preventing the disease process,and the pathogenesis of osteoarthritis is still not fully understood.Bioinformatics analysis was carried out to explore the main pathogenesis of osteoarthritis and related mechanisms of gene coding regulation. OBJECTIVE:To screen core differential genes with a major role in osteoarthritis by gene expression profiling. METHODS:Datasets were downloaded from the Gene Expression Omnibus(GEO):GSE114007,GSE117999,and GSE129147.Differential genes in the GSE114007 and GSE117999 data collections were screened using R software,performing differential genes to weighted gene co-expression network analysis.The module genes most relevant to osteoarthritis were selected to perform protein interaction analysis.Candidate core genes were selected using the cytocape software.The candidate core genes were subsequently subjected to least absolute shrinkage and selection operator regression and COX analysis to identify the core genes with a key role in osteoarthritis.The accuracy of the core genes was validated using an external dataset,GSE129147. RESULTS AND CONCLUSION:(1)A total of 477 differential genes were identified,265 differential genes associated with osteoarthritis were obtained by weighted gene co-expression network analysis,and 8 candidate core genes were identified.The least absolute shrinkage and selection operator regression analysis finally yielded a differential gene ASPM with core value that was externally validated.(2)It is concluded that abnormal gene ASPM expression screened by bioinformatics plays a key central role in osteoarthritis.

C-Reactive protein(CRP)is an important acute-phase response protein,which is widely used in the assessment of inflammation and cardiovascular disease risk,and acts as a pathogenic factor directly involved in the disease process of certain conditions.Therefore,developing immunosuppressants targeting CRP or investigating its pathogenic mechanisms is of significant importance.Most B-cell epitopes are conformational epitopes,and studying conformational epitopes is typically challenging.To date,no methods have been reported for mapping the conformational epitopes of CRP in solution.In this study,a rapid strategy was developed for studying conformational epitopes by combining hydrogen/deuterium exchange mass spectrometry(HDX-MS)with multiparametric prediction of B-cell epitopes and protein secondary structure analysis.This approach was successfully applied to the binding sites and allosteric targets of the 115 kDa full pentameric CRP and the clinically used monoclonal antibody(mAb)5A8.The results showed that the amino acid residues 84-103,138-146,and 165-173 together form the potential conformational epitopes for mAb 5A8 on CRP,while the amino acid residues 21-32 and 175-178 were identified as potential allosteric targets.The discovery of the mAb 5A8 binding sites and allosteric targets was crucial for improving clinical diagnostic capabilities.Experimental results demonstrated that this workflow allowed rapid conformational epitope mapping of CRP under near-physiological conditions,with advantages such as high speed,high sensitivity,and high throughput.

Objective:To explore the medication thinking and compatibility rules of TCM for the treatment of diabetic nephropathy (DN).Methods:Relevant journal literature of TCM for the treatment of DN was retrieved from CNKI, Wanfang Data, VIP, and CBM from January 1, 2000 to December 31, 2023, and a database was established through Excel 2016. Python 3.10 and the ancient and modern medical record cloud platform 2.3.5 were used to conduct Latent Dirichlet Allocation (LDA) topic modeling and association rule analysis to explore the thinking and compatibility rules of TCM prescriptions in the literature.Results:A total of 474 articles were included in the study, including 474 prescriptions, involving 260 kinds of Chinese materia medica, of which 40 kinds of Chinese materia medica with a frequency of ≥ 30, mainly Astragali Radix, Salviae Miltiorrhizae Radix et Rhizoma, Dioscoreae Rhizoma, Poria, and Corni Fructus, etc. The LDA topic model identified three groups of prescriptions, including four classic prescriptions: Liuwei Dihuang Pills, Taohong Siwu Decoction, Erzhi Pills, and Wuling Powder. The commonly used drug combinations extracted by association rules were: Rhizoma Alismatis - Poria, Cortex Moutan Radicis-Fructus Corni and Cortex Moutan Radicis - Rhizoma Dioscoreae.Conclusions:The main therapeutic principle of TCM in treating DN is to nourish the yin and tonify the kidney, supplemented by drugs that promoting blood circulation for removing blood stasis as well as promoting urination and draining dampness. In clinical application, modern doctors tend to use classic prescriptions such as Liuwei Dihuang Pills, Erzhi Pills, Taohong Siwu Decoction, and Wuling Powder as the basis, and modify them according to the specific conditions of patients. The LDA topic model can extract valuable prescription information from a large number of modern TCM literature, providing new perspectives and ideas for the study of clinical medication rules in TCM.

OBJECTIVE: To investigate the expression of CD19/CD73 in chronic lymphocytic leukemia (CLL) and its correlation with clinical features. METHODS: The clinical data of 60 CLL patients and 40 healthy volunteers (control group) from January 2022 to November 2023 were retrospectively analyzed. The levels of CD19 and CD73 in peripheral blood of CLL patients were measured by flow cytometry. Kaplan-Meier method was used for survival analysis. RESULTS: The hemoglobin (Hb) and CD19/CD73 levels in CLL group were significantly lower than those in control group, while CD19, CD73 and β₂-MG were significantly higher (all P <0.001). According to ROC curve analysis, the AUC value of CD19/CD73 for CLL diagnosis was 0.980 (95%CI : 0.949-1.000, P <0.05), the specificity was 92.50%, and the sensitivity was 98.30%. The CD19/CD73 level of CLL patients with splenomegaly was significantly lower than those without splenomegaly (P <0.01). There was no significant correlation between CD19/CD73 and Hb in CLL patients ( r =0.056, P >0.05). CD19/CD73 was positively correlated with β₂-MG ( r =0.837, 95%CI : 0.740 2-0.899 6, P <0.01). According to the median value (12.84) of CD19/CD73, the patients were divided into high and low expression groups. Kaplan-Meier survival analysis showed that the overall survival rate and progression-free survival rate at 18^th month in the low expression group were 87.08% and 93.25%, while those in the high expression group were 96.41% and 99.90%, respectively (both P <0.05). CONCLUSION The level of CD19/CD73 is low in CLL patients, which can be used as an auxiliary index for clinical diagnosis of CLL. CD19/CD73 is closely related to splenomegaly in CLL patients. Low expression of CD19/CD73 predicts poor prognosis.
Humans ; Leukemia, Lymphocytic, Chronic, B-Cell/metabolism* ; 5'-Nucleotidase/metabolism* ; Antigens, CD19/metabolism* ; Retrospective Studies ; Male ; Female ; Prognosis ; Middle Aged ; Aged ; Adult ; GPI-Linked Proteins

OBJECTIVE: To investigate the characteristics of central nervous system regulation in patients with refractory overactive bladder (rOAB) using resting-state functional magnetic resonance imaging (rs-fMRI), and to analyze the differences in brain function and connection between the patients and healthy population. METHODS: From May 1 to November 30, 2024, we performed rs-fMRI for 47 rOAB patients and another 47 matched healthy controls, documented relevant clinical data from all the participants and obtained their Overactive Bladder Symptom Scores (OABSS) and Overactive Bladder Questionnaire (OAB-Q) scores. Based on rs-fMRI, we compared the results of Independent Component Analysis (ICA), amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo) and degree centrality (DC) between the rOAB patients and healthy controls. RESULTS: The rOAB patients, in comparison with the healthy controls, showed dramatically higher daytime urination frequency (11.64 ± 3.85) vs (5.76 ± 0.91), nighttime urination frequency (3.72 ± 1.64) vs (0.31 ± 0.47), OABSS (8.22 ± 2.21) vs (0.64±0.78), OAB-Q1 score (20.85 ± 5.28) vs (6.78 ± 1.04), and OAB-Q2 score (45.04 ± 12.11) vs (14.51 ± 1.66) (all P<0.01). No statistically significant differences were observed in the results of ICA and ALFF between the right superior frontal and right middle frontal regions in the rOAB patients (P>0.05), but fALFF, ReHo and DC were significantly decreased in the patients compared with those in the healthy controls (P<0.01). CONCLUSION Compared with healthy population, the functions and connection of the frontal superior right and frontal middle right brain regions in rOAB patients are significantly down-regulated, which may serve as new therapeutic targets.
Humans ; Urinary Bladder, Overactive/physiopathology* ; Magnetic Resonance Imaging ; Brain/physiopathology* ; Female ; Male ; Adult ; Surveys and Questionnaires ; Case-Control Studies ; Middle Aged ; Rest ; Brain Mapping