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.

Objective: To explore the influencing factors of incident caries at age 5 among caries-free 3-year-old children in Beijing, construct a machine learning prediction model based on oral health behavioral data, and provide a scientific basis and practical tool for early risk identification, stratified prevention and control, and home-kindergarten-medical collaborative intervention of incident dental caries in preschool children. Methods: This study has been reviewed and approved by the Medical Ethics Committee, and written informed consent was obtained from the guardians of the study participants and their guardians. Children with complete baseline data at age 3 and follow-up data at age 5 from Beijing public oral health programs were included. Oral examinations were conducted according to World Health Organization diagnostic criteria, and questionnaires were completed by guardians. Risk factors were screened by Logistic regression. The total sample was randomly divided into a test set (20%) and a validation set (80%). Five-fold cross-validation was performed on the validation set for model training and tuning, and the final model performance was evaluated on the test set. Four machine learning models—decision tree, random forest, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)—were constructed. Model performance was evaluated using the area under the curve (AUC), accuracy, and specificity. Shapley Additive Explanations (SHAP) was used for model interpretation. Results: The incidence of incident caries for 3 372 5-year-old children in Beijing was 50.96%. Multivariate logistic regression showed that parental caries, sleeping with milk, frequent feeding at night, no postprandial cleaning, high sugar intake, insufficient bedtime tooth brushing, and non-fluoride toothpaste use were significant risk factors (P < 0.05). Although all four machine learning models performed well, the XGBoost model performed the best (AUC = 0.806). Feature importance and SHAP analysis indicated that the frequency of bedtime tooth brushing, the frequency of candy consumption, and parental caries status were the top three predictors. Conclusion The XGBoost model based on oral health behaviors at age 3 can accurately predict the risk of incident caries in 5-year-old children in Beijing. Bedtime tooth brushing, sugar control, and parental oral health management are key points for caries prevention in preschool children.

ObjectiveStroke remains the leading cause of acquired disability in adults worldwide, imposing a substantial socioeconomic burden on patients, families, and healthcare systems. Among the various neurological deficits caused by stroke, motor dysfunction——particularly contralateral hemiplegia——is the most common and debilitating consequence, and it predominantly results from damage to the cortical motor conduction pathways. When motor cortex neurons or their projecting fibers are damaged, the distal axons and their associated myelin sheaths undergo a series of progressive, programmed degeneration, fragmentation, and eventual phagocytic clearance. This pathological process is termed Wallerian degeneration (WD). However, the temporal progression of WD following ischemic stroke and the associated alterations in the local glial microenvironment remain incompletely understood. The present study was designed to systematically elucidate the time course of corticospinal tract (CST) axonal WD after ischemic stroke in mice, and to simultaneously characterize the dynamic pathological changes of astrocytes, microglia, oligodendrocyte lineage cells, and myelinating oligodendrocytes during the WD process. MethodsEight-week-old male C57BL/6J mice were randomly assigned to control and ischemic stroke groups. A focal cortical ischemic stroke model was established in the right sensorimotor cortex using the photothrombotic method. This method induces localized intravascular thrombosis in the target cortical region through precisely controlled interaction between the photosensitizer and laser light of specific wavelength. At day 1 post‑surgery, 2,3,5-triphenyltetrazolium chloride (TTC) staining was performed to evaluate infarct volume, hematoxylin and eosin (HE) staining for histopathological examination, and Nissl staining for assessment of neuronal injury. For axonal degeneration time-course analysis, rAAV-CAG-mCherry anterograde viral tracing was employed to specifically label CST neurons. Cervical spinal cord sections at the CST region were collected at day 3, 5, 7, 14, and 60 post-injury. Morphological changes of mCherry-positive CST fibers were observed under fluorescence microscopy, and the fluorescence signal area fraction within the defined region was quantitatively analyzed to evaluate the dynamic process of axonal degeneration. For glial response assessment, immunofluorescence staining against Iba1 (microglia), GFAP (astrocytes), Olig2 (oligodendrocyte lineage cells), and APC (myelinating oligodendrocytes) was performed at day 7, 14, and 60 post‑surgery. The numbers of positive cells were counted to quantitatively analyze the dynamic changes in each glial population at different time points after ischemia, thereby revealing the evolution of the glial microenvironment during WD. ResultsThe photothrombotic method stably and reliably established an ischemic brain injury model confined to the sensorimotor cortex. Viral tracing revealed that the proportion of mCherry‑positive CST fibers was significantly reduced at day 7 after ischemic injury to the neuronal soma. Immunofluorescence staining demonstrated that during WD, the numbers of microglia and astrocytes in the CST region were significantly increased, whereas the numbers of oligodendrocyte lineage cells and myelinating oligodendrocytes showed no significant changes. ConclusionWD of CST axons is observed at day 7 post-ischemic stroke in a delayed manner. This degenerative process selectively activates microglia and astrocytes, while leaving the number of oligodendrocyte lineage cells largely unaffected.

Objective:The relationship between benign prostatic hyperplasia(BPH)and the oxidative balance score(OBS)will be discussed in this study.Methods:The clinical data on 16 dimensions of diet and 4 dimensions of lifestyle from the National Health and Nutrition Examination Survey(NHANES)from 2001 to 2008 were used to calculate OBS.We considered BPH as the out-come and investigated the linear and nonlinear relationships between the two.Additionally,subgroup analyses and interaction tests were conducted as well.Furthermore,the methods of machine learning including XGBoost,support vector machine(SVM)and naive Bayes(NB)were used to establish a predictive model for BPH.Results:Higher OBS was consistently associated with an increased preva-lence of BPH,with Restricted Cubic Splines highlighting a significant positive nonlinear association(P=0.015).Subgroup analyses revealed differences and interactive relationships based on alcohol consumption.Among the seven machine learning models that we in-cluded the OBS score in,the XGBoost model emerged as the best,with an AUC value of 0.769.Conclusion:There is a significant association between OBS and the prevalence of BPH in the American population,which provides a valuable insight for further diagnosis and research of the disease.

Objective:To explore the effect of recombinant human brain natriuretic peptide(rhBNP)combined with dopamine on cystatin C(CysC),homocysteine(Hcy)and cardiac function in patients with severe heart failure(HF).Methods:This randomized controlled study enrolled 110 severe HF patients admitted in Aerospace Center Hospital between December 2021 and December 2022.They were divided into control group(n=55,nitroglycerin combined dopamine)and combined treatment group(n=55,rhBNP combined dopamine).Each group received corresponding therapy based on basic treatment for one week.Therapeutic effect,levels of CysC,Hcy,left ventric-ular end-systolic diameter(LVESd),left ventricular end-diastolic diameter(LVEDd),left ventricular ejection fraction(LVEF),and incidence of adverse reactions were compared between two groups.Results:Compared with patients in control group,those in combined treatment group had significant higher total effective rate(81.82％vs.58.18％)and LVEF[(54.68±4.59)％vs.(44.79±4.37)％],and significant lower CysC[(1.02±0.19)mg/L vs.(1.40±0.21)mg/L],Hcy[(15.98±2.17)μmol/L vs.(21.05±2.82)μmol/L],LVESd[(35.13±3.51)mm vs.(41.71±3.28)mm]and LVEDd[(41.33±4.26)mm vs.(50.51±4.37)mm](P＜0.01 all).There was no significant difference in total incidence of adverse reactions between two groups(16.36％vs.7.27％,P=0.180).Conclusion:rhBNP combined with dopamine could significantly improve the clinical therapeutic effect,im-prove levels of CysC,Hcy and cardiac function with good safety in the treatment of severe HF.

Objective To explore the effect and mechanism of Slc1a2 overexpression on cognitive dysfunction in sleep-deprived mice.Methods A total of 130 mice were divided into five groups:normal sleep(NS),NS+ov-Slc1a2,sleep deprivation(SD),SD+ov-NC,and SD+ov-Slc1a2,with 26 mice in each group.The SD mice model was established using an automatic system based on a rotating rod,and overexpress Slc1a2 adenovirus was injected into the prefrontal cortex(PFC).Immunofluorescence and Western blotting were used to detect the expression of Slc1a2 in the mouse PFC.Electrophysiological tests were used to evaluate non-rapid eye movement(NREM)sleep time,rapid eye movement(REM)sleep time,and wakefulness time in mice.Real-time quantitative PCR was used to detect the expression of glutamate(Glu)and gamma-aminobutyric acid(GABA)metabolic enzymes in the mouse PFC.Whole-cell patch-clamp recording was used to detect the frequency and amplitude of miniature excitatory postsynaptic currents(mEPSC)in mouse PFC.Immunofluorescence was used to detect the proportion of GABA-positive cells in the mouse PFC.The C11-BODIPY fluorescent probe was used to detect lipid reac-tive oxygen species(ROS)levels in mouse PFC.Commercial kits were used to detect Fe2+and malondialdehyde(MDA)levels in the mouse PFC.Cognitive function in mice was evaluated using the open field,novel object recognition,and Y-maze tests.Results Compared with the NS group,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index increased significantly,while wakefulness time decreased significantly in the NS+ov-Slc1a2 group(all P＜0.05).The percentage of Slc1a2+GFAP+cells,expression of Slc1a2 protein,expression of Glul,Slc6a1,and Abat mRNA,frequency and amplitude of mEPSC,and proportion of GABA-positive cells in the PFC increased significantly,whereas lipid ROS,Fe2+,and MDA levels decreased significantly(all P＜0.05).Compared with the NS group,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index of the SD group and the SD+ov-NC group were significantly decreased,whereas wakefulness time was significantly increased(all P＜0.05).The percentage of Slc1a2+GFAP+cells,expression of Slc1a2 protein,expression of Glul,Slc6a1,and Abat mRNA,frequency and amplitude of mEPSC,and proportion of GABA-positive cells in the mouse PFC decreased significantly,whereas lipid ROS,Fe2+,and MDA levels increased significantly(all P＜0.05).Compared with the SD and SD+ov-NC groups,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index of the SD+ov-Slc1a2 group increased significantly,whereas the wakeful-ness time decreased significantly(all P＜0.05).The percentage of Slc1a2+GFAP+cells,the expression of Slc1a2 protein,the expression of Glul,Slc6a1,and Abat mRNA,the frequency and amplitude of mEPSC,and the proportion of GABA-positive cells in the mouse PFC increased significantly,whereas lipid ROS,Fe2+,and MDA levels decreased significantly(all P＜0.05).Conclusion Ectopic overexpres-sion of Slc1a2 in the PFC can improve sleep disorders in SD mice,reduce the damage caused by SD to excitatory synaptic transmission and GABAergic neuron function in the PFC,and alleviate cognitive impairment and anxiety-like behavior in these mice.Its mechanism may be related to the improvement of Glu/GABA metabolic imbalance in the PFC and inhibition of ferroptosis.

Vaccine immunization is the most effective and cost-efficient method for infectious disease prevention and control.Since the outbreak of novel coronavirus pneumonia(caused by the novel coronavirus,COVID-19)at the end of 2019,third generation mRNA nucleic acid vaccines has been applied to stop viral spread.mRNA vaccines,rather than relying on the immune activation mode of traditional vaccines,are an innovative breakthrough using the body's own cells to produce antigens,thereby activating double specific immunity,forming immune memory,and providing more lasting specific immunity.Com-pared with the traditional first-generation(inactivated)and second-generation(genetically engineered)vaccines,mRNA vac-cines,because of the advantages provided by this platform,play important roles in the prevention and control of major sudden infectious diseases.Consequently,mRNA vaccines were the world's first COVID-19 vaccines to be applied clinically,thus ser-ving as a barometer in the field of vaccine research and development.Herein,the molecular design and presentation of mRNA vaccines,and the molecular mechanisms of their activation of the immune response are reviewed,to provide a theoretical basis for future application of novel mRNA vaccines in the prevention and control of animal infectious diseases.