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.

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.

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

ObjectiveTo investigate whether there are differences in the efficacy of Gegen Qinliantang with different contents of Puerariae Lobatae Radix on the acute enteritis （AE） model mice and provide a scientific basis for the interpretation of Gegen Qinliantang in the treatment of "Xie Re Li". MethodsA total of 112 male BALB/c mice were randomly divided into a blank group，model group，single Puerariae Lobatae Radix group，non-Puerariae Lobatae Radix group，regular dose Gegen Qinliantang group （regular dose group），half-dose Puerariae Lobatae Radix group，and doubled-dose Puerariae Lobatae Radix group， with 16 mice in each group. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of the colon tissue. Western blot was employed to detect the expression of ZO-1 （a protein in the tight junction） and Occludin in the colon tissue， as well as the changes of tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）. ResultsCompared with the blank group，the DAI scores of the mice in the model group were significantly higher （P<0.05），and the histopathological sections of their colon tissues showed mucosal damage，glandular atrophy，disordered arrangement，and a large number of inflammatory cells infiltration，and the expression of ZO-1 and Occludin proteins in their colon tissues was significantly down-regulated （P<0.05，P<0.01）. The expression of inflammatory factors TNF-α and IL-1β was significantly up-regulated （P<0.05，P<0.01）. Compared with the model group，the DAI scores of mice in all dosing groups decreased significantly （P<0.05），with the most significant effect in the regular dose group. After 7 d of drug administration，the regular dose group had the best impact on the repair of colonic mucosa in the AE mouse model. The regular dose group significantly down-regulated the expression of TNF-α （P<0.05） and significantly up-regulated the expression of ZO-1 protein （P<0.05）. The doubled-dose Puerariae Lobatae Radix group significantly down-regulated the expression of IL-1β protein （P<0.01），and there was no significant difference between all dosing groups and the model group in terms of the expression of Occludin protein. After 14 d of drug administration，the best effect on the repair of colonic mucosa in the AE mouse model was observed in the doubled dose Puerariae Lobatae Radix group. All groups except the non-Puerariae Lobatae Radix group significantly down-regulated the expression of TNF-α （P<0.01）. Meanwhile，the regular dose group and doubled-dose Puerariae Lobatae Radix group significantly elevated the expression level of Occludin protein （P<0.01）. The doubled-dose Puerariae Lobatae Radix group also significantly inhibited the expression of IL-1β protein （P<0.05） and up-regulated ZO-1 protein expression （P<0.05）. ConclusionGegen Qinliantang can reduce the pathological damage of colon tissue， protect the barrier function and structure of intestinal epithelial cells， and reduce the expression of inflammatory factors， so as to achieve the therapeutic effect of AE model mice. When comparing the therapeutic efficacy of Gegen Qinliantang containing different Gegen contents， Gegen Qinliantang with the proportion of the original formula of Zhongjing was the most effective in AE model mice.

ObjectiveTo investigate whether there are differences in the efficacy of Gegen Qinliantang with different contents of Puerariae Lobatae Radix on the acute enteritis （AE） model mice and provide a scientific basis for the interpretation of Gegen Qinliantang in the treatment of "Xie Re Li". MethodsA total of 112 male BALB/c mice were randomly divided into a blank group，model group，single Puerariae Lobatae Radix group，non-Puerariae Lobatae Radix group，regular dose Gegen Qinliantang group （regular dose group），half-dose Puerariae Lobatae Radix group，and doubled-dose Puerariae Lobatae Radix group， with 16 mice in each group. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of the colon tissue. Western blot was employed to detect the expression of ZO-1 （a protein in the tight junction） and Occludin in the colon tissue， as well as the changes of tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）. ResultsCompared with the blank group，the DAI scores of the mice in the model group were significantly higher （P<0.05），and the histopathological sections of their colon tissues showed mucosal damage，glandular atrophy，disordered arrangement，and a large number of inflammatory cells infiltration，and the expression of ZO-1 and Occludin proteins in their colon tissues was significantly down-regulated （P<0.05，P<0.01）. The expression of inflammatory factors TNF-α and IL-1β was significantly up-regulated （P<0.05，P<0.01）. Compared with the model group，the DAI scores of mice in all dosing groups decreased significantly （P<0.05），with the most significant effect in the regular dose group. After 7 d of drug administration，the regular dose group had the best impact on the repair of colonic mucosa in the AE mouse model. The regular dose group significantly down-regulated the expression of TNF-α （P<0.05） and significantly up-regulated the expression of ZO-1 protein （P<0.05）. The doubled-dose Puerariae Lobatae Radix group significantly down-regulated the expression of IL-1β protein （P<0.01），and there was no significant difference between all dosing groups and the model group in terms of the expression of Occludin protein. After 14 d of drug administration，the best effect on the repair of colonic mucosa in the AE mouse model was observed in the doubled dose Puerariae Lobatae Radix group. All groups except the non-Puerariae Lobatae Radix group significantly down-regulated the expression of TNF-α （P<0.01）. Meanwhile，the regular dose group and doubled-dose Puerariae Lobatae Radix group significantly elevated the expression level of Occludin protein （P<0.01）. The doubled-dose Puerariae Lobatae Radix group also significantly inhibited the expression of IL-1β protein （P<0.05） and up-regulated ZO-1 protein expression （P<0.05）. ConclusionGegen Qinliantang can reduce the pathological damage of colon tissue， protect the barrier function and structure of intestinal epithelial cells， and reduce the expression of inflammatory factors， so as to achieve the therapeutic effect of AE model mice. When comparing the therapeutic efficacy of Gegen Qinliantang containing different Gegen contents， Gegen Qinliantang with the proportion of the original formula of Zhongjing was the most effective in AE model mice.

BACKGROUND: Growing evidence suggests that long non-coding RNAs (lncRNAs) exert pivotal roles in fostering chemoresistance across diverse tumors. Nevertheless, the precise involvement of lncRNAs in modulating chemoresistance within the context of gallbladder cancer (GBC) remains obscure. This study aimed to uncover how lncRNAs regulate chemoresistance in gallbladder cancer, offering potential targets to overcome drug resistance. METHODS: To elucidate the relationship between gemcitabine sensitivity and small nucleolar RNA host gene 1 ( SNHG1 ) expression, we utilized publicly available GBC databases, GBC tissues from Renji Hospital collected between January 2017 and December 2019, as well as GBC cell lines. The assessment of SNHG1, miR-23b-3p, and phosphatase and tensin homolog (PTEN) expression was performed using in situ  hybridization, quantitative real-time polymerase chain reaction, and western blotting. The cell counting kit-8 (CCK-8) assay was used to quantify the cell viability. Furthermore, a GBC xenograft model was employed to evaluate the impact of SNHG1 on the therapeutic efficacy of gemcitabine. Receiver operating characteristic (ROC) curve analyses were executed to assess the specificity and sensitivity of SNHG1. RESULTS: Our analyses revealed an inverse correlation between the lncRNA SNHG1 and gemcitabine resistance across genomics of drug sensitivity in cancer (GDSC) and Gene Expression Omnibus (GEO) datasets, GBC cell lines, and patients. Gain-of-function investigations underscored that SNHG1 heightened the gemcitabine sensitivity of GBC cells in both in vitro and in vivo  settings. Mechanistic explorations illuminated that SNHG1 could activate PTEN -a commonly suppressed tumor suppressor gene in cancers-thereby curbing the development of gemcitabine resistance in GBC cells. Notably, microRNA (miRNA) target prediction algorithms unveiled the presence of miR-23b-3p binding sites within SNHG1 and the 3'-untranslated region (UTR) of PTEN . Moreover, SNHG1 acted as a sponge for miR-23b-3p, competitively binding to the 3'-UTR of PTEN , thereby amplifying PTEN expression and heightening the susceptibility of GBC cells to gemcitabine. CONCLUSION The SNHG1/miR-23b-3p/PTEN axis emerges as a pivotal regulator of gemcitabine sensitivity in GBC cells, holding potential as a promising therapeutic target for managing GBC patients.
Humans ; Deoxycytidine/pharmacology* ; PTEN Phosphohydrolase/genetics* ; Gemcitabine ; RNA, Long Noncoding/metabolism* ; MicroRNAs/genetics* ; Gallbladder Neoplasms/genetics* ; Cell Line, Tumor ; Animals ; Mice ; Drug Resistance, Neoplasm/genetics* ; Mice, Nude ; Antimetabolites, Antineoplastic ; Gene Expression Regulation, Neoplastic

Process analytical technology(PAT) is a key means for digital transformation and upgrading of the traditional Chinese medicine(TCM) manufacturing process, serving as an important guarantee for consistent and controllable TCM product quality. Near-infrared(NIR) spectroscopy has become the core technology for measuring the TCM manufacturing process. By incorporating NIR spectroscopy into PAT and starting from the construction of a smart platform for the TCM manufacturing process, this paper systematically described the development history and innovative application of the combination of NIR spectroscopy with chemometrics in measuring the TCM manufacturing process by the research team over the past two decades. Additionally, it explored the application of a validation method based on accuracy profile(AP) in the practice of NIR spectroscopy. Furthermore, the software development progress driven by NIR spectroscopy supported by modeling technology was analyzed, and the prospect of integrating NIR spectroscopy in smart factory control platforms was exemplified with the construction practices of related platforms. By integrating with the smart platform, NIR spectroscopy could improve production efficiency and guarantee product quality. Finally, the prospect of the smart platform application in measuring the TCM manufacturing process was projected. It is believed that the software development for NIR spectroscopy and the smart manufacturing platform will provide strong technical support for TCM digitalization and industrialization.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/analysis* ; Software ; Medicine, Chinese Traditional ; Quality Control