National biological standards for antibiotics are critical components of the antibiotic quality control system and serve as reference materials for measuring and calibrating the biological activity of antibiotics. This article systematically reviews the classification, definition of potency units, and current research status of commercially available national antibiotic biological standards in China. At present, these standards can be categorized based on chemical structure, number of components, and development methods. The definition of potency units has evolved from an early “arbitrarily assigned unit” to “being represented by the mass of the antibiotic salt” and, more recently, to the current mainstream approach of “being represented by the mass of the active ingredient”. This evolution reflects a shift in quality control philosophy from primarily biological analysis to a system dominated by chemical analysis supplemented by biological methods. Current research focuses on optimizing potency determination methods, studying the unification of content and potency, and implementing dual quality control of both the potency and the ratio/content of active components in multi-component antibiotics. For complex multi-component antibiotics, the microbiological assay based on biological activity remains irreplaceable in quality control. Future efforts should emphasize further method optimization, ensuring batch-to-batch consistency of standards, and advancing precision quality control as key research priorities for antibiotic biological standards.

Aging has emerged as a cutting edge and hotspot in global life science field， with anti-aging and geriatric disease prevention and treatment becoming critical issues urgently demanding solutions in international medical communities. In the face of the challenge of accelerating global population aging， in-depth exploration of aging mechanisms and the development of effective intervention strategies hold significant scientific and clinical value. This study supported by the national key research and development program of China， employed the essence-Qi-spirit theory of Qiluo doctrine as its guiding framework， focusing on the key scientific issue of the core traditional Chinese pathogenesis of aging， namely "depletion of kidney essence， deficiency of primordial Qi， and impairment of body and spirit". The treatment principle of "tonifying the kidney to replenish essence， harmonizing Yin and Yang， warming and invigorating primordial Qi， and nourishing the body and spirit" was established. Centered on holistic aging， systemic aging， and aging-related diseases， the research integrated multidisciplinary research approaches to construct multi-modal aging models and a multi-dimensional evaluation system， and it utilized multi-omics technologies to deeply analyze aging mechanisms. By systematically reviewing historical kidney-tonifying and anti-aging formulas and combining big data with artificial intelligence technologies， an information database of anti-aging traditional Chinese medicine substance was developed to reveal the differences and synergistic effects of various treatment methods and formulas on anti-aging. Based on this treatment method， the research integrated two millennia of kidney-tonifying medicinal experience to develop the innovative anti-aging traditional Chinese medicine， namely Bazhi Bushen capsules. It was validated that this capsule can delay holistic and systemic aging through multiple targets and mechanisms， thereby elucidating the scientific connotation of the essence-Qi-spirit theory of Qiluo doctrine in guiding anti-aging research from multiple dimensions and providing robust support for leveraging the advantages of traditional Chinese medicine to occupy the commanding heights of international anti-aging research.

Osteoarthritis (OA), a highly prevalent degenerative joint disease worldwide, is defined by articular cartilage degradation, abnormal bone remodeling, and persistent chronic inflammation. It severely compromises patients’ quality of life, and currently, there is no radical cure. Abnormal mechanical stress is widely regarded as a core driver of OA pathogenesis, and the exploration of mechanical signal perception and transduction mechanisms has become crucial for deciphering OA’s pathophysiological processes. Piezo1, a key mechanosensitive cation channel belonging to the Piezo protein family, has recently gained significant attention due to its pivotal role in mediating cellular responses to mechanical stimuli in joint tissues. This review systematically examines Piezo1’s expression patterns, regulatory mechanisms, and pathological functions in OA, with a particular focus on its dual roles in modulating chondrocyte homeostasis and bone metabolism disorders, while also delving into the underlying molecular signaling pathways and potential therapeutic implications. Piezo1, consisting of approximately 2 500 amino acids and forming a unique trimeric propeller-like structure, is widely expressed in chondrocytes, osteocytes, mesenchymal stem cells, and synovial cells. It exhibits permeability to cations such as Ca²⁺, K⁺, and Na⁺, and directly responds to membrane tension changes induced by mechanical stimuli like fluid shear stress and mechanical overload. In OA patients and animal models, Piezo1 expression is significantly upregulated, especially in cartilage regions subjected to abnormal mechanical stress (e.g., human temporomandibular joint cartilage). This overexpression is closely associated with aggravated cartilage degeneration, increased chondrocyte apoptosis, accelerated cellular senescence, and intensified inflammatory responses. Mechanical overload and pro-inflammatory cytokines (e.g., IL-1β) are key inducers of Piezo1 upregulation: IL-1β activates the PI3K/AKT/mTOR signaling pathway to enhance Piezo1 expression, forming a pathogenic positive feedback loop that inhibits chondrocyte autophagy, promotes apoptosis, and further accelerates joint degeneration. Mechanistically, Piezo1 mediates OA progression through multiple interconnected pathways. When activated by mechanical stress, Piezo1 triggers excessive Ca²⁺ influx, leading to endoplasmic reticulum stress (ERS) and mitochondrial dysfunction, which directly induce chondrocyte apoptosis. This process involves the activation of downstream signaling cascades such as cGAS-STING and YAP-MMP13/ADAMTS5. YAP, a transcriptional regulator, upregulates the expression of matrix metalloproteinase 13 (MMP13) and aggrecanase (ADAMTS5), thereby accelerating cartilage matrix degradation. Additionally, Piezo1-driven Ca²⁺ overload promotes the accumulation of reactive oxygen species (ROS) and upregulates senescence markers (p16 and p21), accelerating chondrocyte senescence via the p38MAPK and NF-κB pathways. Senescent chondrocytes secrete senescence-associated secretory phenotype (SASP) factors (e.g., IL-6, IL-1β), further amplifying joint inflammation. In terms of bone metabolism, Piezo1 maintains joint homeostasis by promoting the differentiation of fibrocartilage stem cells into chondrocytes and balancing bone formation and resorption through regulating the FoxC1/YAP axis and RANKL/OPG ratio. Therapeutically, targeting Piezo1 shows promising potential. Preclinical studies have demonstrated that Piezo1 inhibitors (e.g., GsMTx4) can reduce joint damage and alleviate pain in OA mice. Simultaneously, siRNA-mediated co-silencing of Piezo1 and TRPV4 (another mechanosensitive channel) decreases intracellular Ca²⁺ concentration, inhibits chondrocyte apoptosis, and promotes cartilage repair. Conditional knockout of Piezo1 using Gdf5-Cre transgenic mice alleviates cartilage degeneration in post-traumatic OA models by downregulating MMP13 and ADAMTS5 expression. Despite existing challenges, such as off-target effects of inhibitors, inefficient local drug delivery, and interindividual genetic variability, strategies like developing selective Piezo1 antagonists, optimizing targeted nanocarriers, and combining Piezo1-targeted therapy with physical therapy provide viable avenues for clinical translation. The authors propose that Piezo1 serves as a critical therapeutic target for OA, and future research should focus on deciphering its context-dependent regulatory networks, developing tissue-specific intervention strategies, and validating their efficacy and safety in clinical trials to address the unmet medical needs of OA patients.

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.

Introduction: Current education on diabetes self-management is time-consuming as it is conducted face-to-face. This study aimed to evaluate the effectiveness of diabetes education via mobile application on hemoglobin A1c (HbA1c). Methodology: This was a double-blinded randomized controlled study conducted in the Department of Endocrinology, Hospital Pulau Pinang and Hospital Raja Permaisuri Bainun. Participants were stratified randomized according to HbA1c to intervention group (using T-Manis) and control group. The primary objective was to assess the difference in HbA1c between the groups. Secondary objectives were to assess the difference in body weight, hospitalization related to diabetes, diabetes knowledge between groups and usability and satisfaction of T-Manis. Laboratory investigations and questionnaires were conducted at baseline, 4 months and 8 months. Results: A total of 112 participants were randomized into two groups each with 56 participants. Mean age was 51 years with similar diabetes duration of 16 years in both groups. Participants comprised of 61.6% females with ethnic distribution of 49.1% Malay, 30.4% Chinese, 19.6% Indian and 0.9% Siamese. Baseline HbA1c levels were comparable between intervention and control groups (10.04% versus 9.91%; mean difference 0.13%; 95% CI −0.56 to 0.81; p = 0.718). At 4 months, HbA1c of the intervention group demonstrated a significant reduction compared to the control group (8.93% versus 9.80%; mean difference −0.86; 95% CI −1.59 to −0.14; p = 0.02). Sustained reduction of HbA1c in the intervention group was observed at 8 months (mean difference −1.01; 95% CI −1.85 to −0.16; p = 0.02). Baseline body weight was 77 kg, with no betweengroup differences in body weight, hospitalization related to diabetes and diabetes knowledge scores, although diabetes knowledge scores improved at 4 months in the intervention group. 89.3% of participants reported satisfaction with T-Manis Conclusion The T-Manis mobile application aided in significantly improving glycemic control with high user satisfaction, supporting its feasibility as an adjunct to standard diabetes care.
Diabetes Mellitus, Type 2 ; Glycemic Control ; Mobile Applications ; Pangolins

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

Colorectal cancer （CRC）， as a highly prevalent malignant tumor worldwide， continues to rank among the leading malignancies in both incidence and mortality. At present， the clinical treatment of CRC mainly relies on surgery， radiotherapy， chemotherapy， and drug therapy. However， due to individual differences among patients and the emergence of drug resistance in cancer cells， the postoperative recurrence rate remains high， significantly affecting patient prognosis. In recent years， traditional Chinese medicine （TCM） has attracted extensive attention in the field of tumor prevention and treatment because of its therapeutic advantages of multi-component， multi-target， multi-pathway， and holistic regulation. Aberrant activation of the Hedgehog signaling pathway is closely associated with the occurrence of various cancers. Studies have shown that the Hedgehog signaling pathway plays a key regulatory role in the occurrence and development of CRC. This pathway regulates the expression of downstream target genes through glioma-associated oncogene homolog （GLI） transcription factors and participates in biological processes such as tumor cell proliferation， apoptosis， invasion， and metastasis. It exerts anti- CRC effects through mechanisms including inducing apoptosis of CRC cells， inhibiting cancer cell proliferation， reversing drug resistance， and suppressing epithelial-mesenchymal transition （EMT）， thereby influencing the progression of CRC. This article systematically reviews the latest research progress in China and abroad and comprehensively discusses the molecular regulatory mechanisms of the Hedgehog signaling pathway in CRC. It particularly focuses on the specific mechanisms by which active components of Chinese medicine， such as alkaloids and terpenoids， and Chinese medicine compound formulas， such as Baitouwengtang and Zhizhenfang， exert anti-CRC effects by interfering with the Hedgehog-GLI signaling axis. By integrating and analyzing the molecular relationship between the Hedgehog signaling pathway and the pathological progression of CRC， and combining the TCM theories of "holistic concept" and "syndrome differentiation and treatment"， this article explores new TCM therapeutic strategies based on the Hedgehog signaling pathway， with the aim of providing innovative theoretical foundations and practical guidance for the prevention and treatment of CRC with TCM.

Objective To analyze the characteristics of HIV-1 pretreatment drug resistance(PDR)and molecular transmission networks in Yubei District,Chongqing,providing evidence for targeted interventions.Methods Using a cross-sectional design,plasma samples were collected from HIV/AIDS patients receiving antiretroviral therapy(ART)in Yubei District from January 2022 to December 2023.Pol gene fragments were extracted and amplified for HIV-1 genotyping and drug resistance analysis.Molecular transmission networks were constructed based on genetic distance calculations.Results Among 478 HIV-1 pol sequences,eight geno-types were identified:with CRF07_BC(60.4%,289/478),CRF08_BC(15.5%,74/478),CRF01_AE(11.7%,56/478),and CRF85_BC(5.9%,28/478).The overall PDR rate was 6.3%(30/478),with resistance to nucleoside reverse transcriptase inhibitors(NRTIs)and non-nucleoside reverse transcriptase inhibitors(NNRTIs)at 1.7%(8/478)and 5.2%(25/478),respectively.No protease inhibitor(PI)resistance was de-tected.The molecular network included 177 cases(37.0%network entry rate),forming 53 clusters with 198 connections.Cluster sizes ranged from 2 to 17 nodes,and 75.3%(149/198)of connections were associated with five subdistricts/towns:Shuanglonghu Street,Huixing Street,Luoqi Town,Gulu Town,and Baoshenghu Street.Conclusion HIV-1 genotypes in Yubei District exhibit diversity and complexity,with moderate PDR prevalence.Regional clustering of transmission networks suggests the need for enhanced molecular surveil-lance and targeted interventions based on analytical findings.

Objective:To evaluate the impact of different levels of enteral caloric support on clinical outcomes in patients with Stevens-Johnson Syndrome(SJS)/Toxic Epidermal Necrolysis(TEN).Methods:A retrospective analysis was conducted in 125 patients with SJS/TEN admitted to the Third People's Hospital of Hangzhou from January 2013 to December 2023.Patients were categorized into three groups based on their daily enteral caloric intake:low-calorie group(<25 kcal/kg,n=75),conventional calorie group(25～30 kcal/kg,n=27),and high-calorie group(>30 kcal/kg,n=23).The inflammatory markers,nutritional indicators,skin lesion healing time,length of hospital stay,complications rates,and mortality were compared among the groups.Results:At discharge,the white blood cell count[WBC,(6.08±0.60)109/L]and C-reactive protein[CRP,(19.04±7.09)mg/L]in the conventional calorie group,as well as the high-calorie group[WBC(6.34±0.71)109/L,CRP(27.78±8.94)mg/L],were significantly lower than those in the low-calorie group[WBC(8.31±0.41)109/L、CRP(62.07±7.41)mg/L](P<0.05).Meanwhile,the albumin[Alb(34.92±0.84)g/L]and prealbumin[PA,(243.48±12.38)mg/L]levels in the conventional calorie group,as well as the high-calorie group[Alb(35.07±0.96)g/L;PA(250.30±12.32)mg/L],were significantly higher than those in the low-calorie group[Alb(27.31±0.38)g/L;PA(146.31±6.01)mg/L](P<0.05).The skin lesion healing time(11.00±3.84)days,length of hospital stay(14.93±4.68)days,in the conventional calorie group were significantly lower than those in the low-calorie group[(skin lesion healing time(15.52±4.61)days,length of hospital stay(19.92±6.17)days,P<0.05];the skin healing time(10.6±2.96)d and length of hospital stay(14.07±4.05)d in the high-calorie group were significantly lower than those in the low-calorie group(P<0.05).There was no significant difference in infection rates(8.70%vs 8.00%)and gastrointestinal intolerance rates(8.70%vs 10.67%)between the two groups(P>0.05).Conclusion:Enteral caloric support of 25～30 kcal/kg/day appears to be optimal for patients with SJS/TEN,effectively meeting energy demands,improving nutritional and inflammatory markers,and promoting better clinical outcomes with fewer complications.