Based on the theory of "yang governs and yin follows"， it is believed that pediatric obesity is primarily involves the key pathogenesis of constraint and stagnation due to yang deficiency， and the excessive accumulation of yin turbid. The root cause lies in the spleen-stomach yang deficiency and impaired digestion and transformation， while the branch manifestation is characterized by constraint and stagnation in sanjiao （三焦） and excessive accumulation of yin turbid. This emphasizes the imbalance between the governing function of yang qi and the transformation mechanism of yin essence in the overall pathological process. Accordingly， the treatment approach of reinforcing yang and unblocking stagnation， inhibiting yin and resolving turbid has been proposed. And a comprehensive treatment plan is suggested， including abdominal tuina combined with spinal manipulation， timed acupuncture according to the the eightfold method of the sacred tortoise， syndrome differentiation-based acupuncture， and mild moxibustion. This approach aims to provide an integrated approach for the prevention and treatment of pediatric obesity.

Objective: To conduct screening for rare blood types within important blood group systems for the Chinese population, such as Rh, Duffy, Kidd, P1Pk, Diego, and MNS, in the Guangzhou region, and to establish a corresponding rare blood type database and physical repository. Methods: The saline medium microplate method was used to screen blood donors with the ccDEE phenotype combined with either Jk(a-) or Jk(b-). The polybrene microplate method was employed to screen for donors with Fy(a-), s(-), Lu(b-), Di(b-), k(-), and p phenotypes. The urea lysis microplate method was applied to screen for the Jk(a-b-) phenotype. A high-resolution melting (HRM) curve method was established for screening some donors with the Di(b-) phenotype. Subsequently, expanded phenotyping of antigens in the Rh, Kidd, MNS, Duffy, P1Pk, Lewis, Kell, and Lutheran blood group systems was performed on identified rare blood type donors using monoclonal antibodies. The test results are entered into the Rare Blood Type Bank Management System of the Guangzhou Blood Center, enabling functions such as confirmation reminders and cryopreservation storage when the donor donates again. Red blood cells of rare blood types are processed into frozen red blood cells for long-term storage. Results: Among voluntary blood donors, 16 cases of the ccDEE combined with Jk(a-) phenotype were identified (0.221 7%, 16/7 216); 10 cases of the ccDEE combined with Jk(b-) phenotype (0.138 6%, 10/7 216); 78 cases of the Fy(a-) phenotype (0.169 5%, 78/46 012); 39 cases of the Lu(b-) phenotype (0.138 2%, 39/28 214); 31 cases of the s(-) phenotype (0.081 8%, 31/37 913); 22 cases of the Di(b-) phenotype (0.029 9%, 22/73 691); 30 cases of the Jk(a-b-) phenotype (0.010 1%, 30/298 250); and 1 case of the k(-) phenotype (0.001 3%, 1/77 382), which was further identified as KELnull phenotype (K0). No p phenotype donors were identified (0/88 528). A total of 228 units of frozen red blood cells were prepared. The screening results were compared and analyzed with rare blood type data from other regions. Conclusion: This study, through a combination of different screening methods, significantly improved the efficiency of rare blood type screening while remaining cost-effective. By conducting large-scale screening and performing data informatization processing, a database and physical repository of rare blood types in the Guangzhou region were successfully established. This provides a strong guarantee for the timely supply of blood to patients with difficult-to-match and rare blood types in the region, effectively enhances the level of transfusion safety in the region, and offers a practical paradigm for constructing a comprehensive blood transfusion support system.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Wilson disease （WD） is one of the few treatable neurogenetic disorders. Currently， Western medicine remains the main treatment method for WD， while since the 1990s， multiple studies conducted by Professor Yang Renmin and his team have shown that traditional Chinese medicine （TCM） also has a favorable therapeutic effect. Based on the principle of low-copper diet for WD， this article systematically elaborates on the advantages， limitations， and key considerations of current Western medicine therapies （pharmacotherapy， liver transplantation， and splenectomy） and reviews the research findings of TCM in China， especially the wide application of Gandou Decoction in clinical practice. Studies have shown that Gandou Decoction can effectively improve neurological symptoms， protect hepatic and renal function， and avoid the adverse drug reactions associated with metal chelating agents， and therefore， it can be used an effective long-term adjuvant therapy for WD. It should be noted that symptoms and signs should be considered in integrated traditional Chinese and Western medicine therapy for WD， and high-copper TCM drugs should be avoided to prevent deterioration.

Objective To elucidate the molecular mechanism of sirtuin-3 (SIRT3) in regulating mitochondrial biogenesis in human renal tubular epithelial cells. Methods Cells were stimulated with different concentrations of H₂O₂ and divided into four groups: control (NC), 50 μmol/L H₂O₂, 110 μmol/L H₂O₂ and 150 μmol/L H₂O₂. SIRT3 protein expression was then measured. SIRT3 was knocked down with siRNA, and cells were further assigned to five groups: control (NC), negative-control siRNA (NCsi), SIRT3-siRNA (siSIRT3), NCsi+H₂O₂, and siSIRT3+H₂O₂. After 24 h, cellular adenosine triphosphate (ATP) and mitochondrial superoxide anion (O₂•⁻) levels were determined, together with mitochondrial expression of SIRT3, peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α), nuclear respiratory factor 1 (NRF1), mitochondrial transcription factor A (TFAM), superoxide dismutase 2 (SOD2), acetylated-SOD2 and adenosine monophosphate activated protein kinase α1 (AMPKα1). Results The 110 and 150 μmol/L H₂O₂ decreased SIRT3 protein (both P<0.05). ATP and mitochondrial O₂•⁻ did not differ between NC and NCsi groups (both P>0.05). Compared to the NCsi group, the siSIRT3 group exhibited elevated O₂•⁻ level, decreased SIRT3 protein and increased expression levels of SOD2 and acetylated SOD2 protein (all P<0.05). Compared to the NCsi group, the NCsi+H₂O₂ group exhibited decreased cellular ATP levels, elevated mitochondrial O₂•⁻ levels, and reduced protein expression levels of SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 (all P<0.05). Compared with the siSIRT3 group, the siSIRT3+H₂O₂ group showed a decrease in cellular ATP levels, an increase in mitochondrial O₂•⁻ levels, a decrease in SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 protein expression levels and a decrease in acetylated SOD2 protein expression levels (all P<0.05). Compared with the NCsi+H₂O₂ group, the siSIRT3+H₂O₂ group showed a decrease in cellular ATP levels, an increase in mitochondrial O₂•⁻ levels, a decrease in SIRT3, AMPKα1, PGC-1α and NRF1, TFAM protein expression levels, and an increase in SOD2 and acetylated SOD2 protein expression levels (all P<0.05). Conclusions SIRT3 promotes mitochondrial biogenesis in tubular epithelial cells via the AMPK/PGC-1α/NRF1/TFAM axis, representing a key mechanism through which SIRT3 ameliorates oxidative stress-induced mitochondrial dysfunction.

Objective To explore the predictive value of the classification of carotid plaque reporting and data system (Plaque-RADS) and ultrasound features for the severity of coronary artery stenosis. Methods This was a single-center prospective observational study. Patients with suspected coronary artery disease or at high cardiovascular risk, who were hospitalized in the Department of Cardiology of Zhongshan Hospital, Fudan University from July 2023 to June 2024, were consecutively enrolled and divided into mild-to-moderate stenosis group and severe stenosis group according to the degree of coronary artery stenosis. Clinical parameters, carotid ultrasound features, and Plaque-RADS classification were compared between the two groups. A multivariate logistic regression model was constructed, and its predictive performance was assessed using receiver operating characteristic curve. Results A total of 271 patients were included, with age of (65.49±9.44) years. The proportion of males, patients with diabetes and hyperlipidemia, and smokers was significantly higher in the severe stenosis group, accompanied by greater plaque thickness as well as lower maximum elasticity (E_max) and mean elasticity (E_mean; P＜0.05). Statistically significant differences were also observed between the two groups in target plaque location, Plaque-RADS classification, and plaque stability distribution (P＜0.05). Specifically, type Ⅱ plaques predominated in the mild-to-moderate stenosis group, whereas the severe stenosis group had a higher proportion of type Ⅲ plaques and vulnerable plaques. Multivariate logistic regression analysis demonstrated that male, diabetes, and type Ⅲ–Ⅳ plaques were risk factors for severe coronary artery stenosis, while E_max served as a protective factor. The predictive model constructed by the above indicators exhibited favorable predictive performance (AUC＝0.838). Conclusions The combination of Plaque-RADS classification, E_max, sex, and comorbid diabetes has certain predictive value for the severity of coronary artery stenosis.

Objective:To investigate the changes in and correlations between melanin-concentrating hormone (MCH) and androgen levels in the serum of patients with polycystic ovary syndrome (PCOS), aiming to provide a novel research perspective for its diagnosis.Methods:A cross-sectional study. A total of 307 subjects were enrolled from the physical examination center and endocrinology clinic of the Affiliated Hospital of Zunyi Medical University from June 2023 to June 2024. The cohort comprised 114 healthy controls and 193 patients with PCOS, diagnosed according to the Rotterdam criteria. The patients were grouped into four phenotypes: Phenotype A (hyperandrogenemia [HA]+ovulatory dysfunction [OA]+polycystic ovarian morphology [PCOM], n=44), Phenotype B (HA+OA, n=50), Phenotype C (HA+PCOM, n=46), and Phenotype D (OA+PCOM, n=53). Clinical data were collected for all subjects. Serum MCH levels were determined by enzyme-linked immunosorbent assay. The relationship between MCH and androgen-related risk factors for PCOS was analyzed using Spearman partial correlation analysis and stepwise multiple linear hierarchical regression. Binary logistic regression was used to analyze factors influencing PCOS onset. The diagnostic value of MCH for PCOS was evaluated using a receiver operating characteristic (ROC) curve. Results:There were no significant differences in age and height between the healthy control group and the PCOS phenotypic groups (both P>0.05). MCH levels [17.63 (12.69, 22.00), 17.31 (11.05, 20.09), 17.82 (11.47, 19.40), 16.50 (11.14, 19.41) μg/L vs. 12.14 (9.78, 15.05) μg/L], homeostatic model assessment of insulin resistance, fasting plasma glucose, fasting serum lisulin, body mass index, and weight were significantly higher across all four PCOS phenotypes (A, B, C, and D) than in healthy controls (all P<0.05), whereas sex hormone-binding globulin (SHBG) contents were significantly lower ( P<0.05). Free androgen index (FAI), total testosterone (TES) and dehydroepiandrosterone (DHEA) levels were significantly higher in PCOS phenotypes A, B, and C than in the control group and PCOS phenotype D (all P<0.05). Spearman partial correlation analysis revealed no significant correlation between MCH and TES, DHEA, or FAI in healthy controls and patients with non-HA PCOS (all P>0.05). However, in PCOS patients with HA, MCH showed a significant positive correlation with TES and DHEA ( r=0.227 and 0.196, respectively; both P<0.05), but not FAI ( P>0.05). Stepwise multiple linear hierarchical regression analysis showed that MCH was positively correlated with TES, DHEA and luteinizing hormone and negatively correlated with SHBG (all P<0.05). Binary logistic regression indicated that an increase in MCH may be a potential risk factor for PCOS occurrence ( OR=1.113, 95% CI 1.012-1.224, P=0.028). ROC analysis showed that MCH has diagnostic value for PCOS ( P<0.05), with an area under the curve of 0.713. Conclusion:Serum MCH is closely related to FAI, TES, and DHEA levels in PCOS patients and may play an important role in the etiology and progression of the syndrome.

Objective:To explore the feasibility of joint screening of the two primary immunodeficiency diseases [severe combined immunodeficiency (SCID) and X-linked agammaglobulinemia(XLA)] and spinal muscular atrophy(SMA) in newborns by multiplex real-time quantitative PCR technology, and to provide evidence for early screening, diagnosis and treatment of children.Methods:Cross-sectional study. From July 2021 to January 2023, a total of 103 240 dry blood spots samples of newborns were collected which were delivered to Neonatal Disease Screening Center of Zhejiang by cold chain transportation. The concentrations of the T cell receptor excision ring (TREC), Kappa deletion of the recombinant excision loop (KREC), and exon 7 deletion of Survival Motor Neuron 1 (SMN1) gene in dry blood spots were simultaneously detected by multiplex real-time fluorescence quantitative PCR, taken ribonuclease P/MRP 30 000 subunits (RPP30) as an internal reference gene. The positive newborns were further diagnosed by other laboratory tests and gene sequencing was taken as gold standard. Children samples from 1 case of SCID, 3 cases of XLA and 2 cases of SMA were used for positive verification. The correlation between detected concentration of TREC/KREC and basic information in newborns were analyzed. The differences among groups for each factor were analyzed.Results:One case of SCID, 2 cases of XLA, 9 cases of SMA and 7 cases of other genetic diseases (4 cases of DiGeorge syndrome, 1 case of trisomy 21 syndrome, 1 case of Noonan syndrome and 1 case of super male syndrome) were identified by multiplex real-time fluorescence quantitative PCR. The positive predictive values of screening neonatal SCID, XLA and SMA were 2.44% (1/41), 2.78% (2/72) and 9/9 respectively. Taking the samples from clinically diagnosed 1 case of SCID, 3 cases of XLA and 2 cases of SMA as positive validation samples, which were all identified. The detected results of TREC/KREC correlated with time of blood collection, sex, weight, gestational age and delivery mode of newborns, whose r values were 0.162/0.187, 0.066/0.032, 0.045/0.042, ?0.015/?0.088 and 0.014/0.068 respectively (all P<0.05). Conclusions:Relying on current neonatal screening platform in Zhejiang, it is feasible to screen jointly two kinds of primary immunodeficiency diseases and spinal muscular atrophy in newborns by multiple real-time fluorescence quantitative PCR technology.

A 90-year-old female patient with novel coronavirus infection, severe pneumonia, and no history of blood transfusion andtransplantation.The mixed appearance phenomenon appeared in the admission blood group identification, and was sent the sample to our laboratory for difficult blood group identification. In the tube saline method, the patient′s red blood cells were positively reacted with 2 monoclonal anti-A and 5 human anti-A reagents.In the microcolumn gel method, the patient′s red blood cells showed 2 positive and 2 negative reactions with monoclonal anti-A and 5 positive and 1 negative reactions with human anti-A. The patient ′s red blood cells showed negative reaction with peanuts in phytohemagglutinin, and positive reaction with double flower lentils, wild soybeans and a string of purples. The patient ′s red blood cells treated with papain showed negative reaction with all monoclonal anti-A reagents, human anti-A and phytohemagglutinin. The patient ′s ABO gene was sequenced as ABO * B.01/O.01.02, but C1GALT1C1 gene mutation was not founded in the gDNA of the whole blood sample.It is speculated that the exposure of Tn antigen on the patient ′s red blood cells leads to red blood cells polyagglutination, resulting in ABO blood group inconsistency.