Erchentang is a classic formula widely used by medical practitioners throughout history. In this paper，ancient and modern literature of Erchentang were collected， and bibliometrics was employed to analyze its historic evolution，prescription meaning，herbs origin， processing method，preparation methods， and clinical application. A total of 84 pieces of data were collected， and 58 pieces of data involving 53 ancient medical Chinese books were screened， sorted， and processed. Combined with research of modern scholars，the research has found that the Erchentang originated from the Taiping Huimin Huiye Shijie Fang compiled by the Imperial Medical Bureau of the Song Dynasty. The basic information about the origin of the drugs is quite clear. Pinelliae rhizoma in the formula is the dried tuber of Pinellia ternata. Citri exocarpium rubrum is the dried mature peel of Citrus reticulata and its cultivated varieties， with the inner white membrane removed. Poria is the whitest dry sclerotia of Poria cocos； Glycyrrhizae radix et rhizoma is the dried root and rhizome of the Glycyrrhiza uralensis. The dosage is 5.70 g Pinelliae rhizome and Citri exocarpium rubrum， 3.43 g Poria， and 1.69 g Glycyrrhizae radix et rhizoma praeparata cum melle. During the decoction process， the above-mentioned herbs should be chopped， with 300 mL water， 7 g ginger in thick slices， and 2 g Mume fructus added， and it was then simmered together to 180 mL. After removing the medicinal residue， it can be taken warmly. Erchentang has the effect of drying dampness and resolving phlegm， regulating Qi and harmonizing the middle. It can be used in treating the syndrome of phlegm and dampness，as well as symptoms such as frequent cough，white phlegm，fullness in chest and diaphragm，nausea and vomiting，limb drowsiness，anorexia，dizziness，palpitations，white and greasy tongue coating， and slippery pulse. The above results provide reference for future research and development of Erchentang.

ObjectiveTo explore the clinical efficacy and mechanism of Bupi Qingfei prescription （BPQF） in treating stable bronchiectasis in the patients with syndromes of lung-spleen Qi deficiency and phlegm-heat accumulation in the lungs. MethodsA randomized， double-blind， placebo-controlled trial was conducted. Patients were randomized into BPQF and placebo control （PC） groups. On the basis of conventional Western medicine treatment， the BPQF granules and placebo were respectively administered at 10 g each time， twice a day， for a course of 24 weeks. The TCM symptom scores， Quality of Life Questionnaire for Bronchiectasis （QOL-B） scores， lung function indicators， T lymphocyte subsets， level of inflammatory factors in the sputum， level of neutrophil elastase （NE） in the sputum， and occurrence of adverse reactions were observed before and after treatment in the two groups. ResultsA total of 64 patients completed the study， encompassing 32 in the BPQF group and 32 in the PC group. After treatment， the BPQF group showed decreased TCM symptom scores （P<0.01）， increased QOL-B scores （P<0.01）， and declined levels of tumor necrosis factor （TNF）-α and NE （P<0.05， P<0.01）. The PC group showed decreased TCM symptom （except spleen deficiency） scores （P<0.01）， increased the QOL-B health cognition and respiratory symptom domain scores （P<0.05， P<0.01）， and a declined TNF-α level （P<0.01）. Moreover， the BPQF group had lower TCM symptom （except chest tightness） scores （P<0.05， P<0.01）， higher QOL-B （except treatment burden） scores （P<0.05， P<0.01）， and lower levels of interleukin-6 and TNF-α （P<0.05） than the PC group. Neither group showed serious adverse reactions during the treatment process. ConclusionBPQF can ameliorate the clinical symptoms of stable bronchiectasis patients who have lung-spleen Qi deficiency or phlegm-heat accumulation in the lungs by regulating the immune balance and inhibiting airway inflammatory responses.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

To analyze global trends and research hotspots in exercise intervention for overweight and obesity from 2010 to 2024, to provide novel perspectives for comprehensive management research on overweight and obesity.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

AIM: To explore the risk factors associated with diabetic retinopathy(DR)based on ultra-widefield swept-source optical coherence tomography angiography(UWF-SS-OCTA), and to establish a clinical prediction model.METHODS:A total of 235 patients(235 eyes)with type 2 diabetes mellitus who were treated in the Affiliated Hospital of Xuzhou Medical University from July to November 2024 were selected as the research objects. According to the presence or absence of DR, they were divided into 120 cases(120 eyes)in non-DR group(NDR group)and 115 cases(115 eyes)in non-proliferative DR group(NPDR group). Data on general characteristics, laboratory tests, and OCTA results were collected for both groups. Univariate analysis was employed to identify DR-related risk factors. Logistic regression analysis was conducted to analyze these risk factors and to establish a DR prediction model. The efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve, calibration curve, and decision curve analysis(DCA).RESULTS: The duration of diabetes, fasting blood glucose, blood urea nitrogen(BUN), history of hypertension, and the choroidal vascular index(CVI)were found to be statistically significant in the model(all P<0.05). Specifically, the duration of diabetes, fasting blood glucose, BUN, and history of hypertension were identified as risk factors for DR among diabetic patients, while CVI was recognized as a protective factor. The area under the curve for the model predicting the probability of DR was 0.898(0.859-0.938), with a diagnostic threshold of 0.438. The corresponding sensitivity and specificity were 87.8% and 78.3%, respectively, indicating that the model possesses high predictive value for the occurrence of DR.CONCLUSION: The duration of diabetes, fasting blood glucose, BUN, history of hypertension, and CVI are significantly correlated with DR. The established prediction model demonstrates a substantial screening capability for DR.

Traditional Chinese medicine （TCM） therapy has unique clinical advantages in the treatment of atrial fibrillation， mainly reflected in five aspects， improving quality of life， enabling early diagnosis and treatment， promoting cardiac rehabilitation， making up for the limitations of Western medicine， and improving the success rate of catheter ablation. However， there is insufficient evidence in current clinical research. Based on the current status of TCM research in the treatment of atrial fibrillation， it is suggested that future studies should focus on standardized research on syndrome differentiation and classification. This can be achieved through clinical epidemiological surveys， expert consensus， and other methods to establish a unified syndrome differentiation and classification standard for atrial fibrillation. Clinical efficacy evaluation indicators should be standardized， and core outcome measures for clinical research on TCM treatment of atrial fibrillation should be developed through systematic reviews， patient interviews， and other methods. Additionally， clinical research design， implementation， and data management should be improved. By leveraging modern information technologies such as artificial intelligence， the scientific and standardized nature of TCM intervention research on atrial fibrillation can be enhanced， ultimately improving the quality of research.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

ObjectiveTo analyze the impact of maternal postpartum depression (PPD) at 2 months postpartum on caregiving for infants aged2 to 24 months, and to provide a scientific basis for future maternal and infant healthcare services. MethodsBased on the Shanghai Maternal-Child Pairs Cohort, 1 060 mother-child pairs were selected from those fully participating in follow-up visits at 2, 6, 12, and 24 months postpartum. Pregnancy and childbirth-related information was collected using standardized questionnaire surveys and hospital obstetric and maternity records. The Edinburgh postpartum depression scale was used to assess the maternal postpartum depressive symptoms at 2 months postpartum. At 2, 6, 12, and 24 months postpartum, questionnaire survey was used to evaluate the maternal responsiveness in caregiving and the provision of early learning opportunities for infants. Scores for responsive caregiving and early learning opportunities at 2, 6, 12, and 24 months were grouped based on the 25th percentile (P₂₅) of total scores. The mixed-effects model was used to analyze the longitudinal impact of maternal postpartum depression at 2 months on the caregiving of 2 to 24-month-old infants. ResultsThe longitudinal results from the mixed-effects model did not show an impact of maternal PPD on infant responsive caregiving within 12 months and early learning opportunities within24 months. However, cross-sectional analysis revealed that, compared to the non-PPD group, the risk of low responsive caregiving at 2 months in the PPD group was 93% higher (OR=1.931, 95%CI: 1.113‒3.364, P=0.019). The risks for low provision of early learning opportunities at2 months and 24 months increased by 59% (OR=1.589, 95%CI: 1.082‒2.324, P=0.017) and 60% (OR=1.598, 95%CI:1.120‒2.279, P=0.010), respectively. ConclusionMaternal postpartum depression increases the risk of low responsive caregiving at 2 months, but its long-term effects warrant further research.