Poor water solubility is the primary obstacle preventing the development of many pharmacologically active compounds into oral preparations. Self-nanoemulsifying drug delivery systems(SNEDDS) have become a widely used strategy to enhance the oral bioavailability of poorly soluble drugs by inducing a supersaturated state, thereby improving their apparent solubility and dissolution rate. However, the supersaturated solutions formed in SNEDDS are thermodynamically unstable systems with solubility levels exceeding the crystalline equilibrium solubility, making them prone to drug precipitation in the gastrointestinal tract and ultimately hindering drug absorption. Therefore, maintaining a stable supersaturated state is crucial for the effective delivery of poorly soluble drugs. Incorporating polymers as precipitation inhibitors(PPIs) into the formulation of supersaturated self-nanoemulsifying drug delivery systems(S-SNEDDS) can inhibit drug aggregation and crystallization, thus maintaining a stable supersaturated state. This has emerged as a novel preparation strategy and a key focus in SNEDDS research. This review explores the preparation design of SNEDDS and the technical challenges involved, with a particular focus on polymer-based S-SNEDDS for enhancing the solubility and oral bioavailability of poorly soluble drugs. It further elucidates the mechanisms by which polymers participate in transmembrane transport, summarizes the principles by which polymers sustain a supersaturated state, and discusses strategies for enhancing drug absorption. Altogether, this review provides a structured framework for the development of S-SNEDDS preparations with stable quality and reduced development risk, and offers a theoretical reference for the application of S-SNEDDS technology in improving the oral bioavailability of poorly soluble drugs.
Solubility ; Administration, Oral ; Polymers/chemistry* ; Drug Delivery Systems/methods* ; Humans ; Emulsions/chemistry* ; Biological Availability ; Animals ; Pharmaceutical Preparations/administration & dosage*

PURPOSE: Lateral patellar compression syndrome (LPCS) is characterized by a persistent abnormally high stress exerted on the lateral articular surface of the patella due to lateral patellar tilt without dislocation and lateral retinaculum contracture, leading to anterior knee pain. The purpose of this study is to evaluate the efficacy and prognosis of lateral retinaculum release (LRR) combined with chondroplasty in the treatment of LPCS. METHODS: This retrospective study evaluated 40 patients who underwent LRR combined with chondroplasty for LPCS between 2020 and 2021. The assessment included improvement in postoperative tenderness and knee joint function. Patients were evaluated using the Lysholm, Tegner, and International Knee Documentation Committee 2000 scoring systems, as well as the visual analog scale, both preoperatively and postoperatively, with the paired comparisons analyzed using a t-test. Additionally, intraoperative observations were made regarding knee joint lesions, including cartilage damage and osteophyte formation, with analysis by the Chi-square test. RESULTS: The visual analog scale score for tenderness showed a significant decrease after surgery (p < 0.001). Evaluation of knee joint function also indicated significant improvements, as demonstrated by increased Lysholm, Tegner, and International Knee Documentation Committee 2000 scores postoperatively (p < 0.001, p = 0.011, p < 0.001, respectively). Furthermore, all LPCS patients included in the study presented with cartilage injuries and osteophyte formation. Significant differences were noted in the incidence of cartilage damage and osteophyte formation at different locations within the knee among patients with LPCS. CONCLUSION LRR combined with chondroplasty is an effective surgical approach for treating patients with LPCS, with satisfactory recovery observed at the 1-year follow-up. Additionally, the incidence of cartilage damage and osteophyte formation in LPCS patients varies significantly depending on the specific location within the knee joint.
Humans ; Male ; Female ; Retrospective Studies ; Adult ; Middle Aged ; Patella/surgery* ; Knee Joint/physiopathology* ; Recovery of Function ; Young Adult ; Treatment Outcome ; Cartilage, Articular/surgery* ; Adolescent

OBJECTIVE: To assess the efficacy of Qingda Granule (QDG) in ameliorating hypertension-induced cardiac damage and investigate the underlying mechanisms involved. METHODS: Twenty spontaneously hypertensive rats (SHRs) were used to develope a hypertension-induced cardiac damage model. Another 10 Wistar Kyoto (WKY) rats were used as normotension group. Rats were administrated intragastrically QDG [0.9 g/(kg•d)] or an equivalent volume of pure water for 8 weeks. Blood pressure, histopathological changes, cardiac function, levels of oxidative stress and inflammatory response markers were measured. Furthermore, to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertension-induced cardiac injury, a network pharmacology study was conducted. Predicted results were validated by Western blot, radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction, respectively. RESULTS: The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs (P<0.01). Histological examinations, including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac damage. Furthermore, echocardiography demonstrated that QDG improved hypertension-associated cardiac dysfunction. Enzyme-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum (P<0.01). CONCLUSIONS Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertension-induced cardiac damage by regulating the angiotensin converting enzyme (ACE)/angiotensin II (Ang II)/Ang II receptor type 1 axis and ACE/Ang II/Ang II receptor type 2 axis.
Animals ; Drugs, Chinese Herbal/therapeutic use* ; Hypertension/pathology* ; Renin-Angiotensin System/drug effects* ; Rats, Inbred SHR ; Oxidative Stress/drug effects* ; Male ; Rats, Inbred WKY ; Blood Pressure/drug effects* ; Myocardium/pathology* ; Rats ; Inflammation/pathology*

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Xiaoke formula (XKF) is a classic formula for the treatment of insulin resistance (IR), but there is still unclear on bioactive equivalent combinatorial components (BECC) of XKF. In this study, based on the previous research of our team, three components, berberine, astragaloside IV and chlorogenic acid, were selected as the BECC of XKF, and their efficacy and mechanism were investigated. A high-fat diet-induced IR mouse model was used to detect blood glucose, insulin sensitivity, lipid metabolism, immune & inflammatory factors, etc., and staining of pathology sections was used to detect histopathological changes. Network pharmacology was used to predict the potential targets and signaling pathways of XKF and its BECC, and the results of the network were verified by Western blot. The animal welfare and experimental procedures followed the regulations of the Laboratory Animal Ethics Committee of Beijing MDKN Biotech Company (MDKN-2023-019). The results showed that BECC, which was composed of berberine, astragaloside IV and chlorogenic acid in the ratio of the original formula of XKF, was comparable to XKF in improving the glycemia, insulin sensitivity, histopathological damage, dyslipidemia, and immuno-inflammation in IR mice. The results of network pharmacology and Western blot suggested that the BECC of XKF and XKF might alleviate IR by promoting the activation of hepatic phosphatidylinositol 3-kinase (PI3K), phosphorylation of protein kinase B (AKT), and inhibiting the expression of glucose-6-phosphate phosphatase (G6PC) and phosphoenolpyruvate carboxykinase 1 (PCK1), the key limiting enzymes of hepatic gluconeogenesis. The above results suggest that berberine, astragaloside IV and chlorogenic acid can be used as the potential BECC of XKF to improve IR, and can regulate lipid metabolism, immuno-inflammation, and promote hepatic PI3K/AKT signaling to inhibit hepatic gluconeogenesis, regulate glucose homeostasis, and improve IR in mice.

Objective To comprehensively excavate and analyze the research status,research hotspots and future trends of the literature related to the field of acupoint catgut embedding therapy for pain treatment in the CNKI database.Methods We searched the CNKI database from its establishment to June 2022,and scientifically analyzed the authors,keywords,and institutions of the included literature of acupoint catgut embedding therapy for pain treatment through specific algorithms of Citespace to generate a visual knowledge map.Results A total of 319 documents were included for statistical analysis,the number of publications in the field of acupoint catgut embedding therapy for the treatment of pain was generally on the rise,the number of publications by various authors was on the low side,and there was a lack of co-operation between the research teams,with the main institutions being the Guang'anmen Hospital,Chinese Academy of Chinese Medical Sciences,Affiliated Hospital of Youjiang Medical Universities of Nationalities and the Guangzhou University of Chinese Medicine,forming a 10-keyword clustering,and the hotspots of diseases under study were mainly mixed haemorrhoids,postoperative pain,low back and leg pain and dysmenorrhoea,etc..The main interventions were pure acupoint catgut embedding therapy and the combination of acupoint catgut embedding therapy and other acupuncture therapies,and the main research method was clinical research.Conclusion Acupoint catgut embedding therapy for the treatment of pain has a good development prospect,the future needs to deepen the clinical research,strengthen the mechanism research,pay attention to the joint use of acupoint catgut embedding therapy and other traditional Chinese medicine methods,and pay attention to the research of different thread materials.

Bone organoids can simulate the complex structure and function of the bone tissues, which makes them a frontier technology in organoid researches. Bone organoids show a tremendous potential of applications in bone disease modeling, bone injury repair, and medicine screening. Although advancements have been made so far in constructing bone organoids with functional structures like mineralization, bone marrow, trabecular bone, callus, woven bone, etc, the researches in this field are confronted with numerous challenges such as lack of standardized construction strategies and unified evaluation criteria, which limits their further promotion and application. To standardize researches in bone organoids, the Orthopedic Expert Committee of Geriatric Branch of Chinese Association of Gerontology and Geriatrics, the Youth Osteoporosis Group of Orthopedic Branch of Chinese Medical Association, the Osteoporosis Group of Orthopedic Surgeon Branch of Chinese Medical Doctor Association, and the Osteoporosis Committee of Shanghai Association of Integrated Traditional Chinese and Western Medicine organized related experts to formulate Expert consensus on the construction, evaluation, and application of bone organoids ( version 2024) based on an evidence-based approach. A total of 17 recommendations were put forth, aiming to standardize researches and clinical applications of bone organoids and enhance their value in scientific research and clinical practice.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Objective:To explore the osteogenic activity of in vitro cultured preosteoblasts treated by magnesium loaded hydrogel core-shell microspheres.Methods:A microfluidics chip device was designed and made to fabricate magnesium loaded hydrogel core-shell microspheres to precisely control the stable release of magnesium ions in vitro,the mechanism of controllable magnesium ion release in the promotion of osteogenic activity of MC3T3-E1 preosteoblasts was systematically investigated.Results:The magnesium loaded hydro-gel microspheres(PLGA/MgO-alginate microspheres)prepared by the microfluidics chip exhibited to be monodisperse with special core-shell structure and could control the stable release of magnesium ions at a concentration of 50 ppm in vitro.The in vitro study showed that it significantly enhanced the activity and proliferation ability of MC3T3-E1 preosteoblasts,promoted their osteogenic differ-entiation and mineralization ability,and increased ALP activity.Conclusion:Magnesium loaded hydrogel core-shell microspheres can promote the osteogenic activity of MC3T3-E1 osteoblasts in vitro.