Objective: To investigate the damaging effects of red blood cell supernatant (RBC-S) stored for different durations (7 d, 14 d, and 28 d) on vascular endothelial cells, and to explore the underlying mechanisms using bioinformatics analysis, so as to provide references for optimizing red blood cell transfusion strategies. Methods: Human umbilical vein endothelial cells (HUVECs) were co-cultured with RBC-S stored for 7, 14 and 28 days, designated as the 7 d group, 14 d group and 28 d group respectively, which were collectively defined as the experimental groups. Cell damage was evaluated by cell proliferation assay (Cell Counting Kit8, CCK8), lactate dehydrogenase (LDH) release assay, 4′, 6diamidino2phenylindole (DAPI) staining, and flow cytometry for apoptosis and reactive oxygen species (ROS) levels. The damage degree of RBC-S on vascular endothelial cells was assessed by statistical analysis of damage data among different groups. Since the damage effect reached a plateau at all time points, the 28 d storage group was selected as the representative for further mechanistic studies. Transcriptomic analysis was performed to explore the role of frizzled class receptor 1 (FZD1) and Wnt signaling pathway in red blood cell storagerelated endothelial dysfunction. Results: Compared with the control group, the storage groups treated with 7 d, 14 d, and 28 d RBC-S showed significantly decreased cell proliferation rates [control group 100%, 7 d group (69.51±2.30)%, 14 d group (74.54±2.89)%, 28 d group (73.59±2.36)%, P<0.05], significantly reduced numbers of DAPI-stained cell nuclei [control group (213±12.5) per field, 7 d group (140.33±17.04) per field, 14 d group (152.00±23.72) per field, 28 d group (144.33±19.09) per field, P<0.05] and significantly increased LDH release [control group (1), 7 d group (8.33±1.41), 14 d group (9.23±0.83), 28 d group (9.16±0.60), P<0.05]. There was no significant difference in the degree of damage caused by RBC-S among different storage groups (P>0.05). With the prolongation of storage time, free hemoglobin (FHb) gradually increased [control group (not detected), 7 d (16.57±6.38) mg/L, 14 d (76.80±22.83) mg/L, 28 d (286.97±29.02) mg/L, P<0.05]. The apoptotic rate (20.53±2.94)% and ROS relative intensity (5.13±0.91) in the 28 d storage group were significantly higher than those in the control group (P<0.05). Transcriptomic analysis showed that FZD1 played a key role in vascular endothelial dysfunction induced by red blood cell storage and was closely related to the Wnt signaling regulatory network. Conclusion: RBC-S stored for 7 d, 14 d, or 28 d can all significantly damage vascular endothelial cells, and the damaging effect reaches a plateau at 7 d of storage. Mechanistic investigation of the 28 d group indicated that the downregulation of the FZD1/Wnt signaling pathway may play a critical role in vascular endothelial dysfunction induced by red blood cell storage, providing a theoretical basis for further optimizing red blood cell storage and transfusion strategies.

Objective To investigate the epidemiological characteristics of malaria and provide a basis for developing improved prevention and control measures. Methods Data were obtained from the Chinese Disease Prevention and Control Information System. Malaria surveillance data for Nanning City from January 1,2023, to December 31,2024, were exported from the Infectious Disease Reporting Information Management Subsystem. The characteristics of the two groups of malaria cases were compared. Results A total of 103 imported malaria cases were reported in Nanning City in 2024, representing a 38.32% decrease compared with the same period of the previous year. No statistically significant difference were observed between cases reported in 2023 and 2024 in terms of average age, gender ratio, proportion of parasite species, and monthly reporting distribution;however, statistically significant differences were found in the proportion of reporting areas and current residence areas(χ2= 13.572 and 10.355, respectively; P = 0.001 and 0.035, respectively). The proportion of cases reported in Shanglin County and the proportion of cases residing in Shanglin County were both lower than those during the same period of the previous year. Conclusions The high aggregation of imported malaria cases in Nanning City has decreased. Medical institutions in areas other than Shanglin County should strengthen their vigilance against malaria.

Objective To assess the stability of the molluscicidal activity of the fermentation broth supernatant of Bacillus indicus F19, so as to provide insights into development of novel molluscicides derived from this isolate. Methods Healthy Oncomelania hupensis snails free from Schistosoma japonicum infections and acclimated in the laboratory for 7 days were selected. The fermentation broth supernatant of B. indicus F19 was prepared. For each treatment condition, four experimental groups and one control group were established, with 10 mL of the fermentation broth supernatant each group. O. hupensis snails were exposed to different pH values (3, 6, 9 and 12), temperatures (40, 60, 80 °C and 100 °C), and ultraviolet (UV) exposure durations (1, 2, 3 h and 4 h). Then, the supernatant was diluted with dechlorinated water to concentrations of 50%, 10%, and 5% (v/v), and 10 mL of each dilution solution was added to three separate tubes, with an equal volume of dechlorinated water as a blank control. Twenty O. hupensis snails were transferred to each tube, immersed for 48 h and 72 h, and collected for viability assessment using the shell-tapping method. The mortality of O. hupensis snails was calculated and compared among dilution groups and the blank control group to evaluate the molluscicidal activity of the fermentation broth supernatant of B. indicus F19. Results There was a significant difference in the mortality of O. hupensis snails immersed in 5% fermentation broth supernatants of B. indicus F19 for 48 h at various pH levels (χ² = 11.556, P < 0.05), and the mortality reduced to 13.33% (8/60) in the experimental groups at a pH value of 12, which was significantly lower than in the blank control group [33.33% (20/60)] (χ² = 6.708, P < 0.05). There was a significant difference in the mortality of O. hupensis snails immersed in 10% fermentation broth supernatants of B. indicus F19 for 72 h at various pH levels (χ² = 31.691, P < 0.001), and the mortality reduced to 71.67% (43/60) and 65.00% (39/60) in the experimental group at pH values of 9 and 12, which was significantly lower than in the blank control group [100.00% (60/60)] (χ² = 8.571 and 12.110, both P values < 0.01). The mortality of O. hupensis snails both reduced to 23.33% (14/60) following immersion in 5% fermentation broth supernatants of B. indicus F19 heated in a water bath at 80 °C and 100 °C for 48 h, which was lower than that of unheated O. hupensis snails [33.33% (20/60)] and snails heated in a water bath at 40 °C [35.00% (21/60)] and 60 °C [33.33% (20/60)], and there was no significant difference in the mortality of O. hupensis snails among groups (χ² = 3.898, P > 0.05). The mortality of O. hupensis snails was 68.33% (41/60), 66.67% (40/60), 65.00% (39/60), and 68.33% (41/60) following immersion in fermentation broth supernatants heated in a water bath at 40, 60, 80 °C and 100 °C for 72 h, which was all lower than that of snails in the control group [71.70% (43/60)]; however, there was no significant difference seen in the snail mortality among groups (χ² = 0.674, P > 0.05). The mortality of O. hupensis snails was 73.33% (44/60), 71.67% (43/60), 71.67% (43/60), and 75.00% (45/60) following 48 h immersion in 10% fermentation broth supernatants of B. indicus F19 irradiated by UV for 1, 2, 3 h and 4 h, 33.33% (20/60), 31.67% (19/60), 35.00% (21/60), and 33.33% (20/60) following 48 h immersion in 10% fermentation broth supernatants of B. indicus F19 irradiated by UV for 1, 2, 3 h and 4 h, and 71.67% (43/60) and 33.33% (20/60) following 48 h immersion in 10% fermentation broth supernatants of B. indicus F19 without UV irradiation, and no significant differences were found among groups (χ² = 0.229 and 0.150, both P values > 0.05). In addition, the mortality of O. hupensis snails was 76.67% (46/60), 71.67% (43/60), 70.00% (42/60), and 76.67% (46/60) following 72 h immersion in 5% fermentation broth supernatants of B. indicus F19 irradiated by UV for 1, 2, 3 h and 4 h, and 71.67% (43/60) in the control group, and there was no significant difference in the snail mortality among groups (χ² = 1.193, P > 0.05). Conclusion The molluscicidal action of the fermentation broth supernatants of B. indicus F19 is tolerant to high temperature and UV irradiation; however, the activity is attenuated under alkaline conditions.

ObjectiveTo propose an X-Gait motor rehabilitation assessment system based on a perception-cognition decoupling architecture to jointly achieve high-accuracy gait recognition and clinical interpretability for low clinical credibility and opaque decision-making workflows in existing intelligent gait assessment models. MethodsIn the perception layer, YOLOv11-Pose and PoseFormerV2 were integrated for 2D-to-3D human pose reconstruction. A long short-term memory network was adopted for temporal classification of normal, abnormal and pathological gaits. The layer-wise relevance propagation algorithm was used to identify discriminative joints and automatically quantify biomechanical indices including trunk forward inclination angle, stance phase percentage and stride symmetry. In the cognition layer, rehabilitation-oriented prompt engineering and prior knowledge graphs were combined to drive large language models, converting quantitative biomechanical measurements into clinically reasonable structured reports. Eight subjects were enrolled for bedside clinical validation to evaluate classification performance and clinical consistency. ResultsThe overall gait classification accuracy of X-Gait reached 94.1%. The 2D pose detection achieved 100% valid detection rate with an average confidence of 0.819. The mean per-joint position error of 3D pose reconstruction was 105.97 mm. In clinical validation of eight cases, outputs generated by explainable artificial intelligence combined with large language models showed high consistency with manual assessments from experienced rehabilitation physicians. ConclusionThe proposed X-Gait system based on perception-cognition decoupling realizes high-precision gait identification and clinically interpretable outputs.

Glycosylation constitutes a critical, highly intricate, and diverse co- and post-translational modification characterized by the covalent attachment of sugar moieties to proteins, lipids, or small RNAs. Complex glycans are ubiquitously present across nearly all living organisms. Despite their prevalence, our comprehension of glycan diversity remains limited, likely due to the inherent challenges associated with elucidating their structural complexity. Among post-translational modifications, protein glycosylation is notably prevalent, involving the enzymatic transfer of oligosaccharides to specific amino acid residues by glycosyltransferases. This modification plays a pivotal role in modulating protein function, including participation in various biological and biochemical recognition processes. G protein-coupled receptors (GPCRs), encoded by approximately one thousand genes, share a conserved architecture comprising seven transmembrane helices interconnected by three intracellular and three extracellular loops. Representing the largest family of human membrane proteins, GPCRs regulate a vast array of physiological and pathological processes, thereby constituting the most extensive class of therapeutic targets. In mammalian systems, the majority of GPCRs undergo glycosylation predominantly at their extracellular N-terminus or extracellular loops, primarily through N-linked and O-linked glycosylation. These covalent carbohydrate modifications exert profound effects on multiple facets of GPCR biology, including endoplasmic reticulum folding and quality control, membrane trafficking and surface expression, receptor internalization and recycling or degradation, ligand binding and signal transduction, biased signaling, and receptor dimerization. Notably, glycosylation can exert both positive and negative regulatory influences on these processes. Dysregulation of GPCR glycosylation has been implicated in a range of pathological conditions, such as cancer, diabetes, and neurological disorders, underscoring its physiological and pathological significance. Aberrant glycosylation patterns may lead to dysfunctional receptor signaling, thereby contributing to disease progression. Consequently, elucidating the precise roles of glycosylation in GPCR function not only enhances fundamental understanding of receptor biology but also facilitates the development of novel therapeutic strategies targeting glycosylation pathways or specific GPCR glycoforms. Although the functional consequences of glycosylation have been investigated for several decades, delineating their exact structural underpinnings has remained challenging due to the intrinsic flexibility and heterogeneity of carbohydrate structures. Recent advances in structural biology, particularly single-particle cryo-electron microscopy (cryo-EM) and X-ray crystallography, have catalyzed a paradigm shift in our understanding of GPCR glycosylation. The integration of these sophisticated structural techniques with biochemical approaches has redefined glycosylation as a complex structural element integral to receptor function. These developments provide a molecular framework for comprehending how glycans influence receptor pharmacology and open new avenues for the rational design of glyco-engineered biologics and allosteric modulators targeting specific extracellular motifs. This mini-review concentrates on glycosylation within the GPCR superfamily, summarizing the impact of glycosylation modifications on receptor function and regulatory mechanisms, recent progress in the structural biology of GPCR glycosylation, and prospective directions for future research in this field.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

Objective To understand the situation of dental cone beam computed tomography (CBCT) quality control testing phantoms in radiation health technical service institutions in Guangdong province, analyze the differences among different phantoms, and provide a reference for dental CBCT quality control testing. Methods The testing phantoms of 49 radiation health technical service institutions were used as the research objects. The designated CBCT equipment was used for scanning and imaging. The Z-score method was used to evaluate the high-contrast resolution, low-contrast resolution, and distance measurement deviation of each phantom. Results The satisfaction rates of various items for the phantoms in 49 institutions ranged from 85.7% to 100%. The distance measurement deviations of four institutions were “suspicious”, and the high-contrast resolution of four institutions and the distance measurement deviation of one institution were “unsatisfactory”. Conclusion The overall performance of dental CBCT quality control testing phantoms in radiological health technical service institutions in Guangdong province is satisfactory. However, there are still some phantoms with poor results in items such as distance measurement deviation and high-contrast resolution. The structural design, material selection, and manufacturing process of the phantom may all affect the results of quality control testing. Therefore, appropriate phantoms, optimized exposure conditions, and suitable reconstruction algorithms should be used in CBCT quality control testing to ensure accurate and reliable measurements.

Objective To explore the predictive value of dose surface histogram(DSH)in image guided radiotherapy(IGRT)for radiotherapy-induced acute radiation proctitis(ARP)in cervical cancer(CCA).Methods Totally 380 patients with CCA IGRT admitted to some hospital from May 2019 to May 2023 were selected prospectively and randomly divided into a control group(n=1 80)and an experimental group(n=200).The patients in the 2 groups were followed up and the incidence rates of ARP were counted,and rectal dose distribution was evaluated using dose volume histogram(DVH)in the control group and DSH in the experimental group.The predictive values of DVH and DSH for ARP were evaluated and compared using ROC curves.Statistical analysis was performed using SPSS 21.0 software.Results The two groups did not have statistically significant difference in the incidence rate of ARP(P＞0.05),while there were significant differences in the evaluation indicators of the rectal dose distribution(P＜0.05).V40,V50,S40 and S50 proved to have low predictive values for grade Ⅰ-Ⅳ ARP with AUC 0.700(P＜0.05);V60 and S60 had moderate predictive values for grade Ⅰ-Ⅳ ARP with AUC greater than 0.700 and less than or equal to 0.900(P＜0.05);V70,V78,S70 and S7s showed high predictive values for grade Ⅰ-Ⅳ ARP with AUC higher than 0.900(P＜0.05).Delong's test results indicated that DVH and DSH had no significant differences in AUC when used to predict gradeⅠ-Ⅳ ARP(allP＞0.05).Conclusion DSH is essentially the same as DVH when used for the prediction of grade Ⅰ-Ⅳ ARP due to CCA IGRT,and thus can be used for the supplementation and optimization of radiotherapy planning systems.[Chinese Medical Equipment Journal,2025,46(3):48-53]

Objective　To analyze and study the status quo and deficiencies in the construction of talent teams at all levels of CDCs in Hainan Province and put forward countermeasures to provide a reference basis for the high-quality development of talent team construction in all levels of CDCs in Hainan Province. Methods Using field surveys and data retrieval, spatial analysis was employed to compare the overall differences in human resource status of the provincial-level CDC and CDCs in five regional areas (East, West, South, North, and Central Hainan). The coordination between human resource allocation and development strategies was analyzed. A descriptive analysis mainly utilized CDC survey questionnaires and other research forms to explore the health human resources of the province's CDCs. Results The professional and technical personnel in the provincial CDCs comprise 1 431 individuals, accounting for 82.3% (1 431/1 739) of the total number of actual employees, which falls short of the Central Institutional Reform Commission's (CIRC) mandate that technical professionals comprise at least 85% of the total workforce (CIRC Document [2014] No. 2). Among Hainan's CDC personnel, 115 individuals are recognized as high-level talents within the Hainan Free Trade Port framework. These include one Class C talent, 22 Class D talents, and 93 Class E talents. Class A, B, and C-level talents are deficient. The majority of staff at both the provincial and regional CDCs hold bachelor's degrees. There is a significant proportion of staff with associate degrees or lower qualifications, coupled with a severe shortage of highly educated personnel. Postgraduates with master’s degrees or above account for 27.8% (65/233) in the provincial CDC, indicating low educational credentials among personnel in Hainan's CDCs. The central region, characterized by slower economic and social development, faces greater challenges in attracting and retaining high-level talent. There is a scarcity of public health professionals with interdisciplinary expertise. Some public health staff lack clinical knowledge, experience, and skills in disease treatment. Furthermore, there is a need to strengthen on-site emergency response capabilities for public health emergencies. The structural ratio of senior, intermediate, and junior professional and technical positions in the provincial CDC is 40%∶45%∶15%. The position settings are limited to ranking levels without distinction by professional category, leading to a bottleneck-type competition like crossing the "one log bridge" for technical position promotions. Conclusion　Hainan Province faces significant challenges in developing its public health workforce, both in technical expertise and management capacity. Especially under the context of the closure operation of the Hainan Free Trade Port, it is necessary to continuously strengthen top-level talent design to cultivate a favorable policy, system, and cultural environment, thereby promoting the sustained and healthy development of the province's public health career.

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.