Objective: To fabricate a hydrogel loaded with inositol hexaphosphate-zinc and preliminarily evaluate its performance in self-mineralization and osteoinduction, thereby providing a theoretical basis for the development of bone regeneration materials. Methods: The hydrogel framework (designated DF0) was formed by copolymerizing methacryloyloxyethyltrimethylammonium chloride and four-armed poly(ethylene glycol) acrylate, followed by sequentially loading inositol hexaphosphate anions via electrostatic interaction and zinc ions via chelation. The hydrogel loaded only with inositol hexaphosphate anions was named DF1, while the co-loaded hydrogel was named DF2. The self-mineralization efficacy of the DF0 , DF1 and DF2 hydrogels was characterized using scanning electron microscopy, transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and selected area electron diffraction (SAED). The biocompatibility was assessed via live/dead cell staining and a CCK-8 assay. The osteoinductive capacity of the DF0 , DF1 and DF2 hydrogels on MC3T3-E1 cells was assessed via alkaline phosphatase (ALP) and Alizarin Red S (ARS) staining. In the aforementioned cell experiments, cells cultured in standard medium served as the control group Results: The DF0, DF1, and DF2 hydrogels were successfully synthesized. Notably, DF1 and DF2 exhibited distinct self-mineralization within 6 days. Results from TEM, EDS, and SAED confirmed that the mineralization products were amorphous calcium phosphate in group DF1, and amorphous calciumzinc phosphate in group DF2. Biocompatibility tests revealed that none of the hydrogels (DF0, DF1, and DF2) adversely affected cell viability or proliferation. In osteogenic induction experiments, both ALP and ARS staining were intensified in the DF1 and DF2 groups, with the most profound staining observed in the DF2 group. Conclusion The developed inositol hexaphosphate-zinc hydrogel (DF2) demonstrates the dual capacity to generate calcium-phosphate compounds through self-mineralization while exhibiting excellent osteoinductive properties. This biocompatible, dual-promoting osteogenic hydrogel presents a novel strategy for bone regeneration.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective: To investigate the objective characteristics of tongue manifestation in different stages of damp-heat syndrome in diabetic kidney disease (DKD). Methods: A cross-sectional study enrolled 134 patients with DKD G3-5 stages who met the diagnostic criteria for damp-heat syndrome in DKD. The patients were treated at Dongzhimen Hospital, Beijing University of Chinese Medicine, from May 2023 to January 2024. The patients were divided into three groups: DKD G3, DKD G4, and DKD G5 stage, with 53, 33, and 48 patients in each group, respectively. Clinical general data (gender, age, and body mass index) and damp-heat syndrome scores were collected from the patients. The YZAI-02 traditional Chinese medicine (TCM) AI Tongue Image Acquisition Device was used to capture tongue images from these patients. The accompanying AI Open Platform for TCM Tongue Diagnosis of the device was used to analyze and extract tongue manifestation features, including objective data on tongue color, tongue quality, coating color, and coating texture. Clinical data and objective tongue manifestation characteristics were compared among patients with DKD G3-5 based on their DKD damp-heat syndrome status. Results: No statistically significant difference in gender or body mass index was observed among the three patient groups. The DKD G3 stage group had the highest age (P<0.05). The DKD G3 stage group had a lower score for symptoms of poor appetite and anorexia(P<0.05) than the DKD G5 group. No statistically significant difference was observed in damp-heat syndrome scores among the three groups. Compared with the DKD G5 stage group, the DKD G3 stage group showed a decreased proportion of pale color at the tip and edges of the tongue (P<0.05). The DKD G4 stage group exhibited an increased proportion of crimson at the root of the tongue, a decreased proportion of thick white tongue coating at the root, a decreased proportion of pale color at the tip and edges of the tongue, an increased hue value (indicating color tone) of the tongue color in the middle, an increased brightness value (indicating color lightness) of the tongue coating color in the middle, and an increased thickness of the tongue coating (P<0.05). No statistically significant difference was observed in other tongue color proportions, color chroma values, body characteristics, coating color proportions, coating color chroma values, and coating texture characteristics among the three groups. Conclusion Tongue features differ in different stages of DKD damp-heat syndrome in multiple dimensions, enabling the inference that during the DKD G5 stage, the degree of qi and blood deficiency in the kidneys, heart, lungs, liver, gallbladder, spleen, and stomach is prominent. Dampness is more likely to accumulate in the lower jiao, particularly in the kidneys, whereas heat evil in the spleen and stomach is the most severe. These insights provide novel ideas for the clinical treatment of DKD.

Objective To develop a risk assessment scale for immune checkpoint inhibitor (ICI)-associated myocarditis based on multidisciplinary collaboration, and to evaluate its diagnostic performance. Methods Based on multidisciplinary cooperation, integrating clinical experience from oncology and cardiology, literature data, and patient conditions, a risk assessment scale for ICI-associated myocarditis was developed. A total of 101 patients with malignancies who received immunotherapy at Zhongshan Hospital, Fudan University, from October 2020 to October 2024 were included as the validation cohort. Patients were stratified into low-risk (0-1 point), medium-risk (2-4 points), and high-risk (≥5 points) groups based on their scale scores. The association between pretictive risk stratifications and actual assessment results was assessed using the Cox proportional hazards regression model. The predictive value of the scale for ICI-associated myocarditis was evaluated using receiver operating characteristic (ROC) curve. Agreement between the scale scores and actual assessment results was assessed using Cohen’s Kappa coefficient. Results Based on the scale pretictive results, 28(27.7%), 8(7.9%), 65(64.4%) patients were at low risk, medium risk, and high risk for ICI-related myocarditis, respectively; however, 46(45.5%), 8(7.9%), 47(46.5%) were at low risk, medium risk, and high risk actually. Kaplan-Meier survival analysis showed that the cumulative incidence of ICI-related myocarditis in the high-risk group was significantly higher than that in the medium- and low-risk groups (P＜0.05). In the multivariable-adjusted Cox proportional hazards model, the ICI-related myocarditis risk in high-risk group was about 4 times that in the low-risk group. ROC curve analysis demonstrated that the average area under the curve (AUC) for predicting ICI-related myocarditis was 0.81, with an accuracy of 0.74. The Cohen’s Kappa coefficient was 0.55, indicating moderate agreement. In the actual high-risk group, no patient was predicted to be at low risk; in the actual low-risk group, 16 patients were predicted to be at high risk. Conclusions This risk assessment scale for ICI-associated myocarditis shows high predictive performance. It provides oncologists with a simple yet effective multidisciplinary diagnostic reference tool, potentially enhancing early identification of ICI-associated myocarditis.

By using a strategy of leveraging the ability of metal-organic frameworks(MOFs)materials to precisely regulate the spatial orientation of cyclodextrins(CD),a polystyrene-modified γ-cyclodextrin metal-organic frameworks(PS-CD-MOFs)capillary coating was established and applied to the chiral separation of amino acids in open-tubular capillary electrochromatography(OT-CEC)based on the excellent film-forming property of polystyrene(PS).Characterization results by Fourier transform infrared spectroscopy(FT-IR),X-ray diffraction(XRD)indicated that PS was successfully grafted onto the surface of CD-MOFs.The modification significantly improved the structural stability and thermal stability of CD-MOFs while maintaining the integrity of the MOFs.The PS-CD-MOFs coated capillary electrophoresis system exhibited excellent performance in separating dansylated amino acid enantiomers(Dns-D,L-AAs).Specifically,under the optimal separation conditions(Sodium dodecyl sulfate/boric acid buffer system,20 cm capillary,and 10 kV effective voltage),good separation was achieved for D,L-methionine(D,L-Met)and D,L-serine(D,L-Ser).Further quantitative analysis showed that Dns-D,L-Met presented a good linear relationship in the concentration range of 10.0-1500.0 μmol/L,with a correlation coefficient close to 0.998,demonstrating high sensitivity and repeatability.Not only did it overcome the problem that traditional CD(used as additives in capillary electrophoresis)could not precisely control the spatial orientation of chiral resolvents,but also it solved the issues of insufficient stability and bonding amount of CD-MOFs coatings by utilizing the excellent film-forming property of polymers on the inner wall of capillaries.This study provided an efficient and controllable new strategy for construction of chiral separation stationary phases.

Objective To investigate the value of first platelet count(PLT)to respiratory rate(RR)ratio(PLT/RR)on admission in the diagnosis and prognosis of secondary sepsis in pneumonia patients.Methods A total of 100 patients with pneumonia admitted to the First Affiliated Hospital of Army Medical University from May 2023 to August 2024 were selected as subjects.According to the presence or absence of pneumonia sepsis,they were divided into sepsis group(63 cases)and non-sepsis group(37 cases).The secondary sepsis in pneumonia pa-tients were followed up continuously for 30 d.According to the survival situation,they were divided into sur-vival group(54 cases)and death group(9 cases).PLT in peripheral blood was measured,vital signs were col-lected on the first day of admission,and PLT/RR was calculated.The receiver operating characteristic curve was used to evaluate the predictive value of PLT,RR and PLT/RR for secondary sepsis in pneumonia pa-tients.The systemic inflammatory response syndrome(SIRS)score,modified early warning score(MEWS)and quick sequential organ failure assessment(qSOFA)score on admission were calculated,and the clinical predictive value of SIRS score,MEWS and qSOFA score was compared.Results PLT and PLT/RR in sepsis group were lower than those in non-sepsis group(P<0.000 1),RR was higher than that in non-sepsis group(P<0.01).The area under the curve(AUC,95%CI)of PLT,RR and PLT/RR were 0.858(0.785-0.931),0.693(0.589-0.796)and 0.902(0.843-0.962),respectively.The optimal cut-off values were 146.5×109/L,20.5 per minute and 8.075,respectively.The specificity were 8.1%,83.8%and 2.7%,respec-tively.The sensitivity was 33.3%,50.8%and 30.2%,respectively.Compared with the non-sepsis group,the sepsis group had a significantly higher SIRS score(P<0.001),a significantly lower MEWS(P<0.000 1),and no significant difference in qSOFA score between the two groups(P>0.05).The AUC(95%CI)of SIRS score,MEWS and qSOFA score in predicting secondary sepsis in pneumonia patients were 0.717(0.616-0.818),0.748(0.650-0.846)and 0.505(0.389-0.622),respectively.The optimal cut-off values were 4.5,2.5 and 1.5 points,respectively.The specificity were 91.9%,2.7%and 100.0%,respectively.The sensitivity was 42.9%,33.3%and 6.3%,respectively.PLT and PLT/RR in death group were lower than those in sur-vival group(P<0.05),RR was higher than that in survival group(P<0.05).Secondary sepsis in pneumonia patients were followed up for 30 d,Kaplan-Meier survival curve showed that patients with PLT≤138.5×109/L had a lower 30 d survival rate(P=0.007 8).Patients with RR>24.5 per minute had a lower 30 d sur-vival rate(P=0.016 1).Patients with PLT/RR≤6.375 had a lower 30 d survival rate(P=0.002 3).Conclu-sion PLT/RR can be used as a biological index to predict secondary sepsis in pneumonia patients,which is better than SIRS score,MEWS and qSOFA score,and the prognosis of secondary sepsis in pneumonia patients with low PLT/RR is worse.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.