Objective To study the seasonal distribution characteristics of polycyclic aromatic hydrocarbons (PAHs) in PM_2.5 in Lianyungang City, and analyze the sources of PAHs pollution, and to evaluate the health risks of PAHs in different seasons. Methods PM2.5 samples were collected regularly from January 2019 to December 2023, and 16 types of PAHs were determined by HPLC. Kruskal-Wallis H test was used to compare the concentrations of PM2.5 and PAHs in different years and seasons. The source of PAHs was analyzed by characteristic ratio and principal component analysis (PCA). Health risks were assessed using the BaP equivalent method and the incremental lifetime cancer risk (ILCR) model. Results The annual exceedance rates of PM_2.5 and BaP in Lianyungang showed a decreasing trend from 2019 to 2023. PM_2.5, total PAHs and PAHs monomers (except Ace, Flu and Acy) all showed significant seasonal differences, with the highest concentration in winter (P<0.001). The average proportion of 4-ring PAHs was the highest and the average proportion of 2-ring PAHs was the lowest. The proportion of 5-6 ring PAHs was relatively high in winter and spring. PM2.5and PAHs were negatively correlated with temperature, relative humidity and precipitation, and were positively correlated with atmospheric pressure. PM_2.5 was negatively correlated with wind speed, while some PAHs monomers were positively correlated with wind speed. The characteristic ratio and PCA results showed that the main sources of PAHs in Lianyungang City were mixed sources of road dust and vehicle emissions, oil pollution sources and biomass combustion sources. The results of ILCR showed that the highest risk was found in adults, with males slightly higher than females. In Lianyungang, the maximum value of ILCR in winter was more than 10-6 in people over 9 years old. Conclusion The main sources of PAHs in PM_2.5 in Lianyungang City are mixed sources of road dust and vehicle emissions, oil pollution sources, and biomass combustion sources. Under the current exposure level of PAHs in PM_2.5, residents have a certain potential carcinogenic risk.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

OBJECTIVE: To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) undergoing total knee arthroplasty (TKA). METHODS: A retrospective cohort study was conducted including RA patients who underwent unilateral TKA between January 2019 and December 2024. Inpatient and 30-day postoperative outpatient follow-up data were collected. Six machine learning algorithms, including decision tree, random forest, logistic regression, support vector machine, extreme gradient boosting, and light gradient boosting machine, were used to construct predictive models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall. SHapley Additive exPlanations (SHAP) values were employed to interpret and rank the importance of individual variables. RESULTS: According to the inclusion criteria, a total of 1 548 patients were enrolled. Ultimately, 18 preoperative indicators were identified as effective predictive features, and 8 postoperative complications were defined as prediction labels for inclusion in the study. Within 30 days after surgery, 453 patients (29.2%) developed one or more complications. Considering overall accuracy, precision, recall, and F1-score, the random forest model [AUC=0.930, 95% CI (0.910, 0.950)] and the extreme gradient boosting model [AUC=0.909, 95% CI (0.880, 0.938)] demonstrated the best predictive performance. SHAP analysis revealed that anti-cyclic citrullinated peptide antibody, C-reactive protein, rheumatoid factor, interleukin-6, body mass index, age, and smoking status made significant contributions to the overall prediction of postoperative complications. CONCLUSION Machine learning-based models enable accurate prediction of postoperative complication risks among RA patients undergoing TKA. Inflammatory and immune-related blood biomarkers, such as anti-cyclic citrullinated peptide antibody, C-reactive protein, and rheumatoid factor, interleukin-6, play key predictive roles, highlighting their potential value in perioperative risk stratification and individualized management.
Humans ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthritis, Rheumatoid/blood* ; Machine Learning ; Postoperative Complications/blood* ; Female ; Male ; Retrospective Studies ; Middle Aged ; Aged ; Risk Factors ; Preoperative Period ; C-Reactive Protein/analysis* ; Risk Assessment

An ideal dermal filler should integrate filling, repair, and anti-aging effects, with immediate tissue augmentation, slow degradation, and progressive stimulation of collagen regeneration. However, commonly used hyaluronic acid (HA) hydrogels, while effective for rapid filling, suffer from limited duration of support, weak cell adhesion, and an inability to promote collagen regeneration. Silk fibroin (SF), a natural protein from silkworm cocoons, is known for its excellent cell adhesion and collagen-stimulating abilities. However, its limited gelation capability restricts its potential application as a standalone injectable hydrogel. Based on a complementary strategy, this study combines the rapid gelling properties of HA with the collagen regenerative properties of SF to create a co-crosslinked HA-SF hydrogel. The composite hydrogel merges HA's rapid filling effect with SF's strong tissue adhesion and collagen-stimulating abilities. The formulation, physicochemical properties, degradation, biocompatibility, and filling effects of the HA-SF hydrogel were systematically investigated. HA-SF hydrogel exhibits excellent mechanical properties and ensures long-term support while maintaining injectability. Interestingly, after intradermal injection in the UVB-induced photoaging model, HA-SF hydrogel not only enhances hydrogel-cell interaction but also continues to stimulate collagen regeneration, especially type III collagen. This dual action achieves the biological effects of repair and anti-aging while maintaining the filling effect. Proteomic analysis confirms that repair and anti-aging effects are enhanced by the regulation of skin fibroblasts and modulation of amino acid and lipid metabolism. This composite hydrogel holds strong promise for clinical applications, offering a safer, long-lasting, and more natural injectable filler that combines filling, repair, and anti-aging into one system.

Sennoside A (SA), a typical prodrug, exerts its laxative effect only after its transformation into rheinanthrone catalyzed by gut microbial hydrolases and reductases. Hydrolases have been identified, but reductases remain unknown. By linking a photoreactive group to the SA scaffold, we synthesized a photoaffinity probe to covalently label SA reductases and identified SA reductases using activity-based protein profiling (ABPP). From lysates of an active strain, Bifidobacterium pseudocatenulatum (B. pseudocatenulatum), 397 proteins were enriched and subsequently identified using mass spectrometry (MS). Among these proteins, chromate reductase/nicotinamide adenine dinucleotide (NADH) phosphate (NADPH)-dependent flavin mononucleotide (FMN) reductase/oxygen-insensitive NADPH nitroreductase (nfrA) was identified as a potent SA reductase through further bioinformatic analysis and The Universal Protein Resource (UniProt) database screening. We also determined that recombinant nfrA could reduce SA. Our study contributes to further illuminating mechanisms of SA transformation to rheinanthrone and simultaneously offers an effective method to identify gut bacterial reductases.

The comprehensive detection and identification of active ingredients in complex matrices is a crucial challenge.Liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS)is the most prominent analytical platform for the exploration of novel active compounds from complex matrices.However,the LC-HRMS-based analysis workflow suffers from several bottleneck issues,such as trace content of target compounds,limited acquisition for fragment information,and uncertainty in interpreting relevant MS2 spectra.Lycibarbarspermidines are vital antioxidant active ingredients in Lycii Fructus,while the reported structures are merely focused on dicaffeoylspermidines due to their low content.To comprehensively detect the new structures of lycibarbarspermidine derivatives,a"depict"strategy was developed in this study.First,potential new lycibarbarspermidine derivatives were designed according to the biosynthetic pathway,and a comprehensive database was established,which enlarged the coverage of lycibarbarspermidine derivatives.Second,the polarity-oriented sample prep-aration of potential new compounds increased the concentration of the target compounds.Third,the construction of the molecular network based on the fragmentation pathway of lycibarbarspermidine derivatives broadened the comprehensiveness of identification.Finally,the weak response signals were captured by data-dependent scanning(DDA)followed by parallel reaction monitoring(PRM),and the efficiency of acquiring MS2 fragment ions of target compounds was significantly improved.Based on the integrated strategy above,210 lycibarbarspermidine derivatives were detected and identified from Lycii Fructus,and in particular,170 potential new compounds were structurally characterized.The integrated strategy improved the sensitivity of detection and the coverage of low-response components,and it is expected to be a promising pipeline for discovering new compounds.

Objective:To develop and validate a predictive model of 28-day mortality in sepsis based on lactate dehydrogenase-to-albumin ratio (LAR).Methods:Sepsis patients diagnosed in the department of intensive care medicine of the First Affiliated Hospital of Soochow University from August 1, 2017 to September 1, 2022 were retrospective selected. Clinical data, laboratory indicators, disease severity scores [acute physiology and chronic health evaluation Ⅱ(APACHEⅡ), sequential organ failure assessment (SOFA)] were collected. Patients were divided into death group and survival group according to whether they died at 28 days, and the difference between the two groups was compared. The dataset was randomly divided into training set and validation set according to 7∶3. Lasso regression method was used to screen the risk factors affecting the 28-day death of sepsis patients, and incorporating multivariate Logistic regression analysis (stepwise regression) were included, a prediction model was constructed based on the independent risk factors obtained, and a nomogram was drawn. The nomogram prediction model was established. Receiver operator characteristic curve (ROC curve) was drawn to analyze and evaluate the predictive efficacy of the model. Hosmer-Lemeshow test, calibration curve and decision curve analysis (DCA) were used to evaluate the accuracy and clinical practicability of the model, respectively.Results:A total of 394 patients with sepsis were included, with 248 survivors and 146 non-survivors at 28 days. Compared with the survival group, the age, proportion of chronic obstructive pneumonia, respiratory rate, lactic acid, red blood cell distribution width, prothrombin time, activated partial thromboplastin time, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, creatinine, blood potassium, blood phosphorus, LAR, SOFA score, and APACHEⅡ score in the death group were significantly increased, while oxygenation index, monocyte count, platelet count, fibrinogen, total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, and blood calcium were significantly reduced. In the training set, LAR, age, oxygenation index, blood urea nitrogen, lactic acid, total cholesterol, fibrinogen, blood potassium and blood phosphorus were screened by Lasso regression. Multivariate Logistic regression analysis finally included LAR [odds ratio ( OR) = 1.029, 95% confidence interval (95% CI) was 1.014-1.047, P < 0.001], age ( OR = 1.023, 95% CI was 1.005-1.043, P = 0.012), lactic acid ( OR = 1.089, 95% CI was 1.003-1.186, P = 0.043), oxygenation index ( OR = 0.996, 95% CI was 0.993-0.998, P = 0.002), total cholesterol ( OR = 0.662, 95% CI was 0.496-0.865, P = 0.003) and blood potassium ( OR = 1.852, 95% CI was 1.169-2.996, P = 0.010). A total of 6 predictor variables were used to establish a prediction model. ROC curve showed that the area under the curve (AUC) of the model in the training set and validation set were 0.773 (95% CI was 0.715-0.831) and 0.793 (95% CI was 0.703-0.884), which was better than APACHEⅡ score (AUC were 0.699 and 0.745) and SOFA score (AUC were 0.644 and 0.650), and the cut-off values were 0.421 and 0.309, the sensitivity were 62.4% and 82.2%, and the specificity were 82.2% and 68.9%, respectively. The results of Hosmer-Lemeshow test and calibration curve showed that the predicted results of the model were in good agreement with the actual clinical observation results, and the DCA showed that the model had good clinical application value. Conclusion:The prediction model based on LAR has a good predictive value for 28-day mortality in patients with sepsis and can guide clinical decision-making.

Objective:To summarize long-term clinical follow-up results of segment instability between the upper instrumented vertebra (UIV) and the adjacent upper vertebra (UIV+1) and to establish the optimal timing for surgery for UIV+1.Methods:A retrospective analysis was conducted on 265 patients with lumbar degenerative diseases who underwent transforaminal lumbar interbody fusion (TLIF) surgery at the Department of Spinal Surgery, Zhongda Hospital, from January 2014 to December 2018. The cohort included 119 male and 146 female patients, with an average age of 64.93 years (range: 32-86 years). Preoperative dynamic imaging measured sagittal angulation (SA) and sagittal translation (ST) of the UIV+1/UIV segment. Patients with SA>10° or ST>2 mm were categorized into the unstable group, further divided into the unstable non-fusion group and the unstable fusion group based on whether UIV+1 expansion fusion was performed. The remaining patients were classified into the stable group. Imaging indicators, Visual Analogue Scale (VAS) scores, Oswestry disability index (ODI) scores, and Japanese Orthopaedic Association (JOA) scores were compared among the groups, with JOA improvement rates calculated to assess clinical efficacy. Pearson correlation coefficient analysis was employed to examine correlations between preoperative imaging indicators and final follow-up JOA improvement rates. Receiver Operating Characteristic (ROC) curves and the maximum Youden index were utilized to determine thresholds for preoperative SA and ST.Results:The follow-up duration for all patients was 73.53±12.92 months (range: 61-108 months). The stable group (124 cases) included 61 males and 63 females, aged 64.31±9.83 years (range: 44-82 years). The unstable non-fusion group (59 cases) included 22 males and 37 females, aged 65.76±11.01 years (range: 32-86 years). The unstable fusion group (82 cases) included 36 males and 46 females, aged 65.26±8.68 years (range: 47-80 years). At the last follow-up, the unstable non-fusion group exhibited ΔSA 0.90°±1.97° and ΔST 0.77±1.27 mm, both significantly higher than the stable group's ΔSA 0.25°±1.57° and ΔST 0.34±0.34 mm ( t=3.564, P<0.001; t=2.311, P=0.022). Clinical improvements were lower in the unstable non-fusion group compared to the other two groups: VAS (2.28±0.83), ODI (5.91%±3.46%), JOA (24.11±1.78), with a JOA improvement rate of 60%. The stable group showed VAS (1.51±0.69), ODI (3.71%±1.75%), JOA (27.33±1.91), with a JOA improvement rate of 83%. The unstable fusion group had VAS (1.46±0.83), ODI (3.46%±1.81%), JOA (26.48±1.66), with a JOA improvement rate of 78%. These differences were statistically significant ( F=32.117, P<0.001; F=24.827, P<0.001; F=92.658, P<0.001; F=93.341, P<0.001). The JOA improvement rate was negatively correlated with preoperative SA ( r=-0.363, P<0.001) to a low extent, and with preoperative ST ( r=-0.596, P<0.001) to a moderate extent. ROC curve analysis determined the preoperative SA threshold as 11.5° and the preoperative ST threshold as 1.85 mm. Conclusion:Pre-existing instability of the responsible segment UIV and UIV+1 (SA>10° or ST>2 mm) may worsen during long-term follow-up after TLIF. When preoperative SA exceeds 11.5° and ST exceeds 1.85 mm between UIV and UIV+1, performing an extended fusion involving UIV+1 can ensure surgical efficacy over long-term follow-up.

OBJECTIVE To optimize the preparation process of sinomenine microemulsion and evaluate its pharmacodynamics.METHODS HPLC method for sinomenine content determination was established,and sinomenine microemulsion prescription was in-itially screened by solubility test and pseudo-ternary phase diagram.D-optimal mixing experimental design method was used to optimize sinomenine microemulsion prescription with particle size and drug load as investigation indexes,and its particle size,drug load and sta-bility were evaluated.Transdermal absorption was investigated by transdermal test in vitro,and the anti-inflammatory effect was evalua-ted by ear swelling test.RESULTS With methanol:0.1%phosphoric acid(40 ∶ 60)as the mobile phase,the detection wavelength was 262 nm,and the method was suitable for the determination of sinomenine.The optimal formula of microemulsion was obtained as castor oil(7.0%),PEG40 hydrogenated castor oil/anhydrous ethanol(69.0%),the optimal Km value was 3∶1,and distilled water(24.0%).The average particle size of the microemulsion was 18.76 nm,the PDI was 0.072 and the drug loading was 5.225%.The cumulative permeability of 1.0%sinomenine microemulsion at 12 h was 1.223 4 μg·cm-2,and the steady permeability rate was 0.0649 μg·cm-2·h-1,which was better than sinomenine solution.The inhibitory rate of sinomenine microemulsion was 65.07%,which was similar to dexamethasone.CONCLUSION The preparation of sinomenine microemulsion has the advantages of stable process,high drug loading,good transdermal absorption and anti-inflammatory effect,which can provide reference for the development of sinomenine transdermal drug delivery preparation.

Objective:To investigate the clinical outcomes of using autologous mandibular outer cortex "sandwich" grafting to augment mandible for correcting lower facial asymmetry with normal occlusal relationships.Methods:A retrospective analysis was conducted on the clinical data of patients with lower facial asymmetry treated at the Department of Plastic Surgery, the Affiliated Friendship Plastic Surgery Hospital of Nanjing Medical University, from January 2016 to December 2019. Preoperative cone-beam CT (CBCT) scans of the maxillofacial region were obtained to acquire three-dimensional data of the maxillofacial skeleton. Computer-aided design was used to determine the osteotomy range of the mandibular outer cortex and design osteotomy guide template. The outer cortex of the larger mandibular side (donor site) was harvested according to the osteotomy guide template and sectioned. The segmented mandibular outer cortex was then contoured to match the arc of the recipient side’s mandibular outer cortex and fixed to the inner side of the recipient mandibular outer cortex, thus increasing the width and thickness of the expanded mandible. Follow-up was conducted at 7th day and 6 months postoperatively, CBCT scan was performed to measure the changes in ramus height (Co-Go), mandibular body length (Go-Me), and mandibular outer cortex thickness, and volume, and the patient satisfaction with facial appearance (1 to 5 points, with higher scores indicating higher satisfaction), were assessed to evaluate surgical outcomes. Statistical analysis was performed using SPSS 12.0 software. Paired t-tests were used to compare patient satisfaction scores preoperatively and six months postoperatively. Repeated measurement ANOVA was used to compare Co-Go and Go-Me measurements preoperatively, 7th day, and 6 months postoperatively. If a statistically significant difference is found, further analysis using post-hoc testing(Tukey’s HSD test) will be conducted to examine the data. Results:Sixteen patients with lower facial asymmetry were included, comprising of 5 males and 11 females, aged 18 to 40 years, with an average age of 25.2 years. Surgical method included contralateral mandibular outer cortex "sandwich" grafting to the expanded mandible in 9 cases and simultaneous genioplasty in 7 cases. Follow-up ranged from 6 months to 5 years, with an average follow-up of 18.6 months. All patients experienced numbness of the lower lip postoperatively, which resolved within six months, and no severe complications occurred. The symmetry of lower facial contour improved significantly and remained stable. Patient satisfaction score for facial appearance increased from (1.63±0.62) points preoperatively to (4.19±0.75) points six months postoperatively( P<0.01). The differences in Co-Go on the donor side and Go-Me on the recipient side across the three time points(preoperatively, 7th day and 6 months postoperatively) were not statistically significant(all P>0.05). However, the differences in Go-Me on the donor side and Co-Go on the recipient side across the three time points were statistically significant(all P<0.05). On the donor side, the mandibular outer cortex thickness decreased by a maximum of 6 mm on 7th day postoperatively and increased by a maximum of 2 mm at 6 months postoperatively compared to 7th day. On the recipient side, mandibular outer cortex thickness increased by a maximum of 6 mm on 7th day postoperatively and decreased by a maximum of 2 mm at six months postoperatively compared to 7th day. The volume of the mandibular outer cortex on the recipient side increased by (4 415.94±1 017.21)mm 3 at 7th day postoperatively compared to preoperatively, and decreased by (202.63±300.85)mm 3 at 6 months postoperatively. Conclusion:For lower facial asymmetrical with normal occlusal relationships and no occlusal plane deviation, contralateral mandibular outer cortex "sandwich" bone grafting can effectively increase the width and volume of the mandible on the grafted side, achieving favorable clinical outcomes.