ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

BACKGROUND:Photothermal therapy is a novel tumor treatment strategy that uses photothermal agents to transform light energy into heat energy to accomplish non-invasive tumor ablation.The rise of photothermal therapy and nanotechnology has provided a new perspective on breast cancer treatment.OBJECTIVE:To prepare a new type of near-infrared biomimetic nanoprobe that has been modified by breast cancer cell membrane,to investigate the effect of near-infrared fluorescence/ultrasound imaging in vitro,and to observe its targeting ability and photothermal therapy effect on homologous tumor cells in vitro.METHODS:Organic small molecule ITIC-4CI with A-D-A structure was used as photothermal agents;polylactic acid/glycolic acid copolymer as nanocarrier;4T1 cell membrane of mouse breast cancer cells as a surface modifier of nanoparticles;perfluorohexane(PFH)was loaded.A novel near-infrared biomimetic nanoprobe(4T1m/ITIC-4CI/PFH)was prepared by the double emulsion evaporation method and sonication method.The basic characterization of the nanoprobe and the homologous targeting ability were detected.The photothermal properties and photothermal stability of the probe were investigated,and the near-infrared fluorescence/ultrasound imaging effect of the probe under laser irradiation was observed.The CCK-8 assay and calcein/propidium iodide staining were used to assess the efficacy of photothermal therapy.RESULTS AND CONCLUSION:(1)The prepared 4T1m/ITIC-4CI/PFH nanoprobes had uniform size,high stability,and an average particle size of(92.7±2.3)nm.The probe's protein composition was identical to that of the 4T1 cell membrane.The nanoprobe's ability to target homologous 4T1 cells was validated by an in vitro cell uptake assay.(2)The nanoprobe had a red-shift absorption spectrum and tail emission extending to the near-infrared-Ⅱ,which emitted a bright near-infrared-Ⅱ fluorescence signal under laser irradiation.(3)After laser irradiation,the nanoprobe 4T1m/ITIC-4CI/PFH could be turned into microbubbles and enhanced ultrasound imaging.The results of CCK-8 assay and calcein/propidium iodide staining showed that the nanoprobe 4T1m/ITIC-4CI/PFH had an obvious photothermal killing effect on 4T1 cells.(4)The results show that the nanoprobe 4T1m/ITIC-4CI/PFH has the ability to target homologous tumors and enhance near-infrared-Ⅱ fluorescence imaging/ultrasound imaging and photothermal therapy effects.

ObjectiveTo investigate the trends and significant determinants of delayed HIV diagnosis （DHD） among newly reported HIV/AIDS cases in Xuhui District， Shanghai between 2018 and 2022. MethodsIn the newly reported HIV/AIDS cases， patients died within one year without accident， HIV/AIDS cases with CD₄ cell count <200 cells·μL^-1， and AIDS cases with a CD₄ cell count between 200 to 499 cells·μL^-1 were defined as delayed diagnosis. Univariate and multivariate logistic analysis were employed to explore the influencing factors of DHD. ResultsAmong the 862 newly reported HIV/AIDS cases， The DHD rate was 39.79% without statistically significant difference by year（χ²=4.508， P=0.342）. Patients with CD₄ cell count <200 cells·μL^-1 contributed the largest proportion of DHD. During 2018‒2022， the DHD rate declined among HIV/AIDS patients who were younger than 35 years old or 45‒65 years old， never married， original diagnosis from tertiary specialized hospitals. Patients who were 65 years or older， married or divorced， with heterosexual transmitted HIV/AIDS， and original diagnosis from other types of testing and tertiary metropolitan hospital， had sustainably higher DHD rates. The number of HIV screening and diagnosed from voluntary counseling and testing （VCT） decreased during the COVID-19 epidemic， while the DHD rate increased sharply. Multivariate logistic regression analysis suggested the DHD rates were higher among older age， other types of testing（OR=3.805， 95%CI： 2.260‒6.406）and pre-operative testing（OR=2.411， 95%CI： 1.424‒4.081）. Patients who received CD₄ test in 15 days had a higher DHD rate compared to the cases received CD₄ test exceeding 90 days （OR=0.336， 95%CI： 0.216‒0.522）. ConclusionThere is no significant decrease of delayed HIV diagnosis rate in Xuhui District in recent years， and the number of HIV tests has decreased in 2022. Monitoring of newly reported HIV/AIDS should be conducted continuously. Expansion of HIV antibody screening should be conducted in non-infectious departments and inpatient departments in healthcare institutions， particularly metropolitan hospitals. Assistance should be provided to clinicians and elderly patients for improving their ability to recognize and perceive the risk of HIV/AIDS， in order to enhance early diagnosis and subsequent treatment.

ObjectiveIn order to improve the recognition accuracy of named entities in medical record texts and realize the effective mining and utilization of medical record knowledge， a Bert-Radical-Lexicon（BRL） neural network model is constructed to recognize medical record entities with respect to the characteristics of medical record texts. MethodWe selected 408 medical records related to hypertension from the the Complete Library of Famous Medical Records of Chinese Dynasties and constructed a dataset consisting of 1 672 medical records by manually labeling. Then， we randomly divided the dataset into three subsets， including the training set（1 004 cases）， the testing set （334 cases） and the validation set（334 cases）. Based on this dataset， we built a BRL model that fused various text features of medical records， as well as its variants BRL-B， BRL-L and BRL-R， and a baseline model Base for experiments. During the model training phase， we trained the above models using the training set to reduce the risk of overfitting. We continuously monitored the performance of each model on the validation set during training and saved the model with the best performance. Finally， we evaluated the performance of these models on the testing set. ResultCompared with other models， the BRL model had the best performance in the medical records named entity recognition task， with an overall recognition precision of 90.09%， a recall of 90.61%， and the harmonic mean of the precision and recall（F1） of 90.35% for eight types of entities， including disease， symptom， tongue manifestation， pulse condition， syndrome， method of treatment， prescription and traditional Chinese medicine（TCM）. Compared with the Base model， the BRL model improved the overall F1 value of entity recognition by 5.22%， and the F1 value of pulse condition entity increased by 6.92%， which was the largest increase. ConclusionBy incorporating a variety of medical record text features in the embedding layer， the BRL neural network model has stronger named entity recognition ability， and thus extracts more accurate and reliable TCM clinical information.

L-asparaginase (L-ASN) is widely applied in the treatment of malignant tumor and low-acrylamide food production, however, the low expression level hampers its application. Heterologous expression is an effective strategy to increase the expression level of target enzymes, and Bacillus is generally used as the host for efficient production of enzymes. In this study, the expression level of L-asparaginase in Bacillus was enhanced through optimization of expression element and host. Firstly, five signal peptides (SP_SacC, SP_AmyL, SP_AprE, SP_YwbN and SP_WapA) were screened, among which SP_SacC showed the best performance, reaching an activity of 157.61 U/mL. Subsequently, four strong promoters (P43, P_ykzA-P43, P_Ubay and P_bacA) from Bacillus were screened, and tandem promoter P_ykzA-P43 showed the highest yield of L-asparaginase, which was 52.94% higher than that of control strain. Finally, three Bacillus expression hosts (B. licheniformis Δ0F3 and BL10, B. subtilis WB800) were investigated, and the maximum L-asparaginase activity, 438.3 U/mL, was reached by B. licheniformis BL10, which was an 81.83% increase compared with that of the control. This is also the highest level of L-asparaginase in shake flask reported to date. Taken together, this study constructed a B. licheniformis strain BL10/P_ykzA-P43-SP_SacC-ansZ capable of efficiently producing L-asparaginase, which laid the foundation for industrial production of L-asparaginase.
Bacillus licheniformis/metabolism* ; Asparaginase/genetics* ; Bacillus/genetics* ; Protein Sorting Signals ; Promoter Regions, Genetic/genetics* ; Bacillus subtilis/genetics* ; Bacterial Proteins

OBJECTIVE To analyze the current status， hotspots and development trends of research on the treatment of non-alcoholic fatty liver disease （NAFLD）， providing reference for subsequent research. METHODS Searching the Web of Science database， the literature related to the treatment of NAFLD from the establishment of the database to December 31， 2022 were collected. CiteSpace 6.1.R6 was used to construct a visual atlas， perform collaborative network analysis on authors， countries and institutions， and conduct keyword co-occurrence， clustering and emergence analysis to explore its research status and hotspots. RESULTS A total of 3 882 articles were included， and the number of publications had been increasing year by year. The top three countries in terms of publication volume were China， the United States， and Japan. The author with the highest volume of publications was Sanyal from the United States （37 articles）， while the institution with the highest volume of publications was the University of California， San Diego （75 articles）. A closely connected research team abroad mainly conducted large-scale randomized controlled trials （RCT） to evaluate the effectiveness and safety of various interventions， including medication and lifestyle， in treating NAFLD. However， domestic researches mainly focused on basic researches about the treatment of NAFLD with effective medicinal ingredients， and were characterized by traditional Chinese medicine. There were relatively few high-quality large-scale RCT studies related to it. Keyword analysis showed that researches in various countries mainly focused on regulating liver oxidative stress and inflammation， improving the overall balance of glucose and lipid metabolism. Except for hypoglycemic drugs， drugs that act on various comprehensive metabolic homeostasis targets in the body had entered clinical research， and had enormous therapeutic potential. CONCLUSIONS The research on NAFLD treatment continues to grow in popularity and tends to research targets and drugs for regulating systemic metabolic homeostasis. As the main force of research， China should strengthen communication with the international community， grasp the trends and directions of basic research， attach importance to clinical research， and continuously tap the therapeutic potential of traditional Chinese medicine.

Objective:To study the phenotype and genotype distribution of Yersinia pestis ( Y. pestis) in different natural foci of plague in China, so as to provide scientific basis for plague prevention and control. Methods:A total of 2 184 strains of Y. pestis isolated from different time periods, regions, hosts and vectors in 11 plague natural foci of China since 1943 were selected for biochemical type identification, glycolysis test, virulence factor test [capsule antigen (F1), pesticin Ⅰ (Pst Ⅰ), virulence antigen factor (VWa), pigmentation factor (Pgm)], different region (DFR) typing and clustered regularly interspaced short palindromic repeats (CRISPR) typing. Results:There were 16 biochemical types of Y. pestis in the natural foci of plague in China, and each biochemical type showed obvious regional distribution in each foci. Most strains were positive for ass hide glue glycolysis (89.79%, 1 961/2 184), maltose (80.13%, 1 750/2 184), glycerol (94.23%, 2 058/2 184), and denitrification (82.78%, 1 808/2 184), and negative for rhamnose (88.78%, 1 939/2 184) and melibiose (85.62%, 1 870/2 184). Virulence factor test results showed that 99.95% (2 183/2 184) of Y. pestis were F1 positive; 99.73% (2 178/2 184) of Y. pestis can produce Pst Ⅰ; 73.31% (1 601/2 184) of Y. pestis were VWa positive and 26.69% (583/2 184) were VWa negative; Pgm positive strains accounted for 72.62% (1 586/2 184), Pgm negative strains accounted for 21.52% (470/2 184), and Pgm mixed type strains accounted for 5.86% (128/2 184). According to DFR typing results, there were 52 genotypes in 2 184 strains of Y. pestis, of which 19 were major genotypes and 33 were minor genotypes. CRISPR typing revealed 16 major genotypes, of which 7 were newly discovered. Conclusion:The phenotypes and genotypes of Y. pestis in various natural foci of plague in China are diverse and have geographical distribution characteristics.

Background Most metro system are underground, airtight, with inadequate ventilation and massive gatherings, posing health risks to metro riders. Objective To evaluate air quality of Metro Line 1 in a city, and provide suggestions and basis for preventing harmful factors and protecting the health of passengers. Methods Station halls, station platforms, and metro carriages of Metro Line 1 in a city were monitored in summer (from July to August in 2021) and winter (from January to February in 2022). Six metro stations were selected by stratified sampling. Each station and carriage were monitored for three consecutive days in rush hours (9:00–11:00 and 19:00–21:00) and non-rush hours (11:00–13:00), with the same monitoring frequency. The monitored indicators were physical factors (temperature, relative humidity, wind speed, illumination, and noise), chemical factors (carbon monoxide, carbon dioxide, inhalable particles, formaldehyde, benzene, toluene, xylene, ammonia, and ozone), biological factor (airborne total bacterial count), and radiation factor (radon). The monitoring results were compared by location, time period, and season. Results According to the Hygienic indicators and limits for public places (GB 37488—2019), the selected physical factors did not meet the standard, especially the temperature and relative humidity of station hall and platform, and wind speed and noise of carriage. The results of physical factors varied significantly by location (P<0.05). In summer, the temperature of carriage [M (P₂₅, P₇₅), 23.9 (23.3, 24.6)℃] was the lowest, and the wind speed [0.78 (0.37, 1.11) m·s⁻¹] and noise [76.0 (72.0, 80.3) dB] of carriage were the highest; in winter, the temperatures of station hall and platform were the lowest [16.2 (13.2, 17.2)℃ and 16.2 (13.4, 17.0)℃, respectively], the relative humidity of carriage [26.4% (24.2%, 27.9%)] was the lowest, and the wind speed and noise of carriage were the highest [0.83 (0.47, 1.18) m·s⁻¹ and 74.5 (70.1, 78.3) dB, respectively]. The physical factors varied significantly by time period (P<0.05). In summer, the temperature was the lowest during morning rush hours [24.0 (23.0, 24.8)℃] and non-rush hours [24.2 (23.2, 24.9)℃], and the relative humidity during evening rush hours was the lowest [41.9% (37.0%, 47.8%)]; in winter, the temperature was the lowest during morning and evening rush hours [16.8 (13.4, 19.7)℃ and 16.5 (15.1, 19.4)℃, respectively], the relative humidity during the non-rush period was the lowest [26.8% (24.7%, 28.6%)], and the wind speed during evening rush hours was the highest [0.28 (0.19, 0.51) m·s⁻¹]. All measured chemical factors, biological factor, and radiation factor met the national standard (GB 37488—2019). Conclusion The chemical, biological, and radiative factors are complied with the national standard (GB 37488—2019) except physical factors such as temperature, relative humidity, wind speed, and noise. We suggest that the metro operators make full use of air conditioning system in combination with humidifiers to better regulate temperature and relative humidity, and .arrange working hours reasonably and provide noise-proof earplugs for carriage staff to protect against noise hazard.

In order to strengthen the supervision of the use of drugs in hospitals，the Sichuan Academy of Medical Sciences· Sichuan Provincial People’s Hospital took the lead in compiling the Principles for the Rational Use of National Key Monitoring Drugs （the Second Batch） with a number of experts from multiple medical units in accordance with the Second Batch of National Key Monitoring Rational Drug Use List （hereinafter referred to as “the List”） issued by the National Health Commission. According to the method of the WHO Guidelines Development Manual， the writing team used the Delphi method to unify expert opinions by reading and summarizing the domestic and foreign literature evidence of related drugs， and applied the evaluation， formulation and evaluation method of recommendation grading （GRADE） to evaluate the quality of evidence formed， focusing on more than 30 drugs in the List about the evaluation of off-label indications of drugs， key points of rational drug use and key points of pharmaceutical monitoring. It aims to promote the scientific standardization and effective management of clinical medication， further improve the quality of medical services， reduce the risk of adverse drug reactions and drug abuse， promote rational drug use， and improve public health.

ObjectiveTo investigate the identification of kidney Yang deficiency syndrome of patients with osteoporosis（OP）， and to form the clinical syndrome identification rules of traditional Chinese medicine（TCM）. MethodBasic information， etiology， clinical symptoms and other characteristics of 982 OP patients were included， and statistical tests were used to screen the variables associated with kidney Yang deficiency syndrome. Taking the decision tree as the base model， bootstrap aggregation algorithm（Bagging algorithm） was utilized to establish the classification model of kidney Yang deficiency syndrome in OP， generating numerous rules and removing redundancy. Combining least absolute shrinkage and selection operator（LASSO） regression to screen key rules and integrate them to construct an identification model， achieving the identification of kidney Yang deficiency syndrome in OP patients. ResultEighteen key identification rules were screened out， and of these， where 11 rules with regression coefficients>0 correlated positively with the kidney Yang deficiency syndrome， the rule with the highest coefficient was chilliness（present）&feverish sensation over the palm and sole（absent）. The other 7 rules with regression coefficients<0 correlated negatively with the syndrome， the rule with the lowest coefficient was reddish tongue（present）&diarrhea（absent）&deficiency of endowment（absent）. According to the regression coefficients of each key rule， variables with importance>0.2 were ranked as chilliness， reddish tongue， feverish sensation over the palm and sole， cold limbs， clear urine， diarrhea， deficiency of endowment， prolonged illness. The results of the partial dependence analysis of the identification model showed that compared to OP patients without chilliness， those with chilliness（present） had a 0.266 8 higher probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identification of the syndrome. Similarly， compared to OP patients without reddish tongue， those with reddish tongue had a 0.141 9 lower probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identifying non-kidney Yang deficiency syndrome. The accuracy， sensitivity， specificity and area under receiver operating characteristic curve（AUC） of the established kidney Yang deficiency syndrome identification model in the test set were 0.865 9， 0.853 7， 0.872 0 and 0.931 5， respectively. ConclusionA precise identification model of OP kidney Yang deficiency syndrome is conducted basing on the rule ensemble method of Bagging combining LASSO regression， and the screened key rules can explain the identification process of kidney Yang deficiency syndrome. In this research， according to the regression coefficients of rules， the importance and partial dependence of variables， combined with the thinking of TCM， the influence of patient characteristics on the identification of syndromes is described， so as to reveal the primary and secondary syndromes of identification and assist the clinical identification of kidney Yang deficiency syndrome.