ObjectiveTo analyze the epidemiological characteristics of 21 respiratory pathogens in influenza-like illness (ILI) cases in Jing’an District, Shanghai in 2024, and to provide a scientific basis for the prevention and control of respiratory infectious diseases. MethodsData of1 907 ILI cases at four sentinel hospitals in Jing’an District were collected from January to December 2024. Nasopharyngeal swab samples were collected and tested for 21 respiratory pathogens using polymerase chain reaction (PCR) methods. Chi-square test and Cochran-Armitage trend test were used for data analyses. ResultsAmong the 1 907 ILI cases, 1 340 were tested positive (70.27%), including 1 160 (60.83%) virus-positive cases, 424 (22.23%) bacteria-positive cases , and 86 (4.51%) positive cases of other pathogens (fungi, mycoplasma, and chlamydia). The top five viruses by detection rate were: influenza virus (14.84%), SARS-CoV-2 (14.47%), rhinovirus (12.69%), adenovirus (7.08%), and parainfluenza virus (6.71%). The top two bacteria by detection rate were Streptococcus pneumoniae (14.47%) and Haemophilus influenzae (10.33%). Among other pathogens (fungi, mycoplasma, and chlamydia), Mycoplasma pneumoniae showed the highest detection rate (4.30%). In terms of age distribution, statistically significant differences were observed in the detection rates of SARS-CoV-2, Legionella, and Klebsiella pneumoniae (P<0.05), with the highest rates found in individuals aged 65 years and above. Statistically significant differences were also found in the detection rates of rhinovirus, adenovirus, enterovirus, common coronavirus, respiratory syncytial virus, bocavirus, parainfluenza virus, human metapenu-movirus, Streptococcus pneumoniae, Haemophilus influenzae, and Mycoplasma pneumoniae among different age groups (P<0.05), all showing the highest detection rates in the 0‒<15 years age group. In terms of seasonal distribution, SARS-CoV-2, adenovirus, parainfluenza virus, enterovirus, Streptococcus pneumoniae, Haemophilus influenzae, and Mycoplasma pneumoniae showed epidemic peaks in summer; rhinovirus, common coronavirus, bocavirus, and Klebsiella pneumoniae had higher detection rates in autumn. Influenza virus exhibited a peak incidence during winter, while human metapenu-movirus peaked in winter and spring. Significant differences in co-infection detection rates were observed among age groups, with the rate in children aged 0‒<15 years (34.81%) being the highest. The co-infection detection rate was higher in males than in females (P=0.019). Both the single-pathogen detection rate and the co-infection detection rate (P<0.001) varied significantly across seasons: the single-pathogen detection rate was highest in winter (62.06%), while the co-infection detection rate peaked in summer (31.20%) and was lowest in winter (14.52%). ConclusionBased on detection rates, the main pathogens in the ILI population of Jing’an District, Shanghai, 2024 were influenza virus, SARS-CoV-2, rhinovirus, adenovirus, parainfluenza virus, common coronavirus, enterovirus, Human metapenu-movirus, Streptococcus pneumoniae, Haemophilus influenzae, and Mycoplasma pneumoniae. Pathogen detection rates varied by age and season. Coinfection rates were much higher in children than in adults, higher in males than in females, and peaked in summer while being lowest in winter.

BackgroundBoth modified Suanzaoren Decoction and estazolam serve as effective treatments for chronic insomnia disorder （CID）. Default mode network （DMN） dysfunction is recognized as the primary pathophysiological mechanism underlying CID. However， it remains unclear whether the two treatments exert their therapeutic effects via convergent modulation of DMN functional connectivity. ObjectiveTo investigate the convergent remodeling characteristics of bidirectional effective connectivity （EC） of core DMN nodes with both the intra-network and the remaining whole-brain regions in CID patients with Yin-deficiency and fire-hyperactivity syndrome following the treatment with modified Suanzaoren Decoction or estazolam， so as to provide neuroimaging evidence for the convergent neural mechanisms underlying the therapeutic effects of both therapies in treating CID. MethodsEighty-two patients diagnosed with CID according to the International Classification of Sleep Disorder， third edition （ICSD-3） were consecutively recruited from the outpatient clinic of the Inner Mongolia Autonomous Region Mental Health Center from October 2020 to September 2023. Based on treatment preference， patients were assigned to receive a 6-week intervention in either the modified Suanzaoren Decoction group （n=52） or the estazolam group （n=30）. Ultimately， 66 patients completed follow-up assessments （modified Suanzaoren Decoction group， n=41； estazolam group， n=25）. All CID patients underwent resting-state functional magnetic resonance imaging scanning before and after treatment. Core DMN nodes including medial prefrontal cortex （mPFC）， bilateral inferior parietal lobule （IPL）， and precuneus （PCUN） were selected as seed regions. Granger causality analysis （GCA） was employed to assess bidirectional EC between the seed regions and both the other intra-DMN nodes and the remaining whole-brain regions. Hepatic and renal function indices were detected pre- and post-treatment to evaluate the safety profiles of both treatments. ResultsAt baseline， significant between-group differences were identified in EC from the left IPL to the left middle fronto-orbital gyrus/gyrus rectus （t=5.24， Z=4.84， voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）， with the modified Suanzaoren Decoction group exhibiting stronger EC than the estazolam group. No significant between-group differences were observed in EC between other core DMN nodes and remaining whole-brain regions （P>0.05）. Within-group pre- to post-treatment comparisons demonstrated consistent connectivity alterations in both groups. Specifically， EC from the left IPL to the supplementary motor area （SMA） decreased after treatment （modified Suanzaoren Decoction group： t=-6.28， Z=5.208； estazolam group： t=-5.58， Z=4.425）. Conversely， EC from the SMA to the left IPL increased （modified Suanzaoren Decoction group： t=5.89， Z=4.968； estazolam group： t=6.15， Z=4.720）. Furthermore， both groups demonstrated reduced EC from the PCUN to the left IPL （modified Suanzaoren Decoction group： t=-5.85， Z=4.94； estazolam group： t=-5.75， Z=4.515）， and elevated EC from the left IPL to the PCUN （modified Suanzaoren Decoction group： t=5.29， Z=4.579； estazolam group： t=4.55， Z=3.826） （voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）. No significant pre- to post-treatment differences were observed in hepatic or renal function indices in either group （P>0.05）. ConclusionIn CID patients with Yin-deficiency and fire-hyperactivity syndrome， both modified Suanzaoren Decoction and estazolam induce convergent bidirectional remodeling of EC between the left IPL and the SMA and the PCUN. ［Funded by Natural Science Fund Project of Inner Mongolia Autonomous Region （number， 2019MS08099）； ClinicalTrials.gov number， NCT06452953］

OBJECTIVES: To evaluate the clinical efficacy of hospital-prepared Chinese medicine Feigan granules for influenza patients. This study has been registered at the International Traditional Medicine Clinical Trial Registry platform (ITMCTR2025000162). METHODS: A prospective observational study was conducted on influenza patients who visited the Fever Clinic of the First Affiliated Hospital, Zhejiang University School of Medicine between February and March 2024. Patients were divided into the observation group (Feigan granules combined with conventional Western medicine) and the control group (conventional Western medicine). Main symptoms (including fever, cough and sore throat) and secondary symptoms (including chest tightness, poor appetite, muscle soreness and dry mouth) were evaluated with traditional Chinese medicine (TCM) symptom scale on the first day of the patient's visit and the third day after treatment. The degrees of improvement in the TCM symptom scores before and after treatment were compared using paired rank-sum test, and the differences in the overall symptom efficacy index between two groups were compared using the Wilcoxon test. RESULTS: A total of 217 influenza patients were included. After treatment, the TCM symptom scores of both groups were significantly improved compared with those before treatment (all P<0.01). The median differences in the main symptom score before and after treatment in the observation and the control groups were 7 points (95%CI: 6.0-8.0) and 6 points (95%CI: 6.0-8.0), respectively. The median difference in the secondary symptom score was 3 points (95%CI: 2.0-4.0) in both groups. The median differences in the total score were 9 points (95%CI: 8.0-10.5) and 8 points (95%CI: 7.0-10.0) in the observation and control groups, respectively. In the subgroup with an initial cough score >2, the improvement rates of total score (97.06% vs. 92.59%) and secondary symptoms (92.31% vs. 85.11%) in observation group were significantly higher than those in the control group (P<0.05); while there was no significant difference in the improvement rate of the main symptoms (95.59% vs. 90.74%, P>0.05). CONCLUSIONS Feigan granules can improve the TCM syndromes of influenza patients, especially for patients with more severe cough.
Humans ; Prospective Studies ; Influenza, Human/drug therapy* ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/therapeutic use* ; Female ; Male ; Middle Aged ; Adult ; Aged ; Adolescent ; Young Adult ; Treatment Outcome

Objective:To investigate the differential impact of ultra-high-resolution photon-counting detector CT (UHR PCD-CT) and energy-integrating detector CT (EID-CT) on image quality and calcified plaque-induced luminal stenosis in coronary CT angiography (CCTA).Methods:This retrospective analysis was conducted on patients who underwent both EID-CT and UHR PCD-CT CCTA at the Geriatric Hospital of Nanjing Medical University between January 2021 and November 2024. A total of 141 patients were included in the study, within 46 patients having scans within a 12-month interval. Image quality of all coronary artery segments was subjectively evaluated. Patients with paired scans (interval≤12 months) were included for calcified plaque analysis. Subjective visualization of calcified plaques evaluated. The blooming artifact was calculated as an objective evaluation index for assessing the calcified plaques. Additionally, the degree of coronary artery lumen stenosis resulting from calcified plaques was assessed, along with the measurement of plaque volume and the Agatston score. Changes in lumen stenosis between the two scans were also evaluated. The Wilcoxon signed-rank test was used to compare the subjective scores of coronary artery image quality and calcified plaques between the two groups, and paired-sample t-tests were used to compare the blooming artifact and lumen stenosis degree. Results:The PCD-CT image quality score was significantly higher than that of EID-CT [PCD-CT : 5 (4,5), EID-CT: 4 (4,5); Z=-21.38, P<0.001]. Compared to EID-CT, PCD-CT reduced the blooming artifact (PCD-CT: 38.88%±9.09%, EID-CT: 50.11%±11.52%; t=-12.97, P<0.001), significantly improving the subjective score for visualization of calcified plaques [PCD-CT: 5 (4,5), EID-CT: 3 (2,3); Z=-9.68, P<0.001], and the measured lumen stenosis was notably lower in PCD-CT(PCD-CT:34.88%±18.20%, EID-CT:45.31%±23.42%; t=-9.93, P<0.001). Among 129 analyzed calcified plaques, luminal stenosis was reduced on PCD-CT in 110 plaques (85.3%) and increased in 19 (14.7%), including 4 plaques that had unclear boundaries with the adjacent lumen in EID-CT CCTA images, making the stenosis difficult to assess. Conclusion:Compared to EID-CT, UHR PCD-CT for CCTA significantly improves coronary artery image quality, provides clearer visualization of calcified plaques and adjacent lumen details, and it can reduce the overestimation of coronary artery caleified plaque stenosis.

Objective To explore the risk factors of hemodynamic abnormalities in patients with coronary heart disease(CHD)after percutaneous coronary intervention(PCI)and to determine the contribution of these factors.Methods A total of 150 CHD patients undergoing PCI in our de-partment from January 2021 to December 2023 were prospectively recruited in the study.Accord-ing to the hemodynamic conditions,they were divided into a normal group(104 cases)and an abnor-mal group(46 cases).The causes of hemodynamic abnormalities were analyzed,and attributable risk percentage and population attributable risk percentage of these factors were estimated with logistic regression analysis.Results The hemodynamic abnormalities incidence was 30.7％.The abnormal group had significantly larger proportions of diabetes,smoking,and failures to take medication on time and in the prescribed dosage after surgery,longer stent length,and more stents,but lower level of high density lipoprotein cholesterol(HDLC)when compared with the normal group(P＜0.05,P＜0.01).Multivariate logistic regression analysis identified the following risk factors,estimated attributable risk percentage and population attributable risk percentage,diabetes,HDL-C,stent length,smoking,number of stents,and postoperative medication use in turn accord-ing to their contribution levels.Conclusion Rather complex causes lead to hemodynamic abnor-malities in CHD patients after PCI.In order of the contribution levels from high to low,they are diabetes,HDL-C,stent length,smoking,number of stents,and postoperative medication use.

Sacroiliac complex injuries are commonly seen in high-energy pelvic fractures. The injuries make a big difference in treatment patterns due to the diverse injury types, posing considerable challenges in formulating optimal treatment strategies, and hence are persistent clinical difficulties in orthopedic trauma. The clinical management of sacroiliac complex injuries presents several key challenges such as a non-negligible rate of missed diagnoses in associated vascular and visceral injuries, absence of standardized protocols for surgical approaches and reduction-fixation strategies across different injury patterns, and ongoing controversies regarding surgical indications and optimal timing for patients combined with concomitant lumbosacral plexus injuries. Currently, no systematic clinical guidelines are available for the diagnosis and treatment of sacroiliac complex injuries both domestically and internationally. To this end, the Pelvic and Acetabular Surgery Group, Orthopedic Branch, China International Exchange and Promotive Association for Medical and Health Care and Orthopedic Physician Branch, Chinese Medical Doctor Association organized a panel of domestic experts in the field to develop the Clinical guideline for the diagnosis and treatment of sacroiliac complex injuries ( version 2025), based on evidence-based medicine and adhering to the principles of scientific rigor, clinical applicability, and innovation. These guidelines provided 11 recommendations covering diagnosis, therapeutic principles and techniques, management protocols for lumbosacral plexus injuries, outcome evaluation, and postoperative rehabilitation pathways, etc., aiming to standardize the clinical management of sacroiliac complex injuries.

Recently, diffusion models have emerged as a promising paradigm for molecular design and optimization. However, most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geometries, with limited research on molecular sequence diffusion models. The International Union of Pure and Applied Chemistry (IUPAC) names are more akin to chemical natural language than the Simplified Molecular Input Line Entry System (SMILES) for organic compounds. In this work, we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language (SMILES) and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language. We propose DiffIUPAC, a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings. Evaluation results demonstrate that our model outperforms existing methods and successfully captures the semantic rules of both chemical languages. Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints. Additionally, to illustrate the model's applicability in drug design, we conducted case studies in functional group editing, analogue design and linker design.

BackgroundThe functional changes of the default mode network （DMN） are closely related to the onset of major depressive disorders. However， the relationship between the DMN subsystem （core subsystem， dorsomedial prefrontal cortex subsystem， medial temporal lobe subsystem） and symptoms of first-episode major depressive disorder remains unclear. ObjectiveTo investigate abnormal functional connectivity between DMN subsystems and the whole brain in first-episode major depressive disorder patients during the resting-state， and to analyse the correlations between these functional connectivity patterns and clinical symptoms， so as to reveal the potential neural mechanisms from the perspective of DMN subsystem. MethodsFrom September 2020 to September 2023， a total of 64 first-episode outpatients and inpatients meeting the diagnostic criteria for major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were enrolled at the Inner Mongolia Autonomous Region Mental Health Center as the study group. During the same period， 54 healthy volunteers matched for age， gender， and years of education were recruited from the community as the control group. Both groups were assessed using the Hamilton Depression Scale-24 item （HAMD-24）. Resting-state functional magnetic resonance images （rs-fMRI） of the two groups were acquired using a Siemens 3.0 T scanner， and differences in functional connectivity between DMN subsystems （core subsystem， dorsomedial prefrontal cortex subsystem， medial temporal lobe subsystem） and the whole brain were compared. The functional connectivity values of brain regions with statistically significant differences between the two groups were extracted. Spearman's rank correlation coefficient analysis was used to investigate the correlation between these functional connectivity values and HAMD-24 scores of the study group. ResultsUltimately， 46 patients and 43 controls completed the study. Compared with the control group， the study group exhibited significantly stronger functional connectivity in the following pathways： between the right superior parietal lobule （core subsystem） and right cerebellar lobule VIII （t=3.954， P<0.05， GRF-corrected）， between the right lateral temporal cortex （dorsomedial prefrontal cortex subsystem） and right cerebellar lobule VIII， right and left hippocampi， right medial， and paracingulate gyrus （t=4.595， 4.208， 5.200， 4.038， P<0.05， GRF-corrected）， and between the temporoparietal junction （dorsomedial prefrontal cortex subsystem） and left lingual gyrus and right cerebellar lobule VIII （t=3.557， 4.274， P<0.05， GRF-corrected）. Conversely， weaker functional connectivity was observed between the right inferior frontal gyrus and left gyrus rectus （t=-3.824， P<0.05， GRF-corrected）. Furthermore， within the study group， the functional connectivity values between the right lateral temporal cortex and right hippocampus， as well as between the temporoparietal junction and right cerebellar lobule VIII， were both negatively correlated with the HAMD-24 cognitive impairment factor score （r=-0.306， -0.318， P<0.05）. ConclusionIncreased functional connectivity between the DMN （specifically its core and dorsomedial prefrontal cortex subsystems） and cerebellum， partial limbic system， and lingual gyrus may be associated with the neuropathology of first-episode major depressive disorder. Furthermore， alterations in functional connectivity between the dorsomedial prefrontal cortex subsystem and both the cerebellum and hippocampus in these patients may be related to cognitive function. ［Funded by 2019 Annual Inner Mongolia Autonomous Region Natural Science Foundation Project （number， 2019MS03038）； 2023 Annual Inner Mongolia Autonomous Region Natural Science Foundation Project （number， 2023MS08028）］

Objective To construct a database for molecular mass spectra of toxins and drugs in order to facilitate the management and retrieval of mass spectra for nerve agents,metabolites and other small molecules.Methods Requirement analysis and functional design were performed using software engineering methods.The Spec2Vec algorithm was used for vector representation of mass spectra,while SMILES molecular structures were vectorized using the extended connectivity fingerprint(ECFP).A data storage model integrating structured information and vector representations was established using the Milvus database.Similarity search of mass spectra and molecular structures was conducted via vector similarity comparison and the FlashEntropySearch algorithm.Results The constructed database of mass spectra encompassed over 400,000 entries from such sources as OCAD,NIST,MASSBANK,metabolic products,and natural products of TCM,which was capable of searching for similarities in mass spectra and molecular structures.On a standard server,similarity search of mass spectra took no more than 5 seconds,while that of molecular structures took no more than 1 second.Conclusion The system enables efficient management of complex mass spectra and provides rapid retrieval and comparison of mass spectra-related information through advanced vector indexing technology,offering robust data support and research tools for toxicology and pharmacology.

Recently,diffusion models have emerged as a promising paradigm for molecular design and optimization.However,most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geom-etries,with limited research on molecular sequence diffusion models.The International Union of Pure and Applied Chemistry(IUPAC)names are more akin to chemical natural language than the simplified molecular input line entry system(SMILES)for organic compounds.In this work,we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language(SMILES)and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language.We propose DiffIUPAC,a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings.Evaluation results demonstrate that our model out-performs existing methods and successfully captures the semantic rules of both chemical languages.Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints.Additionally,to illustrate the model's applicability in drug design,we conducted case studies in functional group editing,analogue design and linker design.