Objective To assess the clinical efficacy of sodium hyaluronate （0.3%） eye drops combined with herbal self-heating steam eye mask in the treatment of dry eye disease. Methods A prospective randomized controlled clinical trial was performed on 60 patients diagnosed with dry eye at the ophthalmic clinic of a Grade A, Class Ⅲ hospital in Shanghai from June 2023 to September 2024. Specifically, patients were randomly divided into control group and study group. Patients in the control group were treated with sodium hyaluronate （0.3%） eye drops for six weeks; while in the study group, patients received the eye drops combined with the herbal self-heating steam eye mask mainly containing powders of Flos Buddlejae. Subsequently, comparisons and analysis were performed before and after treatment between the two groups in the clinical symptom questionnaire score traditional Chinese medicine （TCM syndrome score），the Chinese dry eye questionnaire score and determination of tear film fluorscein breakup time （FBUT）, and curative effect. Results The quality control standard of the herbal powder in the self-heating steam eye mask was established through TLC and HPLC, and good heating behavior of the herbal self-heating steam eye mask was ascertained heating temperature （43±5）℃; heating duration （≥20 min）, meeting requirements of the product quality control. After treatment for 6 weeks, FBUT was increased, while TCM syndrome score and the Chinese dry eye questionnaire score were both decreased in the study group （P<0.001）. Besides, compared with the control group, TCM syndrome score and the Chinese dry eye questionnaire score were much lower, while the FBUT were higher in the study group （P<0.001）. Moreover, the overall response rate in the study group （81.7%） was much better than that in the control group （25.9%）. Conclusion The combination of sodium hyaluronate （0.3%） eye drops with herbal self-heating steam eye mask could be applied to the clinical treatment of dry eye disease due to its good clinical effects on relieving dry eye symptoms.

Traditional Chinese medicine （TCM） diagnostics is a discipline that studies the basic theories and fundamental skills of diagnostic methods， disease diagnosis， and differentiation in accordance with the theories of TCM. The artificial intelligence （AI） technology has gained remarkable achievements in the intelligentization of the four diagnostic methods in TCM and the standardization of differentiation and diagnosis. However， it still faces many challenges. The standardization of clinical data collection is difficult， and the data quality is uneven， which affects the usability of the data. The integration of the four diagnostic information is insufficient. Most instruments can only collect data from a single diagnostic method， lacking overall integrity. The scientific nature of the diagnostic model needs to be improved. The existing models lack dynamics and the reasoning logic of TCM differentiation. The accuracy of intelligent methods needs to be improved， and the existing evaluation indicators cannot fully reflect the practical application effect of the model. Furthermore， the relevant laws and regulations are still not perfect， and data security and patient privacy lack guarantees. The cultivation of compound talents is insufficient， and there is a lack of interdisciplinary talents who are proficient in both TCM and AI. On this basis， this paper expounded on the current development status， difficulties， and bottlenecks of AI in TCM diagnosis and then explored the development trend of AI in the field of TCM diagnosis. It proposed solutions such as optimizing the data collection process， constructing multimodal diagnostic models， facilitating multi-disciplinary exchanges and cooperation， improving laws and regulations， and cultivating compound talents. It is hoped that modern， standardized， normalized， and intelligent TCM diagnosis can be further promoted， thereby providing new impetus and methods for the inheritance and innovation of TCM.

OBJECTIVE: To explore the genetic etiology of 46 Chinese pedigrees affected with Hereditary multiple exostoses (HME) and provide genetic counseling and reproductive intervention. METHODS: Whole-exome sequencing and Sanger sequencing were carried out on 87 patients from the 46 pedigrees to analyze the variants of EXT1 and EXT2 genes. Pathogenicity of the variants was assessed based on the guidelines from the American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP). Prenatal diagnosis and preimplantation genetic testing (PGT) were provided for couples with identified pathogenic mutations. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: LL-SC-SG-2014-010). RESULTS: In total 17 and 22 pathogenic variants were respectively identified in the EXT1 and EXT2 genes, among which 5 EXT1 and 12 EXT2 variants were unreported previously. Three patients with no family history were found to harbor de novo variants of the EXT1 gene. Twenty nine couples had opted for PGT or underwent prenatal diagnosis following natural conception, and 17 healthy babies were born. CONCLUSION This study has clarified the genetic etiology of 45 HME pedigrees and identified 17 novel variants, which has enriched the mutational spectrum of the EXT1 and EXT2 genes. Reproductive intervention through PGT and prenatal diagnosis have prevented the recurrence of HME in these families.
Humans ; Female ; Male ; Pedigree ; Exostoses, Multiple Hereditary/diagnosis* ; N-Acetylglucosaminyltransferases/genetics* ; Adult ; Exostosin 1 ; Asian People/genetics* ; Genetic Testing ; Exostosin 2 ; Mutation ; China ; Prenatal Diagnosis ; Pregnancy ; Genetic Counseling ; Preimplantation Diagnosis ; Exome Sequencing ; East Asian People

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

ObjectiveThis paper aims to systematically reveal the effect difference and mechanisms of Zishenwan against chronic prostatitis （CP） before and after salt-processing of Anemarrhenae rhizoma and Phellodendri chinensis cortex based on an integrated strategy of ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry （UPLC-Q-Orbitrap-MS/MS）， network pharmacology， and serum metabolomics. MethodsZishenwan samples before and after salt-processing of Anemarrhenae rhizoma and Phellodendri chinensis cortex were extracted by alcohol-water dual extraction. The chemical components of each sample were detected by UPLC-Q-Orbitrap-MS/MS， and differential components were screened by multivariate statistical analysis. Network pharmacology analysis was performed based on the identified chemical components of Zishenwan to construct a protein-protein interaction （PPI） network of "component， target， and pathway"， and the core components， targets， and pathways of Zishenwan against CP were screened. Forty-two male Sprague-Dawley （SD） rats were randomly divided into a blank group， a model group， a Qianliekang group （1.54 g·kg^-1）， low- and high-dose raw Zishenwan groups （1.8， 5.4 g·kg^-1）， and low- and high-dose salt-processed Zishenwan groups （1.8， 5.4 g·kg^-1）. The CP rat model was established by intraprostatic injection of carrageenan. After one week of recovery， the rats were administered the corresponding drugs for 21 days， while those in the blank group and model group received the same volume of normal saline. After the experiment， serum and tissue samples were collected to evaluate pharmacodynamic indicators including organ indices， histopathology， and inflammatory factors in serum. Subsequently， untargeted serum metabolomics technology was used to analyze metabolite changes and perform pathway enrichment analysis. The network pharmacology was used to construct a network of "differential metabolite， reaction， enzyme， and gene". ResultsA total of 76 components were identified in raw and salt-processed Zishenwan， and 34 differential components were screened by multivariate statistical analysis. Among them， the contents of 14 components， including berberine， berberrubine， and phellodendrine， increased after salt-processing， while the contents of 20 components， such as neomangiferin， decreased. The 28 active components and 185 potential targets were screened out by network pharmacology. The core components included berberine， phellodendrine， magnoflorine， and jatrorrhizine， and the core targets included signal transducer and activator of transcription 3 （STAT3）， protein kinase B1 （Akt1）， and transcription factor AP-1 （JUN）. These targets were significantly enriched in pro-inflammatory signaling pathways such as phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） and mitogen-activated protein kinase （MAPK）. Compared with the model group， all Zishenwan administration groups showed decreased prostate index， reduced levels of interleukin （IL）-1β， IL-18， and B-cell lymphoma-2 （Bcl-2） in serum （P<0.05， P<0.01）， as well as varying degrees of alleviation in histopathological damage. At the same dose， compared with the raw Zishenwan groups， the salt-processed Zishenwan groups showed lower prostate index， pathological scores， and IL-1β， IL-18， and Bcl-2 levels in serum， but the differences were not statistically significant. Metabolomics reveals that 38 differential metabolites were reversed after salt-processed Zishenwan administration. Both raw and salt-processed Zishenwan regulated pathways such as β-alanine metabolism and tryptophan metabolism. In addition to the common regulated pathways， the salt-processed group specifically regulated pantothenate and coenzyme A biosynthesis， pyrimidine metabolism， and arginine and proline metabolism. The intersecting pathways between network pharmacology and metabolomics were tryptophan metabolism and arginine and proline metabolism， with overlapping targets including monoamine oxidase A （MAOA） and arginase 1 （ARG1）. ConclusionThe increased contents of components such as berberine and phellodendrine in salt-processed Zishenwan may enhance its therapeutic effect on CP by inhibiting the PI3K/Akt and MAPK signaling pathways， along with multi-target regulation of tryptophan， arginine， and pantothenate metabolism pathways to comprehensively regulate inflammatory and immune responses.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective:To explore the spousal correlations of total cholesterol(TC),total triglyceride(TG),low-density lipoprotein cholesterol(LDL-C),and high-density lipoprotein cholesterol(HDL-C),and to investigate the reasons behind these spousal correlations.Methods:Participants and data were from the baseline survey of family-based cohort studies in Fangshan,Beijing and Tulou,Fujian.The ori-gin of spousal correlations were explored from perspectives of convergence,assortative mating,social ho-mogamy.Pearson's correlation and generalized linear models(GLM)were used to estimate the spousal correlation.Convergence was assessed by Pearson's correlation between the phenotypic differences be-tween couples and the duration of marriage,with GLM used for further validation.Pearson's correlation of genetic risk scores(GRS)and couple-specific Mendelian randomization(MR)were calculated to assess the genetic correlation and possible causal relationships between spouses.Two-independent-sample t-tests were used to compare GRS consistency across subgroups divided by education attainment,couple-specific MR and Q statistics used to test assortative mating in subgroups and intergroup differences.Results:In the study,342 couples(287 couples from Fangshan and 55 couples from Fujian)were included,with the average age of(64.91±8.76)years.Spousal correlations of TC,TG,HDL-C,and LDL-C showed statistically significant associations both before and after adjusting for covariates,with effect sizes of 0.229(95％CI:0.125-0.327),0.257(95％CI:0.155-0.354),0.179(95％CI:0.074-0.280),and 0.181(95％CI:0.076-0.282).For convergence,for each additional year of marriage,ΔTC increased by 0.016 mmol/L(95％CI:0.001-0.033 mmol/L),and ΔLDL-C increased by 0.017 mmol/L(95％CI:0.002-0.031 mmol/L).For assortative mating,GRS correlations and results of couple specific MR didn't show any statistical significance.For social homogamy,no differences in GRS or assortative mating were found between subgroups stratified by education attainment.Conclusion:The blood lipid in participants exhibit spousal phenotypic correlations,however,no effects of convergence,assortative mating or social homogamy were observed.More independent studies with larger sample sizes are warranted to further validate these findings in the future.

The purpose of this study was to evaluate the application value of targeted next-generation sequencing(tNGS)for rapid detection of Mycobacterium tuberculosis.From September 2021 to October 2024,1 178 clinical samples from hospitalized pa-tients at the Non-tuberculous Mycobacteria Disease Diagnosis and Treatment Center of Guangzhou Chest Hospital were collected,in-cluding 272 sputum samples,871 broncho alveolar lavage fluid(BALF)samples,and 35 other samples.These samples were analyzed with tNGS and the liquid culture+DNA microarray chip method(referred to as the"culture identification method"),and the detection results between methods were compared.The numbers of Mycobacterium tuberculosis complex(MTBC)samples identified with tNGS and the culture identification method were 172 and 127,respectively,and the numbers of non-tuberculous mycobacteria(NTM)samples detected were 517 and 474,respectively.The detection rate of Mycobacterium was 56.88%with tNGS and was significantly lower(49.49%)with the culture identification method(χ2=13.27,P<0.05).For NTM identification,when sputum was used,the detection rate of tNGS was higher than that of the culture identification method(χ2=24.14,P<0.05).However,when BALF was used,no significant difference in detection rates was observed between tNGS and the culture identification method(χ2=3.97,P=0.06).When different sample types from the same patient were analyzed with tNGS for NTM,BALF was found to be a better choice than sputum(χ2=4.05,P<0.05).However,with the culture identification method,we observed no significant difference between sample types(χ2=2.72,P=0.10).Furthermore,both the MTBC and NTM sequences detected with tNGS were significantly higher in the culture-positive group than the culture-negative group.With increasing sequence numbers,the proportion of cases in the culture-positive group progressively rose,whereas an inverse trend was observed in the culture-negative group.With clinical diagno-sis as the reference standard,the sensitivity,specificity,and Kappa value of tNGS and the culture identification method in identifying mycobacterial diseases were 85.41%,91.32%,0.74 and 74.73%,93.15%,0.63,respectively.Compared with the culture identifica-tion method,tNGS for rapid detection of Mycobacterium exhibited excellent sensitivity,specificity and consistency,and its timeliness should help clinicians make precise individualized treatment plans earlier.

Autism spectrum disorder(ASD)is a severe neurodevelopmental disorder with onset in child-hood,characterized by persistent social communication deficits and restricted,repetitive patterns of behavior.In recent years,its global prevalence has shown a continuous upward trend.However,there remains a lack of effective treatments capable of improving brain function in ASD.This article systematically reviews the mechanisms,clinical efficacy,and safety of HBOT in ASD,while exploring its potential therapeutic value.Research indicates that HBOT exerts its effects through the following mechanisms:enhancing plasma oxygen saturation,thereby improving oxygen supply to ischemic brain regions;inhibiting microglial activation,reducing pro-inflammatory cytokine levels;modulating gut microbiota homeostasis,restoring brain-gut axis dysfunction.Clinical studies demonstrate that when HBOT is combined with Applied Behavior Analysis(ABA),it significantly reduces behavioral scale scores in children with ASD while improving their social interaction,self-care abilities,and verbal communication.Additionally,HBOT positively regulates oxidative stress markers and enhances perfusion in specific brain regions.Regarding safety,strict adherence to operational protocols minimizes the risk of adverse effects(e.g.,baro-trauma).This review provides evidence-based support for the standardized application of HBOT in ASD.Future re-search should focus on optimizing treatment protocols(e.g.,pressure and oxygen concentration parameters)and evaluating long-term efficacy.

Objective To explore the effects of different education and examination methods on the examination results during the screening/evaluation of patent foramen ovale by contrast-enhanced transcranial Doppler(cTCD).Methods Patients who underwent cTCD screening/evaluation for patent foramen ovale in our hospital from May 2023 to February 2024 were retrospectively selected as the research subjects.The patients were divided into the observation group and the control group according to different education and examination methods during the peri-examination period.Patients who received video education,modified Valsalva maneuver,and injection of contrast agent with 20 mL syringe were included into the observation group,and patients who received artificial education,Valsalva maneuver,and injection of contrast agent with 10 mL syringe were included into the control group.The positive detection rate of patent foramen ovale,right-to-left shunt microbubble grading during Valsalva/modified Valsalva maneuver,systolic blood flow velocity,pulsatility index(PI),resistive index(RI),examination duration,total physician-patient communication time,whether occlusion surgery was performed,and patient satisfaction were compared between the two groups.Results The positive detection rate of patent foramen ovale by cTCD(82.93%vs.95.92%),the detection rate of the maximum amout(grade Ⅲ)of microbubbles(39.02%vs.61.22%),the total physician-patient communication time during the peri-examination period[11.30(10.00,14.00)minutes vs.8.23(7.00,10.00)minutes],the rate of occlusion surgery(48.78%vs.73.47%),and the total patient satisfaction(80.49%vs.91.84%)showed statistically significant differences between the control group and the observation group(P<0.05).Additionally,the receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC)for diagnosing patent foramen ovale were 0.718 in the control group and 0.855 in the observation group.Conclusion Peri-examination interventions such as video education,modified Valsalva maneuver,and injection of contrast agent with 20 mL syringe can improve the positive detection rate of patent foramen ovale,reduce ineffective physician-patient communication,and improve patient satisfaction.