Objective To develop a deep learning method for small sample multi-omics data using attention mechanism and Meta-learning for the establishment of autism diagnosis model.Methods MLAN(Meta-learning based attentive network)consisting of the omics feature pre-reduction module,the multi-omics data fusion and feature learning module,and the parameter optimization module was designed.Firstly,differential expression analysis was performed on high-dimensional multi-omics data to preliminarily screen out unimportant features.Secondly,a multi-channel attention mechanism was used to learn the importances of every set of omics data and to realize data fusion,and a two-layer fully connected network was constructed to further extract latent features and realize the diagnosis task.Finally,the Meta-learning algorithm Reptile was used to optimize the initial parameters of the above model to obtain the optimal parameters.A total of 58 children's saliva samples were collected,including 21 children diagnosed with autism,12 children with social disorders,and 25 healthy controls,and the protein and metabolomics data were detected by mass spectrometry.All data were randomly divided into training set and test set by 4∶1,and the training set was divided into training data and validation data in the same way for model training and validation.The test set was used for the final evaluation of the model effect.Five baseline models and three ablated models were constructed and evaluated along with MLAN based on metrics including multi-classification accuracy,F1-macro and F1-weighted scores.Results The constructed multi-classification autism diagnosis model MLAN achieved multi-classification accuracy,F1-macro and F1-weighted scores of 0.850±0.066,0.817±0.103 and 0.834±0.087.The values of all three indicators were better than those of baseline models and the ablated models.Conclusion The proposed MLAN can effectively deal with heterogeneous multi-omics data with small samples and achieve good results,which is expected to provide assistance for the clinical diagnosis of autism.

The classic formula Mulisan is the 45th of the 93 formulas in the Catalogue of Ancient Classic Formulas （second batch） of Han medicine published by the National Administration of Traditional Chinese Medicine. It consists of Ostreae Concha， Astragali Radix， Ephedrae Radix et Rhizoma， and wheat， with the effect of replenishing qi and stopping sweating. It is a common formula in the clinical treatment with traditional Chinese medicine. This study analyzes the historical evolution， composition， dosage， original plants and their processing methods， decocting method， efficacy， indications， and modern clinical application of Mulisan by tracing， comparative analysis， and bibliometric methods. The results showed that Mulisan firstly appeared in the Pulse Classic written by WANG Shuhe in the Western Jin Dynasty. The formulation idea can be traced back to the Important Prescriptions Worth a Thousand Gold for Emergency in the Tang Dynasty. The herb composition， dosage， efficacy， and indications of Mulisan were first recorded in the Treatise on Diseases， Patterns， and formulas Related to Unification of the Three Etiologies in the Southern Song dynasty. In terms of original plants and their processing methods， Ostreae Concha is the shell of Ostrea rivularis， which should be calcined before use. Astragali Radix and Ephedrae Radix et Rhizoma are the dried roots of Astragalus membranaceus var. mongholicus and Ephedra sinica， respectively， the raw material of which should be used. Wheat is the dried mature fruit of T. aestivum， which can be used without processing， while the stir-fried fruit， being thin and deflated， demonstrates better effect. The composition of Mulisan is Ostreae Concha 8.26 g， Astragali Radix 8.26 g， Ephedrae Radix et Rhizoma 8.26 g， and wheat 7.92 g. The medicinal materials should be ground into coarse powder and decocted with 450 mL water to reach a volume of 240 mL， and the decoction should be taken warm. In modern clinical practice， Mulisan has a wide range of indications， including spontaneous sweating and night sweating caused by Yang deficiency or Qi deficiency. The clinical disease spectrum treated by Mulisan involves endocrine system diseases， neurological diseases， respiratory system diseases， and cancer. This formula plays a significant role in the treatment of internal medicine diseases in traditional Chinese medicine. This study aims to provide a scientific basis for the subsequent research， development， and clinical application of Mulisan.

The classic formula Mulisan is the 45th of the 93 formulas in the Catalogue of Ancient Classic Formulas （second batch） of Han medicine published by the National Administration of Traditional Chinese Medicine. It consists of Ostreae Concha， Astragali Radix， Ephedrae Radix et Rhizoma， and wheat， with the effect of replenishing qi and stopping sweating. It is a common formula in the clinical treatment with traditional Chinese medicine. This study analyzes the historical evolution， composition， dosage， original plants and their processing methods， decocting method， efficacy， indications， and modern clinical application of Mulisan by tracing， comparative analysis， and bibliometric methods. The results showed that Mulisan firstly appeared in the Pulse Classic written by WANG Shuhe in the Western Jin Dynasty. The formulation idea can be traced back to the Important Prescriptions Worth a Thousand Gold for Emergency in the Tang Dynasty. The herb composition， dosage， efficacy， and indications of Mulisan were first recorded in the Treatise on Diseases， Patterns， and formulas Related to Unification of the Three Etiologies in the Southern Song dynasty. In terms of original plants and their processing methods， Ostreae Concha is the shell of Ostrea rivularis， which should be calcined before use. Astragali Radix and Ephedrae Radix et Rhizoma are the dried roots of Astragalus membranaceus var. mongholicus and Ephedra sinica， respectively， the raw material of which should be used. Wheat is the dried mature fruit of T. aestivum， which can be used without processing， while the stir-fried fruit， being thin and deflated， demonstrates better effect. The composition of Mulisan is Ostreae Concha 8.26 g， Astragali Radix 8.26 g， Ephedrae Radix et Rhizoma 8.26 g， and wheat 7.92 g. The medicinal materials should be ground into coarse powder and decocted with 450 mL water to reach a volume of 240 mL， and the decoction should be taken warm. In modern clinical practice， Mulisan has a wide range of indications， including spontaneous sweating and night sweating caused by Yang deficiency or Qi deficiency. The clinical disease spectrum treated by Mulisan involves endocrine system diseases， neurological diseases， respiratory system diseases， and cancer. This formula plays a significant role in the treatment of internal medicine diseases in traditional Chinese medicine. This study aims to provide a scientific basis for the subsequent research， development， and clinical application of Mulisan.

BACKGROUND: Without timely and effective rehabilitation, hearing loss may profoundly affect human life quality. China has a large population of hearing-impaired individuals, which imposes a heavy health burden on society. Moreover, this population is projected to increase rapidly owing to China's aging society. METHODS: We used data from a population-representative epidemiological investigation of hearing loss and ear diseases in four Chinese provinces. We estimated the national prevalence using multiple linear regression of the age-group proportions and prevalence in 31 provinces with clustering analysis. We used years lived with disability (YLDs) to analyze the disease burden and forecasted the prevalence of hearing loss by 2060 in China. RESULTS: An estimated 115 million people had moderate-to-complete hearing loss in 2015 across the 31 provinces of China (8.4% of 1.37 billion people). Of these, 85.7% were older than age 50 years (99 million people) and 2.4% were younger than 20 years old (2.8 million people). Of all YLDs attributable to hearing loss, 68.9% were attributable to moderate-to-complete cases. By 2060, a projected 242 million people in China will have moderate-to-complete hearing loss, a 110.0% increase from 2015. CONCLUSIONS The hearing loss prevalence in China is high. Population aging and socioeconomic factors substantially affect the prevalence and severity of hearing loss and the disease burden. The prevalence and severity of hearing loss are unevenly distributed across different provinces. Future public health policies should take these trends and regional variations into account.
Humans ; China/epidemiology* ; Hearing Loss/epidemiology* ; Prevalence ; Middle Aged ; Male ; Female ; Adult ; Aged ; Adolescent ; Young Adult ; Child ; Child, Preschool ; Infant ; Aged, 80 and over ; Cost of Illness

Concepts are the cornerstone of the development of disciplines. The concepts of TCM present that a superior concept contains more subordinate concepts. The superordinate concepts are often used to refer to different subordinate concepts, which can refer to both superior concepts themselves and non-specific subordinate concepts, that is, the characteristics of subordinate coverage and indefinite reference, which cause confusion in concept meaning, concept relationships, reasoning logic, and other problems. Nowadays, the TCM scholars pay little attention to this characteristic. Therefore, this article analyzed this characteristic, discussed its impact on the inheritance and development of TCM, and proposed that starting from the anchoring of concepts and entities to clarify the connotation of concepts, looking forward to provide new ideas for the definition of the concepts of TCM and the development of the discipline.

Objective To develop a deep learning method for small sample multi-omics data using attention mechanism and Meta-learning for the establishment of autism diagnosis model.Methods MLAN(Meta-learning based attentive network)consisting of the omics feature pre-reduction module,the multi-omics data fusion and feature learning module,and the parameter optimization module was designed.Firstly,differential expression analysis was performed on high-dimensional multi-omics data to preliminarily screen out unimportant features.Secondly,a multi-channel attention mechanism was used to learn the importances of every set of omics data and to realize data fusion,and a two-layer fully connected network was constructed to further extract latent features and realize the diagnosis task.Finally,the Meta-learning algorithm Reptile was used to optimize the initial parameters of the above model to obtain the optimal parameters.A total of 58 children's saliva samples were collected,including 21 children diagnosed with autism,12 children with social disorders,and 25 healthy controls,and the protein and metabolomics data were detected by mass spectrometry.All data were randomly divided into training set and test set by 4∶1,and the training set was divided into training data and validation data in the same way for model training and validation.The test set was used for the final evaluation of the model effect.Five baseline models and three ablated models were constructed and evaluated along with MLAN based on metrics including multi-classification accuracy,F1-macro and F1-weighted scores.Results The constructed multi-classification autism diagnosis model MLAN achieved multi-classification accuracy,F1-macro and F1-weighted scores of 0.850±0.066,0.817±0.103 and 0.834±0.087.The values of all three indicators were better than those of baseline models and the ablated models.Conclusion The proposed MLAN can effectively deal with heterogeneous multi-omics data with small samples and achieve good results,which is expected to provide assistance for the clinical diagnosis of autism.

Objective:To explore the risk factors of ultrasound-guided closed reduction failure of unstable lateral humeral condylar fractures in children.Methods:A retrospective case-control study was conducted to analyze the clinical data of 158 children with unstable lateral humeral condyle fractures admitted to Anhui Provincial Children′s Hospital from January 2022 to August 2023, including 102 males and 56 females, aged 1-14 years [5(4, 8)years]. The patients were divided into reduction success group ( n=136) and reduction failure group ( n=22) according to the results of ultrasound-guided closed reduction. The gender, age, body mass index, injury side, time from injury to surgery, direction of sagittal plane displacement of the fracture fragment, Milch classification, Song classification, concomitant subcutaneous bruising or not, nighttime surgery or not, surgeons′ lack of experience or not, and concomitant elbow dislocation or not were recorded in both groups. Univariate analysis and binary Logistic regression analysis were used to evaluate and identify the independent risk factors for ultrasound-guided closed reduction failure of unstable lateral humeral condylar fractures in children. Results:Univariate analysis showed that there were significant differences in the time from injury to surgery, direction of sagittal plane displacement of the fracture fragment, and surgeons′ lack of experience or not between the reduction success group and reduction failure group ( P<0.01), while there were no significant differences in gender, age, body mass index, injury side, Milch classification, Song classification, concomitant subcutaneous bruising or not, nighttime surgery or not, or concomitant elbow dislocation or not between the two groups ( P>0.05). Binary Logistic regression analysis showed that the time from injury to surgery≥5 days ( OR=1.47, 95% CI 1.17, 1.86, P<0.01), sagittal anterior displacement of the fracture fragment ( OR=7.07, 95% CI, 1.79, 27.98, P<0.01) and surgeons′ lack of experience ( OR=4.67, 95% CI, 1.21, 18.05, P<0.05) were significantly correlated with ultrasound-guided closed reduction failure of unstable lateral humeral condylar fractures in children. Conclusion:The time from injury to surgery ≥5 days, sagittal anterior displacement of the fracture fragment and surgeons′ lack of experience are the independent risk factors for ultrasound-guided closed reduction failure of unstable lateral humeral condylar fractures in children.

Objective To optimize the formulation and preparation of diphenhydramine hydrochloride and caffeine orally disintegrating tablet. Methods Melt granulation technology of steric acid and API was used to mask the unpleasant tasting of diphenhydramine hydrochloride. The tablets were prepared by direct pressing the dry powder with CCMC-Na as disintegrating agent. The formulation was optimized by orthogonal experiments to achieve the shortest disintegration time and the best taste correction. Results The optimized formula of orally disintegrating tablet was as follows： diphenhydramine hydrochloride 25 mg, caffeine 60 mg, stearic acid 25 mg, aspatan 40 mg, blueberry essence 7 mg, mannitol 45 mg, MCC 210 mg, CCMC-NA 25 mg, SDS 8 mg and magnesium stearate 5 mg. Conclusion This preparation method for orally disintegrating tablet of diphenhydramine hydrochloride and caffeine is practical and easy for quality control.

We conducted a prospective study to assess the non-inferiority of adjuvant chemotherapy alone versus adjuvant concurrent chemoradiotherapy (CCRT) as an alternative strategy for patients with early-stage (FIGO 2009 stage IB-IIA) cervical cancer having risk factors after surgery. The condition was assessed in terms of prognosis, adverse effects, and quality of life. This randomized trial involved nine centers across China. Eligible patients were randomized to receive adjuvant chemotherapy or CCRT after surgery. The primary end-point was progression-free survival (PFS). From December 2012 to December 2014, 337 patients were subjected to randomization. Final analysis included 329 patients, including 165 in the adjuvant chemotherapy group and 164 in the adjuvant CCRT group. The median follow-up was 72.1 months. The three-year PFS rates were both 91.9%, and the five-year OS was 90.6% versus 90.0% in adjuvant chemotherapy and CCRT groups, respectively. No significant differences were observed in the PFS or OS between groups. The adjusted HR for PFS was 0.854 (95% confidence interval 0.415-1.757; P = 0.667) favoring adjuvant chemotherapy, excluding the predefined non-inferiority boundary of 1.9. The chemotherapy group showed a tendency toward good quality of life. In comparison with post-operative adjuvant CCRT, adjuvant chemotherapy treatment showed non-inferior efficacy in patients with early-stage cervical cancer having pathological risk factors. Adjuvant chemotherapy alone is a favorable alternative post-operative treatment.
Female ; Humans ; Uterine Cervical Neoplasms/drug therapy* ; Prospective Studies ; Quality of Life ; Neoplasm Staging ; Chemoradiotherapy ; Chemotherapy, Adjuvant/adverse effects* ; Adjuvants, Immunologic ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Retrospective Studies

Female ; Humans ; Hypoglycemic Agents/therapeutic use* ; Insulin Resistance ; Metformin/therapeutic use* ; Phosphatidate Phosphatase ; Pioglitazone/therapeutic use* ; Polycystic Ovary Syndrome/genetics*