AIM: To observe the clinical outcomes of Phorcides analytic engine-assisted topography-guided personalized laser assisted in situ keratomileusis(LASIK)for the treatment of myopia and astigmatism in virgin eyes with the refractive astigmatism significantly deviating from corneal topography.METHODS: Retrospective clinical study. A total of 32 cases(42 eyes)with myopia and astigmatism that received corneal topography-guided personalized LASIK in the Ophthalmology Refractive Surgery Center of the First Affiliated Hospital of Xi'an Jiaotong University from December 2019 to March 2021 were selected. The uncorrected distance visual acuity(UDVA), best corrected distance visual acuity(CDVA), refractive state and aberrations before and at 6 mo after surgery were recorded.RESULTS: There were 15 males and 17 females, with an age of 23.00(18.00, 29.25)years old; preoperative sphere was -5.75(-6.25, -4.00)D, and cylinder was -0.75(-1.38, -0.25)D. At 6 mo postoperatively, the UDVA exceeded the preoperative CDVA in 19 eyes(45%). The spherical equivalent(SEQ)of all eyes(100%)was -0.50 to +0.50 D at 6 mo postoperatively, and the postoperative SEQ of 23 eyes(55%)was -0.13 to +0.13 D. There were 33 eyes(79%)had a postoperative astigmatism ≤ 0.25 D, the target-induced astigmatism(TIA)was 0.94±0.96 D, and the surgically induced astigmatism(SIA)was 0.94±0.86 D, with no statistical significance between TIA and SIA(P>0.05). The astigmatism axial deviation ranged from -5° to +5° in 33 eyes(79%)at 6 mo postoperatively. Compared to pre-operation, the total higher-order aberrations and spherical aberrations within the central 6 mm diameter of the anterior corneal surface increased at 6 mo postoperatively(Z=-3.778, P<0.001; Z=-4.929, P<0.001); the postoperative coma aberrations had no change(Z=-1.763, P=0.078); the postoperative trefoil aberrations decreased(Z=-2.490, P=0.013). Compared to pre-operation, the Strehl ratio of the anterior corneal surface increased significantly at 6 mo after surgeries(t=-5.401, P=0.013).CONCLUSION: Using the Phorcides analytic engine to assist topography-guided personalized LASIK for the treatment of myopia and astigmatism in virgin eyes with the refractive astigmatism significantly deviating from topography-measured astigmatism can achieve good therapeutic effects. Postoperative UDVA exceeded preoperative CDVA in nearly half of the eyes, and the quality of postoperative corneal imaging was improved.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective To investigate the current status and analyze the factors affecting the osteoporosis knowledge among orthopedic nurses,and to provide references for improving osteoporosis knowledge among orthopedic nurses.Methods We investigated 5 681 orthopedic nurses from 621 hospitals in 31 provinces(autonomous regions/municipalities)using a convenient sampling method from September 2023 to November 2023.We collected information using a general information questionnaire and osteoporosis knowledge assessment tool.We used univariate and multivariate logistic regression to identify risk factors.Results A total of 5 204 orthopedic nurses were included.The total mean score of osteoporosis knowledge assessment tool of nurses was[13.00(12.00,14.00)],and 23.48％nurses had a low level of osteoporosis awareness.Logistic regression analysis showed that the age,title and position of the nurses,location of the hospital,the level of the hospital,whether to conduct the fracture liaison service/to set up the refracture prevention team,whether to use calcium tablets/vitamin D,whether to carry out anti-osteoporosis drug therapy,and whether to conduct topical lectures on osteoporosis or secondary fractures,were the factors that affected orthopedic nurses'knowledge of osteoporosis(P＜0.05).Conclusion The osteoporosis knowledge of orthopedic nurses needs to be improved.Nursing managers should carry out personalized interventions from both hospital and nurse levels to improve the osteoporosis knowledge of orthopedic nurses in our country.

Objective A cross-sectional survey on the postoperative home care status and barriers was conducted among elderly patients with osteoporotic fractures nationwide,in order to provide a basis for promoting the improvement of standardized home care for elderly patients with osteoporotic fractures.Methods From October to November 2023,a survey on the current situation and barriers of home environment protection was conducted among elderly patients with osteoporotic fractures in the orthopedic wards of 594 hospitals across 31 provinces(autonomous regions/municipalities directly under the central government)using a convenience sampling method.Results A total of 14,349 questionnaires were distributed,and 12,496 valid questionnaires were collected,resulting in an effective response rate of 87.09％.Among the patients,5,502 cases(44.03％)had implemented home-based prevention and treatment of osteoporosis before the fracture.2 095(16.77％)of the patients experienced a subsequent fracture,of which 65.11％of the patients who experienced a subsequent fracture received medication intervention after the initial fracture,while 19.86％of the patients who experienced a subsequent fracture did not comply with the treatment for osteoporosis after the initial fracture.Additionally,77.66％(n=1 627/2 095)of the patients received community medical services after the initial fracture.Barriers to care factors in the home environment after fracture from the patient's perspective presented the complexity of the social-ecological system model in 6 dimensions at 2 levels:micro(basic personal situation,physiological factors,psychological factors,and behavioural factors),and meso(social support factors,and healthcare worker factors).Conclusion In the vast majority of elderly patients in China,before osteoporotic fracture,home-based measures to prevent osteoporosis have not been adequately implemented;after the initial osteoporotic fracture,the pathway of re-fracture prevention and management in the patient's home environment is not yet complete and its popularity needs to be improved;the barriers to home care faced by elderly patients with osteoporotic fracture are complex.It is recommended to promote effective linkages among hospitals,community health centres and families to strengthen the closed-loop management of re-fracture prevention and management.

AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.

Objective To explore influencing factors of subsequent fracture among elderly osteoporotic patients and provide a basis for improving the management and early intervention after osteoporotic fracture.Methods A total of 14 349 elderly patients with osteoporotic fracture in 594 hospitals across 31 provinces(autonomous regions and municipalities)were selected by convenience sampling method from September to December 2023.A general information questionnaire and a clinical characteristics of fracture questionnaire were used.The univariate analysis and logistic regression were used to clarify the influencing factors and gender differences.Results A total of 11364 valid questionnaires were collected,with a valid questionnaire recovery rate of 79.20％.Gender,age,occupation,education,marital status,family history of osteoporosis,comorbid osteoarthropathies/rheumatism/ophthalmopathies,bone mineral density,risk of fall,risk of fracture grade,reasons and site for first fracture,whether to use walking aid and receive home rehabilitation guidance were associated with the occurrence of subsequent fracture.Gender comparisons found that widowhood,family history of osteoporosis,comorbid rheumatism,vertebral fracture,alcohol consumption,fall or no causative factor triggering the fracture,and educational level,home rehabilitation instruction were associated with the risk of subsequent fracture only in women(P＜0.05).Smoking was associated with the risk of subsequent fracture only in men(P＜0.05).Conclusion Osteoporotic subsequent fracture in the elderly is affected by multidimensional factors,with significant gender differences.The surveillance of key populations should be strengthened in prevention,control and intervention.

Objective·To investigate the efficacy and safety of a dose-reduced,all-oral lenalidomide/melphalan/prednisone acetate(RMP)regimen in elderly and frail patients with newly diagnosed multiple myeloma(NDMM).Methods·Elderly and frail NDMM patients who visited the Department of Hematology of Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,and the Third People's Hospital of Kunshan from April 2018 to March 2024 were retrospectively included.Clinical data and laboratory indicators were collected,and all patients were treated with the RMP regimen.SPSS 27.0 and R software were used for statistical analysis.Independent t-test was applied to normally distributed quantitative data,Mann-Whitney U test to non-normally distributed quantitative data,and x2 test and Fisher's exact probability method to qualitative data.Kaplan-Meier survival curves and Log-rank test were used for survival analysis.Results·Among the 22 elderly and frail NDMM patients treated with RMP,the median age was 76.3(68.4,95.0)years,and the median follow-up time was 25.5 months.The overall response rate(ORR)was 68.2%,and the rate of≥very good partial response(VGPR)was 36.4%.The median progression-free survival(PFS)was 20.53 months.The median PFS in the≤75-year-old group was 25.23(95%CI 12.95?37.52)months,while in the>75-year-old group it was 18.23(95%CI 14.86?21.61)months.There was no significant difference between the two groups.The median PFS in the≥partial response(PR)group was 20.67(95%CI 13.57?27.76)months,and in the

Objective·To investigate the efficacy and safety of a dose-reduced,all-oral lenalidomide/melphalan/prednisone acetate(RMP)regimen in elderly and frail patients with newly diagnosed multiple myeloma(NDMM).Methods·Elderly and frail NDMM patients who visited the Department of Hematology of Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,and the Third People's Hospital of Kunshan from April 2018 to March 2024 were retrospectively included.Clinical data and laboratory indicators were collected,and all patients were treated with the RMP regimen.SPSS 27.0 and R software were used for statistical analysis.Independent t-test was applied to normally distributed quantitative data,Mann-Whitney U test to non-normally distributed quantitative data,and x2 test and Fisher's exact probability method to qualitative data.Kaplan-Meier survival curves and Log-rank test were used for survival analysis.Results·Among the 22 elderly and frail NDMM patients treated with RMP,the median age was 76.3(68.4,95.0)years,and the median follow-up time was 25.5 months.The overall response rate(ORR)was 68.2%,and the rate of≥very good partial response(VGPR)was 36.4%.The median progression-free survival(PFS)was 20.53 months.The median PFS in the≤75-year-old group was 25.23(95%CI 12.95?37.52)months,while in the>75-year-old group it was 18.23(95%CI 14.86?21.61)months.There was no significant difference between the two groups.The median PFS in the≥partial response(PR)group was 20.67(95%CI 13.57?27.76)months,and in the

AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.