OBJECTIVE To explore the characteristics and influential factors of pharmaceutical clinic service demands， providing evidence for optimizing pharmaceutical service models and facilitating pharmaceutical service models of pharmacist role transformation. METHODS A cross-sectional survey design was adopted， and 410 outpatient participants were selected from Fudan University Shanghai Cancer Center through convenience sampling for questionnaire administration from February to May 2025. Kano model was applied to analyze the demand attributes of 25 pharmaceutical services， while questionnaires were used to assess patients’ awareness and demand status. Subgroup analyses were conducted based on key demographic variables such as gender， age， educational attainment， and economic burdens， to SACA- systematically examine the differences in Kano attribute classification among patients in each subgroup. RESULTS The awareness rate of pharmaceutical outpatient services among patients was only 14.63%， yet those who were aware demonstrated a significantly higher demand rate for such services compared to those who were unaware （P＜0.001）. The demand for pharmaceutical clinic services exhibited a hierarchical characteristic： twelve items were identified as attractive attributes （e. g.， providing suggestions for more affordable treatment options， offering online consultation services， etc.）， five items as expected attributes （e.g.， having a good attitude and being able to patiently answer your questions， etc.）， three items as must-have attributes （e.g.， providing guidance on medication dosage and usage， providing guidance on medication precautions， etc.）， five items as indifferent attributes （e.g.， providing treatment plan recommendations based on the patient’s condition）. There were zero items classified as reverse attribute. Subgroup analysis revealed that female patients showed greater concern for “neat and clean attire of medical staff” than male patients （P＜0.001）； patients under 60 years of age demonstrated stronger demand for “providing treatment plan recommendations based on patients’ conditions” compared to patients aged 60 or above （P＝0.016）； those with below high school education placed greater emphasis on “providing guidance on medication precautions” compared to those with a high school education or above （P＝0.011）； patients with lower economic burdens exhibited stronger preferences for “neat and clean attire of medical staff ” （P＝0.002）. CONCLUSIONS The public awareness rate of pharmaceutical clinic services is considerably low； however， those who are aware of such services demonstrate significantly higher demand. The medication safety-related services and convenience-oriented demands should be prioritized in the development of pharmaceutical clinics. Moreover， the study also revealed that factors such as gender， age， educational level， and economic burdens exert significant influences on patients’ service demands.

When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture the multidimensional nature of disease transmission. In recent years, combining different models to improve infectious disease prediction has gradually become a research trend and hotspot. Existing studies have shown that combined models usually have higher prediction performance and better generalization ability. The current combined models mainly combine machine learning and other models, including time-series models, dynamic models, etcetera. In addition, integrated learning that combines diverse machine learning techniques also holds significant importance across various research domains. This paper reviews the progress of applying combined models around machine learning in infectious disease prediction to promote the innovation and practice of combined models for infectious diseases and help to build smarter and more efficient infectious disease early warning and prediction methods and systems.

Methods such as compartmental models, agent-based models, time series models, and machine learning can be used for the prediction of infectious disease incidence. When disease epidemics are complex, it is often difficult to use a single model to comprehensively and accurately capture the multi dimensional nature of the disease. Exploring the combined application of different models has gradually become a research trend and hotspot in recent years, and the prediction performance of combined models is often better than that of single ones. Current research related to combined models mainly focus on machine learning or compartmental models. In this review, we focus on the combination of compartmental models and other models, and summarize their combination principles, application progress, and advantages or disadvantages for the purpose of promoting the innovation and application of combined models for infectious disease incidence prediction, and establishing a more intelligent and efficient early warning and prediction method or systems for the prevention and control of infectious disease.

Objective:To compare the diagnostic efficacy of 68Ga-prostate-specific membrane antigen (PSMA)-617 PET/CT and multiparametric magnetic resonance imaging (mpMRI) in detecting extraprostatic extension (EPE) and seminal vesicle invasion (SVI) in prostate cancer. Methods:A retrospective analysis was conducted on the clinical data of 113 patients with localized prostate cancer who underwent both 68Ga-PSMA-617 PET/CT and mpMRI at Xiangya Hospital, Central South University, from May 2018 to May 2024 prior to radical prostatectomy (RP). The median age of the patients was 66.0 (61.3, 71.0) years old, with a median body mass index of 28.86 (19.01, 24.77) kg/m 2, and a median prostate-specific antigen (PSA) level of 13.50(9.26, 21.99) ng/ml. The pathological results after RP were used as the gold standard to compare the sensitivity, specificity, positive predictive value, and negative predictive value of the two imaging modalities in diagnosing EPE and SVI. Additionally, the diagnostic value of combining both imaging modalities was explored, employing a parallel strategy where a positive result from either modality was deemed positive, and only when both tests were negative was the result considered negative. Results:Pathological results after RP indicated EPE in 46 cases (40.71%) and SVI in 11 cases (9.70%). In diagnosing EPE, the sensitivity, specificity, positive predictive value, and negative predictive value of 68Ga-PSMA-617 PET/CT were 17.39% (8/46), 97.01% (65/67), 80.00% (8/10), and 63.11% (65/103), respectively, while for mpMRI they were 34.78% (16/46), 83.58% (56/67), 59.26% (16/27), and 65.12% (56/86), respectively. The sensitivity of mpMRI was significantly higher than that of 68Ga-PSMA-617 PET/CT ( P=0.048), while the specificity was the opposite ( P=0.008). When combining both imaging modalities, the sensitivity, specificity, positive predictive value, and negative predictive value were 45.65% (21/46), 80.60% (54/67), 61.76% (21/34), and 68.35% (54/79), respectively. In diagnosing SVI, the sensitivity, specificity, positive predictive value, and negative predictive value of 68Ga-PSMA-617 PET/CT were 27.27% (3/11), 96.08% (98/102), 42.86% (3/7), and 92.45% (98/106), respectively, while for mpMRI they were 36.36% (4/11), 88.24% (90/102), 25.00% (4/16), and 92.78% (90/97), respectively. The specificity of 68Ga-PSMA-617 PET/CT was significantly higher than that of mpMRI ( P=0.033). When combining both imaging modalities, the sensitivity, specificity, positive predictive value, and negative predictive value were 45.45% (5/11), 85.29% (87/102), 25.00% (5/20), and 93.55% (87/93), respectively. Conclusions:mpMRI has higher sensitivity in diagnosing EPE and SVI in prostate cancer, while 68Ga-PSMA-617 PET/CT shows higher specificity. The combined use of both imaging modalities can increase diagnostic sensitivity but may reduce specificity. PSMA PET/MRI may be a more accurate diagnostic tool for discerning EPE and SVI.

Objective:To understand the development status of maternal and child health care institutions in China from 2012 to 2022, identify the challenges they face, and provide references for further promoting the high-quality development of these institutions.Methods:Data from the China Health Statistics Yearbook (2013—2015), China Health and Family Planning Statistics Yearbook (2016—2017), and China Health and Wellness Statistics Yearbook (2018—2023) were used. Descriptive analysis was conducted on the data related to resource allocation and utilization efficiency, service provision, income and expenditure structure, and operational status of maternal and child health care institutions in China from 2012 to 2022, using methods such as fixed-base growth rate, year-on-year growth rate, and average annual growth rate. Results:From 2012 to 2022, the number of maternal and child health care institutions in China decreased from 3 044 to 3 031. In terms of resource allocation, the average annual growth rates of bed numbers and business-use floor area were 5.404% and 10.923%, respectively, while the average annual growth rate of health professionals was 7.183%. Regarding service provision, the average annual growth rates of outpatient visits and inpatient admissions were 3.954% and 1.572%, respectively. In terms of service efficiency, the bed occupancy rate decreased from 76.9% to 53.9%, and the average number of patients seen per physician per day decreased from 8.85 to 7.30. In terms of income and expenditure and operations, the income-expenditure surplus rate decreased from 9.16% to 5.41%, and the debt-to-asset ratio increased from 27.88% to 33.60%. During the same period, the average annual growth rates of bed numbers and business-use floor area in grassroots maternal and child health care institutions were 4.545% and 10.091%, respectively, lower than the national average. The number of outpatient visits increased from 89.03 million to 126.93 million, with an average annual growth rate of 3.610%, while the number of inpatient admissions decreased from 4.19 million to 3.91 million, with an average annual decline of 0.689%. The income-expenditure surplus rate of grassroots institutions decreased from 7.76% to 4.05%, 1.36 percentage points lower than the national level, and the debt-to-asset ratio increased from 27.53% to 36.37%, higher than the overall level.Conclusions:From 2012 to 2022, maternal and child health care institutions in China achieved certain developments in resource allocation and service scale. However, several challenges remain, including unbalanced resource allocation, decreased utilization efficiency, slowed growth in medical service volume, imbalanced income and expenditure structure, increased asset operation risks, and restricted development of grassroots institutions. It is recommended that relevant management departments and maternal and child health care institutions optimize resource allocation, plan for service transformation and upgrading, expand income sources, strengthen internal financial control, and reinforce the construction of high-quality and efficient maternal and child health care systems to promote the high-quality development of maternal and child health care institutions in China.

Objective To study the application of mesoporous silica nanoparticle(MSN)as drug carriers in the treatment of osteoarthritis(OA).Methods Core-cone structured MSN(MSN-CC)was synthesized by sol-gel method,modified by polyethyleneimine(PEI),and loaded with hyaluronic acid synthase 2(HAS2).Forty OA model rats were randomly assigned to OA group,MSN-CC-PEI group,hyaluronic acid(HA)group,or MSN-CC-PEI-HAS2 group.Ten healthy rats were assigned to control group.Normal saline 100 μL was injected into the knee joint in the control group and OA group.MSN-CC-PEI 100 μL,HA solution 100 μL,and MSN-CC-PEI-HAS2 100 μL were injected in MSN-CC-PEI group,HA group,and MSN-CC-PEI-HAS2 group,respectively.The levels of HA,interleukin-1β(IL-1β),and prostaglandin E2(PGE2)in the joint effusion and the foot swelling degree were measured at 1,2,and 3 weeks after injection.Results HA level in the MSN-CC-PEI-HAS2 group was significantly lower than that in the HA group at 1 week after intervention(P<0.05),while HA level in the MSN-CC-PEI-HAS2 group was significantly higher than that in the HA group at 2 and 3 weeks after intervention(P<0.05).With the time going on,HA level in the HA group was gradually decreased(P<0.05),but HA level in the MSN-CC-PEI-HAS2 group was gradually increased(P<0.05).At 1 and 2 weeks after intervention,compared with the HA group,IL-1β,PGE2 and foot swelling degree in the MSN-CC-PEI-HAS2 group were increased(P<0.05).At 3 weeks after intervention,compared with the HA group,IL-1β,PGE2 and foot swelling degree in the MSN-CC-PEI-HAS2 group were decreased(P<0.05).With the time going on,IL-1β,PGE2 and foot swelling degree in the HA group and MSN-CC-PEI-HAS2 group were gradually decreased(P<0.05).Conclusion MSN carrier can stably stimulate the secretion of endogenous HA,reduce the inflammatory response within joint cavity of OA rats,and improve the joint morphology and soft tissue pathological changes.

Neuroinflammatory response runs through the pathological process of epilepsy, and the regulation of proinflammatory factors such as (tumor necrosis factor-α, TNF-α), (interleukin, IL)-1β, IL-6 and Toll-like receptors 4/nuclear factor-kappa B signaling pathways may help improve epilepsy symptoms. Traditional Chinese medicines with anti-epileptic effects can be mainly divided into the following 6 categories: Pinggan Xifeng drugs (平肝息风药, liver-calming and wind-extinguishing herbs), Qingre drugs (清热药, heat-clearing drugs), Huatan drugs (化痰药, phlegm-relieving drugs), Huoxue Huayu drugs (活血化瘀药, circulation-promoting and stasis-removing drugs), Buxu drugs (补虚药, tonifying drugs), and Kaijiao drugs (开窍药, consciousness-restoring drugs). The active ingredients contained in these traditional Chinese medicines can play a therapeutic role in epilepsy treatment by regulating the release of key proinflammatory factors and inflammatory signaling pathways. Adverse reactions caused by Chinese patent medicines involve a variety of factors, which can be summarized into the process of medicinal materials preparation, the principle of traditional Chinese medicine compatibility, the accuracy of dialectical treatment, individual differences, etc. When using anti-epileptic Chinese medicine in clinical practice, it should be flexibly applied according to specific conditions to achieve the goal of precise treatment.

When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture the multidimensional nature of disease transmission. In recent years, combining different models to improve infectious disease prediction has gradually become a research trend and hotspot. Existing studies have shown that combined models usually have higher prediction performance and better generalization ability. The current combined models mainly combine machine learning and other models, including time-series models, dynamic models, etcetera. In addition, integrated learning that combines diverse machine learning techniques also holds significant importance across various research domains. This paper reviews the progress of applying combined models around machine learning in infectious disease prediction to promote the innovation and practice of combined models for infectious diseases and help to build smarter and more efficient infectious disease early warning and prediction methods and systems.

Methods such as compartmental models, agent-based models, time series models, and machine learning can be used for the prediction of infectious disease incidence. When disease epidemics are complex, it is often difficult to use a single model to comprehensively and accurately capture the multi dimensional nature of the disease. Exploring the combined application of different models has gradually become a research trend and hotspot in recent years, and the prediction performance of combined models is often better than that of single ones. Current research related to combined models mainly focus on machine learning or compartmental models. In this review, we focus on the combination of compartmental models and other models, and summarize their combination principles, application progress, and advantages or disadvantages for the purpose of promoting the innovation and application of combined models for infectious disease incidence prediction, and establishing a more intelligent and efficient early warning and prediction method or systems for the prevention and control of infectious disease.

Neuroinflammatory response runs through the pathological process of epilepsy, and the regulation of proinflammatory factors such as (tumor necrosis factor-α, TNF-α), (interleukin, IL)-1β, IL-6 and Toll-like receptors 4/nuclear factor-kappa B signaling pathways may help improve epilepsy symptoms. Traditional Chinese medicines with anti-epileptic effects can be mainly divided into the following 6 categories: Pinggan Xifeng drugs (平肝息风药, liver-calming and wind-extinguishing herbs), Qingre drugs (清热药, heat-clearing drugs), Huatan drugs (化痰药, phlegm-relieving drugs), Huoxue Huayu drugs (活血化瘀药, circulation-promoting and stasis-removing drugs), Buxu drugs (补虚药, tonifying drugs), and Kaijiao drugs (开窍药, consciousness-restoring drugs). The active ingredients contained in these traditional Chinese medicines can play a therapeutic role in epilepsy treatment by regulating the release of key proinflammatory factors and inflammatory signaling pathways. Adverse reactions caused by Chinese patent medicines involve a variety of factors, which can be summarized into the process of medicinal materials preparation, the principle of traditional Chinese medicine compatibility, the accuracy of dialectical treatment, individual differences, etc. When using anti-epileptic Chinese medicine in clinical practice, it should be flexibly applied according to specific conditions to achieve the goal of precise treatment.