The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Objective:To explore the current status and influencing factors of fatigue in patients with Cushing syndrome in China, so as to provide a basis for clinical interventions.Methods:Convenience sampling was used to select 260 inpatients with Cushing syndrome who met the inclusion and exclusion criteria in 9 ClassⅢ Grade A hospitals within the 7 geographic subregions of China from February to April 2023 for the study. General Information Questionnaire, the Chinese version of the Multidimensional Fatigue Inventory-20, Barthel Index, and Self-Rating Depression Scale were used for the survey.Results:A total of 260 questionnaires were distributed and 241 valid questionnaires were recovered, with an effective recovery rate of 92.7% (241/260). The MFI-20 score of 241 patients with Cushing syndrome was 58.00 (46.00, 64.00). 65.1% (157/241) of patients with Cushing syndrome suffered from fatigue, and 73.2% (115/157) of patients with fatigue exhibited multidimensional fatigue. Univariate analysis showed that there were statistically significant differences in fatigue scores among patients with Cushing syndrome with different cultural levels, recurrence frequency, activity of daily living, hypertension, and depression ( P<0.05). Multiple linear regression analysis showed that depression was a risk factor for fatigue in patients with Cushing syndrome, and the difference was statistically significant ( P<0.05) . Conclusions:Fatigue in patients with Cushing syndrome needs attention. Medical and nursing staff should pay close attention to the psychological status of patients with Cushing syndrome, encourage them to actively cope, alleviate their depression, in order to improve their fatigue.

Objective:To explore the latent profile characteristics of cancer-related fatigue (CRF) in breast cancer patients during the rehabilitation phase and to analyze the influencing factors of different latent profiles.Methods:A convenience sampling method was used to recruit 190 breast cancer patients in the rehabilitation phase from the follow-up cohort at Peking Union Medical College Hospital between March and May 2024. Data was collected using a general information questionnaire, the Cancer Fatigue Scale, the Self-Rating Anxiety Scale, the Self-Rating Depression Scale, the Pittsburgh Sleep Quality Index and the Visual Analogue Scale. Logistic regression analysis was conducted to identify the influencing factors of CRF latent profiles. A total of 190 questionnaires were distributed, and 183 valid responses were collected, yielding an effective response rate of 96.32% (183/190) .Results:Three latent profiles of CRF were identified: mild fatigue, moderate fatigue, and severe fatigue. Menopausal status, depressive symptoms, and pain scores were significant influencing factors of the CRF latent profiles ( P<0.05) . Conclusions:Cancer-related fatigue in breast cancer patients during the rehabilitation phase exhibits distinct latent profile characteristics. Early identification of profile types and associated influencing factors may provide a scientific basis for healthcare professionals to develop targeted clinical interventions to help patients alleviate fatigue.

Objective:To explore the current status and research trends of cancer-related cognitive impairment (CRCI) worldwide, and to provide a reference for clinical nursing practice.Methods:Literature related to CRCI nursing was retrieved from the Web of Science Core Collection and China National Knowledge Infrastructure, with the search period from database inception to December 31, 2024. CiteSpace software was used to conduct bibliometric analysis of the included studies.Results:A total of 463 English and 43 Chinese articles were included. The overall number of publications showed an upward trend, with some degree of collaboration among institutions and authors. Research hotspots focused on influencing factors of CRCI, construction of risk prediction models, symptom management, and nursing interventions.Conclusions:The volume of CRCI nursing research has increased annually. Foreign countries started earlier in this field, while China is still in the initial stage. There is a need to strengthen international cooperation, multi-institutional collaboration, and interdisciplinary research to improve research quality and provide guidance for CRCI nursing research development in China.

BACKGROUND:A novel aggregation induced luminescence fluorescence probe based on the mechanism of intramolecular motility restriction can be used for the detection of disease markers,tumor diagnosis,and bacterial imaging recognition.OBJECTIVE:To prepare a near-infrared Ⅱ nanoprobe called FA-DSPE-PEG-AIE@NPs based on aggregation-induced luminescence,and to explore its potential of targeted fluorescence imaging and photothermal therapy for prostate cancer.METHODS:Lecithin,polyethylene glycol phospholipids,folate polyethylene glycol phospholipids,and aggregation induced luminescent molecule 2TT-oC26B were used as raw materials.The folate-targeted nanoprobe FA-DSPE-PEG-AIE@NPs were prepared by nanoprecipitation method,and basic characterization of the nanoprobe was detected.PC3 human prostate cancer cells and human umbilical vein endothelial cells were selected as experimental objects.The cytotoxicity and phototoxicity of FA-DSPE-PEG-AIE@NPs were detected.PC3 human prostate cancer cells were selected as the experimental objects.Flow cytometry and calcein/propidium iodide staining were used to assess the efficacy of photothermal therapy.PC3 human prostate cancer cells were injected subcutaneously into the abdomen of BALB/C nude mice to establish a tumor model,and nanoprobes FA-DSPE-PEG-AIE@NPs were injected into the tail vein.The mice were immediately subjected to near-infraced Ⅱ fluorescence imaging.12 hours later,the tumor was irradiated by laser for 5 minutes,and the photothermal treatment effect was observed within 14 days.RESULTS AND CONCLUSION:(1)The nanoprobes FA-DSPE-PEG-AIE@NPs with a mean diameter of(171.0±0.3)nm showed a well-defined spherical morphology.The nanoprobe had a wide absorption spectrum and tail emission extending to the near-infrared Ⅱ which emitted a bright near-infrared Ⅱ fluorescence signal under laser irradiation.(2)The nanoprobes FA-DSPE-PEG-AIE@NPs had low cytotoxicity and high phototoxicity.The results of flow cytometry and calcein/propidium iodide staining showed that nanoprobes FA-DSPE-PEG-AIE@NPs had an obvious photothermal killing effect on human prostate cancer cells.(3)The nanoprobes FA-DSPE-PEG-AIE@NPs successfully achieved near-infrared Ⅱ fluorescence imaging of mouse blood vessels and the maximum enrichment time of the tumor was 12 hours.The vessel widths of the hind leg and single blood vessels of abdomen were estimated to be 0.63 mm and 0.42 mm.The tumor volume of mice was significantly smaller after 14 days of treatment.(4)The results show that nanoprobes FA-DSPE-PEG-AIE@NPs can achieve near-infrared Ⅱ fluorescence imaging and photothermal therapy of prostate cancer effectively,which may provide a new method for early diagnosis and combined treatment of prostate cancer.

Objective:To apply the Timed Up and Go Test(TUGT)to investigate the correlation between motor function, emotional state, cognitive function, and sleep quality among elderly individuals in the Chinese community.Methods:A cross-sectional study was conducted, involving 739 subjects aged 60 to 90 years, who were randomly recruited from December 2021 to August 2023 across Beijing, Tianjin, Zhejiang, Guangdong, and Hainan Provinces in China.Basic demographic information was collected, and the TUGT was utilized to assess motor function.Based on the TUGT time(t), the subjects were divided into three groups: normal motor function group, mild motor abnormality group, and significant motor abnormality group.Cognitive function was evaluated using the Chinese Revised Mini-Mental State Examination(MMSE), while the Patient Health Questionnaire Depression Scale(PHQ-9)was employed to measure the degree of depression.Additionally, the Epworth Sleepiness Scale(ESS)was used to assess excessive daytime sleepiness.The correlation between subjects' motor function and their cognitive abilities, mood, and sleep was subsequently analyzed.Results:Systolic blood pressure, heart rate, PHQ-9, MMSE, and ESS scores were identified as significant factors influencing TUGT time.Specifically, TUGT time was positively correlated with PHQ-9 and ESS scores, while exhibiting negative correlations with systolic blood pressure, heart rate, and MMSE scores.Additionally, TUGT time was negatively correlated with the MMSE subcomponents of orientation, immediate memory, and verbal ability.All observed differences were statistically significant(all P<0.05).Logistic regression analysis indicated that an increase in the PHQ-9 score was associated with an odds ratio( OR)of 1.099(95% CI: 1.045-1.155, P<0.001)(mild motor abnormality group)and 1.150(95% CI: 1.066-1.242, P<0.001)(Significant motor abnormality group).Additionally, a reduction in the MMSE score was observed, with an OR of 0.939(95% CI: 0.886-0.995, P<0.001)(mild motor abnormality group)and 0.793(95% CI: 0.729-0.862, P<0.001)(Significant motor abnormality group).Furthermore, an increase in the ESS score was noted, with ORs of 1.139(95% CI: 1.094-1.186, P<0.001)(mild motor abnormality group)and 1.203(95% CI: 1.132-1.279, P<0.001)(Significant motor abnormality group).These findings suggest that these variables are independently related to decreased motor function. Conclusions:Depression, cognitive impairment, and excessive daytime sleepiness are independent risk factors for motor dysfunction among elderly individuals in community settings.The Timed Up and Go Test TUGT can be utilized for the early screening of motor function decline in this population.

Objective:To analyze the factors influencing postoperative complications and survival in patients undergoing hepatectomy for primary liver cancer (PLC).Methods:Two hundred and eighty-eight patients with PLC who underwent hepatectomy at Tianjin Medical University Cancer Hospital from April 2018 to December 2020 were prospectively enrolled, including 235 males and 53 females, aged (58.5±9.5) years. Nutritional evaluations included the nutritional risk screening 2002 (NRS-2002), patient-generated subjective global assessment (PG-SGA), and physical metrics such as body mass index, handgrip strength, arm circumference, mid-arm muscle circumference (MAMC), and triceps skinfold thickness (TSF). Based on the occurrence of postoperative complications during hospitalization including abdominal infection, bleeding, bile leakage, intra-abdominal fluid accumulation, pulmonary infection, intestinal fistula, and wound dehiscence, patients were divided into two groups: the complication group ( n=205) and the non-complication group ( n=83). Multivariate logistic regression analysis was performed to identify the factors related to postoperative complications, while Cox proportional hazards regression was used to evaluate the impact of various variables on postoperative survival. Survival analysis was conducted using the Kaplan-Meier method, and differences in survival rates were compared using the log-rank test. Results:Compared with the non-complication group, patients in the complication group had a significantly longer postoperative hospital stay [13(8, 16) d vs. 7(5, 9) d], higher proportions of low MAMC [34.1% (24/83) vs. 20.0% (41/205)], lower grip strength [28.9% (24/83) vs. 17.6% (36/205)], higher incidence of intraoperative blood loss ≥200 ml [44.6% (37/83) vs. 22.0% (45/205)], and greater proportion of resection involving ≥3 liver segments [45.8% (38/83) vs. 26.3% (54/205)] (all P<0.05). Multivariate logistic regression analysis identified the low MAMC ( OR=2.01, 95% CI: 1.09-3.71, P=0.025), intraoperative blood loss ≥200 ml ( OR=2.75, 95% CI: 1.55-4.90, P=0.001), and resection involving ≥3 liver segments ( OR=2.02, 95% CI: 1.15-3.55, P=0.015) as independent risk factors for postoperative complications in patients undergoing hepatectomy for PLC. Multivariate Cox regression analysis revealed that low TSF ( HR=1.94, 95% CI: 1.01-3.72, P=0.047), low handgrip strength ( HR=2.23, 95% CI: 1.29-3.88, P=0.004), and resection involving ≥3 liver segments ( HR=1.96, 95% CI: 1.15-3.36, P=0.014) were risk factors associated with poor survival after surgery. Conclusions:Low MAMC, intraoperative blood loss ≥200 ml, and resection involving ≥3 liver segments are risk factors for postoperative complications in patients undergoing hepatectomy for PLC, while low TSF, reduced handgrip strength, and resection involving ≥3 liver segments are predictors of poor postoperative survival.

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.

OBJECTIVES: To evaluate the impact of HBV infection on pre- and postpartum health-related quality of life (HRQoL) in pregnant women. METHODS: A prospective matched cohort consisting of 70 HBV-infected and 70 healthy pregnant women was recruited from the Fifth Affiliated Hospital of Guangzhou Medical University between April 17 and September 25, 2023. HRQoL of the participants was assessed at 16-24 weeks of gestation, between 32 weeks and delivery, and 5-13 weeks postpartum. Mixed linear models were used for evaluating temporal trends of HRQoL changes, and univariate ANOVA with multiple linear regression was used to identify the predictors of HRQoL. RESULTS: Compared with healthy pregnant women, HBV-infected pregnant women had consistently lower total HRQoL scores across all the 3 intervals, with the lowest scores observed between 32 weeks of gestation and delivery, during which these women had significantly reduced mental component scores (74.27±13.43 vs 80.21±12.9, P=0.009) and postpartum mental (76.52±16.19 vs 85.02±6.51, P<0.001) and physical component scale scores (77.17±14.71 vs 83.09±10.1, P=0.009). HBV infection was identified as an independent risk factor affecting HRQoL during late pregnancy and postpartum periods. Additional independent risk factors for postpartum HRQoL reduction included self-pay medical expenses, spouse's neutral attitude toward the current pregnancy, and preexisting comorbidities (all P<0.05). CONCLUSIONS HRQoL of pregnant women deteriorates progressively in late pregnancy, and HBV infection exacerbates reductions of physical function and role emotion in late pregnancy and after delivery, suggesting the importance of targeted interventions for financial burdens, partner support and comorbid conditions to improve HRQoL of pregnant women with HBV infection.
Humans ; Female ; Pregnancy ; Quality of Life ; Prospective Studies ; Postpartum Period ; Hepatitis B, Chronic/psychology* ; Adult ; Pregnancy Trimester, Third ; Pregnancy Trimester, Second ; Pregnancy Complications, Infectious

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.