Colorimetric analysis is a detection and quantification method based on observable color changes in response to analytes,which offers significant advantages including visually detectable signals,straightforward operation,rapid response,and low cost.Consequently,it plays a crucial role in a variety of fields.With increasingly diverse and complex application,colorimetric analysis requires continuous improvement in sensitivity,adaptability to diverse detection environments,and complex data handling capabilities.In recent years,the development of artificial intelligence technology,particularly within its core domain of machine learning(ML),has led to significant advancements in colorimetric analysis.The ML-assisted colorimetric analysis enables high-throughput and high-sensitivity detection,alongside automated analysis,thereby providing novel strategies to overcome the inherent limitations.This review categorized machine learning techniques and summarized their application in colorimetric analysis,introducing two fundamental categories of supervised learning,and unsupervised learning based on the division of core learning paradigms.The research progress of ML-assisted colorimetric analysis in the fields of environmental monitoring,biochemical detection,and food safety were summarized.Finally,the current challenges facing by this research area were analyzed and the research prospect of ML-assisted colorimetric analysis was outlined.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

BACKGROUND: In the interim analysis of MONARCH plus, adding abemaciclib to endocrine therapy (ET) improved progression-free survival (PFS) and objective response rate (ORR) in predominantly Chinese postmenopausal women with HR+/HER2- advanced breast cancer (ABC). This study presents the final pre-planned PFS analysis. METHODS: In the phase III MONARCH plus study, postmenopausal women in China, India, Brazil, and South Africa with HR+/HER2- ABC without prior systemic therapy in an advanced setting (cohort A) or progression on prior ET (cohort B) were randomized (2:1) to abemaciclib (150 mg twice daily [BID]) or placebo plus: anastrozole (1.0 mg/day) or letrozole (2.5 mg/day) (cohort A) or fulvestrant (500 mg on days 1 and 15 of cycle 1 and then on day 1 of each subsequent cycle) (cohort B). The primary endpoint was PFS of cohort A. Secondary endpoints included cohort B PFS (key secondary endpoint), ORR, overall survival (OS), safety, and health-related quality of life (HRQoL). RESULTS: In cohort A (abemaciclib: n  = 207; placebo: n  = 99), abemaciclib plus a non-steroidal aromatase inhibitor improved median PFS vs . placebo (28.27 months vs . 14.73 months, hazard ratio [HR]: 0.476; 95% confidence interval [95% CI]: 0.348-0.649). In cohort B (abemaciclib: n  = 104; placebo: n  = 53), abemaciclib plus fulvestrant improved median PFS vs . placebo (11.41 months vs . 5.59 months, HR: 0.480; 95% CI: 0.322-0.715). Abemaciclib numerically improved ORR. Although immature, a trend toward OS benefit with abemaciclib was observed (cohort A: HR: 0.893, 95% CI: 0.553-1.443; cohort B: HR: 0.512, 95% CI: 0.281-0.931). The most frequent grade ≥3 adverse events in the abemaciclib arms were neutropenia, leukopenia, anemia (both cohorts), and lymphocytopenia (cohort B). Abemaciclib did not cause clinically meaningful changes in patient-reported global health, functioning, or most symptoms vs . placebo. CONCLUSIONS: Abemaciclib plus ET led to improvements in PFS and ORR, a manageable safety profile, and sustained HRQoL, providing clinical benefit without a high toxicity burden or reduced quality of life. TRIAL REGISTRATION ClinicalTrials.gov (NCT02763566).
Humans ; Female ; Fulvestrant/therapeutic use* ; Breast Neoplasms/metabolism* ; Aminopyridines/therapeutic use* ; Benzimidazoles/therapeutic use* ; Middle Aged ; Aromatase Inhibitors/therapeutic use* ; Aged ; Receptor, ErbB-2/metabolism* ; Adult ; Letrozole/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Anastrozole/therapeutic use*

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Objective This study aimed to comprehensively analyze and compare the clinicopathological features and prognosis of Chinese patients with human epidermal growth factor receptor 2(HER2)-low early breast cancer(BC)and HER2-IHC0 BC. Methods Patients diagnosed with HER2-negative BC(N=999)at our institution between January 2011 and December 2015 formed our study population.Clinicopathological characteristics,association between estrogen receptor(ER)expression and HER2-low,and evolution of HER2 immunohistochemical(IHC)score were assessed.Kaplan-Meier method and log-rank test were used to compare the long-term survival outcomes(5-year follow-up)between the HER2-IHC0 and HER2-low groups. Results HER2-low BC group tended to demonstrate high expression of ER and more progesterone receptor(PgR)positivity than HER2-IHC0 BC group(P<0.001).The rate of HER2-low status increased with increasing ER expression levels(Mantel-Haenszel χ2 test,P<0.001,Pearson's R=0.159,P<0.001).Survival analysis revealed a significantly longer overall survival(OS)in HER2-low BC group than in HER2-IHC0 group(P=0.007)in the whole cohort and the hormone receptor(HR)-negative group.There were no significant differences between the two groups in terms of disease-free survival(DFS).The discordance rate of HER2 IHC scores between primary and metastatic sites was 36.84%. Conclusion HER2-low BC may not be regarded as a unique BC group in this population-based study due to similar clinicopathological features and prognostic roles.

Although conventional anti-osteoporotic drugs are effective in the prevention and treatment of osteoporosis(OP),they are also associated with a variety of adverse drug reactions in the course of their efficacy.Terpenoids have favorable therapeutic effects on bone resorption,bone formation,and concomitant inflammation.In this paper,we review a variety of herbal terpenoids commonly used in the treatment of OP,with a view to providing ideas for future clinical treatment and related basic research.

Although conventional anti-osteoporotic drugs are effective in the prevention and treatment of osteoporosis(OP),they are also associated with a variety of adverse drug reactions in the course of their efficacy.Terpenoids have favorable therapeutic effects on bone resorption,bone formation,and concomitant inflammation.In this paper,we review a variety of herbal terpenoids commonly used in the treatment of OP,with a view to providing ideas for future clinical treatment and related basic research.

With the continuous exploration of microemulsions as solvents for traditional Chinese medicine extraction, polyoxyethy-lene(35) castor oil(CrEL), a commonly used surfactant, is being utilized by researchers. However, the problem of detecting residues of this surfactant in microemulsion extracts has greatly hampered the further development of microemulsion solvents. Based on the chemical structures of the components in CrEL and the content determination method of castor oil in the 2020 edition of the Chinese Pharmacopoeia(Vol. Ⅳ), this study employed gas chromatography(GC) and single-factor experiments to optimize the preparation method of methyl ricinoleate from CrEL. The conversion coefficient between the two was validated, and the optimal sample preparation method was used to process microemulsion extracts of Zexie Decoction from three batches. The content of methyl ricinoleate generated was determined, and the content of CrEL in the microemulsion extracts of Zexie Decoction was calculated using the above conversion coefficient. The results showed that the optimal preparation method for CrEL was determined. Specifically, 10 mL of 1 mol·L~(-1) KOH-methanol solution was heated at 60 ℃ for 15 min in a water bath. Subsequently, 10 mL of boron trifluoride etherate-methanol(1∶3) solution was heated at 60 ℃ for 15 min in a water bath, followed by extraction with n-hexane twice. CrEL could stably produce 20.84% methyl ricinoleate. According to this conversion coefficient, the average mass concentration of CrEL in the three batches of Zexie Decoction microemulsion extracts was 11.94 mg·mL~(-1), which was not significantly different from the CrEL mass concentration of 11.57 mg·mL~(-1) during microemulsion formulation, indicating that the established content determination method of this study was highly accurate, sensitive, and repeatable. It can be used for subsequent research on microemulsion extracts of Zexie Decoction and provide a reference for quality control of other drug formulations containing CrEL.
Polyethylene Glycols/chemistry* ; Castor Oil ; Methanol ; Surface-Active Agents/chemistry* ; Solvents ; Water/chemistry* ; Emulsions/chemistry*

In this paper， the key technical problems in the research and development of famous classical formulas are analyzed. Firstly， the puzzled problem for a long-time， which is conversion relationship from medicinal metrology of Han dynasty （HD） to that of modern （gram，g）， is comprehensively expounded that one Liang （两） of HD=3 g is more appropriate. Secondly， the model and principles of quality consistency evaluation are given for the transformation from the quality of authoritative basic sample prepared by casserole （ABS-C） to the quality consistency in Laboratory process， pilot-scale process and industrial production. The consistency evaluation model is ξ_ABS-X=K₁（Q₁^ABS-X/Q₁^ABS-C）+K₂（Q₂^ABS-X/Q₂^ABS-C）+……+K_i（Q_i^ABS-X/Q_i^ABS-C）=∑K_i（Q_i^ABS-X/Q_i^ABS-C）（i=1，2，3……n）. In the formula， ABS-X means laboratory reference sample ABS-C （ABS-L）， pilot-scale ABS-C （ABS-mP） or industrial production ABS-C （ABS-P）， ξ_ABS-X means the quality consistency rate or similarity degree of ABS-L， ABS-mP and ABS-P processes with ABS-C， K_i means the weight of each quality evaluation index （i）， Q_i^ABS-X is the data of i in ABS-L， ABS-mP， ABS-P samples， and Q_i^ABS-C is the data （or mean） of i in ABS-C sample. Thirdly， in order to control the quality of the herbal medicines whose active ingredients were unknown， their chemical constituents should be studied deeply， and if necessary， the bioassay research should be carried out according to the main efficacy or indication of famous classical formulas. Finally， for the special processing of some herbal medicines， it is difficult to formulate the processing method， technology and standard of prepared slices. It is suggested that the scientific connotation and historical evolution of the special processing method should be thoroughly sorted out， and its technological characteristics are summarized， the modern processing technology and production processes are simulated， and then the corresponding processing methods and quality standards are formulated.