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*

"Weibing" is a fundamental concept in traditional Chinese medicine (TCM), representing a transitional state characterized by diminished self-regulatory abilities without overt physiological or social dysfunction. This perspective delves into the biological foundations and quantifiable markers of Weibing, aiming to establish a research framework for early disease intervention. Here, we propose the "Health Quadrant Classification" system, which divides the state of human body into health, sub-health, disease-susceptible state, and disease. We suggest the disease-susceptible stage emerges as a pivotal point for TCM interventions. To understand the intrinsic dynamics of this state, we propose laboratory and clinical studies utilizing time-series experiments and stress-induced disease susceptibility models. At the molecular level, bio-omics technologies and bioinformatics approaches are highlighted for uncovering intricate changes during disease progression. Furthermore, we discuss the application of mathematical models and artificial intelligence in developing early warning systems to anticipate and avert the transition from health to disease. This approach resonates with TCM's preventive philosophy, emphasizing proactive health maintenance and disease prevention. Ultimately, our perspective underscores the significance of integrating modern scientific methodologies with TCM principles to propel Weibing research and early intervention strategies forward.

Flavonoid 3-O-glucosyltransferase (3GT) is a key enzyme in the glucosidation of anthocyanins. To investigate the 3GT gene in rhododendron, we cloned an open reading frame (ORF) of 3GT gene (named Rh3GT) from Rhododendron hybridum Hort (Red cultivar) and then characterized this gene and the deduced protein in terms of the biochemical characteristics, expression level, and enzymatic function. The results showed that Rh3GT had a full length of 993 bp and encoded 330 amino acid residues. The deduced protein was hydrophilic, stable, weak acid, belonging to the glycosyltransferase family (GT-B type), with glutamine (Q) at position 44 in the PSPG box. The phylogenetic analysis showed that Rh3GT was most closely related to Vc3GT from Vaccinium corymbosum and Vm3GT from Vaccinium myrtillus. Rh3GT was expressed in the stems, leaves, and flowers and almost not expressed in the roots, with the highest expression level in petals during full blooming stage. Introduction of pCAMBIAL1302-Rh3GT into petals significantly up-regulated the expression level of Rh3GT and increased the total anthocyanin accumulation. Rh3GT was successfully expressed in Escherichia coli BL21 in the form of inclusion bodies with a size of about 36 kDa. The results of HPLC showed that the recombinant Rh3GT after denaturation, purification, and dilution could catalyze the synthesis of cyanidin and UDP-glucose to synthesize cyanidin 3-O-glucoside, indicating that the expressed protein had 3GT activity. This study provides basic data for further studying the molecular regulation mechanism of anthocyanin biosynthesis and theoretical support for molecular breeding of rhododendron.
Rhododendron/classification* ; Glucosyltransferases/metabolism* ; Cloning, Molecular ; Escherichia coli/metabolism* ; Recombinant Proteins/biosynthesis* ; Anthocyanins/biosynthesis* ; Phylogeny ; Plant Proteins/metabolism* ; Amino Acid Sequence

Objective To analyze the serum of patients with pancreatic cancer by fourier transform infrared spectroscopy(FTIR),explore the characteristic spectral parameters related to pancreatic cancer,and evaluate its potential clinical diagnostic value.Methods Serum samples were collected from 100 patients diagnosed with pancreatic cancer and 92 healthy volunteers at Chongming Hospital Affiliated to Shanghai Health Medical College from August 2022 to July 2023.These samples underwent FTIR and principal component analysis(PCA)to assess spectral differences between the two cohorts.The diagnostic potential of the serum spectra in distinguishing pancreatic cancer patients from healthy individuals was further evaluated using machine learning techniques,specifically support vector machine(SVM),k-nearest neighbor(kNN),and linear discriminant analysis(LDA)as classification methods.The diagnostic efficacy across various thresholds was evaluated using the receiver operating characteristic(ROC)curve.Results The findings indicate that the peak positions within the 1 090～1 070cm-1(1 076.537±15.183cm-1 vs 1 081.061±4.043cm-1),1 420～1 380 cm-1(1 399.958±1.508cm-1 vs 1 400.500±1.782cm-1),2 990～2 950cm-1(2 940.167±15.287cm-1 vs 2 945.124±7.498cm-1)and 3 500～3 000 cm-1(3 293.155±3.096cm-1 vs 3 294.893±2.582cm-1)range in the serum of individuals with pancreatic cancer exhibited a significant blue-shift compared to the healthy group and was statistically significant(t=2.265～4.236,all P<0.05),suggesting alterations in the structures of proteins,lipids and nucleic acids.Furthermore,a statistically significant disparity in peak absorption was observed between the group of patients with pancreatic cancer and the healthy group within the spectral ranges of 1 700～1 600cm-1(0.918±0.012cm-1 vs 0.858±0.021cm-1)and 3 500～3 000 cm-1(0.766±0.096cm-1 vs 0.804±0.090cm-1)(t=-24.031,2.830,all P<0.05),indicating that the protein concentration changes.PCA results showed that the PC2 axis was clearly separated,which could distinguish serum samples from patients with pancreatic cancer.Utilizing a machine learning model to differentiate the serum spectra of patients with pancreatic cancer from those of healthy controls,the sensitivity,the spesitivity,the specificity and accuracy of linear discriminant analysis(LDA)classification method were 93.2%,97.3%and 95.8%,respectively.The area under curve(AUC)as determined by ROC analysis was 0.982.Conclusion Serum spectroscopy using FTIR combined with PCA and machine learning model can be a simple,minimally invasive and reliable diagnostic test for pancreatic cancer detection.

BACKGROUND:Programmed cell death protein 1 belongs to the immunoglobulin gene superfamily and can regulate the differentiation of osteoblasts and affect bone homeostasis.However,there are few studies on the regulatory role and mechanism of programmed cell death protein 1 in diabetic osteoporosis.OBJECTIVE:To investigate the regulatory role and mechanism of programmed cell death protein 1 on osteogenic differentiation of rat bone marrow mesenchymal stem cells under high-glucose environment.METHODS:(1)Animal experiment:A total of 12 Sprageu-Dawley rats were randomized into a control group(n=6)and a model group(n=6).The control group was fed routinely,whereas the model group was injected intraperitoneally with streptozotocin to establish a model of type 1 diabetes mellitus,and the high-fat feed was fed for 8 weeks to establish a model of type 1 diabetic osteoporosis.After 8 weeks of feeding,the femurs of rats in the two groups were taken and subjected to hematoxylin-eosin staining and micro-CT assay.The mRNA expression of programmed cell death protein 1 and programmed death ligand 1 was detected.(2)Cell experiment:Passage 3 rat bone marrow mesenchymal stem cells were randomly divided into four groups:normal control group,high-glucose model group cultured in low glucose medium,programmed cell death protein 1-silenced group transfected with programmed cell death protein 1 siRNA,and programmed cell death protein 1-silenced null group transfected with siRNA-NC.After 48 hours of transfection,the normal control group was cultured in a new low-glucose medium,and the other three groups were cultured in a high-glucose medium for another 48 hours of culture followed by osteogenic induction.After 21 days of osteogenic induction,alizarin red staining,and qRT-PCR(programmed cell death protein 1 and RUNX2 mRNA expression)and western blot(β-catenin,GSK-3β,p-GSK-3β and Axin2 protein expression)were performed.RESULTS AND CONCLUSION:In the animal experiment,hematoxylin-eosin staining and micro-CT assay showed successful modeling of type 1 diabetic osteoporosis in the model group.qRT-PCR assay showed that the mRNA expression of programmed cell death protein 1 and programmed cell death ligand 1 was higher in the model group than the control group(P<0.05).In the cell experiment,the results of alizarin red staining showed that the ability of mineralized nodule formation was lower in the high-glucose model group and the programmed cell death protein 1-silenced null group than in the control group and the programmed cell death protein 1-silenced group.Compared with the normal control group,the programmed cell death protein 1 mRNA expression and GSK3β and Axin2 protein expression were elevated in the high-glucose model group and the programmed cell death protein 1-silenced null group(P<0.05),and the RUNX2 mRNA expression and p-GSK3β and β-catenin protein expression were decreased(P<0.05).Compared with the high-glucose model group and the programmed cell death protein 1-silenced null group,programmed cell death protein 1 mRNA expression and GSK3β and Axin2 protein expression were decreased in the programmed cell death protein 1-silenced group(P<0.05),and RUNX2 mRNA expression and p-GSK3β and β-catenin protein expression were elevated(P<0.05).To conclude,programmed cell death protein 1 silencing can activate the Wnt/β-catenin and improve the osteogenic differentiation of rat bone marrow mesenchymal stem cells under high-glucose conditions.

Objective To analyze the serum of patients with pancreatic cancer by fourier transform infrared spectroscopy(FTIR),explore the characteristic spectral parameters related to pancreatic cancer,and evaluate its potential clinical diagnostic value.Methods Serum samples were collected from 100 patients diagnosed with pancreatic cancer and 92 healthy volunteers at Chongming Hospital Affiliated to Shanghai Health Medical College from August 2022 to July 2023.These samples underwent FTIR and principal component analysis(PCA)to assess spectral differences between the two cohorts.The diagnostic potential of the serum spectra in distinguishing pancreatic cancer patients from healthy individuals was further evaluated using machine learning techniques,specifically support vector machine(SVM),k-nearest neighbor(kNN),and linear discriminant analysis(LDA)as classification methods.The diagnostic efficacy across various thresholds was evaluated using the receiver operating characteristic(ROC)curve.Results The findings indicate that the peak positions within the 1 090～1 070cm-1(1 076.537±15.183cm-1 vs 1 081.061±4.043cm-1),1 420～1 380 cm-1(1 399.958±1.508cm-1 vs 1 400.500±1.782cm-1),2 990～2 950cm-1(2 940.167±15.287cm-1 vs 2 945.124±7.498cm-1)and 3 500～3 000 cm-1(3 293.155±3.096cm-1 vs 3 294.893±2.582cm-1)range in the serum of individuals with pancreatic cancer exhibited a significant blue-shift compared to the healthy group and was statistically significant(t=2.265～4.236,all P<0.05),suggesting alterations in the structures of proteins,lipids and nucleic acids.Furthermore,a statistically significant disparity in peak absorption was observed between the group of patients with pancreatic cancer and the healthy group within the spectral ranges of 1 700～1 600cm-1(0.918±0.012cm-1 vs 0.858±0.021cm-1)and 3 500～3 000 cm-1(0.766±0.096cm-1 vs 0.804±0.090cm-1)(t=-24.031,2.830,all P<0.05),indicating that the protein concentration changes.PCA results showed that the PC2 axis was clearly separated,which could distinguish serum samples from patients with pancreatic cancer.Utilizing a machine learning model to differentiate the serum spectra of patients with pancreatic cancer from those of healthy controls,the sensitivity,the spesitivity,the specificity and accuracy of linear discriminant analysis(LDA)classification method were 93.2%,97.3%and 95.8%,respectively.The area under curve(AUC)as determined by ROC analysis was 0.982.Conclusion Serum spectroscopy using FTIR combined with PCA and machine learning model can be a simple,minimally invasive and reliable diagnostic test for pancreatic cancer detection.

BACKGROUND:Programmed cell death protein 1 belongs to the immunoglobulin gene superfamily and can regulate the differentiation of osteoblasts and affect bone homeostasis.However,there are few studies on the regulatory role and mechanism of programmed cell death protein 1 in diabetic osteoporosis.OBJECTIVE:To investigate the regulatory role and mechanism of programmed cell death protein 1 on osteogenic differentiation of rat bone marrow mesenchymal stem cells under high-glucose environment.METHODS:(1)Animal experiment:A total of 12 Sprageu-Dawley rats were randomized into a control group(n=6)and a model group(n=6).The control group was fed routinely,whereas the model group was injected intraperitoneally with streptozotocin to establish a model of type 1 diabetes mellitus,and the high-fat feed was fed for 8 weeks to establish a model of type 1 diabetic osteoporosis.After 8 weeks of feeding,the femurs of rats in the two groups were taken and subjected to hematoxylin-eosin staining and micro-CT assay.The mRNA expression of programmed cell death protein 1 and programmed death ligand 1 was detected.(2)Cell experiment:Passage 3 rat bone marrow mesenchymal stem cells were randomly divided into four groups:normal control group,high-glucose model group cultured in low glucose medium,programmed cell death protein 1-silenced group transfected with programmed cell death protein 1 siRNA,and programmed cell death protein 1-silenced null group transfected with siRNA-NC.After 48 hours of transfection,the normal control group was cultured in a new low-glucose medium,and the other three groups were cultured in a high-glucose medium for another 48 hours of culture followed by osteogenic induction.After 21 days of osteogenic induction,alizarin red staining,and qRT-PCR(programmed cell death protein 1 and RUNX2 mRNA expression)and western blot(β-catenin,GSK-3β,p-GSK-3β and Axin2 protein expression)were performed.RESULTS AND CONCLUSION:In the animal experiment,hematoxylin-eosin staining and micro-CT assay showed successful modeling of type 1 diabetic osteoporosis in the model group.qRT-PCR assay showed that the mRNA expression of programmed cell death protein 1 and programmed cell death ligand 1 was higher in the model group than the control group(P<0.05).In the cell experiment,the results of alizarin red staining showed that the ability of mineralized nodule formation was lower in the high-glucose model group and the programmed cell death protein 1-silenced null group than in the control group and the programmed cell death protein 1-silenced group.Compared with the normal control group,the programmed cell death protein 1 mRNA expression and GSK3β and Axin2 protein expression were elevated in the high-glucose model group and the programmed cell death protein 1-silenced null group(P<0.05),and the RUNX2 mRNA expression and p-GSK3β and β-catenin protein expression were decreased(P<0.05).Compared with the high-glucose model group and the programmed cell death protein 1-silenced null group,programmed cell death protein 1 mRNA expression and GSK3β and Axin2 protein expression were decreased in the programmed cell death protein 1-silenced group(P<0.05),and RUNX2 mRNA expression and p-GSK3β and β-catenin protein expression were elevated(P<0.05).To conclude,programmed cell death protein 1 silencing can activate the Wnt/β-catenin and improve the osteogenic differentiation of rat bone marrow mesenchymal stem cells under high-glucose conditions.

Objective To investigate the expression of miR-6768-5p in lung cancer tissue and its effect on the proliferation and invasion of lung cancer cells through targeted regulation of carboxypeptidase A4(CPA4).Methods The expression of miR-6768-5p in lung cancer tissues and adjacent tissues was analyzed u-sing the TCGA database.Quantitative real-time PCR(qPCR)was used to detect the expression of miR-6768-5p in human lung cancer cell lines(HCC1588,H1650,H1299,A549,HCC827)and normal alveolar epithelial cells(HPAEpiC cells).Lung cancer cells were transfected with NC mimics and miR-6768-5p mimics,respec-tively,and divided into NC group and miR-6768-5p group.The MTS assay and Matrigel invasion assay were used to detect the cell proliferation and invasion ability of each group,respectively.The putative binding sites of miR-6768-5p and CPA4 were verified using RNAhybrid software and dual-luciferase reporter gene experi-ment.The expression of CPA4 mRNA in each group of cells was detected by qPCR.The expression of AKT/c-MYC signaling pathway proteins in the cells of each group was analyzed by Western blot.Results Com-pared with the adjacent tissues,the relative expression level of miR-6768-5p in lung cancer tissues was signifi-cantly decreased,and the difference was statistically significant(P＜0.05).Compared with HPAEpiC cells,the relative expression level of miR-6768-5p was significantly decreased in lung cancer cell lines,and the differ-ence was statistically significant(P＜0.05).Compared with the NC group,the cell proliferation rate of miR-6768-5p group was significantly decreased(P＜0.05).The number of invasive cells in NC group and miR-6768-5p group was(131.30±12.55)and(37.45±7.77),respectively,and the number of invasive cells in miR-6768-5p group was significantly lower than that in NC group(P＜0.05).The relative expression level of CPA4 mRNA in H1299 cells of miR-6768-5p group was significantly lower than that in NC group(t=4.93,P＜0.05).Compared with the NC group,the expressions of AKT/c-myC signaling pathway proteins p-AKT,p-mTORC1,XIAP,MDM2 and C-myC proteins in miR-6768-5p group were significantly decreased.Conclusion The expression of miR-6768-5p is decreased in lung cancer tissues,and miR-6768-5p may inhibit the activation of AKT/c-MYC signaling pathway by targeting CPA4,and reduce the proliferation and invasion ability of lung cancer H1299 cells.

Objective:To study the biological traits and mutations of the influenza A (H3N2) virus in order to produce a vaccine and offer references for controlling and preventing influenza epidemics.Methods:Four strains of the influenza A(H3N2) virus were chosen from the Huai′an surveillance network laboratory. Nucleic acid extraction, library building, and sequencing (CridION x5 MKI Nanopore) were used to produce the whole-genome sequences. Using homologous alignments of whole-genome sequences, phylogenetic tree construction, and amino acid variant screening, bioinformatics analysis was carried out.Results:The nucleotide identity between 8 gene segments ranged from 97.1% to 100.0%. The gene that differed the most from the reference sequences was HA (97.1%-99.9%), and the gene that differed the least was MP (98.6%-99.9%). The HA gene (3.06%) and MP gene (1.43%) were the regions with the greatest and lowest frequencies of nucleotide site change, respectively. The rates of nucleotide change varied significantly between the genes ( χ2=14.293, P=0.046). Four influenza A(H3N2) virus strains′ whole-genome phylogenies from each of the eight gene segments maintained a roughly consistent topological structure. One strain was linked to the 3C.2a1b.1b clade, which was lost at the 142NWT, 149NGT(HA1), and 436NLS(NA). Three strains were linked to the 3C.2a1b.2a.1a clade lineage. Amantadine and NA inhibitors were effective against all Huai′an strains. Conclusions:The antigenicity of one strain of Huai'an strain changed and its matching with the vaccine strain of that year was low. It is suggested that the genetic surveillance of H3N2 influenza virus should be continuously strengthened to provide scientific basis for influenza prevention and control and influenza vaccine screening.

Objective: To determine the current prevalence of health risk behaviors among college students in Henan Province, and to conduct an in depth analysis of the impact of cumulative ecological risks on health risk behaviors, so as to provide scientific basis for promoting healthy development of adolescents. Methods: Using a multi stage stratified cluster sampling method, 9 743 college students from six universities in Henan Province were included as the research subjects from April to June 2023. A questionnaire survey was conducted using the College Student Cumulative Ecological Risk Scale and the China Urban Adolescent Health Related Behavior Survey Questionnaire (University Version). Data were analyzed by descriptive statistical analysis, Chi square test and binary Logistic regression. Results: The reporting rates of unhealthy eating behavior, unhealthy weight loss behaviors, lack of physical activity, daily risk behaviors, negative emotions, current smoking behavior current drinking behaviors, Internet addiction emotions and dangerous sexual behaviors among college students in Henan Province were 40.2%, 39.5%, 76.0%, 13.7%, 28.1%, 11.3%, 12.7%, 5.9% and 2.2%, respectively. The reporting rates of negative emotions, current smoking behaviors, current drinking behaviors, dangerous sexual behaviors and daily risk behaviors of college students were higher in boys than in girls ( χ 2=44.00, 995.20, 902.49, 121.95, 103.09, P <0.05). In terms of reporting rates of unhealthy diet, unhealthy weight loss and lack of exercise behavior, girls were higher than boys ( χ 2=107.59, 13.01, 145.83, P <0.05). Cumulative ecological risk was positively correlated with overall health risk behaviors. For every unit increase in the cumulative ecological risk index, the risk of health risk behaviors among college students increased by 48%. Conclusions The prevalence of health risk behaviors among college students is relatively common. It should adrocate for a healthy lifestyle, reduce the cumulative ecological risk and the occurrence of health risk behaviors to promote the healthy development of adolescents.