Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:Based on the stress process theory, the influencing factors and pathways of social alienation among young and middle-aged patients undergoing maintenance hemodialysis (MHD) were explored, so as to provide evidence for healthcare professionals to develop targeted interventions.Methods:Convenience sampling method was used to select young and middle-aged MHD patients from Nanyang Central Hospital between October 2023 and April 2024. A cross-sectional survey was conducted using a General Information Questionnaire, the General Alienation Scale, the Perceived Social Support Scale, and the Medical Coping Modes Questionnaire, the Social Impact Scale.Results:A total of 307 questionnaires were distributed, and 296 valid questionnaires were returned, with an effective response rate of 96.4%. Among the 296 participants, 190 were male and 106 were female; 124 were aged 18-45 years, and 172 were aged 46-59 years. The score of social alienation in young and middle-aged MHD patients was (40.79 ± 7.67). Stepwise multiple linear regression analysis revealed that education level, monthly household income per capita, duration of dialysis, number of chronic comorbidities, fatigue level, stigma, perceived social support, yielding coping style, avoidance coping style were significant influencing factors of social alienation in young and middle-aged MHD patients ( t values were -3.43-6.05, all P<0.05). The pathways analysis indicated that stigma, yielding coping style, and avoidance coping style had direct positive effects on social alienation in young and middle-aged MHD patients, with the effect values of 0.441, 0.286, 0.166, respectively (all P<0.05); perceived social support had a direct negative effect, with the effect value of -0.210 ( P<0.05); stigma and perceived social support exerted indirect effects on social alienation, with the effect values of 0.216, -0.108, respectively (both P<0.05). Conclusions:A relatively high level of social alienation was observed among young and middle-aged MHD patients, indicating an urgent need for improvement. Healthcare professionals should prioritize interventions targeting patient stigma. Enhancing perceived social support, offering psychological counseling, and teaching stress-coping strategies may help reduce maladaptive coping behaviors, thereby alleviating social alienation and promoting social reintegration.

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: 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*

As a biocatalyst, laccase has been widely studied and applied in the papermaking industry. However, the low catalytic efficiency and poor stability of natural laccase limit its application in the pulping process. To develop the laccase with high activity and strong tolerance, we carried out directed evolution for modification of the laccase derived from Bacillus pumilus and screened out the mutants F282L/F306L and Q275P from the random mutant library by high-throughput screening. The specific activities of F282L/F306L and Q275P were 280.87 U/mg and 453.94 U/mg, respectively, which were 1.42 times and 2.30 times that of the wild-type laccase. Q275P demonstrated significantly improved thermal stability, with the relative activity 20% higher than that of the wild-type laccase after incubation at 40 ℃, 50 ℃, and 70 ℃ for 4 h. F282L/F306L and Q275P showed greater tolerance to metal ions and organic solvents than the wild-type laccase. The K_m value of the wild-type laccase was 374.97 μmo/L, and those of F282L/F306L and Q275P were reduced to 318.96 μmo/L and 360.71 μmo/L, respectively, which suggested that the substrate affinity of laccase was improved after mutation. The k_cat values of F282L/F306L and Q275P for the substrate ABTS were 574.00 s^-1 and 898.03 s^-1, respectively, which were 1.1 times and 1.7 times that of the wild-type laccase, indicating the improved catalytic efficiency. Q275P demonstrated better performance than the wild-type laccase in pulping, as manifested by the reduction of 0.82 in the Kappa number and the increases of 2.00% ISO, 7.8%, and 7.2% in whiteness, tensile index, and breaking length, respectively. This work lays a foundation for improving the adaptation of laccase to the environment of the papermaking industry.
Laccase/chemistry* ; Directed Molecular Evolution ; Enzyme Stability ; Bacillus pumilus/genetics* ; Mutation ; Biocatalysis ; Catalysis

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 explore the correlation between the clinical, pathological, genetic features, prognosis, and tumor lymph node metastasis in patients with stage ⅠA-Ⅲ B lung invasive non-mucinous adenocarcinoma(INMA). Methods: A retrospective analysis was conducted on 67 eligible patients with INMA. Clinical data, histopathological assessments, and genetic testing were collected. Disease progression-free survival(PFS) was the primary endpoint through follow-up. The chi-square test or Fisher's exact test was used to analyse the correlation between tumour lymph node metastasis and clinicopathological and genetic characteristics. The Cox proportional hazards regression model and Kaplan-Meier method were used to analyse the impact of tumour lymph node metastasis on prognosis. Results: A total of 67 patients were included, aged 46-77 years, with a median age of 61 years. Age, gender, and smoking history were not significantly associated with tumor lymph node metastasis. Larger tumor diameter, tumor progression, and receiving postoperative adjuvant treatment were associated with tumour lymph node metastasis(P<0.05). Poorer differentiated tumors according to International Association for the Study of Lung Cancer(IASLC) grading system was more likely to have lymph node metastasis(P=0.043). There was no significant difference in the types of driver gene mutations and lymph node metastasis. However,EGFRmutations were more common in patients without lymph node metastasis, while co-mutations were more common in patients with lymph node metastasis. Lymph node metastasis was significantly associated with PFS. Patients without lymph node metastasis had a significantly better PFS compared to those with lymph node metastasis(P=0.002). Under different treatment conditions, patients without lymph node metastasis exhibited a significant advantage in PFS when untreated. While treatment showed a trend toward improved PFS, the difference did not reach statistical significance. Additionally, no significant differences in PFS were observed between patients with or without lymph node metastasis following chemotherapy or targeted therapy. Conclusion Lymph node metastasis in INMA patients is related to tumor size, progression status, and gene co-mutations, and is a key prognostic indicator affecting PFS.

Objective:To investigate the value of gadoxetate disodium-enhanced MRI combined with T 1 mapping in preoperative prediction of cytokeratin 19 (CK19) and glypican-3 (GPC3) positive dual-phenotype hepatocellular carcinoma (DPHCC). Methods:This case-control study included retrospectively enrolled patients with pathologically confirmed HCC from Central People′s Hospital of Zhanjiang (training set, n=85; December 2020 to July 2022) and the Second Affiliated Hospital, School of Medicine, South China University of Technology (test set, n=35; April 2023 to April 2024). Patients were categorized into CK19 and GPC3 positive DPHCC group (training set=19, test set=11) and non-DPHCC group (training set=66, test set=24) based on postoperative immunohistochemical staining. All patients received preoperative MRI scans, including gadoxetate disodium-enhanced imaging and T 1 mapping. Clinical data were collected, qualitative MRI features were evaluated, and quantitative parameters were measured, including signal intensity, T 1 values, apparent diffusion coefficient (ADC), tumor-to-liver ADC ratio (rADC), tumor-to-liver signal intensity ratio, and T 1 relaxation time reduction rate (ΔT 1%). Statistical comparisons between groups were performed using independent t-tests, Mann-Whitney U tests, or χ2 tests. Multivariate logistic regression identified independent predictors of CK19 and GPC3 positive DPHCC, and a combined model was constructed. Predictive performance was evaluated using area under the receiver operating characteristic curve (AUC), with DeLong test comparing model performance. Results:Significant intergroup differences were observed in alpha-fetoprotein (AFP), total bilirubin, direct bilirubin, DWI target sign, rADC, hepatobiliary-phase T 1 (T 1HBP), and ΔT 1% ( P<0.05). Multivariate analysis identified AFP>20 ng/ml ( OR=5.835, 95% CI 1.019-33.397, P=0.048), DWI target sign ( OR=13.408, 95% CI 2.216-81.131, P=0.005), and ΔT1%≤31% ( OR=14.429, 95% CI 2.166-96.125, P=0.006) as independent predictors of DPHCC. The AUC values of the aforementioned three independent predictors and the combined model for predicting DPHCC were 0.641 (95% CI 0.530-0.742), 0.679 (95% CI 0.569-0.777), 0.740 (95% CI 0.634-0.829), and 0.886 (95% CI 0.799-0.945) in the training set, and 0.568 (95% CI 0.390-0.743), 0.669 (95% CI 0.490-0.818), 0.689 (95% CI 0.511-0.843), and 0.824 (95% CI 0.658-0.931) in the test set, respectively. The DeLong test results showed that in the training set, the diagnostic performance of the combined model was superior to those of the three individual features ( Z=3.68, P<0.001; Z=3.15, P=0.002; Z=3.15, P=0.002). In the test cohort, the combined model demonstrated better diagnostic performance than AFP>20 ng/ml and ΔT 1%≤31% ( Z=2.15, P=0.032; Z=2.12, P=0.034), while no statistically significant difference was observed compared with the DWI target sign ( Z=1.77, P=0.076). Conclusion:The integrated model incorporating clinical data, gadoxetate disodium-enhanced MRI, and T 1 mapping parameters effectively predicts CK19 and GPC3 positive DPHCC.

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.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.