Integrating image and gene-data with a semi-supervised attention model for prediction of KRAS gene mutation status in non-small cell lung cancer.

KRAS is a pathogenic gene frequently implicated in non-small cell lung cancer (NSCLC). However, biopsy as a diagnostic method has practical limitations. Therefore, it is important to accurately determine the mutation status of the KRAS gene non-invasively by combining NSCLC CT images and genetic data for early diagnosis and subsequent targeted therapy of patients. This paper proposes a Semi-supervised Multimodal Multiscale Attention Model (S2MMAM). S2MMAM comprises a Supervised Multilevel Fusion Segmentation Network (SMF-SN) and a Semi-supervised Multimodal Fusion Classification Network (S2MF-CN). S2MMAM facilitates the execution of the classification task by transferring the useful information captured in SMF-SN to the S2MF-CN to improve the model prediction accuracy. In SMF-SN, we propose a Triple Attention-guided Feature Aggregation module for obtaining segmentation features that incorporate high-level semantic abstract features and low-level semantic detail features. Segmentation features provide pre-guidance and key information expansion for S2MF-CN. S2MF-CN shares the encoder and decoder parameters of SMF-SN, which enables S2MF-CN to obtain rich classification features. S2MF-CN uses the proposed Intra and Inter Mutual Guidance Attention Fusion (I2MGAF) module to first guide segmentation and classification feature fusion to extract hidden multi-scale contextual information. I2MGAF then guides the multidimensional fusion of genetic data and CT image data to compensate for the lack of information in single modality data. S2MMAM achieved 83.27% AUC and 81.67% accuracy in predicting KRAS gene mutation status in NSCLC. This method uses medical image CT and genetic data to effectively improve the accuracy of predicting KRAS gene mutation status in NSCLC.

Ubiquitin-specific protease 5 promotes bladder cancer progression through stabilizing Twist1.

Aberrant activation of the epithelial-mesenchymal transition (EMT) pathway drives the development of solid tumors, which is precisely regulated by core EMT-related transcription factors, including Twist1. However, the expression pattern and regulatory mechanism of Twist1 in the progression of bladder cancer is still unclear. In this study, we explore the role of Twist1 in the progression of bladder cancer. We discovered that the EMT regulon Twist1 protein, but not Twist1 mRNA, is overexpressed in bladder cancer samples using RT-qPCR, western blot and immunohistochemistry (IHC). Mechanistically, co-immunoprecipitation (Co-IP) coupled with liquid chromatography and tandem mass spectrometry identified USP5 as a binding partner of Twist1, and the binding of Twist1 to ubiquitin-specific protease 5 (USP5) stabilizes Twist through its deubiquitinase activity to activate the EMT. Further studies found that USP5 depletion reduces cell proliferation, invasion and the EMT in bladder cancer cells, and ectopic expression of Twist1 rescues the adverse effects of USP5 loss on cell invasion and the EMT. A xenograft tumor model was used to reconfirmed the inhibitor effect of silencing USP5 expression on tumorigenesis in vivo. In addition, USP5 protein levels are significantly elevated and positively associated with Twist1 levels in clinical bladder cancer samples. Collectively, our study revealed that USP5-Twist1 axis is a novel regulatory mechanism driving bladder cancer progression and that approaches targeting USP5 may become a promising cancer treatment strategy.

A computed tomography-based comprehensive standardized adrenal tumor scoring model for predicting the perioperative outcomes of retroperitoneal laparoscopic adrenal surgery.

Background: Many imaging scoring models have been developed for tumor surgery to provide critical guidance for the selection of surgical methods. However, little research has been aimed at developing scoring models for adrenal tumors and retroperitoneal laparoscopic adrenal surgery (RLAS), which has become the primary technique for treating adrenal tumors. The study set out to establish a computed tomography (CT)-based adrenal tumor scoring model for predicting perioperative outcomes in patients with adrenal tumors who have undergone RLAS. Methods: The retrospective analysis included 306 patients with adrenal tumors diagnosed by preoperative unenhanced or enhanced CT from January 2014 to August 2018 in the First Affiliated Hospital of Fujian Medical University. CT images were used to quantify the tumor location and size; the relationships of the tumors with the surrounding organs and tissues, the large abdominal blood vessels, and the upper poles of the kidneys and renal hila; the adhesion of periadrenal fat (PF); and the tumor CT enhancement value. We conducted multivariate ordinal logistic regression analysis to screen variables and performed principal component analysis to construct a novel scoring model for RLAS. The perioperative outcomes of RLAS were evaluated according to postoperative length of stay, operative time (OT), intraoperative blood loss (IBL), and postoperative complications. Results: The final scoring model included tumor size; the relationships of the tumors with the surrounding organs and tissues, the large abdominal blood vessels, and the upper poles of the kidneys and renal hila; the tumor CT enhancement value; the adhesion of the PF; and the functional status of adrenal tumors. The total score had positive correlations with the OT (rs=0.431), IBL (rs=0.446), and postoperative length (rs=0.180) (all P values <0.001). Compared to any single metric, the total score provided better prediction of OT and IBL. The grading system for RLAS based on the scoring model also performed well in predicting the complexity and difficulty of RLAS. The coincidence rate for these factors was good (all P values <0.001). Conclusions: The developed model is feasible and repeatable in the prediction of the perioperative outcomes, complexity, and difficulty of RLAS.

Prospective analysis of the diagnostic accuracy of digital rectal examination and magnetic resonance imaging for T staging of prostate cancer.

Background: Accurate staging of prostate cancer (PCa) is the basis for the risk stratification to select targeted treatment. Therefore, this study aimed to compare the diagnostic accuracy rates of magnetic resonance imaging (MRI) and digital rectal examination (DRE) for preoperative T staging of potentially resectable PCa. Methods: From March 2021 to March 2022, patients with PCa with T staging by prostate biopsy were included. All examinations used postoperative histopathologic T staging as the reference standard. All patients underwent DRE and MRI before the puncture. Two blinded urologists and radiologists independently evaluated DRE and MRI, respectively. Before the examination, patients were then divided into early- (T1, T2) and late-(T3, T4) stage cancer. Analysis of a paired sample sign test was performed to determine differences between DRE and MRI. Results: A total of 136 study participants with PCa were evaluated histopathologically, of whom 71% (97/136) and 29% (39/136) were at the early- and late-stage cancer, respectively. MRI had a significantly higher accuracy (91.9% vs. 76.5%, P < 0.001) compared with DRE. Further, MRI showed a higher sensitivity than DRE to diagnose early PCa (92.8% vs. 74.2%; P < 0.001). However, the specificity was not significantly different between them (89.7% vs. 82.1%; P = 0.375). Area under the curve (receiver operating curve) values were calculated as 0.78 ± 0.038 (95% confidence interval [CI], 0.71-0.86), 0.91 ± 0.028 (95% CI, 0.86-0.97), and 0.872 ± 0.028 (95% CI, 0.80-0.92) for DRE-, MRI-, MRI + DRE-based PCa predictions, respectively. The prediction performance of MRI was better than that of DRE (DeLong test, z = 3.632, P = 0.0003) and MRI + DRE (DeLong test, z = 3.715, P = 0.0002). Conclusion: For resectable PCa, the diagnostic potential of MRI in assessing the T stage was higher than that of DRE. However, DRE is still valuable, especially for patients with locally advanced PCa.

A novel CD8+ T cell-related gene signature for predicting the prognosis and immunotherapy efficacy in bladder cancer.

OBJECTIVE: To identify CD8+ T cell-related molecular clusters and establish a novel gene signature for predicting the prognosis and efficacy of immunotherapy in bladder cancer (BCa). METHODS: Transcriptome and clinical data of BCa samples were obtained from the Cancer Genome Atlas (TCGA) and GEO databases. The CD8+ T cell-related genes were screened through the CIBERSORT algorithm and correlation analysis. Consensus clustering analysis was utilized to identified CD8+ T cell-related molecular clusters. A novel CD8+ T cell-related prognostic model was developed using univariate Cox regression analysis and Lasso regression analysis. Internal and external validations were performed and the validity of the model was validated in a real-world cohort. Finally, preliminary experimental verifications were carried out to verify the biological functions of SH2D2A in bladder cancer. RESULTS: A total of 52 CD8+ T cell-related prognostic genes were screened and two molecular clusters with notably diverse immune cell infiltration, prognosis and clinical features were developed. Then, a novel CD8+ T cell-related prognostic model was constructed. The patients with high-risk scores exhibited a significantly worse overall survival in training, test, whole TCGA and validating cohort. The AUC was 0.766, 0.725, 0.739 and 0.658 in the four cohorts sequentially. Subgroup analysis suggested that the novel prognostic model has a robust clinical application for selecting high-risk patients. Finally, we confirmed that patients in the low-risk group might benefit more from immunotherapy or chemotherapy, and validated the prognostic model in a real-world immunotherapy cohort. Preliminary experiment showed that SH2D2A was capable of attenuating proliferation, migration and invasion of BCa cells. CONCLUSIONS: CD8+ T cell-related molecular clusters were successfully identified. Besides, a novel CD8+ T cell-related prognostic model with an excellent predictive performance in predicting survival rates and immunotherapy efficacy of BCa was developed.

Risk Prediction Model of Early-Onset Preeclampsia Based on Risk Factors and Routine Laboratory Indicators.

Background: Globally, 10-15% of maternal deaths are statistically attributable to preeclampsia. Compared with late-onset PE, the severity of early-onset PE remains more harmful with higher morbidity and mortality. Objective: To establish an early-onset preeclampsia prediction model by clinical characteristics, risk factors and routine laboratory indicators were investigated from pregnant women at 6 to 10 gestational weeks. Methods: The clinical characteristics, risk factors, and 38 routine laboratory indicators (6-10 weeks of gestation) including blood lipids, liver and kidney function, coagulation, blood count, and other indicators of 91 early-onset preeclampsia patients and 709 normal controls without early-onset preeclampsia from January 2010 to May 2021 in Peking University Third Hospital (PUTH) were retrospectively analyzed. A logistic regression, decision tree model, and support vector machine (SVM) model were applied for establishing prediction models, respectively. ROC curves were drawn; area under curve (AUCROC), sensitivity, and specificity were calculated and compared. Results: There were statistically significant differences in the rates of diabetes, antiphospholipid syndrome (APS), kidney disease, obstructive sleep apnea (OSAHS), primipara, history of preeclampsia, and assisted reproductive technology (ART) (p < 0.05). Among the 38 routine laboratory indicators, there were no significant differences in the levels of PLT/LYM, NEU/LYM, TT, D-Dimer, FDP, TBA, ALP, TP, ALB, GLB, UREA, Cr, P, Cystatin C, HDL-C, Apo-A1, and Lp(a) between the two groups (p > 0.05). The levels of the rest indicators were all statistically different between the two groups (p < 0.05). If only 12 risk factors of PE were analyzed with the logistic regression, decision tree model, and support vector machine (SVM), and the AUCROC were 0.78, 0.74, and 0.66, respectively, while 12 risk factors of PE and 38 routine laboratory indicators were analyzed with the logistic regression, decision tree model, and support vector machine (SVM), and the AUCROC were 0.86, 0.77, and 0.93, respectively. Conclusions: The efficacy of clinical risk factors alone in predicting early-onset preeclampsia is not high while the efficacy increased significantly when PE risk factors combined with routine laboratory indicators. The SVM model was better than logistic regression model and decision tree model in early prediction of early-onset preeclampsia incidence.

A tumor-associated macrophages related model for predicting biochemical recurrence and tumor immune environment in prostate cancer.

OBJECTIVE: To identify tumor-associated macrophages (TAMs) related molecular subtypes and develop a TAMs related prognostic model for prostate cancer (PCa). METHODS: Consensus clustering analysis was used to identify TAMs related molecular clusters. A TAMs related prognostic model was developed using univariate and multivariate Cox analysis. RESULTS: Three TAMs related molecular clusters were identified and were confirmed to be associated with prognosis, clinicopathological characteristics, PD-L1 expression levels and tumor microenvironment. A TAMs related prognostic model was constructed. Patients in low-risk group all showed a more appreciable biochemical recurrence-free survival (BCRFS) than patients in high-risk group in train cohort, test cohort, entire TCGA cohort and validation cohort. SLC26A3 attenuated progression of PCa and prevented macrophage polarizing to TAMs phenotype, which was initially verified. CONCLUSIONS: We successfully identified molecular clusters related to TAMs. Additionally, we developed a prognostic model involving TAMs that exhibits excellent predictive performance for biochemical recurrence-free survival in PCa.

Durable and rechargeable antimicrobial cotton driven by enhanced UV stability and real-time detection of biocidal factors.

In this study, graphene oxide/N-halamine nanocomposite was synthesized through Pickering miniemulsion polymerization, which was then coated on cotton surface. The modified cotton exhibited excellent superhydrophobicity, which could effectively prevent microbial infestation and reduce the probability of hydrolysis of active chlorine, with virtually no active chlorine released in water after 72 h. Deposition of reduced graphene oxide nanosheets endowed cotton with ultraviolet-blocking properties, attributing to enhanced UV adsorption and long UV paths. Moreover, encapsulation of polymeric N-halamine resulted in improved UV stability, thus extending the life of N-halamine-based agents. After 24 h of irradiation, 85 % of original biocidal component (active chlorine content) was retained, and approximately 97 % of initial chlorine could be regenerated. Modified cotton has been proven to be an effective oxidizing material against organic pollutants and a potential antimicrobial substance. Inoculated bacteria were completely killed after 1 and 10 min of contact time, respectively. An innovative and simple scheme for determination of active chlorine content was also devised, and real-time inspection of bactericidal activity could be achieved to assure antimicrobial sustainability. Moreover, this method could be utilized to evaluate hazard classification of microbial contamination in different locations, thus broadening the application scope of N-halamine-based cotton fabrics.

A Liquid-Liquid Phase Separation-Related Index Associate with Biochemical Recurrence and Tumor Immune Environment of Prostate Cancer Patients.

To identify liquid-liquid phase separation (LLPS)-related molecular clusters, and to develop and validate a novel index based on LLPS for predicting the prognosis of prostate cancer (PCa) patients. We download the clinical and transcriptome data of PCa from TCGA and GEO database. The LLPS-related genes (LRGs) were extracted from PhaSepDB. Consensus clustering analysis was used to develop LLPS-related molecular subtypes for PCa. The LASSO cox regression analysis was performed to establish a novel LLPS-related index for predicting biochemical recurrence (BCR)-free survival (BCRFS). Preliminary experimental verification was performed. We initially identified a total of 102 differentially expressed LRGs for PCa. Three LLPS related molecular subtypes were identified. Moreover, we established a novel LLPS related signature for predicting BCRFS of PCa patients. Compared to low-risk patients in the training cohort, testing cohort and validating cohort, high-risk populations meant a higher risk of BCR and significantly poorer BCRFS. The area under receiver operating characteristic curve were 0.728, 0.762, and 0.741 at 1 year in the training cohort, testing cohort and validating cohort. Additionally, the subgroup analysis indicated that this index was especially suitable for PCa patients with age ≤ 65, T stage III-IV, N0 stage or in cluster 1. The FUS, which was the potential biomarker related to PCa liquid-liquid phase separation, was preliminarily identified and verified. This study successfully developed three LLPS-related molecular subtypes and identified a novel LLPS related molecular signature, which performed well in predicting BCRFS of PCa.

Body composition parameters were associated with response to abiraterone acetate and prognosis in patients with metastatic castration-resistant prostate cancer.

OBJECTIVE: To investigate the predictive value of body composition parameters for biochemical response to abiraterone acetate (AA) in metastatic castration-resistant prostate cancer (mCRPC) patients with prior chemohormonal therapy. METHODS: We retrospectively evaluated the clinicopathologic information of 132 mCRPC cases receiving AA treatment after chemohormonal therapy at hormone-sensitive stage from July 2018 to June 2021. All patients were divided into AA responders and non-responders according to the biochemical response to AA (prostate-specific antigen (PSA) reduction ≥50% than pretreatment). Multivariate Logistic analysis was used to determine the independent predictors and develop predictive model of biochemical response to AA. Cox regression analysis was utilized to investigate the prognostic factors for time to biochemical progression (TTBP), radiological progression-free survival (rPFS), failure-free survival (FFS), and overall survival (OS) after AA treatment. RESULTS: There were 57 AA responders and 75 AA non-responders. Periprostatic fat area/prostate area (PPFA/PA) was decreased and skeletal muscle index (SMI) was increased in AA responders compared with AA non-responders. Multivariable logistic analysis demonstrated that ADT duration ≥12 months, bone metastasis only, high SMI and low PPFA/PA were independent predictors of biochemical response to AA treatment. The FFS, TTBP, rPFS, and OS of patients with lower SMI or higher PPFA/PA was decreased compared with that of patients with higher SMI or lower PPFA/PA, respectively. Combining SMI, PPFA/PA, ADT duration and metastatic sites performed well in differentiating AA responders from non-responders. CONCLUSIONS: High SMI and low PPFA/PA could predict biochemical response to AA treatment and preferable prognosis in mCRPC patients with prior chemohormonal therapy at hormone-sensitive stage.

Shear Wave Elastography for Assessment of Biopsy-Proven Renal Fibrosis: A Systematic Review and Meta-analysis.

The purpose of this meta-analysis was to evaluate the diagnostic performance of shear wave elastography (SWE) for the staging of renal fibrosis in patients with chronic kidney disease (CKD). Classification of CKD into mild, moderate and severe fibrosis was based on renal biopsy pathology (glomerulosclerosis, tubulointerstitial injury and vascular sclerosis). The Cochrane Library, Medline, PubMed, Web of Science, EMBASE and CNKI databases were searched from January 1, 2009, to April 20, 2022. Pooled sensitivity, specificity, diagnostic odds ratio and area under the receiver operating characteristic curve (AUROC) were calculated using random effects models. A total of 1394 patients from 14 studies were included in the final analysis. For mild, moderate and severe renal fibrosis, SWE had a sensitivity of 0.79 (95% confidence interval [CI]: 0.67-0.88), 0.73 (95% CI: 0.65-0.80) and 0.87 (95% CI: 0.71-0.95); a specificity of 0.82 (95% CI: 0.75-0.87), 72% (95% CI: 0.67-0.77) and 0.83 (95% CI: 0.80-0.86); an AUROC of 0.87 (95% CI: 0.84-0.90), 0.78 (95% CI: 0.75-0.82) and 0.86 (95% CI: 0.82-0.88); and a diagnostic odds ratio of 17 (95% CI: 7-43), 7 (95% CI: 4-12) and 34 (95% CI: 13-88), respectively. Meta-regressions revealed that the publication date, system used and number of valid measurements of SWE were the main causes of heterogeneity. SWE is a good technique for diagnosing mild and severe renal fibrosis, as well as a fair technique for diagnosing moderate fibrosis.

Effect of regulatory cell death on the occurrence and development of head and neck squamous cell carcinoma.

Head and neck cancer is a malignant tumour with a high mortality rate characterized by late diagnosis, high recurrence and metastasis rates, and poor prognosis. Head and neck squamous cell carcinoma (HNSCC) is the most common type of head and neck cancer. Various factors are involved in the occurrence and development of HNSCC, including external inflammatory stimuli and oncogenic viral infections. In recent years, studies on the regulation of cell death have provided new insights into the biology and therapeutic response of HNSCC, such as apoptosis, necroptosis, pyroptosis, autophagy, ferroptosis, and recently the newly discovered cuproptosis. We explored how various cell deaths act as a unique defence mechanism against cancer emergence and how they can be exploited to inhibit tumorigenesis and progression, thus introducing regulatory cell death (RCD) as a novel strategy for tumour therapy. In contrast to accidental cell death, RCD is controlled by specific signal transduction pathways, including TP53 signalling, KRAS signalling, NOTCH signalling, hypoxia signalling, and metabolic reprogramming. In this review, we describe the molecular mechanisms of nonapoptotic RCD and its relationship to HNSCC and discuss the crosstalk between relevant signalling pathways in HNSCC cells. We also highlight novel approaches to tumour elimination through RCD.

Head-to-head comparisons of [68Ga]Ga-PSMA-11 PET/CT, multiparametric MRI, and prostate-specific antigen for the evaluation of therapeutic responses to neoadjuvant chemohormonal therapy in high-risk non-metastatic prostate cancer patients: a prospective study.

PURPOSE: The optimal tool to evaluate the tumour therapeutic responses to neoadjuvant chemohormonal therapy (NCHT) in patients with high-risk non-metastatic prostate cancer (PCa) remains uncertain. We compared the role of [68Ga]-labeled prostate-specific membrane antigen (PSMA)-11 positron emission tomography/computerized tomography ([68Ga]Ga-PSMA-11 PET/CT), multiparametric MRI (mpMRI), and prostate-specific antigen (PSA) and assessed the practical value of the recent European Association of Urology and European Association of Nuclear Medicine (EAU/EANM) recommended criteria of PSMA PET/CT to evaluate the therapeutic responses to NCHT in patients with high-risk non-metastatic PCa. METHODS: This prospective study included 72 high-risk non-metastatic PCa patients receiving NCHT followed by radical prostatectomy from June 2021 to March 2022. PSA testing, [68Ga]Ga-PSMA-11 PET/CT, and mpMRI scanning were conducted in all patients before and after NCHT. Therapeutic responses to NCHT were evaluated with PSA, RECIST 1.1, PERCIST 1.0, and EAU/EANM recommended criteria. Postoperative pathological results were considered the reference standard. A favourable pathological response was defined as pathologic complete remission (pCR) or minimal residual disease (MRD). Diagnostic accuracy was assessed by sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV), negative predictive value (NPV), and Cohen's kappa index. Logistic regression analysis was used to determine the independent predictive value of [68Ga]Ga-PSMA-11 PET/CT-derived parameters. RESULTS: All cases experienced a marked decrease in PSA levels after NCHT. Twenty-four (33.33%) cases experienced a favourable pathological response, including five (6.94%) cases of pCR and 19 (26.39%) cases of MRD. According to the results of [68Ga]Ga-PSMA-11 PET/CT, EAU/EANM recommended criteria indicated that 20 (27.78%) cases had a CR, whereas PERCIST 1.0 criteria indicated that 23 (31.94%) cases had a CR. There was a strong association between EAU/EANM recommended criteria and PERCIST 1.0 criteria (Pearson's R=0.857). The sensitivity (75.00%, 79.17% vs. 58.33%, 58.33%), specificity (95.83%, 91.67% vs. 83.33%, 68.75%), PLR (18.00, 9.50 vs. 3.50, 1.87), NLR (0.26, 0.23 vs. 0.50, 0.61), PPV (90.0%, 82.6% vs. 63.6%, 48.3%), and NPV (88.5%, 89.8% vs. 80.0%, 76.7%) of [68Ga]Ga-PSMA-11 PET/CT (including EAU/EANM recommended criteria and PERCIST 1.0 criteria) to predict favourable pathological responses were all superior to those of mpMRI and nadir PSA. The kappa index to predict a favourable pathological response was 0.257 for PSA, 0.426 for RECIST 1.1, 0.716 for PERCIST 1.0, and 0.739 for EAU/EANM recommended criteria. Multivariate logistic analysis revealed that the post-NCHT maximum standardized uptake value (SUVmax) before radical prostatectomy was an independent predictor of a favourable pathological response to NCHT. CONCLUSIONS: [68Ga]Ga-PSMA-11 PET/CT had a better concordance with a favourable pathological response to NCHT compared with nadir PSA and mpMRI. EAU/EANM recommended criteria and PERCIST 1.0 criteria performed equally to identify pathological responders when [68Ga]Ga-PSMA-11 PET/CT was used as a therapeutic response assessment tool.

Low TLR and PSMA-TV predict biochemical response to abiraterone acetate in metastatic prostate cancer patients developing castration resistance after chemohormonal therapy at hormone-sensitive stage.

OBJECTIVE: To explore whether 68Ga-PSMA-11 PET/CT-derived parameters could predict biochemical response to abiraterone acetate (AA) treatment and prognosis in metastatic prostate cancer patients developing castration resistance after chemohormonal therapy at hormone-sensitive stage. METHODS: The clinicopathologic data of 106 mCRPC cases receiving AA treatment were retrospectively analyzed. Logistic regression analysis was used to determine the independent predictors of biochemical response to AA treatment. Cox analyses were applied to investigate the independent prognostic factors for time to biochemical progression (TTBP) and radiological progression-free survival (rPFS). Survival analysis and ROC curve were also used. RESULTS: Multivariable Logistic analysis demonstrated that prior ADT duration ≥ 12 months, low prostate specific membrane antigen receptor-expressing tumor volume (PSMA-TV), low tumor to liver ratio (TLR) were independent predictors of biochemical response to AA treatment. Multivariate Cox analysis demonstrated that low PSMA-TV and low TLR were independent prognostic factors of longer TTBP and rPFS. The TTBP and rPFS of patients with higher PSMA-TV or TLR were significantly decreased compared with that of patients with lower PSMA-TV and TLR. The area under ROC curve (AUC) of combining ADT duration, PSMA-TV and TLR was 0.82 for predicting biochemical response to AA, which was significantly increased compared with that of other 68Ga-PSMA-11 PET/CT-derived parameters alone. CONCLUSIONS: Low PSMA-TV, low TLR were vital independent predictors of biochemical response to AA treatment and were associated with preferable prognosis in mCRPC patients. Combining ADT duration, PSMA-TV and TLR performed well in distinguishing AA responders from non-responders in mCRPC patients.

A radiation resistance related index for biochemical recurrence and tumor immune environment in prostate cancer patients.

PURPOSE: To establish and verify a novel radiation resistance related index for predicting biochemical recurrence and tumor immune environment in prostate cancer (PCa) patients. MATERIALS AND METHODS: The transcriptome information of PCa were obtained from GEO and TCGA portal. We identified radiation resistance related genes (RRGs) between radioresistant and radiosensitive PCa cells. We conducted multivariate Cox analysis to construct a novel radiation resistance related index for predicting biochemical recurrence (BCR)-free survival (BCRFS). Internal and external validations were conducted. Preliminary experimental verifications were performed. RESULTS: We identified 194 differentially expressed RRGs and three radiation resistance related molecular clusters for PCa. Moreover, we established a novel radiation resistance related index and succeeded in conducting internal and external validations. High-risk populations meant significantly worse BCRFS in training, testing and validating cohort. The area under receiver operating characteristic curve were 0.809, 0.698, and 0.712 in training, testing, and validating cohort. The immune microenvironment was significantly different between high and low-risk score patients. Preliminary experiment identified and validated three potential biomarkers related to radiation resistance (ZNF695, TM4SF19, CCDC3) of PCa. CONCLUSIONS: This study successfully established and verified a novel radiation resistance related index, which had an excellent performance in predicting BCR and tumor immune microenvironment in patients with PCa.

Colorimetric sensing strategy for detection of cysteine, phenol cysteine, and phenol based on synergistic doping of multiple heteroatoms into sponge-like Fe/NPC nanozymes.

Nanozymes have both the high catalytic activity of natural enzymes and the stability and economy of mimetic enzymes. Research on nanozymes is rapidly emerging, and the continuous development of highly catalytic active nanozymes is of far-reaching significance. This work reports heteroatomic nitrogen (N) and phosphorus (P) double-doped mesoporous carbon structures and metallic Fe coordination generated sponge-like nanozymes (Fe/NPCs) with good peroxidase activity. On this basis, we constructed a highly sensitive colorimetric sensor with cysteine and phenol as simulated analytes using Fe/NPCs nanozymes, and the response limits reached 53.6 nM and 5.4 nM, respectively. Besides, the method has high accuracy in the detection of cysteine and phenol at low concentrations in serum and tap water, which lays a foundation for application in the fields of environmental protection and biosensors.

Stellate ganglion block as an intervention in refractory eosinophilic granulomatosis with polyangiitis: a case report.

BACKGROUND: Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare vasculitis. Although glucocorticoid therapy with or without immunosuppressants leads to remission in the majority of cases, most EGPA patients remain dependent on glucocorticoid therapy and experience frequent relapses. Here, we report a case of refractory EGPA which responded to stellate ganglion blocks (SGBs). CASE PRESENTATION: A 32-year-old woman with aggravated wheezing, purpura, numbness of multiple fingers, and epigastric and abdominal pain was referred to our clinic. Laboratory and radiographic studies led to the diagnosis of EGPA. After an initial favorable response to glucocorticoid and immunosuppressant therapy, she experienced a relapse during a glucocorticoid taper. We found that SGB brought symptomatic relief and impeded disease progression. The mechanism of action of SGB on EGPA is undetermined, but may be related to vasodilation, immune modulation, and central nervous system regulation. CONCLUSIONS: This report not only proposes a novel treatment modality for EGPA, but also provides a clinical reference point for further in-depth studies of SGB in multiple immune-linked disorders.

Structure-guided discovery of antioxidant peptides bounded to the Keap1 receptor as hunter for potential dietary antioxidants.

Human health can be damaged by free radicals, and antioxidant peptides are excellent radical scavengers. Antioxidant tripeptides data set based on 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulofnic acid) (ABTS) assay was created, 9 types of descriptors were integrated and 4 quantitative structure-activity relationship (QSAR) models were constructed in this study. Several structural factors influencing the activity of antioxidant tripeptides and the dominant amino acids at each position of tripeptides were revealed by the optimal model. Ten food-derived tripeptides with higher activity were selected for synthesis and activity determination. Molecular docking results demonstrated that these tripeptides were stably bound to the Keap1 receptor, further elucidating the antioxidant mechanism. It was known from the simulation of gastrointestinal digestion experiments that the model results possessed a guiding effect on the selection of proteins with high antioxidant activity. The performance of the model was proved to be robust after validation.

Antioxidant identification using a colorimetric sensor array based on Co-N-C nanozyme.

Here we develop a simple and effective nose/tongue sensor array based on Co-N-C single-atom nanozymes-3,3',5,5'-tetramethylbenzidine (TMB)-H2O2 for colorimetric discrimination of antioxidants, which makes use of the color reaction of TMB oxidation by H2O2 in two different pH (3.8 and 4.6) environments under the catalysis of Co-N-C nanoenzyme with peroxidase-like activity. Different antioxidants have varying reducing ability to the oxidation products of TMB (oxTMB), thus resulting in differential absorbance and color changes. Linear discriminant analysis (LDA) results indicate that the sensor array successfully identified 7 antioxidants, i.e., glutathione (GSH), ascorbic acid (AA), cysteine (Cys), tannin (TA), Catechin (C), dopamine (DA), and uric acid (UA) in both buffer and even serum samples. Additionally, the performance of the sensor array was validated with antioxidant mixtures, individual antioxidants with different concentrations, and target antioxidants and interfering substances. In general, the versatile sensor array based on Co-N-C single-atom nanozymes provides an excellent strategy for identifying a variety of antioxidants, which exhibits a broad application prospect in medical diagnosis.

[Comparison between manual acupuncture and electroacupuncture for hot flashes and sex hormone of perimenopausal syndrome].

OBJECTIVE: To compare the effect and differences sex the influence of hormone levels of perimenopau-sal syndrome patients between manual acupuncture and electroacupuncture (EA). METHODS: A total of 50 cases with perimenopausal syndrome were randomly assigned into an manual acupuncture group (27 cases) and an EA group (23 cases), and 1 case dropped in the EA group. The acupoints in the two groups were Guanyuan (CV 4), Zigong (EX-CA 1), Tianshu (ST 25), and Sanyinjiao (SP 6). Acupuncture with 3-time small and even manipulation of lifting, thrusting and twirling was used in the acupuncture group, once 10 min. EA with sparse-dense wave and 10 Hz/50 Hz was applied in the EA group for 30 min. The treatments in the two groups were for continuous 8 weeks (24 times in total), once the other day, 3 times a week. The scores of 24-hour hot flashes even, menopausal rating scale (MRS) and menopause-specific quality of life questionnaire (MENQOL) were recorded before treatment and after 4-week and 8-week treatment, as well as 12 and 24 weeks after treatment. Serum sex hormone levels were tested before and after 8-week treatment as well as 12 weeks after treatment, including serum follicle-stimulating hormone (FSH), luteinizing hormone (LH), and estracliol (E2). RESULTS: Compared with those before treatment, the 24-hour hot flashes even score, MRS and MENQOL scores were significantly lower after 4-week and 8-week treatments, 12 and 24 weeks after treatment (all P<0.05). All the above scores after 8-week treatment were lower than those after 4-week treatment (all P<0.05); and the scores 12 and 24 weeks after treatment were lower than those after 4-week and 8-week treatments (all P<0.05); all the scores after treatment were not significantly different at any time between the two groups (all P>0.05). Compared with those before treatment, serum FSH and E2 apparently improved in the two groups after 8-week treatment and 12 weeks after treatment (all P<0.05). LH levels did not significantly change in the two groups (all P>0.05). All the serum sex hormone levels showed no significant difference between the two groups (all P>0.05). CONCLUSIONS: Both acupuncture and EA can improve perimenopausal symptoms and serum sex hormone. The effects are similar.