A three-dimensional network structure of metal-based nanozymes for the construction of colorimetric sensors for the detection of antioxidants.

Although many excellent nanozymes have been developed, designing and synthesizing highly active nanozymes is still challenging. Here, we developed a metal-based nanozyme (metal = Co, Fe, Cu, Zn) with a three-dimensional network structure. It possesses excellent peroxidase activity and catalyzes the reaction between H2O2 and TMB to produce blue oxTMB, while antioxidants have different reducing power on the oxidation product of TMB (oxTMB), which leads to different absorbance and color changes. Using these color reactions, different nanozymes were used to form a colorimetric sensor array with seven antioxidants, and seven antioxidants were sensitively identified. And the differences between the three nanozymes were compared by density functional theory calculations and enzyme kinetic curve results. In conclusion, the colorimetric sensor array based on metal-based nanozymes provides a good strategy for the identification and detection of antioxidants, which has a broad application prospect.

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.

Polycationic Open-Shell Cyclophanes: Synthesis of Electron-Rich Chiral Macrocycles, and Redox-Dependent Electronic States.

π-Conjugated chiral nanorings with intriguing electronic structures and chiroptical properties have attracted considerable interests in synthetic chemistry and materials science. We present the design principles to access new chiral macrocycles (1 and 2) that are essentially built on the key components of main-group electron-donating carbazolyl moieties or the π-expanded aza[7]helicenes. Both macrocycles show the unique molecular conformations with a (quasi) figure-of-eight topology as a result of the conjugation patterns of 2,2',7,7'-spirobifluorenyl in 1 and triarylamine-coupled aza[7]helicene-based building blocks in 2. This electronic nature of redox-active, carbazole-rich backbones enabled these macrocycles to be readily oxidized chemically and electrochemically, leading to the sequential production of a series of positively charged polycationic open-shell cyclophanes. Their redox-dependent electronic states of the resulting multispin polyradicals have been characterized by VT-ESR, UV-vis-NIR absorption and spectroelectrochemical measurements. The singlet (ΔES-T = -1.29 kcal mol-1) and a nearly degenerate singlet-triplet ground state (ΔES-T(calcd) = -0.15 kcal mol-1 and ΔES-T(exp) = 0.01 kcal mol-1) were proved for diradical dications 12+2• and 22+2•, respectively. Our work provides an experimental proof for the construction of electron-donating new chiral nanorings, and more importantly for highly charged polyradicals with potential applications in chirospintronics and organic conductors.

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.

Lower serum AMH concentration is correlated with serum IgG1 decreased in the infertile woman: A real-world retrospective study.

OBJECTIVES: In this real-world approach, we examined the serum Anti-Mullerian Hormone (AMH) level and the relationship with serum IgG subclass in the infertile women. METHODS: A total of 574 female participants were recruited for this study. The serum AMH, IgG subclass(IgG1, IgG2, IgG3, IgG4) and immunoglobulin (Ig) G、IgM、IgA、IgE as well as complement C3, C4 were analyzed. The difference in serum AMH level was assessed according categorized as above or below the median of the ratio of serum IgG subclass(IgG1, IgG2, IgG3, IgG4) to total IgG (RIgG subclass/IgG). RESULTS: The serum AMH level of the low RIgG1/IgG group is significantly decreased than that high RIgG1/IgG group (p < 0.05). The Spearman correlation analysis showed that the serum AMH level was significantly negatively correlated with age and significantly positively correlated with serum IgG1 levels respectively (p < 0.05). GLMMs multivariate model showed that after adjusting the covariate and possible mixed factors including age, serum immunoglobulin, complement C3 and C4, the serum AMH level was significantly positively correlated with IgG1 level (p < 0.01). CONCLUSIONS: Decreased serum IgG1 may significantly affect the ovarian reserve function of women. Confirmation of this association and elucidation of its underlying mechanisms are needed to place these results in a clinical perspective.

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.

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 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.

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.

Colorimetric identification of multiple terpenoids based on bimetallic FeCu/NPCs nanozymes.

Nanozymes have been relatively well explored, and bimetal-doped nanozymes have attracted much exploration due to their superior catalytic activity. We developed bimetallic FeCu/NPCs and Cu/NPCs nanozymes, which have good catalytic properties due to the coordination of Fe and Cu with N and P. The nanozymes acted as sensing elements in a cascade reaction system to effectively recognize seven terpenoids, including menthol (Men), paeoniflorin (Pae), camphor (Cam), paclitaxel (Pac), andrographolide (Andro), ginkgolide A (Gin A), and piperone (Pip). Terpenoids act as inhibitors of acetylcholinesterase (AChE) and reduce the hydrolysis of acetylcholine (ATCh), providing insight into establishing a simple and distinct assay for terpenoids. Notably, the sensor array distinguished seven terpenoids with concentrations as low as 10 ng/mL and achieved high-precision detection of mixed samples with different molar ratios and 21 unknown samples. Finally, the sensor array successfully distinguished and identified multiple terpenoids in herbal samples.

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.

Associations between Short-Term Air Pollution Exposure and the Peripheral Leukocyte Distribution in the Adult Male Population in Beijing, China.

The inflammatory effects of air pollution exposure may account for increased public health risk. However, evidence regarding the effects of air pollution on peripheral blood leukocytes in the population is inconsistent. We investigated the association between the short-term effects of ambient air pollution and the peripheral blood leukocyte distribution in adult men in Beijing, China. From January 2015 to December 2019, a total of 11,035 men aged 22-45 years in Beijing were included in the study. Their peripheral blood routine parameters were measured. The ambient pollution monitoring parameters (particulate matter ≤ 10 µm (PM10), PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3)) were collected daily. The potential association between ambient air pollution exposure and peripheral blood leukocyte count and classification was analyzed with generalized additive models (GAMs). After adjusting for confounding factors, PM2.5, PM10, SO2, NO2, O3, and CO were significantly correlated with changes to at least one peripheral leukocyte subtype. Short-term and cumulative air pollutant exposure dramatically increased the participants' peripheral blood neutrophil, lymphocyte, and monocyte numbers and decreased eosinophils and basophils. Our results demonstrated that air pollution induced inflammation in the participants. The peripheral leukocyte count and classification can be utilized to evaluate the inflammation induced by air pollution in the exposed male population.

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.

The spatiotemporal evolution and influencing factors of urban green innovation in China.

Green innovation (GI) is an important way to build an ecological civilization and an innovative country. The study on urban green innovation (UGI) is of great significance for enriching the research on GI and rationally formulating high-quality urban development policies. The green patent data obtained using a web crawler was used to represent the level of UGI. The spatiotemporal evolution and influencing factors of UGI in China were analyzed by standard deviation ellipses, spatial autocorrelation, and Geodetector. The research shows that: From 2005 to 2020, the level of UGI in China tended to rise rapidly. The center of gravity of UGI in China was located in the southeast of China's geometric center and tended to move to the south and west. The standard deviation ellipse was distributed in a "northeast-southwest" pattern, the area was gradually shrinking, and the length of the two semi-axes was shortening. UGI in China showed obvious global and local spatial autocorrelations. The degree of global spatial autocorrelation was gradually increasing. Among the types of local spatial autocorrelation, the largest number of low-low agglomeration cities was mainly located in the northwest and southwest part of China, while high-high agglomeration cities were distributed in Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta. The government intervention expressed by the proportion of scientific and technological expenditure in fiscal expenditure and environmental regulation is the dominant factor affecting UGI.

Effect of ferulic acid covalent conjugation on the functional properties and antigenicity of ß-lactoglobulin.

Binding to phenolics can improve the functional properties of proteins. Changes in structure, functional properties, and antigenicity of ß-lactoglobulin (ß-LG) after covalent conjugation with ferulic acid (FA) at different mass ratios were reported here. The results of SDS-PAGE and gel exclusion chromatography confirmed that covalent complexes were formed. When the mass ratio of ß-LG and FA was 10:6, the binding content of FA was the highest. Fluorescence spectroscopy, UV-visible absorption spectrometry, and FTIR analysis showed that the structure of the complexes was more stretched compared to native ß-LG. The addition of FA significantly improved the emulsifying property of ß-LG. When the mass ratio was 10:6, the radical scavenging activities of DPPH and ABTS reached 65.06% and 88.22%, respectively, and the antigenicity of ß-LG reduced by about 35%. This study provides novel ß-LG-FA complexes in food systems to reduce the antigenicity of ß-LG and improve functional properties.

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.