Secular trends in the prevalence of meeting 24-hour movement guidelines among U.S. adolescents: evidence from NHANES 2007-2016.

Background: The 24-Hour Movement Guidelines (24-HMG) recommend a balanced combination of physical activity (PA), sedentary behavior (SB) and sleep (SLP) for optimal health. However, there is limited understanding of how well U.S. adolescents adhere to these guidelines. This study aims to analyze the prevalence trends of meeting the 24-HMG among a nationally representative sample of U.S. general adolescents. Methods: The study included 2,273 adolescents (55.3% boys) aged 16-19 who participated in the National Health and Nutrition Examination Surveys (NHANES) from 2007 to 2016. The researchers categorized the adolescents based on whether they met various PA, SB, and SLP recommendations, as well as different combinations of these recommendations, separately for boys and girls. The prevalence rate, weighted by survey data, was calculated along with a 95% confidence interval (CI) to assess the changes in meeting the 24-HMG among U.S. adolescents across different survey years and sociodemographic subgroups. Results: In the 2015-2016 cycle, approximately 6.3% of adolescents did not meet any of the three recommendations, while only 19.2% of adolescents achieved all three guidelines. Compliance with PA and SB recommendations among adolescents has decreased over time, from 72.5% (65.9% to 79.2%) to 64.2% (57.4% to 70.9%) for PA, and from 59.0% (49.6% to 68.4%) to 46.6% (37.8% to 55.5%) for SB, respectively, from 2007-2008 cycle to 2015-2016 cycle. Boys exhibited more favorable patterns in meeting different sets of recommendations compared to girls (p-value <0.001). This includes meeting both PA and SB guidelines (15.5% for boys and 11.1% for girls) and meeting both PA and SLP guidelines (19.5% for boys and 15.7% for girls). The level of parental education was found to have effect on meeting all three guidelines (Ptrend < 0.05). Conclusion: We analyzed ten consecutive years of representative NHANES data to evaluate the prevalence meeting 24-HMG and found that the proportion of adolescents aged 16-19 in the U.S. who adhered to all three movement guidelines simultaneously has consistently remained low throughout each survey cycle. Notably, there has been a significant decline in the proportion of adolescents meeting the SB guideline.

Cumulative effects of excess high-normal alanine aminotransferase levels in relation to new-onset metabolic dysfunction-associated fatty liver disease in China.

BACKGROUND: Within the normal range, elevated alanine aminotransferase (ALT) levels are associated with an increased risk of metabolic dysfunction-associated fatty liver disease (MAFLD). AIM: To investigate the associations between repeated high-normal ALT measurements and the risk of new-onset MAFLD prospectively. METHODS: A cohort of 3553 participants followed for four consecutive health examinations over 4 years was selected. The incidence rate, cumulative times, and equally and unequally weighted cumulative effects of excess high-normal ALT levels (ehALT) were measured. Cox proportional hazards regression was used to analyse the association between the cumulative effects of ehALT and the risk of new-onset MAFLD. RESULTS: A total of 83.13% of participants with MAFLD had normal ALT levels. The incidence rate of MAFLD showed a linear increasing trend in the cumulative ehALT group. Compared with those in the low-normal ALT group, the multivariate adjusted hazard ratios of the equally and unequally weighted cumulative effects of ehALT were 1.651 [95% confidence interval (CI): 1.199-2.273] and 1.535 (95%CI: 1.119-2.106) in the third quartile and 1.616 (95%CI: 1.162-2.246) and 1.580 (95%CI: 1.155-2.162) in the fourth quartile, respectively. CONCLUSION: Most participants with MAFLD had normal ALT levels. Long-term high-normal ALT levels were associated with a cumulative increased risk of new-onset MAFLD.

Diagnostic challenge and survival analysis of pulmonary oligometastases and primary lung cancer in breast cancer patients.

BACKGROUND: The aim of this study was to compare breast cancer patients with pulmonary oligometastases (POM) and primary lung cancer (PLC) and to assess whether there were differences in clinical features, CT features, and survival outcomes between the two groups. METHODS: From January 2010 to December 2021, the clinical records of 437 with malignant pulmonary nodules who had breast cancer patients were reviewed. POM was identified in 45 patients and PLC in 43 patients after the initial detection of pulmonary nodules. The clinicopathological characteristics, CT appearance of pulmonary nodules, and survival of the two groups were compared. RESULTS: Stage II to IV breast tumors (p < 0.001), high pathological grade of breast cancer (p = 0.001), low proportion of luminal-type breast cancer (p = 0.003), and the higher serum CYFRA 21-1 level (p = 0.046) were the clinical characteristics of pulmonary nodules suggestive of POM rather than PLC. The CT features of lung nodules indicative of PLC rather than POM were the subsolid component (p < 0.001), lobulation (p = 0.010), air bronchogram (p < 0.001) and pleural indentation (p = 0.004). Ten-year survival rate for PLC was 93.2%, which was higher compared with 57.8% in those with POM (p = 0.001). CONCLUSIONS: Elevated serum CYFRA 21-1 levels and late-stage breast cancer may be beneficial for the diagnosis of POM. CT imaging appearances of the subsolid component, lobulation, air bronchogram, and pleural indentation increase the likelihood of PLC. Breast cancer patients with PLC presented better survival with attentive monitoring than those with POM.

Fluorination of porphyrin ß-periphery boosts nickel(II)-catalyzed hydrogen evolution reaction.

Tunichlorin, the naturally occurring chlorophyll cofactor containing Ni(II) ion, sets up a golden standard for designing the electrocatalysts for hydrogen evolution reaction (HER) via ß-peripheral modification. Besides the fine-tuning of the porphyrin ß-periphery such as adjusting the aromatics (the saturated level of tetrapyrrole) or installing hydroxyl group (hydrogen bond network) to enhance the catalytic HER efficiency, here we report that ß-fluorination of porphyrin is also an important approach to increase the reactivity of Ni(II) center. Benefiting the previously reported derivatization of ß-fluorinated porpholactones, we constructed a ß-fluorinated tunichlorin mimic (6). Compared with the non-fluorinated analogs (1, 3, and 5), we found that 2, 4, and 6 exhibit significant electrocatalytic HER reactivity acceleration (in terms of turnover frequencies, TOF, s-1) of ca. 37, 170, 133-fold, respectively. Mechanism studies suggested that ß-fluorination negatively shifts the metal complexes' reduction potentials and accelerates the electron transfer process, both contributing to the boosting of HER reaction. Notably, 6 showed an 890-fold increase of TOFs than 1, demonstrating the combining advantages of the of fluorination, hydrogenation, and hydroxylation at porphyrin ß-periphery.

Overexpression of ABCC1 and ABCG2 confers resistance to talazoparib, a poly (ADP-Ribose) polymerase inhibitor.

AIMS: The overexpression of ABC transporters on cancer cell membranes is one of the most common causes of multidrug resistance (MDR). This study investigates the impact of ABCC1 and ABCG2 on the resistance to talazoparib (BMN-673), a potent poly (ADP-ribose) polymerase (PARP) inhibitor, in ovarian cancer treatment. METHODS: The cell viability test was used to indicate the effect of talazoparib in different cell lines. Computational molecular docking analysis was conducted to simulate the interaction between talazoparib and ABCC1 or ABCG2. The mechanism of talazoparib resistance was investigated by constructing talazoparib-resistant subline A2780/T4 from A2780 through drug selection with gradually increasing talazoparib concentration. RESULTS: Talazoparib cytotoxicity decreased in drug-selected or gene-transfected cell lines overexpressing ABCC1 or ABCG2 but can be restored by ABCC1 or ABCG2 inhibitors. Talazoparib competitively inhibited substrate drug efflux activity of ABCC1 or ABCG2. Upregulated ABCC1 and ABCG2 protein expression on the plasma membrane of A2780/T4 cells enhances resistance to other substrate drugs, which could be overcome by the knockout of either gene. In vivo experiments confirmed the retention of drug-resistant characteristics in tumor xenograft mouse models. CONCLUSIONS: The therapeutic efficacy of talazoparib in cancer may be compromised by its susceptibility to MDR, which is attributed to its interactions with the ABCC1 or ABCG2 transporters. The overexpression of these transporters can potentially diminish the therapeutic impact of talazoparib in cancer treatment.

SCpRh(III)-Catalyzed Asymmetric C-H Trifluoromethylalkylation of N-Methoxybenzamides with ß-Trifluoromethyl-α,ß-Unsaturated Ketones.

Asymmetric C-H trifluoromethylalkylation represents a novel and straightforward synthetic method for the construction of chiral CF3-containing compounds. However, the reported examples remain limited, given the challenges of reactivity and enantioselective control. Herein, we report a SCpRh(III)-catalyzed asymmetric aryl and alkenyl C-H trifluoromethylalkylation reaction with ß-trifluoromethyl-α,ß-unsaturated ketones. The chiral CF3-bearing adducts were obtained in moderate to good yields with high enantioselectivity (up to 81% yield and 96% ee). The reaction features mild conditions and broad substrate scope. The chiral CF3-bearing products could undergo diverse functional group transformations.

GPX2 acts as an oncogene and cudraflavone C has an anti-tumor effect by suppressing GPX2-dependent Wnt/ß-catenin pathway in colorectal cancer cells.

Colorectal carcinoma (CRC) is a common cancer associated with poor prognosis, and cudraflavone C (Cud C) is a natural flavonol with reported anti-CRC capacity. However, the precise mechanisms underlying the anti-CRC effect require further demonstration. The aim of present study was to evaluate the impact of Cud C on the cell viability and apoptosis of CRC cells and to determine the underlying mechanisms. The Human Protein Atlas (THPA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases were used to analyze the expression status of glutathione peroxidase 2 (GPX2) in CRC. Cell viability was examined using cell counting kit-8 (CCK-8) assay. Flow cytometry was utilized to evaluate apoptosis. The levels of gene transcription and protein expression of GPX2, caspase-3, cleaved caspase-3), ß-catenin, and c-Myc were determined by RT-qPCR and Western blotting. Our results showed that GPX2 was overexpressed in CRC as compared to normal tissue and the extent of GPX2 overexpression is greatest in CRC when compared with other cancers according to GEPIA and THPA databases. GPX2 knockdown significantly suppressed the cell viability, induced apoptosis of CRC cell lines, and restrained the activity of Wnt/ß-catenin pathway. Cud C treatment decreased cell viability, induced apoptosis in CRC cell lines, and diminished the expression level of GPX2-dependent activation of Wnt/ß-catenin pathway, while such effects can be abolished by GPX2 overexpression. In conclusion, Cud C suppressed GPX2-dependent Wnt/ß-catenin pathway to exert anti-CRC function.

MRI-based automated machine learning model for preoperative identification of variant histology in muscle-invasive bladder carcinoma.

OBJECTIVES: It is essential yet highly challenging to preoperatively diagnose variant histologies such as urothelial carcinoma with squamous differentiation (UC w/SD) from pure UC in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly. We developed a non-invasive automated machine learning (AutoML) model to preoperatively differentiate UC w/SD from pure UC in patients with MIBC. METHODS: A total of 119 MIBC patients who underwent baseline bladder MRI were enrolled in this study, including 38 patients with UC w/SD and 81 patients with pure UC. These patients were randomly assigned to a training set or a test set (3:1). An AutoML model was built from the training set, using 13 selected radiomic features from T2-weighted imaging, semantic features (ADC values), and clinical features (tumor length, tumor stage, lymph node metastasis status), and subsequent ten-fold cross-validation was performed. A test set was used to validate the proposed model. The AUC of the ROC curve was then calculated for the model. RESULTS: This AutoML model enabled robust differentiation of UC w/SD and pure UC in patients with MIBC in both training set (ten-fold cross-validation AUC = 0.955, 95% confidence interval [CI]: 0.944-0.965) and test set (AUC = 0.932, 95% CI: 0.812-1.000). CONCLUSION: The presented AutoML model, that incorporates the radiomic, semantic, and clinical features from baseline MRI, could be useful for preoperative differentiation of UC w/SD and pure UC. CLINICAL RELEVANCE STATEMENT: This MRI-based automated machine learning (AutoML) study provides a non-invasive and low-cost preoperative prediction tool to identify the muscle-invasive bladder cancer patients with variant histology, which may serve as a useful tool for clinical decision-making. KEY POINTS: • It is important to preoperatively diagnose variant histology from urothelial carcinoma in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly. • An automated machine learning (AutoML) model based on baseline bladder MRI can identify the variant histology (squamous differentiation) from urothelial carcinoma preoperatively in patients with MIBC. • The developed AutoML model is a non-invasive and low-cost preoperative prediction tool, which may be useful for clinical decision-making.

MRI-based radiomic models to predict surgical margin status and infer tumor immune microenvironment in breast cancer patients with breast-conserving surgery: a multicenter validation study.

OBJECTIVES: Accurate preoperative estimation of the risk of breast-conserving surgery (BCS) resection margin positivity would be beneficial to surgical planning. In this multicenter validation study, we developed an MRI-based radiomic model to predict the surgical margin status. METHODS: We retrospectively collected preoperative breast MRI of patients undergoing BCS from three hospitals (SYMH, n = 296; SYSUCC, n = 131; TSPH, n = 143). Radiomic-based model for risk prediction of the margin positivity was trained on the SYMH patients (7:3 ratio split for the training and testing cohorts), and externally validated in the SYSUCC and TSPH cohorts. The model was able to stratify patients into different subgroups with varied risk of margin positivity. Moreover, we used the immune-radiomic models and epithelial-mesenchymal transition (EMT) signature to infer the distribution patterns of immune cells and tumor cell EMT status under different marginal status. RESULTS: The AUCs of the radiomic-based model were 0.78 (0.66-0.90), 0.88 (0.79-0.96), and 0.76 (0.68-0.84) in the testing cohort and two external validation cohorts, respectively. The actual margin positivity rates ranged between 0-10% and 27.3-87.2% in low-risk and high-risk subgroups, respectively. Positive surgical margin was associated with higher levels of EMT and B cell infiltration in the tumor area, as well as the enrichment of B cells, immature dendritic cells, and neutrophil infiltration in the peritumoral area. CONCLUSIONS: This MRI-based predictive model can be used as a reliable tool to predict the risk of margin positivity of BCS. Tumor immune-microenvironment alteration was associated with surgical margin status. CLINICAL RELEVANCE STATEMENT: This study can assist the pre-operative planning of BCS. Further research on the tumor immune microenvironment of different resection margin states is expected to develop new margin evaluation indicators and decipher the internal mechanism. KEY POINTS: • The MRI-based radiomic prediction model (CSS model) incorporating features extracted from multiple sequences and segments could estimate the margin positivity risk of breast-conserving surgery. • The radiomic score of the CSS model allows risk stratification of patients undergoing breast-conserving surgery, which could assist in surgical planning. • With the help of MRI-based radiomics to estimate the components of the immune microenvironment, for the first time, it is found that the margin status of breast-conserving surgery is associated with the infiltration of immune cells in the microenvironment and the EMT status of breast tumor cells.

Identifying interactions among air pollutant emissions on diabetes prevalence in Northeast China using a complex network.

BACKGROUND: Low air quality related to ambient air pollution is the largest environmental risk to health worldwide. Interactions between air pollution emissions may affect associations between air pollution exposure and chronic diseases. Therefore, this study aimed to quantify interactions among air pollution emissions and assess their effects on the association between air pollution and diabetes. METHODS: After constructing long-term emission networks for six air pollutants based on data collected from routine monitoring stations in Northeast China, a mutual information network was used to quantify interactions among air pollution emissions. Multiple linear regression analysis was then used to explore the influence of emission interactions on the association between air pollution exposure and the prevalence of diabetes based on data reported from the Northeast Natural Cohort Study in China. RESULTS: Complex network analysis detected three major emission sources in Northeast China located in Shenyang and Changchun. The effects of particulate matter (PM2.5 and PM10) and ground-level ozone (O3) emissions were limited to certain communities but could spread to other communities through emissions in Inner Mongolia. Emissions of sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) significantly influenced other communities. These results indicated that air pollutants in different geographic areas can interact directly or indirectly. Adjusting for interactions between emissions changed associations between air pollution emissions and diabetes prevalence, especially for PM2.5, NO2, and CO. CONCLUSIONS: Complex network analysis is suitable for quantifying interactions among air pollution emissions and suggests that the effects of PM2.5 and NO2 emissions on health outcomes may have been overestimated in previous population studies while those of CO may have been underestimated. Further studies examining associations between air pollution and chronic diseases should consider controlling for the effects of interactions among pollution emissions.

Genetic correlation, shared loci, but no causality between bipolar disorder and inflammatory bowel disease: A genome-wide pleiotropic analysis.

BACKGROUND AND AIMS: The comorbidity between bipolar disorder (BD) and inflammatory bowel disease (IBD) has been widely reported in observational studies. However, unclear whether this comorbidity reflects a shared genetic architecture. METHODS: Leveraging large-scale genome-wide association study (GWAS) summary statistics of BD, IBD and its subtypes, ulcerative colitis (UC) and Crohn's disease (CD), we performed a genome-wide pleiotropic analysis to estimate heritability and genetic correlation, identify pleiotropy loci/genes, and explore the shared biological pathway. Mendelian randomization (MR) studies were subsequently employed to infer whether the potential causal relationship is present. RESULTS: We found a positive significant genetic correlation between BD and IBD (rg = 0.10, P = 7.00 × 10-4), UC (rg = 0.09, P = 2.90 × 10-3), CD (rg = 0.08, P = 6.10 × 10-3). In cross-trait meta-analysis, a total of 29, 24, and 23 independent SNPs passed the threshold for significant association between BD and IBD, UC, and CD, respectively. We identified five novel pleiotropy genes including ZDHHC2, SCRN1, INPP4B, C1orf123, and BRD3 in both BD and IBD, as well as in its subtypes UC and CD. Pathway enrichment analyses revealed that those pleiotropy genes were mainly enriched in several immune-related signal transduction pathways and cerebral disease-related pathways. MR analyses provided no evidence for a causal relationship between BD and IBD. CONCLUSION: Our findings corroborated that shared genetic basis and common biological pathways may explain the comorbidity of BD and IBD. These findings further our understanding of shared genetic mechanisms underlying BD and IBD, and potentially provide points of intervention that may allow the development of new therapies for these co-occurrent disorders.

Association of genetic risk and lifestyle with pancreatic cancer and their age dependency: a large prospective cohort study in the UK Biobank.

BACKGROUND: Pancreatic cancer (PC) is influenced by both genetic and lifestyle factors. However, further research is still needed to comprehensively clarify the relationships among lifestyle, genetic factors, their combined effect on PC, and how these associations might be age-dependent. METHODS: We included 340,631 participants from the UK Biobank. Three polygenic risk score (PRS) models for PC were applied, which were derived from the previous study and were categorized as low, intermediate, and high. Two healthy lifestyle scores (HLSs) were constructed using 9 lifestyle factors based on the World Cancer Research Fund/American Institute of Cancer Research (WCRF/AICR) lifestyle score and the American Cancer Society (ACS) guidelines and were categorized as unfavorable, intermediate, and favorable. Data were analyzed using Cox proportional hazards models. RESULTS: There were 1,129 cases of incident PC during a median follow-up of 13.05 years. Higher PRS was significantly associated with an increased risk of PC (hazard ratio [HR], 1.58; 95% confidence intervals [CI], 1.47-1.71). Adhering to a favorable lifestyle was associated with a lower risk (HR, 0.48; 95% CI, 0.41-0.56). Participants with an unfavorable lifestyle and a high PRS had the highest risk of PC (HR, 2.84; 95% CI, 2.22-3.62). Additionally, when stratified by age, a favorable lifestyle was most pronounced associated with a lower risk of PC among participants aged ≤ 60 years (HR, 0.35; 95% CI, 0.23-0.54). However, the absolute risk reduction was more pronounced among those aged > 70 years (ARR, 0.19%, 95% CI, 0.13%-0.26%). A high PRS was more strongly associated with PC among participants aged ≤ 60 years (HR, 1.89; 95% CI, 1.30-2.73). Furthermore, we observed a significant multiplicative interaction and several significant additive interactions. CONCLUSIONS: A healthy lifestyle was associated with a lower risk of PC, regardless of the participants' age, sex, or genetic risk. Importantly, our findings indicated the age-dependent association of lifestyle and genetic factors with PC, emphasizing the importance of early adoption for effective prevention and potentially providing invaluable guidance for setting the optimal age to start preventive measures.

Machine learning radiomics of magnetic resonance imaging predicts recurrence-free survival after surgery and correlation of LncRNAs in patients with breast cancer: a multicenter cohort study.

BACKGROUND: Several studies have indicated that magnetic resonance imaging radiomics can predict survival in patients with breast cancer, but the potential biological underpinning remains indistinct. Herein, we aim to develop an interpretable deep-learning-based network for classifying recurrence risk and revealing the potential biological mechanisms. METHODS: In this multicenter study, 1113 nonmetastatic invasive breast cancer patients were included, and were divided into the training cohort (n = 698), the validation cohort (n = 171), and the testing cohort (n = 244). The Radiomic DeepSurv Net (RDeepNet) model was constructed using the Cox proportional hazards deep neural network DeepSurv for predicting individual recurrence risk. RNA-sequencing was performed to explore the association between radiomics and tumor microenvironment. Correlation and variance analyses were conducted to examine changes of radiomics among patients with different therapeutic responses and after neoadjuvant chemotherapy. The association and quantitative relation of radiomics and epigenetic molecular characteristics were further analyzed to reveal the mechanisms of radiomics. RESULTS: The RDeepNet model showed a significant association with recurrence-free survival (RFS) (HR 0.03, 95% CI 0.02-0.06, P < 0.001) and achieved AUCs of 0.98, 0.94, and 0.92 for 1-, 2-, and 3-year RFS, respectively. In the validation and testing cohorts, the RDeepNet model could also clarify patients into high- and low-risk groups, and demonstrated AUCs of 0.91 and 0.94 for 3-year RFS, respectively. Radiomic features displayed differential expression between the two risk groups. Furthermore, the generalizability of RDeepNet model was confirmed across different molecular subtypes and patient populations with different therapy regimens (All P < 0.001). The study also identified variations in radiomic features among patients with diverse therapeutic responses and after neoadjuvant chemotherapy. Importantly, a significant correlation between radiomics and long non-coding RNAs (lncRNAs) was discovered. A key lncRNA was found to be noninvasively quantified by a deep learning-based radiomics prediction model with AUCs of 0.79 in the training cohort and 0.77 in the testing cohort. CONCLUSIONS: This study demonstrates that machine learning radiomics of MRI can effectively predict RFS after surgery in patients with breast cancer, and highlights the feasibility of non-invasive quantification of lncRNAs using radiomics, which indicates the potential of radiomics in guiding treatment decisions.

Development of a radiomics model to discriminate ammonium urate stones from uric acid stones in vivo: A remedy for the diagnostic pitfall of dual-energy computed tomography.

BACKGROUND: Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them. METHODS: This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated. RESULTS: When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899-0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796-0.995) and 0.870 (95% CI, 0.769-0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model. CONCLUSIONS: DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.

The survival and outcome of older patients with primary aneurysmal subarachnoid haemorrhage: a 2-year follow-up, multi-centre, observational study.

BACKGROUND AND PURPOSE: The management of older aneurysmal subarachnoid haemorrhage (aSAH) cases is a clinical challenge. This study aimed to analyse the survival and functional outcomes in older aSAH patients (age ≥ 70 years) to provide evidence for making treatment decisions for such patients. METHODS: We performed a 2-year follow-up analysis of the Chinese Multi-Centre Cerebral Aneurysm Database for older patients suffering from aSAH from 2017 to 2020. A survival analysis was used to investigate the mean survival and hazard ratios for death. Binary logarithmic regression was performed to investigate the odds ratio for independent survival and dependent survival. RESULTS: A total of 1,136 consecutive older patients with aSAH were assessed in this study, and 944 patients (83.1%) were followed up. The overall mean survival was 37.79 ± 1.04 months. A total of 380 (40.25%) patients died within 2 years after aSAH. In survival analysis, the predictors of mortality were older age, intracerebral haemorrhage (ICH) history, Hunt-Hess (H-H) grade, World Federation of Neurosurgical Societies (WFNS) grade and operative treatment decreased the risk of mortality compared to conservative treatment. In binary logarithmic regression, the predictors of dependent survival were hypertension, diabetes, WFNS grade. CONCLUSIONS: The risk for 2-year mortality after aSAH increases markedly with older age, ICH history, H-H grade and WFNS grade. Risk factors for 2-year dependent survival were associated with hypertension, diabetes and WFNS grade in older patients with aSAH. Operative treatment markedly decreased mortality but did not significantly decrease the morbidity of dependent survival compared to conservative treatment.

Neutrophil extracellular traps correlate with severity and prognosis in patients with ischemic stroke: a systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE: A correlation between neutrophil extracellular traps (NETs) and ischemic stroke (IS) has been hypothesized, but the results of relevant studies remain controversial. The purpose was to determine whether NETs have an impact on ischemic stroke. METHODS: The studies on the correlation between NETs and IS were retrieved from CNKI, Wanfang Data, VIP, CBM, PubMed, Web of Science, Embase, and Cochrane databases by computer from the start of the database to December 2022. The study adhered to PRISMA guidelines. The PICOS model was used to create inclusion criteria. Two researchers screened the literature and extracted the relevant data. The quality of the included studies was evaluated using the NOS and the 11 items recommended by the AHRQ, and meta-analysis was completed using Stata 15.1 software. RESULTS: The researchers included 752 patients in 7 studies (4 case-control studies and 3 cross-sectional studies). The meta-analysis found NETs are positively associated with the severity of IS at the time of onset [r(95% CI) = 0.31(0.24, 0.38), P < 0.001]. NETs are positively associated with a worse prognosis of IS [r(95% CI) = 0.34(0.13, 0.53), P = 0.003]. CONCLUSION: The presence of NETs is positively related to the severity and prognosis of IS. Higher levels of NETs indicate a more severe disease and a poorer prognosis. Because the number and quality of included studies are limited, the above results must be supported by further high-quality studies. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/ , identifier: CRD42022356619.

RNA­binding protein quaking 5 inhibits the progression of non­small cell lung cancer by upregulating netrin­4 expression.

It was recently reported that netrin­4 (Ntn­4), a component of the extracellular matrix, when downregulated, is involved in the progression of several types of cancer, including breast cancer, colorectal tumours, neuroblastoma and gastric cancer. In the present study, the level of Ntn­4 was examined in a public non­small cell lung cancer (NSCLC) dataset from the Netherlands Cancer Institute. This analysis revealed that the mRNA expression level of Ntn­4 was lower in the samples of patients with NSCLC compared with that in the control samples. Consistent with the mRNA level, the protein level of Ntn­4 was also found to be decreased in NSCLC cells. However, both the function of Ntn­4 and the underlying mechanisms of Ntn­4 downregulation in NSCLC have yet to be fully elucidated. As was anticipated, the overexpression of Ntn­4 led to a marked decrease in the proliferation, migration and invasion of NSCLC cells. Notably, RNA­binding protein quaking 5 (Qki­5) was found to exhibit antitumor activity in lung cancer, not only by enhancing the level of Ntn­4 by binding to Ntn­4 mRNA, but also by suppressing the proliferation, invasion and migration of NSCLC cells. However, Qki­5 is known to be frequently downregulated in NSCLC. Moreover, the knockdown of Ntn­4 was found to reverse the suppressive effects of Qki­5 on NSCLC progression both in vitro and in vivo. Taken together, the findings of the present study demonstrate that Ntn­4 is able to suppress the progression of NSCLC, and that the level of Ntn­4 can be regulated by Qki­5. Therefore, Ntn­4 may be a novel diagnostic and therapeutic target for the treatment of NSCLC.

Modular Synthesis of Biphen[n]arenes Directed by Five-Membered Heterocycles.

Modular synthesis of novel biphen[n]arenes (n = 2-4) with customizable heterocycle blocks, functional skeletons, binding sites, and topological structures could be facilely achieved through the rational design and replacement of reaction modules (furan and thiophene), functional modules (substituted benzene, biphenyl, and naphthalene), and linking modules (methylene). These biphen[n]arenes were characterized by NMR, HRMS, and X-ray crystalline diffraction, complemented by DFT calculations. Their photophysical properties were thoroughly studied.

Old wine in a new bottle: Applying the novel dynamic ARDL simulations approach to explore the impact of energy efficiency, financial development, economic growth, foreign direct investment, and urbanization on CO2 emissions.

Achieving carbon neutrality targets is crucial while considering the adverse impacts of carbon dioxide emissions (CE) on human life and the ecosystem. Therefore, its socioeconomic drivers have frequently been probed in the existing body of literature. Therefore, we investigate the impact of energy efficiency, FDI, financial development, urbanization, and economic growth on CE in Pakistan from 1975 to 2020. For this purpose, we apply the novel dynamic ARDL simulation approach to retrieve the short- and long-run estimates. The empirical results confirm that cointegration exists among the considered variables. Further, both the short- and long-run results reveal that energy efficiency impedes emissions, whereas urbanization, financial development, and FDI increase emissions. Considering the outcomes, there is a need to enhance energy efficiency in Pakistan. For this purpose, investment in technological advancements and innovations is required. Moreover, R&D in the energy sector should be promoted.