Surgery versus no surgery in platinum-sensitive relapsed ovarian cancer: final overall survival analysis of the SOC-1 randomized phase 3 trial.

Surgery for platinum-sensitive, relapsed ovarian cancer (PSROC) is widely practiced but had contradictory survival outcomes in previous studies. In this multicenter, open-label, phase 3 trial, women with PSROC, and having had one previous therapy and no platinum-based chemotherapy (platinum-free interval) of 6 months or more, were randomly assigned to either the surgery group (182 patients) or the no-surgery group (control) (175 patients). Patients with resectable diseases were eligible according to the international model (iMODEL), combined with a positron emission tomography-computed tomography imaging. Overall survival (OS) and progression-free survival were coprimary endpoints in hierarchical testing, and a significantly longer progression-free survival with surgery was previously reported. Final analysis of OS was planned at data maturity of 59%. Between 19 July 2012 and 3 June 2019, 357 patients were enrolled. Median follow-up was 82.5 months. Median OS was 58.1 months with surgery and 52.1 months for control (hazard ratio (HR) 0.80, 95% confidence interval (CI) 0.61-1.05, P = 0.11). The predefined threshold for statistical significance was not met, but prespecified sensitivity analysis was performed. Overall, 61 of 175 (35%) patients in control had crossed over to surgery following subsequent relapse, and adjusted HR for death in the surgery group compared with control was 0.76, 95% CI 0.58-0.99. In subgroup analysis of relapse sites by imaging, median survival was not estimable in the surgery group and was 69.5 months in control in patients with <20 sites (HR 0.69, 95% CI 0.46-1.03). Patients with a complete resection had the most favorable outcome, with a median OS of 73.0 months. Twenty-four of 182 (13.2%) patients remained relapse free and alive >60 months in the surgery group as compared with five of 175 (2.9%) patients in the control group. In patients with PSROC, surgery did not increase OS in the intention-to-treat population but resulted in a prolongation of survival following adjustment of crossover.ClinicalTrials.gov registration: NCT01611766 .

Nanosecond-pulsed plasma protects against bacterial fruit blotch and promotes melon seedling growth.

BACKGROUND: Bacterial fruit blotch (BFB), known as the 'cancer' of cucurbits, is a seed-borne disease of melons caused by Acidovorax citrulli. Traditional chemical treatments for BFB are ineffective and adversely affect the environment. Using dielectric barrier discharge (DBD) nanosecond-pulsed plasma technology, melon seeds were treated to promote germination and growth and to control BFB. RESULTS: Based on the evaluation parameters of seed germination, seedling growth, leaf yellowing and bacterial infection after seed plasma treatments, 9 min at 20 kV was selected as the optimal plasma discharge parameter. In this study, seedling growth was significantly improved after treating melon seeds carrying A. citrulli using this discharge parameter. The number of first true leaves measured on the eighth day was 2.3 times higher and the disease index was reduced by 60.5% compared to the control group. Attenuated total reflectance-Fourier transform infrared measurements show that plasma treatments penetrate the seed coat and denature polysaccharides and proteins in the seed kernel, affecting their growth and sterilization properties. CONCLUSION: Pre-sowing treatment of melon seeds carrying A. citrulli using nanosecond-pulsed plasma technology can effectively control seedling BFB disease and promote melon seedling growth by optimizing DBD parameters. © 2024 Society of Chemical Industry.

Flavan-3-ol monomers intake is associated with osteoarthritis risk in Americans over 40 years of age: results from the National Health and Nutritional Examination Survey database.

Objectives: Osteoarthritis (OA) stands as the prevailing progressive musculoskeletal disease, serving as the primary cause of chronic pain and activity limitations among adults over 40. Flavan-3-ols, common polyphenolic compounds, are believed to harbor anti-inflammatory and anti-aging properties. This study explores the relationship between flavan-3-ol intake and osteoarthritis risk in individuals over the age of 40 in the US. Methods: This study included 7452 participants over the age of 40 from three cycles (2007-2008, 2009-2010, and 2017-2018) of the National Health and Nutrition Examination Survey. Information on OA history was obtained via home surveys. Information on flavan-3-ol monomers intake was obtained using a survey from the Food and Nutrient Database for Dietary Studies. We used a logistic regression model and restricted cubic spline to analyze the relationships between flavan-3-ol monomers and OA. Stratified analyses were also conducted in this study. Results: There were 1056 participants with OA and 6396 without OA. Compared to the first tertile (T1) group, the adjusted odds ratio with a 95% confidence interval (CI) of logistic regression model 2 for the flavan-3-ol T2 group was 1.296 (0.979-1.715) (p = 0.068), the OR for (-)-epigallocatechin was 1.292 (1.025-1.629) (p = 0.032), and the OR for (-)-epicatechin 3-gallate was 1.348 (1.013, 1.793) (p = 0.042). A dose-response curve indicated a non-linear association (p for non-linearity <0.05) between OA and total flavan-3-ol monomers (nadir point: 483.29 mg, 95% CI: 0.61-0.90). No interaction effects were found in the subgroup analysis. Conclusions: In individuals over 40 in the US, the average daily dietary intake of flavan-3-ol monomers manifests a J-shaped relationship with OA risk.

Longitudinal strain correlates with 6-minute walk distance whereas ejection fraction and diastolic parameters do not.

BACKGROUND: Impaired functional capacity is a common symptom in patients with heart failure. Standard measures of left ventricular (LV) function, such as ejection fraction (EF) and LV diastolic parameters, do not correlate with measures of functional capacity. The aim of this study is to determine if measures of global and regional LV strain better correlate with 6-minute walk distance than does EF or measures of LV diastolic function. METHODS: 120 patients referred to a cardiology clinic for evaluation of known or suspected heart failure were approached for enrollment. Of those 120 patients, 58 had an echocardiogram within 3 months of enrollment with images adequate for regional and global strain assessment, had no contra-indication to exercise testing, and had no previously documented non-cardiac explanation for dyspnea on exertion. In those 58 patients, 6-minute walk distance was measured, LV EF was determined with Simpson's biplane method, and global and regional longitudinal strain were measured with TomTec Image Arena 4.5.1 software. RESULTS: LV EF had no correlation with 6-minute walk distance (r = 0.22, p = 0.09) even when controlling for age, gender, and BMI (p = 0.07). No measures of LV diastolic function (including E velocity, Deceleration Time, e' annular velocities, or E/e') had a correlation with 6-minute walk distance. Multiple measures of global and regional LV longitudinal systolic function had a correlation with 6-minute walk distance. Longitudinal strain of the basal LV segments had the strongest correlation with 6-minute walk distance (r= -0.36, p = 0.005), and correlation persisted after controlling for age, gender, BMI, and systolic blood pressure (p = 0.004). CONCLUSIONS: Longitudinal strain correlates with a measure of functional capacity, but LVEF and traditional measures of LV diastolic dysfunction do not. Measures of longitudinal strain, especially in basal LV segments, will likely be an important marker of clinically relevant LV function.

Automatic detection of cognitive impairment in patients with white matter hyperintensity and causal analysis of related factors using artificial intelligence of MRI.

PURPOSE: White matter hyperintensity (WMH) is a common feature of brain aging, often linked with cognitive decline and dementia. This study aimed to employ deep learning and radiomics to develop models for detecting cognitive impairment in WMH patients and to analyze the causal relationships among cognitive impairment and related factors. MATERIALS AND METHODS: A total of 79 WMH patients from hospital 1 were randomly divided into a training set (62 patients) and a testing set (17 patients). Additionally, 29 patients from hospital 2 were included as an independent testing set. All participants underwent formal neuropsychological assessments to determine cognitive status. Automated identification and segmentation of WMH were conducted using VB-net, with extraction of radiomics features from cortex, white matter, and nuclei. Four machine learning classifiers were trained on the training set and validated on the testing set to detect cognitive impairment. Model performances were evaluated and compared. Causal analyses were conducted among cortex, white matter, nuclei alterations, and cognitive impairment. RESULTS: Among the models, the logistic regression (LR) model based on white matter features demonstrated the highest performance, achieving an AUC of 0.819 in the external test dataset. Causal analyses indicated that age, education level, alterations in cortex, white matter, and nuclei were causal factors of cognitive impairment. CONCLUSION: The LR model based on white matter features exhibited high accuracy in detecting cognitive impairment in WMH patients. Furthermore, the possible causal relationships among alterations in cortex, white matter, nuclei, and cognitive impairment were elucidated.

KBPT: knowledge-based prompt tuning for zero-shot relation triplet extraction.

Knowledge representation is increasingly recognized as an effective method for information extraction. Nevertheless, numerous studies have disregarded its potential applications in the zero-shot setting. In this article, a novel framework, called knowledge-based prompt tuning for zero-shot relation triplet extraction (KBPT), was developed, founded on external ontology knowledge. This framework serves as a catalyst for exploring relation triplet extraction (RTE) methods within low-resource scenarios, warranting further scrutiny. Zero-shot setting RTE aims to extract multiple triplets that consist of head entities, tail entities, and relation labels from an input sentence, where the extracted relation labels are those that do not exist in the training set. To address the data scarcity problem in zero-shot RTE, a technique was introduced to synthesize training samples by prompting language models to generate structured texts. Specifically, this involves integrating language model prompts with structured text methodologies to create a structured prompt template. This template draws upon relation labels and ontology knowledge to generate synthetic training examples. The incorporation of external ontological knowledge enriches the semantic representation within the prompt template, enhancing its effectiveness. Further, a multiple triplets decoding (MTD) algorithm was developed to overcome the challenge of extracting multiple relation triplets from a sentence. To bridge the gap between knowledge and text, a collective training method was established to jointly optimize embedding representations. The proposed model is model-agnostic and can be applied to various PLMs. Exhaustive experiments on four public datasets with zero-shot settings were conducted to demonstrate the effectiveness of the proposed method. Compared to the baseline models, KBPT demonstrated enhancements of up to 14.65% and 24.19% in F1 score on the Wiki-ZSL and TACRED-Revisit datasets, respectively. Moreover, the proposed model achieved better performance compared with the current state-of-the-art (SOTA) model in terms of F1 score, precision-recall (P-R) curves and AUC. The code is available at https://Github.com/Phevos75/KBPT.

Association of co-exposure to organophosphate esters and per- and polyfluoroalkyl substances and mixture with cardiovascular-kidney-liver-metabolic biomarkers among Chinese adults.

BACKGROUND: Organophosphate esters (OPEs) and Per- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental contaminants with common exposure sources, leading to their widespread presence in human body. However, evidence on co-exposure to OPEs and PFAS and its impact on cardiovascular-kidney-liver-metabolic biomarkers remains limited. METHODS: In this cross-sectional study, 467 adults were enrolled from January to May 2022 during physical visits in Shijiazhuang, Hebei province. Eleven types of OPEs and twelves types of PFAS were detected, among which eight OPEs and six PFAS contaminants were detected in more than 60% of plasma samples. Seventeen biomarkers were assessed to comprehensively evaluate the cardiovascular-kidney-liver-metabolic function. Multiple linear regression, multipollutant models with sparse partial least squares, and Bayesian kernel machine regression (BKMR) models were applied to examine the associations of individual OPEs and PFAS and their mixtures with organ function and metabolism, respectively. RESULTS: Of the over 400 exposure-outcome associations tested when modelling, we observed robust results across three models that perfluorohexanoic acid (PFHxS) was significantly positively associated with alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and indirect bilirubin (IBIL). Perfluorononanoic acid was significantly associated with decreased AST/ALT and increased very-low-density lipoprotein cholesterol levels. Besides, perfluorodecanoic acid was correlated with increased high lipoprotein cholesterol and perfluoroundecanoic acid was consistently associated with lower glucose level. BKMR analysis showed that OPEs and PFAS mixtures were positively associated with IBIL and TBIL, among which PFHxS was the main toxic chemicals. CONCLUSIONS: Our findings suggest that exposure to OPEs and PFAS, especially PFHxS and PFNA, may disrupt organ function and metabolism in the general population, providing insight into the potential pathophysiological mechanisms of OPEs and PFAS co-exposure and chronic diseases.

Au nanozyme-based colorimetric sensor array integrates machine learning to identify and discriminate monosaccharides.

As different monosaccharides exhibit different redox characteristics, this paper presented a novel colorimetric sensor array based on the glucose oxidase-like (GOx-like) activity of Au nanoparticles (NPs) for monosaccharides identification. AuNPs can use O2, ABTS+•, or [Ag(NH3)2]+ as an electron acceptor to catalyze the oxidation of monosaccharides in different velocity, resulting in cross-responsive signals. The current sensor array can distinguish between different monosaccharides or their mixtures through linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA). Moreover, the glucose and fructose concentrations can be estimated simultaneously using a neural network regression model based on the sensor array. This method shows potential for monosaccharide detection in industrial, medical, and biological applications.

Is it a normal phenomenon for pediatric patients to have brain leptomeningeal contrast enhancement on 3-tesla magnetic resonance imaging?

Determining whether sevoflurane sedation in children leads to "pseudo" prominent leptomeningeal contrast enhancement (pLMCE) on 3 Tesla magnetic resonance imaging will help reduce overdiagnosis by radiologists and clarify the pathophysiological changes of pLMCE.

Sodium-glucose cotransporter-2 inhibitors and incidence of atrial fibrillation in older adults with type 2 diabetes: a retrospective cohort analysis.

Objectives: To investigate the risk of atrial fibrillation (AF) with sodium-glucose cotransporter-2 inhibitors (SGLT2is) compared to dipeptidyl peptidase-4 inhibitor (DPP4i) use in older US adults and across diverse subgroups. Methods: We conducted a retrospective cohort analysis using claims data from 15% random samples of Medicare fee-for-service beneficiaries. Patients were adults with type 2 diabetes (T2D), no preexisting AF, and were newly initiated on SGLT2i or DPP4i. The outcome was the first incident AF. Inverse probability treatment weighting (IPTW) was used to balance the baseline covariates between the treatment groups including sociodemographics, comorbidities, and co-medications. Cox regression models were used to assess the effect of SGLT2i compared to DPP4i on incident AF. Results: Of the 97,436 eligible individuals (mean age 71.2 ± 9.8 years, 54.6% women), 1.01% (n = 983) had incident AF over a median follow-up of 361 days. The adjusted incidence rate was 8.39 (95% CI: 6.67-9.99) and 11.70 (95% CI: 10.9-12.55) per 1,000 person-years in the SGLT2i and DPP4i groups, respectively. SGLT2is were associated with a significantly lower risk of incident AF (HR 0.73; 95% CI, 0.57 to 0.91; p = 0.01) than DPP4is. The risk reduction of incident AF was significant in non-Hispanic White individuals and subgroups with existing atherosclerotic cardiovascular diseases and chronic kidney disease. Conclusion: Compared to the use of DPP4i, that of SGLT2i was associated with a lower risk of AF in patients with T2D. Our findings contribute to the real-world evidence regarding the effectiveness of SGLT2i in preventing AF and support a tailored therapeutic approach to optimize treatment selection based on individual characteristics.

Chemical-Free Recycling of Cathode Material and Aluminum Foil from Waste Lithium-Ion Batteries by Combining Plasma and Ultrasonic Technology.

With the rapid demand for lithium-ion batteries due to the widespread application of electric vehicles, a significant amount of battery electrode pieces requiring urgent treatment are generated during battery production and disposal. The strong bonding caused by the presence of binders makes it challenging to achieve thorough separation between the cathode active materials and Al foil, posing difficulties in efficient battery material recycling. To address this issue, a plasma-ultrasonically combined physical separation method is proposed in this study. This method utilizes plasma-generated excited-state radicals assisted by ultrasonic waves to separate active materials and current collectors. The results indicate that the binders are effectively decomposed under plasma treatment at 13.56 MHz, 100 W, and 10 min in an oxygen atmosphere, resulting in a separation efficiency of 96.8 wt % for the cathode materials. Characterization results demonstrate that the morphology, crystal structure, and chemical composition of the recycled cathode active materials remain unchanged, facilitating subsequent direct restoration and hydrometallurgical recycling. Simultaneously, the Al foil is also completely recycled for subsequent reuse. Compared with traditional methods of separating cathode active materials and aluminum foil, the method proposed in this study has significant economic and environmental potential. It can promote the recycling of battery materials and the development of sustainable transportation.

Stabilizing High-Valence Copper(I) Sites with Cu-Ni Interfaces Enhances Electroreduction of CO2 to C2+ Products.

In this study, the copper-nickel (Cu-Ni) bimetallic electrocatalysts for electrochemical CO2 reduction reaction(CO2RR) are fabricated by taking the finely designed poly(ionic liquids) (PIL) containing abundant Salen and imidazolium chelating sites as the surficial layer, wherein Cu-Ni, PIL-Cu and PIL-Ni interaction can be readily regulated by different synthetic scheme. As a proof of concept, Cu@Salen-PIL@Ni(NO3)2 and Cu@Salen-PIL(Ni) hybrids differ significantly in the types and distribution of Ni species and Cu species at the surface, thereby delivering distinct Cu-Ni cooperation fashion for the CO2RR. Remarkably, Cu@Salen-PIL@Ni(NO3)2 provides a C2+ faradaic efficiency (FEC2+) of 80.9% with partial current density (jC 2+) of 262.9 mA cm-2 at -0.80 V (versus reversible hydrogen electrode, RHE) in 1 m KOH in a flow cell, while Cu@Salen-PIL(Ni) delivers the optimal FEC2+ of 63.8% at jC2+ of 146.7 mA cm-2 at -0.78 V. Mechanistic studies indicates that the presence of Cu-Ni interfaces in Cu@Salen-PIL@Ni(NO3)2 accounts for the preserve of high-valence Cu(I) species under CO2RR conditions. It results in a high activity of both CO2-to-CO conversion and C-C coupling while inhibition of the competitive HER.

Typicality- and instance-dependent label noise-combating: a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification.

Learning with noisy labels aims to train neural networks with noisy labels. Current models handle instance-independent label noise (IIN) well; however, they fall short with real-world noise. In medical image classification, atypical samples frequently receive incorrect labels, rendering instance-dependent label noise (IDN) an accurate representation of real-world scenarios. However, the current IDN approaches fail to consider the typicality of samples, which hampers their ability to address real-world label noise effectively. To alleviate the issues, we introduce typicality- and instance-dependent label noise (TIDN) to simulate real-world noise and establish a TIDN-combating framework to combat label noise. Specifically, we use the sample's distance to decision boundaries in the feature space to represent typicality. The TIDN is then generated according to typicality. We establish a TIDN-attention module to combat label noise and learn the transition matrix from latent ground truth to the observed noisy labels. A recursive algorithm that enables the network to make correct predictions with corrections from the learned transition matrix is proposed. Our experiments demonstrate that the TIDN simulates real-world noise more closely than the existing IIN and IDN. Furthermore, the TIDN-combating framework demonstrates superior classification performance when training with simulated TIDN and actual real-world noise.

Antiretroviral Stewardship: Top 10 Questions Encountered by Stewardship Teams and Solutions to Optimize Therapy.

PURPOSE: Infectious disease pharmacists and physicians overseeing antimicrobial stewardship programs possess expertise and often advanced certification in management of antiretrovirals to treat HIV. Stewardship programs are responsible for managing facility formularies and must stay up to date with the latest antiretrovirals, including once daily formulations and depot injectables. Furthermore, stewardship program members need to understand drug-interactions, short-, and long-term toxicities of these regimens, including dyslipidemia and cardiovascular effects. Patients receiving chronic antiretroviral therapy may present to the acute care, ambulatory care, and long-term care settings. Like other antimicrobials, audit-and-feedback, drug monitoring, and dose-optimization are often required to prevent antiretroviral associated medication errors and minimize resistance. METHODS: A narrative review was conducted on antiretroviral stewardship, addressing common clinical questions encountered by stewardship teams and best practices to optimize antiretroviral therapy and reduce the risk for treatment interruptions, resistance, drug interactions, long term toxicities, and other adverse effects. FINDINGS: People living with HIV are often hospitalized and treated by medical teams without formal HIV training. For this reason, these patients are at greater risk for medication errors during hospitalization and between transitions of care. Many opportunities are present for antiretroviral stewardship to mitigate these errors. Frequent updates to simplify HIV regimen, maintain select patients on fixed-dose combination tablets, and strategies to minimize drug interactions make it difficult for even the seasoned clinician to keep up regularly. IMPLICATIONS: Despite the availability of free online HIV resources and progress made in HIV management, significant opportunities for antiretroviral stewardship remain. Implementing electronic order entry updates, formulary upgrades, and formal pharmacy renal dose adjustments to optimize antiretroviral therapy will help clinicians harness these opportunities. Dedicated time and expertise for antiretroviral stewardship as part of local antimicrobial stewardship programs are needed.

Alterations in spatiotemporal characteristics of dynamic networks in juvenile myoclonic epilepsy.

BACKGROUND: Juvenile myoclonic epilepsy (JME) is characterized by altered patterns of brain functional connectivity (FC). However, the nature and extent of alterations in the spatiotemporal characteristics of dynamic FC in JME patients remain elusive. Dynamic networks effectively encapsulate temporal variations in brain imaging data, offering insights into brain network abnormalities and contributing to our understanding of the seizure mechanisms and origins. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 37 JME patients and 37 healthy counterparts. Forty-seven network nodes were identified by group-independent component analysis (ICA) to construct the dynamic network. Ultimately, patients' and controls' spatiotemporal characteristics, encompassing temporal clustering and variability, were contrasted at the whole-brain, large-scale network, and regional levels. RESULTS: Our findings reveal a marked reduction in temporal clustering and an elevation in temporal variability in JME patients at the whole-brain echelon. Perturbations were notably pronounced in the default mode network (DMN) and visual network (VN) at the large-scale level. Nodes exhibiting anomalous were predominantly situated within the DMN and VN. Additionally, there was a significant correlation between the severity of JME symptoms and the temporal clustering of the VN. CONCLUSIONS: Our findings suggest that excessive temporal changes in brain FC may affect the temporal structure of dynamic brain networks, leading to disturbances in brain function in patients with JME. The DMN and VN play an important role in the dynamics of brain networks in patients, and their abnormal spatiotemporal properties may underlie abnormal brain function in patients with JME in the early stages of the disease.

Human-like adrenal features in Chinese tree shrews revealed by multi-omics analysis of adrenal cell populations and steroid synthesis.

The Chinese tree shrew ( Tupaia belangeri chinensis) has emerged as a promising model for investigating adrenal steroid synthesis, but it is unclear whether the same cells produce steroid hormones and whether their production is regulated in the same way as in humans. Here, we comprehensively mapped the cell types and pathways of steroid metabolism in the adrenal gland of Chinese tree shrews using single-cell RNA sequencing, spatial transcriptome analysis, mass spectrometry, and immunohistochemistry. We compared the transcriptomes of various adrenal cell types across tree shrews, humans, macaques, and mice. Results showed that tree shrew adrenal glands expressed many of the same key enzymes for steroid synthesis as humans, including CYP11B2, CYP11B1, CYB5A, and CHGA. Biochemical analysis confirmed the production of aldosterone, cortisol, and dehydroepiandrosterone but not dehydroepiandrosterone sulfate in the tree shrew adrenal glands. Furthermore, genes in adrenal cell types in tree shrews were correlated with genetic risk factors for polycystic ovary syndrome, primary aldosteronism, hypertension, and related disorders in humans based on genome-wide association studies. Overall, this study suggests that the adrenal glands of Chinese tree shrews may consist of closely related cell populations with functional similarity to those of the human adrenal gland. Our comprehensive results (publicly available at http://gxmujyzmolab.cn:16245/scAGMap/) should facilitate the advancement of this animal model for the investigation of adrenal gland disorders.

ReaxFF-Based Molecular Dynamics Study of the Mechanism of the Reaction of N2O4 with H2O.

During long-term storage of the liquid propellant N2O4, it absorbs H2O to form the N2O4(H2O)n system, and this in turn generates HNO3, HNO2, and other substances in the storage tank because of corrosion, which seriously affects the performance of weaponry. In this work, we carried out computational simulations of N2O4 with different masses of water based on ReaxFF, analyzed the reaction intermediates and products, and investigated the mechanism of the reaction of N2O4 with H2O and of N2O4(H2O)n. The results show that the reaction product ω(HNO3+HNO2) undergoes a rapid growth in the early stage of the reaction and then tends toward dynamic equilibrium; the potential energy of the system decreases with the increase of ω(H2O), the reaction rate increases, and the rate of decomposition of HNO2 to form HNO3 increases. When ω(H2O) is 0.2 or 1.0%, the intermediate products are N2O4H2O or N2O4(H2O)2, respectively, and the reaction proceeds along two paths; when ω(H2O) ≥ 2.0%, N2O4(H2O)3 appears as the intermediate product, HNO3 and HNO2 are directly produced in one step, and a stable current loop can be formed within the whole system.

A novel colorectal cancer screening framework with feature interpretability to identify high-risk populations for colonoscopy.

BACKGROUND AND AIM: Risk assessment is of paramount importance for the detection and treatment of colorectal cancer. We developed and validated a feature interpretability screening framework to identify high-risk populations and recommend colonoscopy for them. METHODS: We utilized a training cohort consisting of 1 252 605 participants who underwent colonoscopies in Shanghai from 2013 to 2015 to develop the screening framework. We incorporated Shapley additive explanation values into feature selection to provide interpretability for the framework. Two sampling methods were separately employed to mitigate potential model bias caused by class imbalance. Furthermore, we employed various machine learning algorithms to construct risk assessment models and compared their performance. We tested the screening models on an external validation cohort of 359 462 samples and conducted comprehensive evaluation and statistical analysis of the validation results. RESULTS: The external validation results demonstrated that the models in the proposed framework achieved sensitivity over 0.734, specificity over 0.790, and area under the receiver operating characteristic curve ranging from 0.808 to 0.859. In the predictions of the best-performing model, the prevalence rates of colorectal cancer were 0.059% and 1.056% in the low- and high-risk groups, respectively. If colonoscopies were performed only on the high-risk group predicted by the model, only 14.36% of total colonoscopies would be needed to detect 74.86% of colorectal cancer cases. CONCLUSIONS: We developed and validated a novel framework to identify populations at high risk for colorectal cancer. Those classified as high risk should undergo colonoscopy for further diagnosis.

Propelling gold nanozymes: catalytic activity and biosensing applications.

Recently, gold nanomaterials have been rapidly developed owing to their high stability, good biocompatibility, and multifunctionality. The unique catalytic activity of gold nanomaterials has driven the emergence of the concept for a "gold nanozyme." Understanding the characteristics of gold nanozymes is crucial for improving their catalytic performance as well as expanding their applications. In this review, we provide an overview of the intrinsic enzyme-like activities of gold nanozymes, including peroxidase-, catalase-, superoxide dismutase-, and glucose oxidase-like activities, and the catalytic mechanisms involved. In addition, strategies for modulating the catalytic activity of gold nanozymes and their applications in biosensing were discussed in detail. Moreover, we highlight the current challenges of gold nanozymes and look forward to attracting more attention for propelling the developments in this field.

Neurophysiological features of STN LFP underlying sleep fragmentation in Parkinson's disease.

BACKGROUND: Sleep fragmentation is a persistent problem throughout the course of Parkinson's disease (PD). However, the related neurophysiological patterns and the underlying mechanisms remained unclear. METHOD: We recorded subthalamic nucleus (STN) local field potentials (LFPs) using deep brain stimulation (DBS) with real-time wireless recording capacity from 13 patients with PD undergoing a one-night polysomnography recording, 1 month after DBS surgery before initial programming and when the patients were off-medication. The STN LFP features that characterised different sleep stages, correlated with arousal and sleep fragmentation index, and preceded stage transitions during N2 and REM sleep were analysed. RESULTS: Both beta and low gamma oscillations in non-rapid eye movement (NREM) sleep increased with the severity of sleep disturbance (arousal index (ArI)-betaNREM: r=0.9, p=0.0001, sleep fragmentation index (SFI)-betaNREM: r=0.6, p=0.0301; SFI-gammaNREM: r=0.6, p=0.0324). We next examined the low-to-high power ratio (LHPR), which was the power ratio of theta oscillations to beta and low gamma oscillations, and found it to be an indicator of sleep fragmentation (ArI-LHPRNREM: r=-0.8, p=0.0053; ArI-LHPRREM: r=-0.6, p=0.0373; SFI-LHPRNREM: r=-0.7, p=0.0204; SFI-LHPRREM: r=-0.6, p=0.0428). In addition, long beta bursts (>0.25 s) during NREM stage 2 were found preceding the completion of transition to stages with more cortical activities (towards Wake/N1/REM compared with towards N3 (p<0.01)) and negatively correlated with STN spindles, which were detected in STN LFPs with peak frequency distinguishable from long beta bursts (STN spindle: 11.5 Hz, STN long beta bursts: 23.8 Hz), in occupation during NREM sleep (ß=-0.24, p<0.001). CONCLUSION: Features of STN LFPs help explain neurophysiological mechanisms underlying sleep fragmentations in PD, which can inform new intervention for sleep dysfunction. TRIAL REGISTRATION NUMBER: NCT02937727.