A ratiometric fluorescence and colorimetry dual-signal sensing strategy based on o-phenylenediamine and AuNCs for determination of Cu2+ and glyphosate.

A ratiometric fluorescence sensing strategy has been developed for the determination of Cu2+ and glyphosate with high sensitivity and specificity based on OPD (o-phenylenediamine) and glutathione-stabilized gold nanoclusters (GSH-AuNCs). Water-soluble 1.75-nm size GSH-AuNCs with strong red fluorescence and maximum emission wavelength at 682 nm were synthesized using GSH as the template. OPD was oxidized by Cu2+, which produced the bright yellow fluorescence oxidation product 2,3-diaminophenazine (DAP) with a maximum fluorescence emission peak at 570 nm. When glyphosate existed in the system, the chelation between glyphosate and Cu2+ hindered the formation of DAP and reduced the fluorescence intensity of the system at the wavelength of 570 nm. Meanwhile, the fluorescence intensity at the wavelength of 682 nm remained basically stable. It exhibited a good linear relationship towards Cu2+ and glyphosate in water in the range 1.0-10 µM and 0.050-3.0 µg/mL with a detection limit of 0.547 µM and 0.0028 µg/mL, respectively. The method was also used for the semi-quantitative determination of Cu2+ and glyphosate in water by fluorescence color changes visually detected by the naked eyes in the range 1.0-10 µM and 0.30-3.0 µg/mL, respectively. The sensing strategy showed higher sensitivity, more obvious color changes, and better disturbance performance, satisfying with the detection demands of Cu2+ and glyphosate in environmental water samples. The study provides a reliable detection strategy in the environment safety fields.

Diagnostic performance of mpox virus (MPXV) real-time PCR assays: multicenter assessment and extended sensitivity analysis.

PURPOSE: To comprehensively investigate the diagnostic performance of routinely used assays in MPXV testing, the National Center of Clinical Laboratories in China conducted a nationwide external quality assessment (EQA) scheme and an evaluated nine assays used by ≥ 5 laboratories in the EQA. METHODS: MPXV virus-like particles with 2700, 900 and 300 copies/mL were distributed to 195 EQA laboratories. For extended analysis, triple-diluted samples from 9000 to 4.12 copies/mL were repeated 20 times using the assays employed by ≥ 5 laboratories. The diagnostic performance was assessed by analyzing EQA data and calculating the limits of detection (LODs). RESULTS: The performance was competent in 87.69% (171/195) of the participants and 87.94% (175/199) of the datasets. The positive percentage agreements (PPAs) were greater than 99% for samples at 2700 and 900 copies/mL, and 95.60% (761/796) for samples at 300 copies/mL. The calculated LODs for the two clades ranged from 228.44 to 924.31 copies/mL and were greater than the LODs specified by the respective kits. EasyDiagnosis had the lowest calculated LODs and showed superior performance in EQA, whereas BioGerm and Sansure, with higher calculated LODs, did not perform well in EQA. CONCLUSION: This study provides valuable information from the EQA data and evaluation of the diagnostic performance of MPXV detection assays. It also provided insights into reagent optimization and enabled prompt public health interventions for the outbreak.

Transcriptomic and genomic characteristics of intrahepatic metastases of primary liver cancer.

BACKGROUND: Patients with primary multifocal hepatocellular carcinoma (HCC) have a poor prognosis and often experience a high rate of treatment failure. Multifocal HCC is mainly caused by intrahepatic metastasis (IM), and though portal vein tumor thrombosis (PVTT) is considered a hallmark of IM, the molecular mechanism by which primary HCC cells invade the portal veins remains unclear. Therefore, it is necessary to recognize the early signs of metastasis of HCC to arrange better treatment for patients. RESULTS: To determine the differential molecular features between primary HCC with and without phenotype of metastasis, we used the CIBERSORTx software to deconvolute cell types from bulk RNA-Seq based on a single-cell transcriptomic dataset. According to the relative abundance of tumorigenic and metastatic hepatoma cells, VEGFA+ macrophages, effector memory T cells, and natural killer cells, HCC samples were divided into five groups: Pro-T, Mix, Pro-Meta, NKC, and MemT, and the transcriptomic and genomic features of the first three groups were analyzed. We found that the Pro-T group appeared to retain native hepatic metabolic activity, whereas the Pro-Meta group underwent dedifferentiation. Genes highly expressed in the group Pro-Meta often signify a worse outcome. CONCLUSIONS: The HCC cohort can be well-typed and prognosis predicted according to tumor microenvironment components. Primary hepatocellular carcinoma may have obtained corresponding molecular features before metastasis occurred.

Caregivers' experiences in helping individuals with severe and enduring mental health challenges integrate into the community: A qualitative descriptive study in Singapore.

WHAT IS KNOWN ABOUT THE SUBJECT: Individuals with severe and enduring mental health challenges continued to consume mental health services for an average of 13 years as they needed multiple acute psychiatric admissions due to the challenges they experienced in their everyday activities. As caregivers of individuals with severe and enduring mental health challenges, they often bear the brunt of caregiving through their assistance with activities of daily living (ADL), providing emotional support and ensuring medication compliance for their loved ones. When caring for their loved ones, caregivers often reported psychological stress, social isolation and emotional exhaustion due to stressors such as uncertainty of the future, the lack of support from professional services and the isolation from their own social network and support mechanism. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE: Insights from this study revealed that caregivers for individuals with severe and enduring mental health challenges went through a lonely and exhausting journey fraught with psychological, physical, social and financial challenges, echoing the caregiving needs and the prevalence of the caregiver burden. WHAT ARE THE IMPLICATIONS FOR PRACTICE: Insights shared by the caregivers demonstrated the need for a centralised point of contact to navigate Singapore's fragmented mental healthcare sector. Peer-support groups should be further promoted because they offer the benefits of information exchange, mutual support and a sense of empowerment and hopefulness, which may help ease the caregiver burden. Life skills training, such as teaching how to communicate empathetically with family members, resolve conflicts using open communication, maintain a structured daily routine and solve pragmatic problems in daily life, is more critical for individuals with severe and enduring mental health challenges. This will help them learn how to manage their well-being, live independently, and stabilise their conditions. Lastly, public awareness campaigns should honour caregivers by highlighting their strength, resilience, and dedication. The state can provide financial assistance in the form of tax relief for their income per annum or caregiver allowance to alleviate the financial stress that caregivers are facing. ABSTRACT: Introduction The progressive deinstitutionalisation of mental healthcare has increasingly shifted care responsibilities from healthcare professionals to family caregivers for individuals with severe mental illness. Caregivers must balance many obligations, which often compromise their overall health and well-being, while helping their loved ones integrate into the community. Aim To identify and understand caregivers' needs and challenges as they help individuals with severe and enduring mental health challenges integrate into the community. Methods This study used a descriptive qualitative approach to explore the experiences and challenges of caregivers for individuals with severe and enduring mental health challenges when integrating back into the community. A semi-structured guide was used during the video-conferencing interviews conducted between December 2021 and November 2022. This study was reported according to the 32-item Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist. Findings Fourteen caregivers were individually interviewed by the primary author. Most caregivers were female, with an average of 15 years of experience caring for their loved ones. Using Braun and Clark's six-phase thematic framework, we inductively generate the themes and subthemes from the data. The two themes were (i) challenges (whose subthemes included personal challenges in caregiving, the lack of awareness, and stigma and employment) and (ii) support (whose subthemes included the importance of socialisation for individuals with mental health conditions, existing avenues of support and potential areas for support). Discussion Our findings informed the contemporary needs of caregivers caring for individuals with severe and enduring mental health challenges integrating into the community. Like the global challenges for people with mental health issues, psychosocial support and other supplementary support are still common themes in mental health settings. The findings further specifically highlighted the importance of accessible points of contact as resources and employment-enabling and sustaining initiatives to help manage caregivers' emotional and system challenges, which addresses the gaps identified in the findings. Caregivers' peer-support groups, life skills training and public mental health awareness are also necessitated by the caregivers' voices. Implications for Practice Priority areas include having a centralised point of contact within the community for caregivers. Government or not-for-profit organisations can take the lead by initiating employment-enabling initiatives for individuals with severe and enduring mental health challenges and their caregivers.

Status and influencing factors of nurses' burnout: A cross-sectional study during COVID-19 regular prevention and control in Jiangsu Province, China.

Background: Chinese nurses working with immense stress may have issues with burnout during COVID-19 regular prevention and control. There were a few studies investigating status of burnout and associated factors among Chinese nurses. However, the relationships remained unclear. Objectives: To investigate status and associated factors of nurses' burnout during COVID-19 regular prevention and control. Methods: 784 nurses completed questionnaires including demographics, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Insomnia Severity Index, Impact of Event Scale-revised, Perceived Social Support Scale, Connor-Davidson Resilience Scale, General Self-efficacy Scale and Maslach Burnout Inventory. Results: 310 (39.5%), 393 (50.1%) and 576 (73.5%) of respondents were at high risk of emotional exhaustion (EE), depersonalization (DP) and reduced personal accomplishment (PA). The risk of EE, DP and reduced PA were moderate, high and high. Nurses with intermediate and senior professional rank and title and worked >40 h every week had lower scores in EE. Those worked in low-risk department reported lower scores in PA. Anxiety, post-traumatic stress disorder (PTSD), self-efficacy and social support were influencing factors of EE and DP, while social support and resilience were associated factors of PA. Conclusion: Chinese nurses' burnout during COVID-19 regular prevention and control was serious. Professional rank and title, working unit, weekly working hours, anxiety, PTSD, self-efficacy, social support and resilience were associated factors of burnout.

Mechanism and deterioration pattern of sandstone surrounding rock voiding at bottom of heavy-haul railway tunnel.

This study combines laboratory experiments and discrete element simulation methods to analyze the mechanism and deterioration patterns of sandstone surrounding rock voiding the bottom of a heavy-haul railway tunnel. It is based on previously acquired measurement data from optical fiber grating sensors installed in the Taihangshan Mountain Tunnel of the Wari Railway. By incorporating rock particle wastage rate results, a method for calculating the peak strength and elastic modulus attenuation of surrounding rock is proposed. Research indicates that the operation of heavy-haul trains leads to an instantaneous increase in the dynamic water pressure on the bottom rock ranging 144.4-390.0%, resulting in high-speed water flow eroding the rock. After 1-2 years of operation, the bottom water and soil pressures increase by 526.5% and 390.0%, respectively. Focusing on sandstone surrounding rock with high observability, laboratory experiments were conducted to monitor the degradation stages of infiltration, particle loss, and voiding of rock under the action of dynamic water flow. The impact of water flow on the "cone-shaped" bottom rock deformation was also clarified. The extent of rock deterioration and voiding was determined using miniature water and soil pressure sensors in conjunction with discrete element numerical simulations. The measured rock particle loss was used as a criterion. Finally, a fitting approach is derived to calculate the peak strength and elastic modulus attenuation of surrounding rock, gaining insight into and providing a reference for the maintenance and disposal measures for the bottom operation of heavy-haul railway tunnels.

LncRNA FRMD6-AS1/miR-491-5p/USP13 pathway attenuated ferroptosis and contributed to liver fibrosis.

Liver fibrosis is an invertible pathophysiologic process featured by excessive accumulation of extracellular matrix (ECM) which injures liver cells and activates hepatic stellate cells (HSCs). Besides, inducing ferroptosis in activated HSCs can alleviate liver fibrosis. LncRNAs modulate ferroptosis in activated HSCs and ECM deposition in liver fibrosis. However, the role of lncRNA FRMD6-AS1 in liver fibrosis is not discovered. In this study, lncRNA FRMD6-AS1 was dramatically up-regulated in activated HSCs. Knockdown of FRMD6-AS1 markedly increased iron ion, ROS and MDA levels, decreased GSH level, SLC7A11 and GPX4 protein expressions in activated HSCs. In addition, HSCs activation markers α-SMA and COL1α1 expressions were up-regulated in activated HSCs; knockdown of FRMD6-AS1 markedly down-regulated α-SMA and COL1α1 expressions in HSCs. Besides, lncRNA FRMD6-AS1 could interact with miR-491-5p, and negatively modulate miR-491-5p expression. USP13 was a target of miR-491-5p, and could be negatively modulated by miR-491-5p. Moreover, FRMD6-AS1 knockdown increased iron ion and ROS levels, decreased SLC7A11 and GPX4 protein expressions, facilitated HSCs viability, and up-regulated α-SMA and COL1α1 expressions via miR-491-5p/USP13 pathway. Finally, FRMD6-AS1 knockdown restored liver tissue structure and abrogated fibrosis in livers in a CCL4 liver fibrosis mouse model. Hence, lncRNA FRMD6-AS1/miR-491-5p/USP13 pathway repressed ferroptosis, promoted ECM deposition and facilitated liver fibrosis in vitro and in vivo models.

Nomogram predicting survival in patients with lymph node-negative hepatocellular carcinoma based on the SEER database and external validation.

BACKGROUND: The relationship between lymph node (LN) status and survival outcome in hepatocellular carcinoma (HCC) is a highly controversial topic. The aim of this study was to investigate the prognostic factors in patients without LN metastasis (LNM) and to construct a nomogram to predict cancer-specific survival (CSS) in this group of patients. METHODS: We screened 6840 eligible HCC patients in the Surveillance, Epidemiology and End Results（SEER）database between 2010 and 2019 and randomized them into a training cohort and an internal validation cohort, and recruited 160 patients from Zhongnan Hospital of Wuhan University as an external validation cohort. Independent prognostic factors obtained from univariate and multivariate analysis were used to construct a nomogram prediction model. The concordance index (C-index), area under curve (AUC), calibration plots and decision curve analysis (DCA) were used to assess the predictive power and clinical application of the model. RESULTS: Univariate and multivariate analysis revealed age, gender, bone metastasis, lung metastasis, AFP, T stage, surgery and chemotherapy as independent prognostic factors. The C-index of the constructed nomogram for the training cohort, internal validation cohort and external validation cohort are 0.746, 0.740, and 0.777, respectively. In the training cohort, the AUC at 1-, 3-, and 5-year were 0.81, 0.800, and 0.800, respectively. Calibration curves showed great agreement between the actual observations and predictions for the three cohorts. The DCA results suggest that the nomogram model has more clinical application potential. CONCLUSION: We constructed a nomogram to predict CSS in HCC patients without LNM. The model has been internally and externally validated to have excellent predictive performance and can help clinicians determine prognosis and make treatment decisions.

[Research progress of traditional Chinese medicines as quorum sensing inhibitors in collaboration with antibiotics to inhibit drug-resistant bacteria].

Quorum sensing system regulates the expression of genes related to bacterial growth, metabolism and other behaviors by sensing bacterial density, and controls the unified action of the entire bacterial population. This mechanism can ensure the normal secretion of bacterial metabolites and the stability of the biofilm microenvironment, providing protection for the formation of biofilms and the normal growth and reproduction of bacteria. Traditional Chinese medicine, capable of quorum sensing inhibition, can inhibit the formation of bacterial biofilms, reduce bacterial resistance, and enhance the anti-infection ability of antibiotics when combined with antibiotics. In recent years, the combination of traditional Chinese and Western medicine in the treatment of drug-resistant bacterial infections has become a research hotspot. Starting with the associations between quorum sensing, biofilm and drug-resistant bacteria, this paper reviews the relevant studies about the combined application of traditional Chinese medicines as quorum sensing inhibitors with antibiotics in the treatment of drug-resistant bacteria. This review is expected to provide ideas for the development of new clinical treatment methods and novel anti-infection drugs.

Acetylation of Rec8 cohesin complexes regulates reductional chromosome segregation in meiosis.

For establishing sister chromatid cohesion and proper chromosome segregation in mitosis in fission yeast, the acetyltransferase Eso1 plays a key role. Eso1 acetylates cohesin complexes, at two conserved lysine residues K105 and K106 of the cohesin subunit Psm3. Although Eso1 also contributes to reductional chromosome segregation in meiosis, the underlying molecular mechanisms have remained elusive. Here, we purified meiosis-specific Rec8 cohesin complexes localized at centromeres and identified a new acetylation at Psm3-K1013, which largely depends on the meiotic kinetochore factor meikin (Moa1). Our molecular genetic analyses indicate that Psm3-K1013 acetylation cooperates with canonical acetylation at Psm3-K105 and K106, and plays a crucial role in establishing reductional chromosome segregation in meiosis.

External quality assessment for molecular detection of Ureaplasma urealyticum in China.

BACKGROUND AND AIMS: A pilot external quality assessment (EQA) scheme for molecular detection of Ureaplasma urealyticum (UU) was conducted by the National Center for Clinical Laboratories (NCCL) to evaluate the testing capabilities of clinical laboratories and the actual performance of DNA-based nucleic acid amplification tests (NAAT) and RNA-based NAATs when applied in clinical settings. MATERIALS AND METHODS: The EQA panel contained twelve lyophilized samples, including positive samples containing inactivated cell culture supernatants of UU at different concentrations and sterile saline for negative samples. The positive samples were further divided into three groups of high, moderate and low concentrations. The panels were distributed to the participants and the datasets were analyzed according to the qualitative results. RESULTS: A total of 365 laboratories participated in the EQA scheme, and 360 results submitted by 338 laboratories were collected, of which 96.11 % (346/360) of the returned results and 95.86 % (324/338) of the laboratories were deemed competent. The positive percentage agreement (PPA) was ≥ 97.5 % for high and moderate concentration samples, but varied significantly for low concentration samples, decreasing from 86.94 % to 51.94 % as the sample concentration decreased. Additionally, for low concentration samples, RNA-based NAAT showed higher PPAs than DNA-based NAATs, but these results were specific to UU supernatants used in this study. CONCLUSION: Most of UU detection assays employed by the participants were generally consistent with their estimated limit of detection (LOD), and the majority of participants can reliably detect UU samples with high and moderate concentrations, while the poor analytical performance for low concentration samples requires further improvement and optimization.

An [18F]FDG PET/3D-ultrashort echo time MRI-based radiomics model established by machine learning facilitates preoperative assessment of lymph node status in non-small cell lung cancer.

OBJECTIVES: To develop an [18F]FDG PET/3D-UTE model based on clinical factors, three-dimensional ultrashort echo time (3D-UTE), and PET radiomics features via machine learning for the assessment of lymph node (LN) status in non-small cell lung cancer (NSCLC). METHODS: A total of 145 NSCLC patients (training, 101 cases; test, 44 cases) underwent whole-body [18F]FDG PET/CT and chest [18F]FDG PET/MRI were enrolled. Preoperative clinical factors and 3D-UTE, CT, and PET radiomics features were analyzed. The Mann-Whitney U test, LASSO regression, and SelectKBest were used for feature extraction. Five machine learning algorithms were used to establish prediction models, which were evaluated by the area under receiver-operator characteristic (ROC), DeLong test, calibration curves, and decision curve analysis (DCA). RESULTS: A prediction model based on random forest, consisting of four clinical factors, six 3D-UTE, and six PET radiomics features, was used as the final model for PET/3D-UTE. The AUCs of this model were 0.912 and 0.791 in the training and test sets, respectively, which not only showed different degrees of improvement over individual models such as clinical, 3D-UTE, and PET (AUC-training = 0.838, 0.834, and 0.828, AUC-test = 0.756, 0.745, and 0.768, respectively) but also achieved the similar diagnostic efficacy as the optimal PET/CT model (AUC-training = 0.890, AUC-test = 0.793). The calibration curves and DCA indicated good consistency (C-index, 0.912) and clinical utility of this model, respectively. CONCLUSION: The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using machine learning methods could noninvasively assess the LN status of NSCLC. CLINICAL RELEVANCE STATEMENT: A machine learning model of 18F-fluorodeoxyglucose positron emission tomography/ three-dimensional ultrashort echo time could noninvasively assess the lymph node status of non-small cell lung cancer, which provides a novel method with less radiation burden for clinical practice. KEY POINTS: • The 3D-UTE radiomics model using the PLS-DA classifier was significantly associated with LN status in NSCLC and has similar diagnostic performance as the clinical, CT, and PET models. • The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using the RF classifier could noninvasively assess the LN status of NSCLC and showed improved diagnostic performance compared to the clinical, 3D-UTE, and PET models. • In the assessment of LN status in NSCLC, the [18F]FDG PET/3D-UTE model has similar diagnostic efficacy as the [18F]FDG PET/CT model that incorporates clinical factors and CT and PET radiomics features.

Artificial Neural Network Analysis of Determinants of Tacrolimus Pharmacokinetics in Liver Transplant Recipients.

BACKGROUND: The efficacy and toxicity of tacrolimus are closely related to its trough blood concentrations. Identifying the influencing factors of pharmacokinetics of tacrolimus in the early postoperative period is conducive to the optimization of the individualized tacrolimus administration protocol and to help liver transplant (LT) recipients achieve the target blood concentrations. OBJECTIVE: This study aimed to develop an artificial neural network (ANN) for predicting the blood concentration of tacrolimus soon after liver transplantation and for identifying determinants of the concentration based on Shapley additive explanation (SHAP). METHODS: In this retrospective study, we enrolled 31 recipients who were first treated with liver transplantation from the Department of Liver Transplantation and Hepatic Surgery, the First Affiliated Hospital of Shandong First Medical University (Shandong Provincial Qianfoshan Hospital) from November 2020 to May 2021. The basic information, biochemical indexes, use of concomitant drugs, and genetic factors of organ donors and recipients were used for the ANN model inputs, and the output was the steady-state trough concentration (C0) of tacrolimus after oral administration in LT recipients. The ANN model was established to predict C0 of tacrolimus, SHAP was applied to the trained model, and the SHAP value of each input was calculated to analyze quantitatively the influencing factors for the output C0. RESULTS: A back-propagation ANN model with 3 hidden layers was established using deep learning. The mean prediction error was 0.27 ± 0.75 ng/mL; mean absolute error, 0.60 ± 0.52 ng/mL; correlation coefficient between predicted and actual C0 values, 0.9677; and absolute prediction error of all blood concentrations obtained by the ANN model, ≤3.0 ng/mL. The results indicated that the following factors had the most significant effect on C0: age, daily drug dose, genotype at CYP3A5 polymorphism rs776746 in both recipient and donor, and concomitant use of caspofungin. The predicted C0 value of tacrolimus in LT recipients increased in a dose-dependent manner when the daily dose exceeded 3 mg, whereas it decreased with age when LT recipients were older than 48 years. The predicted C0 was higher when recipients and donors had the genotype CYP3A5*3*3 than when they had the genotype CYP3A5*1. The predicted C0 value also increased with the use of caspofungin or Wuzhi capsule. CONCLUSION AND RELEVANCE: The established ANN model can be used to predict the C0 value of tacrolimus in LT recipients with high accuracy and good predictive ability, serving as a reference for personalized treatment in the early stage after liver transplantation.

Active role of amino acid metabolism in early diagnosis and treatment of diabetic kidney disease.

Diabetic Kidney Disease (DKD) is one of the significant microvascular consequences of type 2 diabetes mellitus with a complex etiology and protracted course. In the early stages of DKD, the majority of patients experience an insidious onset and few overt clinical symptoms and indicators, but they are prone to develop end-stage renal disease in the later stage, which is life-threatening. The abnormal amino acid metabolism is tightly associated with the development of DKD, which involves several pathological processes such as oxidative stress, inflammatory response, and immune response and is also closely related to autophagy, mitochondrial dysfunction, and iron death. With a focus on taurine, branched-chain amino acids (BCAAs) and glutamine, we explored the biological effects of various amino acid mechanisms linked to DKD, the impact of amino acid metabolism in the early diagnosis of DKD, and the role of amino acid metabolism in treating DKD, to offer fresh objectives and guidelines for later early detection and DKD therapy.

A novel subspace outlier detection method by entropy-based clustering algorithm.

Subspace outlier detection has emerged as a practical approach for outlier detection. Classical full space outlier detection methods become ineffective in high dimensional data due to the "curse of dimensionality". Subspace outlier detection methods have great potential to overcome the problem. However, the challenge becomes how to determine which subspaces to be used for outlier detection among a huge number of all subspaces. In this paper, firstly, we propose an intuitive definition of outliers in subspaces. We study the desirable properties of subspaces for outlier detection and investigate the metrics for those properties. Then, a novel subspace outlier detection algorithm with a statistical foundation is proposed. Our method selectively leverages a limited set of the most interesting subspaces for outlier detection. Through experimental validation, we demonstrate that identifying outliers within this reduced set of highly interesting subspaces yields significantly higher accuracy compared to analyzing the entire feature space. We show by experiments that the proposed method outperforms competing subspace outlier detection approaches on real world data sets.

Sleep Deprivation Impairs Human Cognitive Reappraisal Ability: A Randomized Controlled Trial.

Purpose: This study aims to examine the impact of sleep deprivation on individual cognitive reappraisal ability using a standardized behavioral paradigm. Methods: A randomized pretest-posttest control group design was conducted. Thirty-nine participants were eventually enrolled and randomly assigned to receive either the sleep control (SC: n = 17) or the sleep deprivation (SD: n = 22). Both of them were required to perform a standardized behavioral paradigm of measuring cognitive reappraisal ability one time under sleep-rested condition and another time under the condition of different sleep manipulation a week later. Results: Mean valence ratings of SD group were more negative than SC group's (p < 0.05) and mean arousal ratings of SD group were higher than SC group's (p < 0.01). Conclusion: Sleep deprivation may impair individual cognitive reappraisal ability and could potentially undermine the efficacy of cognitive therapy in terms of emotion regulation.

PTSD of Chinese nurses in the normalisation of COVID-19 pandemic prevention and control: Prevalence and correlates.

Background: Though the severe prevention and control measures faced by Chinese nurses had changed during the normalisation stage of the coronavirus 2019 (COVID-19) pandemic, they still worked under great stress. Due to a lack of related evidence, we aimed to investigate the prevalence and correlates of post-traumatic stress disorder (PTSD) among Chinese nurses during the normalisation of COVID-19 pandemic prevention and control measures. Methods: Using convenience sampling, we recruited 784 nurses in Jiangsu province, China to complete a survey via their mobile devices. We used a demographic questionnaire, the Perceived Social Support Scale, the Connor-Davidson Resilience Scale, the General Self-Efficacy Scale, and The Impact of Event Scale-Revised to collect data and applied binary logistic regression analysis to identify factors associated with PTSD. Results: The prevalence of PTSD was 26.4%. Married nurses were less likely to experience PTSD than unmarried ones (odds ratio (OR) = 0.573; 95% confidence interval (CI) = 0.33-0.99, P = 0.046). Social support (OR = 0.96; 95% CI = 0.94-0.98, P = 0.000) and resilience (OR = 0.98; 95% CI = 0.97-0.99, P = 0.004) were significant predictors of PTSD. Conclusions: PTSD remained prevalent among Chinese nurses as COVID-19 pandemic prevention and control measures became normalised, with an incidence rate of 26.4%. Resilience, social support, and marital status were factors associated with PTSD. Chinese hospital management must intervene to improve resilience and social support for nurses to reduce symptoms of PTSD.

NOP2-mediated m5C Modification of c-Myc in an EIF3A-Dependent Manner to Reprogram Glucose Metabolism and Promote Hepatocellular Carcinoma Progression.

Mitochondrial dysfunction and glycolysis activation are improtant hallmarks of hepatocellular carcinoma (HCC). NOP2 is an S-adenosyl-L-methionine-dependent methyltransferase that regulates the cell cycle and proliferation activities. In this study, found that NOP2 contributes to HCC progression by promoting aerobic glycolysis. Our results revealed that NOP2 was highly expressed in HCC and that it was associated with unfavorable prognosis. NOP2 knockout in combination with sorafenib enhanced sorafenib sensitivity, which, in turn, led to marked tumor growth inhibition. Mechanistically, we identified that NOP2 regulates the c-Myc expression in an m5C-modification manner to promote glycolysis. Moreover, our results revealed that m5C methylation induced c-Myc mRNA degradation in an eukaryotic translation initiation factor 3 subunit A (EIF3A)-dependent manner. In addition, NOP2 was found to increase the expression of the glycolytic genes LDHA, TPI1, PKM2, and ENO1. Furthermore, MYC associated zinc finger protein (MAZ) was identified as the major transcription factor that directly controlled the expression of NOP2 in HCC. Notably, in a patient-derived tumor xenograft (PDX) model, adenovirus-mediated knockout of NOP2 maximized the antitumor effect and prolonged the survival of PDX-bearing mice. Our cumulative findings revealed the novel signaling pathway MAZ/NOP2/c-Myc in HCC and uncovered the important roles of NOP2 and m5C modifications in metabolic reprogramming. Therefore, targeting the MAZ/NOP2/c-Myc signaling pathway is suggested to be a potential therapeutic strategy for the treatment of HCC.

Advanced root mean square propagation with the warm-up algorithm for fiber coupling.

Fiber coupling plays an important role in applications such as free-space optical communication (FSOC) and self-referencing interferometry. However, the coupling efficiency is often affected by turbulence and platform vibrations, which requires dynamic coupling with optimization algorithms. In this paper, to further mitigate the effects of sudden disturbances and to expand the effective range of fiber coupling systems, we propose a new method called the advanced root mean square propagation with warm-up (ARW) algorithm. By adaptively adjusting both the gain rate and the perturbation rate with warm-up operations, the ARW algorithm can achieve higher effective range and acceptable steady-state coupling efficiency simultaneously. Simulation and experimental results demonstrate that the proposed method requires only 36.4% of the iterations of the SPGD algorithm to deal with sudden disturbances. Moreover, the effective range of the ARW algorithm is 530.50µrad in the specific coupling platform, which is 20% higher than the effective range of SPGD.

A Turn-On Fluorescence Sensor Based on Nitrogen-Doped Carbon Dots and Cu2+ for Sensitively and Selectively Sensing Glyphosate.

Glyphosate has excellent herbicidal activity, and its extensive use may induce residue in the environment and enter into humans living through the food chain, causing negative impact. Here, water-soluble 1.55 nm size nitrogen-doped carbon quantum dots (NCDs) with strong blue fluorescence were synthesized using sodium citrate and adenine. The maximum excitation and emission wavelengths of NCDs were 380 nm and 440 nm, respectively. The above synthesized NCDs were first used for the construction of a fluorescence sensor for glyphosate detection. It was found that Cu2+ could quench the fluorescence of NCDs effectively through the photoinduced electron transfer (PET) process, which was confirmed using fluorescence lifetime measurements. Additionally, the fluorescence was restored with the addition of glyphosate. Hence, a sensitive turn-on fluorescence sensor based on NCDs/Cu2+ for glyphosate analysis was developed. The LODs of glyphosate for water and rice samples were recorded as 0.021 µg/mL and 0.049 µg/mL, respectively. The sensor was applied successfully for ultrasensitive and selective detection of glyphosate in environmental water and rice samples with satisfied recoveries from 82.1% to 113.0% using a simple sample pretreatment technique. The proposed strategy can provide a significant potential for monitoring glyphosate residue in water and agricultural product samples.