A dual-functional module cellular electrochemical sensing platform for simultaneous detection guanine and xanthine.

The separation of the superimposed electrochemical signals of intracellular guanine (G) and xanthine (X) is difficult, which is great obstacle to the application of cell electrochemistry. In this paper, independent functional modules, G-functional module (G-FM) and X-functional module (X-FM), were constructed by molecular imprinting technology for sensitive detection of G and X without mutual interference, then integrated in dual-functional module cellular electrochemical sensing platform (DMCEP) as signal sensing units. DMCEP transmitted signals of G and X in cells synchronously to two windows by two signal sensing channels, and achieved the separation of superimposed signals of G and X in cells. DMCEP exhibited satisfactory reproducibility with relative standard deviation (RSD) of 3.10 and 2.22 %, repeatability with RSD of 3.72 and 3.05 % for G and X detection, and detection limit 0.05 µΜ for G and 0.06 µΜ for X. Good linear relationships between cell concentrations and the signals of G and X on DMCEP were shown in range of 0.75-85 × 106 and 3-85 × 106 cells/mL, respectively. The growth of MCF-7 cells was tracked by DMCEP, and showed consistent trend with the cell counting method, while the change of cell viability from lag to logarithmic phase captured by DMCEP was earlier than that of cell counting method. This strategy provided the foundation for the establishment of the cell viability electrochemical detection method, and new insights into the simultaneous recording of other analyses with superimposed peak positions and the simultaneous tracking of multiple biomarkers.

Potassium reduction with sodium zirconium cyclosilicate in patients with heart failure.

AIMS: Several patients with heart failure and reduced ejection fraction (HFrEF) do not receive renin-angiotensin-aldosterone system (RAAS) inhibitors at the recommended dose or at all, frequently due to actual or feared hyperkalaemia. Sodium zirconium cyclosilicate (SZC) is an orally administered non-absorbed intestinal potassium binder proven to lower serum potassium concentrations. METHODS AND RESULTS: PRIORITIZE-HF was an international, multicentre, parallel-group, randomized, double-blind, placebo-controlled study to evaluate the benefits and risks of using SZC to intensify RAAS inhibitor therapy. Patients with symptomatic HFrEF were eligible and randomly assigned to receive SZC 5 g or placebo once daily for 12 weeks. Doses of study medication and RAAS inhibitors were titrated during the treatment period. The primary endpoint was the proportion of patients at 12 weeks in the following categories: (i) any RAAS inhibitor at less than target dose, and no MRA; (ii) any RAAS inhibitor at target dose and no MRA; (ii) MRA at less than target dose; and (iv) MRA at target dose. Due to challenges in participant management related to the COVID-19 pandemic, the study was prematurely terminated with 182 randomized patients. There was no statistically significant difference in the distribution of patients by RAAS inhibitor treatment categories at 3 months (P = 0.43). The proportion of patients at target MRA dose was numerically higher in the SZC group (56.4%) compared with the placebo group (47.0%). Overall, SZC was well tolerated. CONCLUSIONS: PRIORITIZE-HF was terminated prematurely due to COVID-19 and did not demonstrate a statistically significant increase in the intensity of RAAS inhibitor therapies with the potassium-reducing agent SZC compared with placebo.

Predicting depression and anxiety of Chinese population during COVID-19 in psychological evaluation data by XGBoost.

BACKGROUND: Due to the onset of sudden stress, COVID-19 has greatly impacted the incidence of depression and anxiety. However, challenges still exist in identifying high-risk groups for depression and anxiety during COVID-19. Studies have identified how resilience and social support can be employed as effective predictors of depression and anxiety. This study aims to select the best combination of variables from measures of resilience, social support, and alexithymia for predicting depression and anxiety. METHODS: The eXtreme Gradient Boosting (XGBoost1) model was applied to a dataset including data on 29,841 participants that was collected during the COVID-19 pandemic. Discriminant analyses on groups of participants with depression (DE2), anxiety (AN3), comorbid depression and anxiety (DA4), and healthy controls (HC5), were performed. All variables were selected according to their importance for classification. Further, analyses were performed with selected features to determine the best variable combination. RESULTS: The mean accuracies achieved by three classification tasks, DE vs HC, AN vs HC, and DA vs HC, were 0.78, 0.77, and 0.89. Further, the combination of 19 selected features almost exhibited the same performance as all 56 variables (accuracies = 0.75, 0.75, and 0.86). CONCLUSIONS: Resilience, social support, and some demographic data can accurately distinguish DE, AN, and DA from HC. The results can be used to inform screening practices for depression and anxiety. Additionally, the model performance of a limited scale including only 19 features indicates that using a simplified scale is feasible.

Prevalence and prognostic value of preexisting sarcopenia in patients with mechanical ventilation: a systematic review and meta-analysis.

BACKGROUND: Sarcopenia is defined as age-related loss of muscle mass, strength, and/or function in the context of aging. Mechanical ventilation (MV) is one of the most frequently used critical care technologies in critically ill patients. The prevalence of preexisting sarcopenia and the clinical impact of its prognostic value on patients with MV are unclear. This review sought to identify the prevalence and prognostic value of preexisting sarcopenia on MV patient health outcomes. METHODS: Relevant studies were identified by searching MEDLINE, Embase, and the Cochrane library and were searched for all articles published as of December 2021. The prevalence of sarcopenia was determined using the authors' definitions from the original studies. Comparisons were made between patients who did and did not have sarcopenia for prognostic outcomes, including mortality, the number of days of MV, the length of intensive care unit stay, and the length of hospital stay. Odds ratios (ORs) and weighted mean differences with 95% confidence intervals (CIs) were used for pooled analyses of the relationships between sarcopenia and prognostic outcomes. RESULTS: The initial search identified 1333 studies, 17 of which met the eligibility criteria for the quantitative analysis, including 3582 patients. The pooled prevalence was 43.0% (95% CI 34.0-51.0%; I2 = 96.7%). The pooled analyses showed that sarcopenia was related to increased mortality (OR 2.13; 95% CI 1.70, 2.67; I2 = 45.0%), longer duration of MV (MD = 1.22; 95% CI 0.39, 2.05; I2 = 97.0%), longer days of ICU stay (MD = 1.31; 95% CI 0.43, 2.19; I2 = 97.0%), and hospital stay (MD 2.73; 95% CI 0.58, 4.88; I2 = 98.0%) in patients with MV. CONCLUSION: The prevalence of sarcopenia is relatively high in patients with MV, and it will have a negative impact on the prognosis of patients. However, further, large-scale, high-quality prospective cohort studies are required.

Facile preparation of antibacterial MOF‐fabric systems for functional protective wearables

Metal‐organic frameworks (MOFs) have shown numerous potentials as promising materials to address real‐world problems. However, their practical utilization in commercial products was largely limited by the lack of downstream processing methodologies to transform MOF powders into functional products. In this study, a commercially viable solution for the general synthesis of MOF‐fabric composites was introduced. On account of coordination bonding between poly(acrylic acid) and MOF substrates, MOF powders securely adhered onto the surface of fabric materials via a drip cast method to give MOF‐fabric composites easily. This strategy can be applied to different MOF types, as well as a wide variety of fabric materials. The prepared materials showed excellent bacterial killing efficacy attributed to the embedded HKUST‐1 MOF. In light of the recent coronavirus disease 2019 pandemic, this methodology could enable the large‐scale fabrication of essential MOF‐based personal protective wearables (e.g., clothing and masks) for use by healthcare professionals.

Associations Among the Big Five Personality Traits, Maladaptive Cognitions, and Internet Addiction Across Three Time Measurements in 3 Months During the COVID-19 Pandemic.

The present study examined the longitudinal association among the Big Five personality traits, maladaptive cognitions, and Internet addiction during the COVID-19 pandemic. A total of 481 Chinese university students (247 men; mean age = 20.31 years) were surveyed three times (interval of 1 month) by using the Chinese version of the Big Five Personality Traits Scale, Maladaptive Cognitions Scale, and Internet Addiction Scale. The results of a cross-lagged panel analysis highlighted that (i) extraversion, agreeableness, conscientiousness, and openness were negatively associated with maladaptive cognitions and Internet addiction, whereas neuroticism was found to be positively associated with maladaptive cognitions and Internet addiction across time; (ii) associations among the Big Five personality traits, maladaptive cognitions, and Internet addiction were dynamic and bidirectional; and (iii) maladaptive cognitions played mediating roles in extraversion, agreeableness, conscientiousness, openness, and Internet addiction across time. The Big Five personality traits, maladaptive cognitions, and Internet addiction predicted each other across time, and maladaptive cognitions were likely to be the key mediating factor in the associations between the Big Five personality traits and Internet addiction, which supported and expanded the Davis' cognitive-behavioral model.

Self-help cognitive behavioral therapy application for COVID-19-related mental health problems: A longitudinal trial.

BACKGROUND AND AIM: Recently, the availability and usefulness of mobile self-help mental health applications have increased, but few applications deal with COVID-19-related psychological problems. This study explored the intervention efficacy of a mobile application on addressing psychological problems related to COVID-19. METHODS: A longitudinal control trial involving 129 Chinese participants with depression symptoms was conducted through the mobile application "Care for Your Mental Health and Sleep during COVID-19" (CMSC) based on WeChat. Participants were divided into two groups: mobile internet cognitive behavioral therapy (MiCBT) and wait-list. The primary outcome was improvement in depression symptoms. Secondary outcomes included improvement in anxiety and insomnia. The MiCBT group received three self-help CBT intervention sessions in one week via CMSC. RESULTS: The MiCBT group showed significant improvement in depression and insomnia (allP < 0.05) compared with the wait-list group. Although both groups showed significant improvement in anxiety at the intervention's end, compared with the wait-list group, the MiCBT group had no significant advantage. Correlation analysis showed that improvement in depression and anxiety had a significant positive association with education level. Changes in insomnia were significantly negatively correlated with anxiety of COVID-19 at the baseline. CMSC was considered helpful (n=68, 81.9 %) and enjoyable (n=54, 65.9 %) in relieving depression and insomnia during the COVID-19 outbreak. CONCLUSIONS: CMSC is verified to be effective and convenient for improving COVID-19-related depression and insomnia symptoms. A large study with sufficient evidence is required to determine its continuous effect on reducing mental health problems during the pandemic.