Reduction of Oxidative Stress and Excitotoxicity by Mesenchymal Stem Cell Biomimetic Co-Delivery System for Cerebral Ischemia-Reperfusion Injury Treatment.

A cerebral ischemia-reperfusion injury is ensued by an intricate interplay between various pathological processes including excitotoxicity, oxidative stress, inflammation, and apoptosis. For a long time, drug intervention policies targeting a single signaling pathway have failed to achieve the anticipated clinical efficacy in the intricate and dynamic inflammatory environment of the brain. Moreover, inadequate targeted drug delivery remains a significant challenge in cerebral ischemia-reperfusion injury therapy. In this study, a multifunctional nanoplatform (designated as PB-006@MSC) is developed using ZL006-loaded Prussian blue nanoparticles (PBNPs) camouflaged by a mesenchymal stem cell (MSC) membrane (MSCm). ZL006 is a neuroprotectant. It can be loaded efficiently into the free radical scavenger PBNP through mesoporous adsorption. This can simultaneously modulate multiple targets and pathways. MSCm biomimetics can reduce the nanoparticle immunogenicity, efficiently enhance their homing capability to the cerebral ischemic penumbra, and realize active-targeting therapy for ischemic stroke. In animal experiments, PB-006@MSC integrated reactive oxygen species (ROS) scavenging and neuroprotection. Thereby, it selectively targeted the cerebral ischemic penumbra (about fourfold higher accumulation at 24 h than in the non-targeted group), demonstrated a remarkable therapeutic efficacy in reducing the volume of cerebral infarction (from 37.1% to 2.3%), protected the neurogenic functions, and ameliorated the mortality.

The mediating role of perceived social support on the relationship between lack of occupational coping self-efficacy and implicit absenteeism among intensive care unit nurses: a multicenter cross­sectional study.

BACKGROUND: Implicit absenteeism is very common among nurses. Poor perceived social support of intensive care unit nurses has a negative impact on their mental and physical health. There is evidence that lack of occupational coping self-efficacy can promote implicit absenteeism; however, the relationship between lack of occupational coping self-efficacy in perceived social support and implicit absenteeism of intensive care unit nurses is unclear. Therefore, this study aimed to evaluate the role of perceived social support between lack of occupational coping self-efficacy and implicit absenteeism of intensive care unit nurses, and to provide reliable evidence to the management of clinical nurses. METHODS: A cross-sectional study of 517 intensive care unit nurses in 10 tertiary hospitals in Sichuan province, China was conducted, of which 474 were valid questionnaires with a valid recovery rate of 91.6%. The survey tools included the Chinese version of Implicit Absenteeism Scale, the Chinese version of Perceived Social Support Scale, the Chinese version of Occupational Coping Self-Efficacy Scale and the Sociodemographic characteristics. Descriptive analysis and Pearson correlation analysis were performed using SPSS version 22.0, while the mediating effects were performed using AMOS version 24.0. RESULTS: The average of intensive care unit nurses had a total implicit absenteeism score of (16.87 ± 3.98), in this study, the median of intensive care unit nurses' implicit absenteeism score was 17, there were 210 intensive care unit nurses with low implicit absenteeism (44.3%) and 264 ICU nurses with high implicit absenteeism (55.7%). A total perceived social support score of (62.87 ± 11.61), and a total lack of occupational coping self-efficacy score of (22.78 ± 5.98). The results of Pearson correlation analysis showed that implicit absenteeism was negatively correlated with perceived social support (r = -0.260, P < 0.001) and positively correlated with lack of occupational coping self-efficacy (r = 0.414, P < 0.001). In addition, we found that perceived social support plays a mediating role in lack of occupational coping self-efficacy and implicit absenteeism [ß = 0.049, 95% CI of (0.002, 0.101)]. CONCLUSIONS: Intensive care unit nurses had a high level of implicit absenteeism with a moderate level of perceived social support and lack of occupational coping self-efficacy. Nursing managers should pay attention to the nurses those who were within low levels of social support and negative coping strategies, and take measures to reduce intensive care unit nurses' professional stress, minimize implicit absenteeism.

Effect of extreme high temperature on cognitive function at different time scales: A national difference-in-differences analysis.

BACKGROUND: Mounting evidence has demonstrated that high temperature was associated with adverse health outcomes, especially morbidity and mortality. Nonetheless, the impact of extreme high temperature on cognitive performance, which is the fundamental capacity for interpreting one's surroundings, decision-making, and acquiring new abilities, has not been thoroughly investigated. METHODS: We aimed to assess associations between extreme high temperature at different time scales and poor cognitive function. We used longitudinal survey data from the three waves of data from China Family Panel Study, providing an 8-year follow-up of 53,008 participants from China. We assessed temperature and extreme high temperature exposure for each participant based on the residential area and date of cognitive test. We defined the proportion of days/hours above 32 °C as the metric of the exposure to extreme high temperature. Then we used generalized additive model and difference-in-differences approach to explore the associations between extreme high temperature and cognitive function. RESULTS: Our results demonstrated that either acute exposure or long-term exposure to extreme high temperature was associated with cognitive decline. At hourly level, 0-1 hour acute exposure to extreme high temperature would induce -0.93 % (95 % CI: -1.46 %, -0.39 %) cognitive change. At annual level, 10 percentage point increase in the hours proportion exceeding 32 °C in the past two years induced -9.87 % (95 % CI: -13.99 %, -5.75 %) cognitive change. Furthermore, subgroup analyses indicated adaptation effect: for the same 10 percentage increase in hours proportion exceeding 32 °C, people in warmer areas had cognitive change of -6.41 % (-11.22 %, -1.61 %), compared with -15.30 % (-21.07 %, -9.53 %) for people in cool areas. CONCLUSION: Our results demonstrated that extreme high temperature was associated with reduced cognitive function at hourly, daily and annual levels, warning that people should take better measures to protect the cognitive function in the context of climate change.

Digital health literacy among undergraduate nursing students in China: associations with health lifestyles and psychological resilience.

BACKGROUND: Digital health literacy (DHL) is pivotal for individuals to access trustworthy health information and make informed decisions, closely intertwined with health behaviors and psychological resilience-these factors collectively shape an individual's approach to health management. Despite extensive research on digital health literacy in broader populations, the specific dynamics of digital health literacy in relation to health behaviors and psychological resilience among undergraduate nursing students in China remain understudied, highlighting a gap that this research endeavors to address. This study aims to assess the levels of digital health literacy among undergraduate nursing students in China, and to explore its association with health lifestyles and psychological resilience, which are considered influential factors. METHODS: Employing a descriptive cross-sectional research design, eligible Chinese nursing undergraduates were surveyed from June to October 2023. This study recruited a total of 418 undergraduate nursing students. After excluding 11 students on leave, 407 students participated in questionnaire completion and submission. The College Students' Digital Health Literacy Scale, Healthy Lifestyle Assessment Scale and The Psychological Resilience Scale were used in this study. RESULTS: The mean scores for digital health literacy, health lifestyles, and psychological resilience were 74.78 ± 8.44, 127.14 ± 11.22, and 79.21 ± 11.02, respectively. Pearson correlation analysis results indicated that the correlations between digital health literacy and both health lifestyles (r = 0.707, P < 0.01) and psychological resilience (r = 0.638, P < 0.01) were statistically significant and positive. The multiple linear regression analysis revealed that volunteer activity experience, academic performance, physical fitness, psychological traits, health lifestyle, and psychological resilience significantly predicted digital health literacy (F = 58.091, P < 0.001, R² = 0.678, adjusted R² = 0.666). Specifically, excellent academic performance (ß = 0.210, P < 0.001) and good physical fitness (ß = 0.188, P = 0.002) were the strongest predictors of higher digital health literacy. CONCLUSIONS: There is a correlation between the digital health literacy of nursing undergraduates and their health lifestyles and psychological resilience. Future research should consider interventions in digital health literacy for undergraduate nursing students in China from the perspectives of health lifestyles and psychological resilience.

Association between fear of falling and mortality in middle-aged and older adults: A systematic review and meta-analysis.

BACKGROUND: Fear of falling (FOF) has emerged as a significant public health issue, contributing to excess disability among middle-aged and older adults. The association between FOF and mortality remains unclear. METHODS: Prominent electronic databases (PubMed, Web of Science, the Cochrane Library, Embase, CINHAL, PsycINFO, Scopus, China National Knowledge Infrastructure, China Biology Medicine disc, and Wanfang Database) were searched from inception until October 21, 2023 (data updated on June 9, 2024), for cohort or longitudinal studies investigating the association between FOF and mortality. The heterogeneity between studies was quantitatively assessed using I2. A fixed-effect model calculated the pooled effect size. RESULTS: A total of seven cohort studies, including 27,714 participants, were analyzed in this systematic review and meta-analysis. The meta-analysis results demonstrated a positive association between FOF and mortality, with a significant increase in the risk of mortality for those with FOF (hazard ratio [HR]:1.29, 95 % confidence interval [CI]: 1.19-1.41, p < 0.05). Subgroup analysis indicated that age, male sex, clinical diagnosis of depression, number of chronic diseases, activity restriction due to FOF, and FOF levels were associated with mortality. CONCLUSIONS: FOF and mortality have a positive association, which needs to be confirmed by further prospective studies with large samples and long-term follow-up to provide evidence for clinicians to intervene in FOF to reduce mortality in middle-aged and older adults.

Cascaded Multi-Modal Mixing Transformers for Alzheimer's Disease Classification with Incomplete Data.

Accurate medical classification requires a large number of multi-modal data, and in many cases, different feature types. Previous studies have shown promising results when using multi-modal data, outperforming single-modality models when classifying diseases such as Alzheimer's Disease (AD). However, those models are usually not flexible enough to handle missing modalities. Currently, the most common workaround is discarding samples with missing modalities which leads to considerable data under-utilisation. Adding to the fact that labelled medical images are already scarce, the performance of data-driven methods like deep learning can be severely hampered. Therefore, a multi-modal method that can handle missing data in various clinical settings is highly desirable. In this paper, we present Multi-Modal Mixing Transformer (3MT), a disease classification transformer that not only leverages multi-modal data but also handles missing data scenarios. In this work, we test 3MT for AD and Cognitively normal (CN) classification and mild cognitive impairment (MCI) conversion prediction to progressive MCI (pMCI) or stable MCI (sMCI) using clinical and neuroimaging data. The model uses a novel Cascaded Modality Transformers architecture with cross-attention to incorporate multi-modal information for more informed predictions. We propose a novel modality dropout mechanism to ensure an unprecedented level of modality independence and robustness to handle missing data scenarios. The result is a versatile network that enables the mixing of arbitrary numbers of modalities with different feature types and also ensures full data utilization in missing data scenarios. The model is trained and evaluated on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with the state-of-the-art performance and further evaluated with The Australian Imaging Biomarker & Lifestyle Flagship Study of Ageing (AIBL) dataset with missing data.

Microwave-Assisted Rapid Substitution of Ti for Zr to Produce Bimetallic (Zr/Ti)UiO-66-NH2 with Congenetic "Shell-Core" Structure for Enhancing Photocatalytic Removal of Nitric Oxide.

Efficient nitric oxide (NO) removal without nitrogen dioxide (NO2 ) emission is desired for the control of air pollution. Herein, a series of (Zr/Ti)UiO-66-NH2 with congenetic shell-core structure, denoted as Ti-UION, are rapidly synthesized by microwave-assisted post-synthetic modification for NO removal. The optimal Ti-UION (i.e., 2.5Ti-UION) exhibits the highest activity of 80.74% without NO2 emission with moisture, which is 21.65% greater than that of the UiO-66-NH2 . The NO removal efficiency of 2.5Ti-UION further increases to 95.92% without photocatalyst deactivation under an anhydrous condition. This is because selectively produced NO2 in photocatalysis is completely adsorbed into micropores, refreshing active sites for subsequent reaction. In addition, the enhanced photocatalytic activity after Ti substitution is due to the presence of Ti electron acceptor, the potential difference between the shell and core of Ti-UION crystal, and the high conductivity of TiO units. Additionally, the improved adsorption of gas molecules not only favors NO oxidation, but also avoids the emission of NO2 . This work provides a feasible strategy for rapid metal substitution in metal-organic frameworks and insights into enhanced NO photodegradation.

Ticagrelor is related to nuisance bleeding after flow diversion of unruptured intracranial aneurysms.

Nuisance bleeding (NB) without urgent medical attention is rarely characterized despite its frequent occurrence in patients with cerebral aneurysms undergoing flow diversion (FD) who are maintained on dual antiplatelet therapy (DAPT). This study explored the risk factors for NB. Patients with unruptured cerebral aneurysms who underwent intervention using FD (July 2018 to May 2022) and had follow-up data were enrolled. Patient demographics, clinical characteristics, aneurysm features and follow-up data were analysed. Bleeding complications were classified as NB, internal bleeding and alarming bleeding. NB was characterized by easy bruising, bleeding from small cuts and nonfatal petechiae and ecchymosis. Univariate and multivariate logistic regression analyses were performed to determine risk factors for NB. This study assessed 121 patients. Of these, 52 (43.0%) patients had NB. Compared with the non-bleeding group, the NB group had more females (82.7% vs. 56.5%; p = 0.003), lower smoking rate (7.7% vs. 23.2%; p = 0.027) and smaller aneurysms (6.65 mm [4.60-9.60 mm] vs. 8.82 mm [5.65-15.65 mm]; p = 0.007) and had more patients maintained on ticagrelor-containing DAPT regimen (90.4% vs. 66.7%; p = 0.002). Multivariate logistic regression revealed that ticagrelor-containing DAPT regimen (odds ratio, 3.91; 95% confidence interval, 1.29-11.87; p = 0.016) was associated with NB. These results suggest that NB is a common bleeding complaint in patients on DAPT. In patients undergoing FD, DAPT with ticagrelor was the only independent risk factor for NB.

New Cryoprotectant Loading Method for Cell Droplet Vitrification with Continuous Evaporation.

Droplet-based vitrification is considered to be a promising cryopreservation method, which achieves high cell viability through high cooling rates and low concentrations of cryoprotective agents (CPAs). However, the droplet vitrification cryopreservation process needs in-depth research, such as the balance of the CPA concentration and the cooling rate, the CPA loading process, and the droplet encapsulation method. Here, we developed a chip with a high cooling rate for vitrification droplet encapsulation and provided a new method for continuous loading of low-concentration CPA droplets by evaporation. The results showed that the CPA droplet volume decreased exponentially with the evaporation time, and the larger the initial droplet size, the longer the evaporation time to achieve the critical vitrification concentration. There was no significant difference in the viability of MSCs, NHEK, and A549 cells between the evaporation loading vitrification method and the traditional slow freezing method, but the former was easier to operate and can balance the cooling rate and concentration by controlling the evaporation time. Moreover, a theoretical model was proposed to predict the CPA concentration inside the microdroplets dependent on the evaporation time. The current work provides a potential method to load low-concentration CPAs for cell vitrification preservation, which is more beneficial for cell therapy and other regenerative medicine applications.

An Integrated First Principal and Deep Learning Approach for Modeling Nitrous Oxide Emissions from Wastewater Treatment Plants.

Mathematical modeling plays a critical role toward the mitigation of nitrous oxide (N2O) emissions from wastewater treatment plants (WWTPs). In this work, we proposed a novel hybrid modeling approach by integrating the first principal model with deep learning techniques to predict N2O emissions. The hybrid model was successfully implemented and validated with the N2O emission data from a full-scale WWTP. This hybrid model is demonstrated to have higher accuracy for N2O emission modeling in the WWTP than the mechanistic model or pure deep learning model. Equally important, the hybrid model is more applicable than the pure deep learning model due to the lower requirement of data and the pure mechanistic model due to the less calibration requirement. This superior performance was due to the hybrid nature of the proposed model. It integrated the essential wastewater treatment knowledge as the first principal component and the less understood N2O production processes by the data-driven deep learning approach. The developed hybrid model was also successfully implemented under different circumstances for the prediction of N2O flux, which showed the generalizability of the model. The hybrid model also showed great potential to be applied for the N2O mitigation work. Nevertheless, the capability of the hybrid model in evaluating N2O mitigation strategies still requires validation with experiments. Going beyond N2O modeling in WWTP, the novel hybridization modeling concept can potentially be applied to other environmental systems.

Peritoneal dialysis for acute kidney injury.

BACKGROUND: Peritoneal dialysis (PD) has been suggested as an effective and safe dialysis modality in patients with acute kidney injury (AKI). However, whether PD is superior to extracorporeal therapy (e.g. haemodialysis) in terms of improving survival, recovery of kidney function, metabolic and clinical outcomes is still inconclusive. OBJECTIVES: The aim of this review was to evaluate the benefits and harms of PD for patients with AKI compared with extracorporeal therapy or different PD modalities. SEARCH METHODS: We searched the Cochrane Kidney and Transplant Register of Studies to 29 May 2017 through contact with the Information Specialist using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Register (ICTRP) Search Portal, and ClinicalTrials.gov. We also searched the China Biological Medicine Database. SELECTION CRITERIA: We included patients with AKI who were randomised to receive PD, extracorporeal therapy, or different PD modalities regardless of their age, sex, primary disease and clinical course. DATA COLLECTION AND ANALYSIS: Screening, selection, data extraction and quality assessments for each retrieved article were carried out by two authors using standardised forms. Authors contacted when published data were incomplete. Statistical analyses were performed using the random effects model and results expressed as risk ratio (RR) with 95% confidence intervals (CI). Heterogeneity among studies was explored using the Cochran Q statistic and the I2 test. Outcomes of interest included all-cause mortality, recovery of kidney function, weekly delivered Kt/V, correction of acidosis, fluid removal, duration of dialysis, and infectious complications. Confidence in the evidence was assessing using GRADE. MAIN RESULTS: Six studies (484 participants) met our inclusion criteria. Five studies compared high volume PD with daily haemodialysis, extended daily haemodialysis, or continuous renal replacement therapy. One study focused on the intensity of PD. The overall risk of bias was low to unclear. Compared to extracorporeal therapy, PD probably made little or no difference to all-cause mortality (4 studies, 383 participants: RR 1.12, 95% CI 0.81 to 1.55; I2 = 69%; moderate certainty evidence), or kidney function recovery (3 studies, 333 participants: RR 0.95, 95% CI 0.68 to 1.35; I2 = 0%; moderate certainty evidence). PD probably slightly reduces the amount of fluid removal compared to extracorporeal therapy (3 studies, 313 participants: MD -0.59 L/d, 95% CI -1.19 to 0.01; I2 = 89%; low certainty evidence), and probably made little or no difference to infectious complications (2 studies, 263 participants: RR 1.03, 95% CI 0.60 to 1.78; I2 = 0%; low certainty evidence). It is uncertain whether PD compared to extracorporeal therapy has any effects on weekly delivered Kt/V (2 studies, 263 participants: MD -2.47, 95% CI -5.17 to 0.22; I2 = 99%; very low certainty evidence), correction of acidosis (2 studies, 89 participants: RR 1.32, 95% CI 0.13 to 13.60; I2 = 96%; very low certainty evidence), or duration of dialysis (2 studies, 170 participants: MD -1.01 hours, 95% CI -91.49 to 89.47; I2 = 98%; very low certainty evidence). Heterogeneity was high and this may be due to the different extracorporeal therapies used.One study (61 participants) reported little or no difference to all-cause mortality, kidney function recovery, or infection between low and high and intensity PD. Weekly delivered Kt/V and fluid removal was lower with low compared to high intensity PD. AUTHORS' CONCLUSIONS: Based on moderate (mortality, recovery of kidney function), low (infectious complications), or very low certainty evidence (correction of acidosis) there is probably little or no difference between PD and extracorporeal therapy for treating AKI. Fluid removal (low certainty) and weekly delivered Kt/V (very low certainty) may be higher with extracorporeal therapy.

Valid Probabilistic Predictions for Ginseng with Venn Machines Using Electronic Nose.

In the application of electronic noses (E-noses), probabilistic prediction is a good way to estimate how confident we are about our prediction. In this work, a homemade E-nose system embedded with 16 metal-oxide semi-conductive gas sensors was used to discriminate nine kinds of ginsengs of different species or production places. A flexible machine learning framework, Venn machine (VM) was introduced to make probabilistic predictions for each prediction. Three Venn predictors were developed based on three classical probabilistic prediction methods (Platt's method, Softmax regression and Naive Bayes). Three Venn predictors and three classical probabilistic prediction methods were compared in aspect of classification rate and especially the validity of estimated probability. A best classification rate of 88.57% was achieved with Platt's method in offline mode, and the classification rate of VM-SVM (Venn machine based on Support Vector Machine) was 86.35%, just 2.22% lower. The validity of Venn predictors performed better than that of corresponding classical probabilistic prediction methods. The validity of VM-SVM was superior to the other methods. The results demonstrated that Venn machine is a flexible tool to make precise and valid probabilistic prediction in the application of E-nose, and VM-SVM achieved the best performance for the probabilistic prediction of ginseng samples.

Fully printable mesoscopic perovskite solar cells with organic silane self-assembled monolayer.

By the introduction of an organic silane self-assembled monolayer, an interface-engineering approach is demonstrated for hole-conductor-free, fully printable mesoscopic perovskite solar cells based on a carbon counter electrode. The self-assembled silane monolayer is incorporated between the TiO2 and CH3NH3PbI3, resulting in optimized interface band alignments and enhanced charge lifetime. The average power conversion efficiency is improved from 9.6% to 11.7%, with a highest efficiency of 12.7%, for this low-cost perovskite solar cell.

[Preliminary study on the pathogenic mechanism of myoglobin-induced endoplasmic reticulum stress and apoptosis in crush syndrome].

OBJECTIVE: To explore the pathogenic mechanism of myoglobin-induced endoplasmic reticulum stress (ERS) and apoptosis in tubular epithelial cells in acute kidney injury (AKI) mouse model of crush syndrome. METHODS: Eighteen C56BL/6 mice were randomly divided into control group, modeling 8 h group and modeling 24 h group. The AKI model of crush syndrome was established by intramuscular injection of 50% glycerol saline solution into thigh (8 microL/g), while equivalent volume of physiological saline was injected in control group. AKI was diagnosed when serum creatinine (sCr) level increased to double value of control group. The mice in the experimental groups were sacrificed at the time points of 8 h and 24 h after injection respectively. Serum Cr was detected and renal tissues was observed under electron microscopy. Apoptosis was detected by TUNEL technique. Marker proteins and mRNA of apoptosis and ERS were detected by immunohistochemistry and real-time PCR. Human kidney proximal tubular cell (HK-2) cells cultured in vitro were randomly divided into control, intervention 6 h and intervention 12 h groups. Control group were incubated in standard cell culture (DMEM/F12) and the two intervention groups were incubated in special DMEM/F12 in which ferrohemoglobin was added. After 6 h and 12 h incubation, the cells were collected and apoptosis was detected by flow cytometry. RESULTS: AKI model of crush syndrome was successfully established, which was proved with sCr doubling at the 8 h after the intramuscular injection of glycerol saline. Swelling of endoplasmic reticulum and mitochondria in proximal tubular epithelial cells was more obvious in the two model groups than that in control group. TUNEL staining showed the percentage of positive cells in AKI groups was higher than that in control group (P<0.05). Immunohistochemistry and real-time PCR showed the expressions of caspase3, caspase12 and CHOP in AKI groups were higher than those in control group (P<0.05). Flow cytometry showed cell apoptosis ratio was higher in model groups than control groiap (P<0.05). CONCLUSION: Myoglobin induced ERS and apoptosis may be involved in the pathogenesis of AKI in crush syndrome.

Fully printable transparent monolithic solid-state dye-sensitized solar cell with mesoscopic indium tin oxide counter electrode.

We present a new transparent monolithic mesoscopic solid-state dye-sensitized solar cell based on trilamellar films of mesoscopic TiO2 nanocrystalline photoanode, a ZrO2 insulating layer and an indium tin oxide counter electrode (ITO-CE), which were screen-printed layer by layer on a single substrate. When the thickness of the ITO-CE was optimized to 2.1 µm, this very simple and fully printable solid-state DSSC with D102 dye and spiro-OMeTAD hole transport materials presents efficiencies of 1.73% when irradiated from the front side and 1.06% when irradiated from the rear side under a standard simulated sunlight condition (AM 1.5 Global, 100 mW cm(-2)). Higher parameters could be expected with a better transparent mesoscopic counter electrode and hole conductor for the printable monolithic mesoscopic solid-state DSSC.

Risk factors and prediction model for osteonecrosis of the femoral head in female systemic lupus erythematosus.

Background: Osteonecrosis of the femoral head (ONFH) is a severe complication of systemic lupus erythematosus (SLE) and occurs more frequently in SLE patients than in other autoimmune diseases, which can influence patients' life quality. The objective of this research was to analyze risk factors for the occurrence of ONFH in female SLE patients, construct and validate a risk nomogram model. Methods: Clinical records of SLE patients who fulfilled the 1997 American College of Rheumatology SLE classification criteria were retrospectively analyzed. The Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis were used to summarize the independent risk factors of ONFH in female SLE patients, which were used to develop a nomogram. The predictive performance of the nomogram was assessed using the receiver characteristic (ROC) curve, calibration curves and decision curve analysis (DCA). Results: 793 female SLE patients were ultimately included in this study, of which 87 patients (10.9%) developed ONFH. Ten independent risk factors including disease duration, respiratory involvement, menstrual abnormalities, Sjögren's syndrome, osteoporosis, anti-RNP, mycophenolate mofetil, cyclophosphamide, biologics, and the largest daily glucocorticoid (GC) were identified to construct the nomogram. The area under the ROC curve of the nomogram model was 0.826 (95% CI: 0.780-0.872) and its calibration for forecasting the occurrence of ONFH was good (χ2 = 5.589, P = 0.693). DCA showed that the use of nomogram prediction model had certain application in clinical practice when the threshold was 0.05 to 0.95. In subgroup analysis, we found that the risk of ONFH was significantly increased in age at SLE onset of ≤ 50 years old, largest daily GC dose of ≥50 mg and the therapy of GC combined with immunosuppressant patients with menstrual abnormalities. Conclusion: Menstrual abnormalities were the first time reported for the risk factors of ONFH in female SLE patients, which remind that clinicians should pay more attention on female SLE patients with menstrual abnormalities and take early interventions to prevent or slow the progression of ONFH. Besides, the nomogram prediction model could provide an insightful and applicable tool for physicians to predict the risk of ONFH.

Abnormal prefrontal cortical activation during the GO/NOGO and verbal fluency tasks in adult patients with comorbid generalized anxiety disorder and attention-deficit/hyperactivity disorder: An fNIRS study.

Generalized anxiety disorder (GAD) and adult attention-deficit/hyperactivity disorder (ADHD) are commonly reported comorbidities. Adult GAD patients with comorbid ADHD are often underdiagnosed and undertreated. To explore the clinical value of functional near-infrared spectroscopy (fNIRS) data for assisting in the accurate diagnosis of ADHD in individuals with GAD, haemoglobin (HbO) concentration changes in the prefrontal cortex (PFC) were detected via fNIRS in 49 patients with both GAD and ADHD, 46 patients with GAD, and 34 healthy controls (HCs) during a verbal fluency task (VFT) and a GO/NOGO task. The correlations between PFC fNIRS data and the severity of inattention and hyperactivity symptoms assessed using the adult ADHD Self-Report Scale (ASRS) were analyzed. Our results showed that, during the GO/NOGO task, channels in the left dorsolateral PFC (channels 28 and 29) were hyperactivated, while channels in the medial PFC (channels 36, 37, and 47) were hypoactivated in participants with ADHD and GAD compared with those with GAD alone. During the VFT, compared with the HC group, both the ADHD + GAD group and the GAD group exhibited significantly decreased HbO activation in the medial PFC (channels 37, 38, and 48) and in the left ventrolateral PFC (channel 39); moreover, no difference was found between the ADHD + GAD group and the GAD group. Activation in the left dorsolateral PFC (channels 28 and 29) during the GO/NOGO task showed a significant positive correlation with ASRS-inattention scores. Our results indicated that fNIRS data collected during the GO/NOGO task may help to distinguish patients with comorbid GAD and ADHD from those with GAD alone.

Mediating effect of social support and resilience between loneliness and depression in older adults: A systematic review and meta-analytic structural equation modeling.

BACKGROUND: Loneliness is a powerful stressor for depression in older adults, and resilience and social support may mediate this relationship, while the evidence is limited. Hence, our study aims to explore the mediating role of social support and resilience between loneliness and depression and to test possible moderators. METHODS: We searched 12 databases without language and publish time restrictions and obtained the correlation coefficients. This review constructed two-stage meta-analytical structural equality modeling (MASEA) to test the mediating effect of social support and resilience. Additionally, use one-stage MASEA to test the moderator effect of women proportion, published year, and country of study. RESULTS: This study included 53 studies and 40, 929 older adults. Loneliness directly affected depression (ß = 0.28, 95 % CI: 0.20, 0.36). Social support (ß = 0.06, 95 % CI: 0.02, 0.09) and resilience (ß = 0.15, 95 % CI: 0.12, 0.18) mediated the relationship. The proportion of women in the sample was moderator (χ2(5) = 11.10, p = 0.05). When the proportion exceeded 60 %, the path coefficient of loneliness and social support (ß = -0.45, SE = 0.055) was larger than that of the subgroup below 60 % (ß = -0.32, SE = 0.041). LIMITATIONS: It was indefinite whether the evidence would be supported in longitudinal designs. Influenced by the original research data, it is impossible to calculate the model parameters of gender discrepancy. CONCLUSIONS: Health aging policy-makers adopting social support and resilience intervention will help strengthen the coping skills of older adults confronting loneliness and reduce the risk of depression.

A universal solvent-replacement strategy to convert alginate hydrogels into mechanically strong and transparent alginate eutectogels for sensitive strain sensors.

Eutectogels based on natural polymers have attracted significant attention as an alternative to easily dehydrated hydrogels and expensive ionogels in the development of flexible strain sensors. The feasibility of employing eutectogels derived from pure natural polymers could be greatly enhanced if their mechanical properties satisfy the requirements of applications. Herein, alginate eutectogels (AEs) with high mechanical properties (tensile strain 217 % and strength 2.26 MPa at fracture), and excellent transparency (over 90 %) are acquired via CaCl2 inducing ionic crosslinking and subsequent deep eutectic solvents (DESs, composed of glycerol and choline chloride) initiating physical crosslinking with a universal solvent- replacement strategy. Among them, sodium alginate, a natural polysaccharide polymer, is selected as representative supporting scaffolds and forms water-insoluble alginate hydrogels (AHs) in CaCl2 coagulation bath. The exchange of DESs with water of AHs not only restrengthens the polymer network by physical crosslinking, but also endows the obtained AEs with long-term solvent retention and high temperature resistance. In addition, the AEs not only have high reliability but also exhibit better linear sensitivity in a wide strain range (0-200 %). In particular, the AEs display multiple sensitivity to stretching, bending, and human motions, demonstrating feasibility as sensitive strain sensors.

DOI- and TOF-capable PET array detector using double-ended light readout and stripline-based row and column electronic readout.

We investigate a highly multiplexing readout for depth-of-interaction (DOI) and time-of-flight PET detector consisting of an N×N crystals whose light outputs at the front and back ends are detected by using silicon photomultipliers (SiPM). The front N×N SiPM array is read by using a stripline (SL) configured to support discrimination of the row position of the signal-producing crystal. The back N×N SiPM array is similarly read by an SL for column discrimination. Hence, the detector has only four outputs. We built 4×4 and 8×8 detector modules (DM) by using 3.0×3.0×20 mm3 lutetium-yttrium oxyorthosilicates. The outputs were sampled and processed offline. For both DMs, crystal discrimination was successful. For the 4×4 DM, we obtained an average energy resolution (ER) of 14.1%, an average DOI resolution of 2.5 mm, a non DOI-corrected coincidence resolving time (CRT), measured in coincidence with a single-pixel reference detector, of about 495 ps. For the 8×8 DM, the average ER, average DOI resolution and average CRT were 16.4%, 2.9 mm, and 641 ps, respectively. We identified the intercrystal scattering as a probable cause for the CRT deterioration when the DM was increased from 4×4 to 8×8.