Realizing the Potential of Social Determinants Data: A Scoping Review of Approaches for Screening, Linkage, Extraction, Analysis and Interventions.

Background: Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality. Methods: We searched PubMed using keywords "SDOH" and "EHR", underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions. Results: We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes. Discussion: Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals.

An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.

Medication clusters at hospital discharge and risk of adverse drug events at 30 days postdischarge: A population-based cohort study of older adults.

AIMS: Certain combinations of medications can be harmful and may lead to serious adverse drug events (ADEs). Identifying potentially problematic medication clusters could help guide prescribing and/or deprescribing decisions in hospital. The aim of this study is to characterize medication prescribing patterns at hospital discharge and determine which medication clusters were associated with an increased risk of ADEs in the 30-day posthospital discharge. METHODS: All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016 and February 2017 were included. Identification of medication clusters prescribed at hospital discharge was conducted using latent class analysis. Cluster identification and categorization were based on medications dispensed up to 30-day posthospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs postdischarge, while also evaluating other patient characteristics. RESULTS: In total, 188 354 patients were included in the study cohort. Median age (interquartile range) was 77 (71-84) years, and patients had a median (IQR) (interquartile range [IQR]) of 9 (6-13) medications dispensed prior to admission. Within the study population, 6 separate clusters of dispensing patterns were identified: cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%), and surgical (24%). Overall, 12 680 (7%) patients had an ADE in the 30 days following discharge. After considering other patient characteristics, those belonging to the respiratory cluster had the highest risk of ADEs (adjusted odds ratio: 1.12, 95% confidence interval: 1.08-1.17) compared with all the other clusters, while those in the complex care needs cluster had the lowest risk (adjusted odds ratio: 0.82, 95% confidence interval: 0.77-0.87). CONCLUSION: This study suggests that ADEs post hospital discharge can be linked with identifiable medication clusters. This information may help clinicians and researchers better understand patient populations that are more or less likely to benefit from peri-hospital discharge interventions aimed at reducing ADEs.

Macrophage lineage cells-derived migrasomes activate complement-dependent blood-brain barrier damage in cerebral amyloid angiopathy mouse model.

Accumulation of amyloid beta protein (Aß) in brain vessels damages blood brain barrier (BBB) integrity in cerebral amyloid angiopathy (CAA). Macrophage lineage cells scavenge Aß and produce disease-modifying mediators. Herein, we report that Aß40-induced macrophage-derived migrasomes are sticky to blood vessels in skin biopsy samples from CAA patients and brain tissue from CAA mouse models (Tg-SwDI/B and 5xFAD mice). We show that CD5L is packed in migrasomes and docked to blood vessels, and that enrichment of CD5L impairs the resistance to complement activation. Increased migrasome-producing capacity of macrophages and membrane attack complex (MAC) in blood are associated with disease severity in both patients and Tg-SwDI/B mice. Of note, complement inhibitory treatment protects against migrasomes-mediated blood-brain barrier injury in Tg-SwDI/B mice. We thus propose that macrophage-derived migrasomes and the consequent complement activation are potential biomarkers and therapeutic targets in CAA.

ADSeg: A flap-attention-based deep learning approach for aortic dissection segmentation.

Accurate and rapid segmentation of the lumen in an aortic dissection (AD) is an important prerequisite for risk evaluation and medical planning for patients with this serious condition. Although some recent studies have pioneered technical advances for the challenging AD segmentation task, they generally neglect the intimal flap structure that separates the true and false lumens. Identification and segmentation of the intimal flap may simplify AD segmentation, and the incorporation of long-distance z axis information interaction along the curved aorta may improve segmentation accuracy. This study proposes a flap attention module that focuses on key flap voxels and performs operations with long-distance attention. In addition, a pragmatic cascaded network structure with feature reuse and a two-step training strategy are presented to fully exploit network representation power. The proposed ADSeg method was evaluated on a multicenter dataset of 108 cases, with or without thrombus; ADSeg outperformed previous state-of-the-art methods by a significant margin and was robust against center variation.

Stability and bifurcation control for a fractional-order chemostat model with time delays and incommensurate orders.

In this paper, a delayed fractional Lotka-Volterra food chain chemostat model with incommensurate orders is proposed, and the effect on system stability and bifurcation of this model are discussed. First, for the system with no controller, the stability and Hopf bifurcation with respect to time delay are investigated. Taking the time delay as the bifurcation parameter, the relevant characteristic equations are analyzed, and the conditions for Hopf bifurcation are proposed. The results show that the controller can fundamentally affect the stability of the system, and that they both have an important impact on the generation of bifurcation at the same time. Finally, numerical simulation is carried out to support the theoretical data.

Protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against the omicron variant and severe disease: a systematic review and meta-regression.

BACKGROUND: The global surge in the omicron (B.1.1.529) variant has resulted in many individuals with hybrid immunity (immunity developed through a combination of SARS-CoV-2 infection and vaccination). We aimed to systematically review the magnitude and duration of the protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against infection and severe disease caused by the omicron variant. METHODS: For this systematic review and meta-regression, we searched for cohort, cross-sectional, and case-control studies in MEDLINE, Embase, Web of Science, ClinicalTrials.gov, the Cochrane Central Register of Controlled Trials, the WHO COVID-19 database, and Europe PubMed Central from Jan 1, 2020, to June 1, 2022, using keywords related to SARS-CoV-2, reinfection, protective effectiveness, previous infection, presence of antibodies, and hybrid immunity. The main outcomes were the protective effectiveness against reinfection and against hospital admission or severe disease of hybrid immunity, hybrid immunity relative to previous infection alone, hybrid immunity relative to previous vaccination alone, and hybrid immunity relative to hybrid immunity with fewer vaccine doses. Risk of bias was assessed with the Risk of Bias In Non-Randomized Studies of Interventions Tool. We used log-odds random-effects meta-regression to estimate the magnitude of protection at 1-month intervals. This study was registered with PROSPERO (CRD42022318605). FINDINGS: 11 studies reporting the protective effectiveness of previous SARS-CoV-2 infection and 15 studies reporting the protective effectiveness of hybrid immunity were included. For previous infection, there were 97 estimates (27 with a moderate risk of bias and 70 with a serious risk of bias). The effectiveness of previous infection against hospital admission or severe disease was 74·6% (95% CI 63·1-83·5) at 12 months. The effectiveness of previous infection against reinfection waned to 24·7% (95% CI 16·4-35·5) at 12 months. For hybrid immunity, there were 153 estimates (78 with a moderate risk of bias and 75 with a serious risk of bias). The effectiveness of hybrid immunity against hospital admission or severe disease was 97·4% (95% CI 91·4-99·2) at 12 months with primary series vaccination and 95·3% (81·9-98·9) at 6 months with the first booster vaccination after the most recent infection or vaccination. Against reinfection, the effectiveness of hybrid immunity following primary series vaccination waned to 41·8% (95% CI 31·5-52·8) at 12 months, while the effectiveness of hybrid immunity following first booster vaccination waned to 46·5% (36·0-57·3) at 6 months. INTERPRETATION: All estimates of protection waned within months against reinfection but remained high and sustained for hospital admission or severe disease. Individuals with hybrid immunity had the highest magnitude and durability of protection, and as a result might be able to extend the period before booster vaccinations are needed compared to individuals who have never been infected. FUNDING: WHO COVID-19 Solidarity Response Fund and the Coalition for Epidemic Preparedness Innovations.

Self-Assembled Microfiber-Like Biohydrogel for Ultrasensitive Whole-Cell Electrochemical Biosensing in Microdroplets.

A novel microfiber-like biohydrogel was fabricated by a facile approach relying on electroactive bacteria-induced graphene oxide reduction and confined self-assembly in a capillary tube. The microfiber-like biohydrogel (d = ∼1 mm) embedded high-density living cells and activated efficient electron exchange between cells and the conductive graphene network. Further, a miniature whole-cell electrochemical biosensing system was developed and applied for fumarate detection under -0.6 V (vs Ag/AgCl) applied potential. Taking advantage of its small size, high local cell density, and excellent electron exchange, this microfiber-like biohydrogel-based sensing system reached a linear calibration curve (R2 = 0.999) ranging from 1 nM to 10 mM. The limit of detection obtained was 0.60 nM, which was over 1300 times lower than a traditional biosensor for fumarate detection in 0.2 µL microdroplets. This work opened a new dimension for miniature whole-cell electrochemical sensing system design, which provided the possibility for bioelectrochemical detection in small volumes or three-dimensional local detection at high spatial resolutions.

White Matter Characteristics of Damage Along Fiber Tracts in Patients with Type 2 Diabetes Mellitus.

PURPOSE: The white matter (WM) of the brain of type 2 diabetes mellitus (T2DM) patients is susceptible to neurodegenerative processes, but the specific types and positions of microstructural lesions along the fiber tracts remain unclear. METHODS: In this study 61 T2DM patients and 61 healthy controls were recruited and underwent diffusion spectrum imaging (DSI). The results were reconstructed with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). WM microstructural abnormalities were identified using tract-based spatial statistics (TBSS). Pointwise WM tract differences were detected through automatic fiber quantification (AFQ). The relationships between WM tract abnormalities and clinical characteristics were explored with partial correlation analysis. RESULTS: TBSS revealed widespread WM lesions in T2DM patients with decreased fractional anisotropy and axial diffusivity and an increased orientation dispersion index (ODI). The AFQ results showed microstructural abnormalities in T2DM patients in specific portions of the right superior longitudinal fasciculus (SLF), right arcuate fasciculus (ARC), left anterior thalamic radiation (ATR), and forceps major (FMA). In the right ARC of T2DM patients, an aberrant ODI was positively correlated with fasting insulin and insulin resistance, and an abnormal intracellular volume fraction was negatively correlated with fasting blood glucose. Additionally, negative associations were found between blood pressure and microstructural abnormalities in the right ARC, left ATR, and FMA in T2DM patients. CONCLUSION: Using AFQ, together with DTI and NODDI, various kinds of microstructural alterations in the right SLF, right ARC, left ATR, and FMA can be accurately identified and may be associated with insulin and glucose status and blood pressure in T2DM patients.

Serology Assays Used in SARS-CoV-2 Seroprevalence Surveys Worldwide: A Systematic Review and Meta-Analysis of Assay Features, Testing Algorithms, and Performance.

Background: Many serological assays to detect SARS-CoV-2 antibodies were developed during the COVID-19 pandemic. Differences in the detection mechanism of SARS-CoV-2 serological assays limited the comparability of seroprevalence estimates for populations being tested. Methods: We conducted a systematic review and meta-analysis of serological assays used in SARS-CoV-2 population seroprevalence surveys, searching for published articles, preprints, institutional sources, and grey literature between 1 January 2020, and 19 November 2021. We described features of all identified assays and mapped performance metrics by the manufacturers, third-party head-to-head, and independent group evaluations. We compared the reported assay performance by evaluation source with a mixed-effect beta regression model. A simulation was run to quantify how biased assay performance affects population seroprevalence estimates with test adjustment. Results: Among 1807 included serosurveys, 192 distinctive commercial assays and 380 self-developed assays were identified. According to manufacturers, 28.6% of all commercial assays met WHO criteria for emergency use (sensitivity [Sn.] >= 90.0%, specificity [Sp.] >= 97.0%). However, manufacturers overstated the absolute values of Sn. of commercial assays by 1.0% [0.1, 1.4%] and 3.3% [2.7, 3.4%], and Sp. by 0.9% [0.9, 0.9%] and 0.2% [−0.1, 0.4%] compared to third-party and independent evaluations, respectively. Reported performance data was not sufficient to support a similar analysis for self-developed assays. Simulations indicate that inaccurate Sn. and Sp. can bias seroprevalence estimates adjusted for assay performance; the error level changes with the background seroprevalence. Conclusions: The Sn. and Sp. of the serological assay are not fixed properties, but varying features depending on the testing population. To achieve precise population estimates and to ensure the comparability of seroprevalence, serosurveys should select assays with high performance validated not only by their manufacturers and adjust seroprevalence estimates based on assured performance data. More investigation should be directed to consolidating the performance of self-developed assays.

Global SARS-CoV-2 seroprevalence from January 2020 to April 2022: A systematic review and meta-analysis of standardized population-based studies.

BACKGROUND: Our understanding of the global scale of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection remains incomplete: Routine surveillance data underestimate infection and cannot infer on population immunity; there is a predominance of asymptomatic infections, and uneven access to diagnostics. We meta-analyzed SARS-CoV-2 seroprevalence studies, standardized to those described in the World Health Organization's Unity protocol (WHO Unity) for general population seroepidemiological studies, to estimate the extent of population infection and seropositivity to the virus 2 years into the pandemic. METHODS AND FINDINGS: We conducted a systematic review and meta-analysis, searching MEDLINE, Embase, Web of Science, preprints, and grey literature for SARS-CoV-2 seroprevalence published between January 1, 2020 and May 20, 2022. The review protocol is registered with PROSPERO (CRD42020183634). We included general population cross-sectional and cohort studies meeting an assay quality threshold (90% sensitivity, 97% specificity; exceptions for humanitarian settings). We excluded studies with an unclear or closed population sample frame. Eligible studies-those aligned with the WHO Unity protocol-were extracted and critically appraised in duplicate, with risk of bias evaluated using a modified Joanna Briggs Institute checklist. We meta-analyzed seroprevalence by country and month, pooling to estimate regional and global seroprevalence over time; compared seroprevalence from infection to confirmed cases to estimate underascertainment; meta-analyzed differences in seroprevalence between demographic subgroups such as age and sex; and identified national factors associated with seroprevalence using meta-regression. We identified 513 full texts reporting 965 distinct seroprevalence studies (41% low- and middle-income countries [LMICs]) sampling 5,346,069 participants between January 2020 and April 2022, including 459 low/moderate risk of bias studies with national/subnational scope in further analysis. By September 2021, global SARS-CoV-2 seroprevalence from infection or vaccination was 59.2%, 95% CI [56.1% to 62.2%]. Overall seroprevalence rose steeply in 2021 due to infection in some regions (e.g., 26.6% [24.6 to 28.8] to 86.7% [84.6% to 88.5%] in Africa in December 2021) and vaccination and infection in others (e.g., 9.6% [8.3% to 11.0%] in June 2020 to 95.9% [92.6% to 97.8%] in December 2021, in European high-income countries [HICs]). After the emergence of Omicron in March 2022, infection-induced seroprevalence rose to 47.9% [41.0% to 54.9%] in Europe HIC and 33.7% [31.6% to 36.0%] in Americas HIC. In 2021 Quarter Three (July to September), median seroprevalence to cumulative incidence ratios ranged from around 2:1 in the Americas and Europe HICs to over 100:1 in Africa (LMICs). Children 0 to 9 years and adults 60+ were at lower risk of seropositivity than adults 20 to 29 (p < 0.001 and p = 0.005, respectively). In a multivariable model using prevaccination data, stringent public health and social measures were associated with lower seroprevalence (p = 0.02). The main limitations of our methodology include that some estimates were driven by certain countries or populations being overrepresented. CONCLUSIONS: In this study, we observed that global seroprevalence has risen considerably over time and with regional variation; however, over one-third of the global population are seronegative to the SARS-CoV-2 virus. Our estimates of infections based on seroprevalence far exceed reported Coronavirus Disease 2019 (COVID-19) cases. Quality and standardized seroprevalence studies are essential to inform COVID-19 response, particularly in resource-limited regions.

Cortical gray matter microstructural alterations in patients with type 2 diabetes mellitus.

BACKGROUND AND PURPOSE: Neurodegenerative processes are widespread in the brains of type 2 diabetes mellitus (T2DM) patients; gaps remain to exist in the current knowledge of the associated gray matter (GM) microstructural alterations. METHODS: A cross-sectional study was conducted to investigate alterations in GM microarchitecture in T2DM patients by diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI). Seventy-eight T2DM patients and seventy-four age-, sex-, and education level-matched healthy controls (HCs) without cognitive impairment were recruited. Cortical macrostructure and GM microstructure were assessed by surface-based analysis and GM-based spatial statistics (GBSS), respectively. Machine learning models were trained to evaluate the diagnostic values of cortical intracellular volume fraction (ICVF) for the classification of T2DM versus HCs. RESULTS: There were no differences in cortical thickness or area between the groups. GBSS analysis revealed similar GM microstructural patterns of significantly decreased fractional anisotropy, increased mean diffusivity and radial diffusivity in T2DM patients involving the frontal and parietal lobes, and significantly lower ICVF values were observed in nearly all brain regions of T2DM patients. A support vector machine model with a linear kernel was trained to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%. CONCLUSIONS: NODDI may help to probe the widespread GM neuritic density loss in T2DM patients occurs before measurable macrostructural alterations. The cortical ICVF values may provide valuable diagnostic information regarding the early GM microstructural alterations in T2DM.

Elevated ApoB/ApoA-I ratio is associated with acute anti-N-Methyl-D-aspartate receptor encephalitis, but not disease outcomes.

Objective: The purpose of the present study is to clarify the relationship between the apolipoprotein B100/apolipoprotein A-I (ApoB/ApoA-I) ratio and anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis. Methods: A total of 71 patients with anti-NMDAR encephalitis were included in this study, and their ApoB/ApoA-I ratios in baseline and follow-up were retrospectively analyzed. Results: The ApoB/ApoA-I ratio was closely correlated with the baseline-modified Rankin scale (mRS) score of >3 in patients with anti-NMDAR encephalitis. A subgroup analysis showed obvious differences between the high and low ApoB/ApoA-I ratio groups. The ApoB/ApoA-I ratio was positively correlated with intensive care unit (ICU) treatment, length of hospital stay, baseline mRS score, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). The ratios of the high and low ApoB/ApoA-I groups both improved in the follow-up. Conclusion: The increased ApoB/ApoA-I ratio is associated with acute anti-NMDAR encephalitis, but not disease outcomes. Serum ApoB/ApoA-I ratio was related to inflammation and immunity in peripheral blood. The findings might provide a new idea for further exploration of the pathogenesis and treatment of anti-NMDAR encephalitis.

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features.

Purpose: Cognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment. Methods: In this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with and without cognitive impairment based on T1-weighted structural MRI. The Montreal cognitive assessment score served as an index of the cognitive status of the patients. Results: The classifier could identify T2DM-related cognitive decline with a classification accuracy of 84.85% and achieved an area under the curve of 92.65%. Conclusions: The model can help clinicians analyze and predict cognitive impairment in patients and enable early treatment.

SARS-CoV-2 infection in Africa: a systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021.

INTRODUCTION: Estimating COVID-19 cumulative incidence in Africa remains problematic due to challenges in contact tracing, routine surveillance systems and laboratory testing capacities and strategies. We undertook a meta-analysis of population-based seroprevalence studies to estimate SARS-CoV-2 seroprevalence in Africa to inform evidence-based decision making on public health and social measures (PHSM) and vaccine strategy. METHODS: We searched for seroprevalence studies conducted in Africa published 1 January 2020-30 December 2021 in Medline, Embase, Web of Science and Europe PMC (preprints), grey literature, media releases and early results from WHO Unity studies. All studies were screened, extracted, assessed for risk of bias and evaluated for alignment with the WHO Unity seroprevalence protocol. We conducted descriptive analyses of seroprevalence and meta-analysed seroprevalence differences by demographic groups, place and time. We estimated the extent of undetected infections by comparing seroprevalence and cumulative incidence of confirmed cases reported to WHO. PROSPERO: CRD42020183634. RESULTS: We identified 56 full texts or early results, reporting 153 distinct seroprevalence studies in Africa. Of these, 97 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% (95% CI 1.0% to 9.2%) in April-June 2020 to 65.1% (95% CI 56.3% to 73.0%) in July-September 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 100:1, ranging from 18:1 to 954:1) and steady over time. Seroprevalence was highly heterogeneous both within countries-urban versus rural (lower seroprevalence for rural geographic areas), children versus adults (children aged 0-9 years had the lowest seroprevalence)-and between countries and African subregions. CONCLUSION: We report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and potential protection against COVID-19 severe disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.

Altered Functional Network Connectivity of Precuneus and Executive Control Networks in Type 2 Diabetes Mellitus Without Cognitive Impairment.

In epidemiological studies, type 2 diabetes mellitus (T2DM) has been associated with cognitive impairment and dementia, but studies about functional network connectivity in T2DM without cognitive impairment are limited. This study aimed to explore network connectivity alterations that may help enhance our understanding of damage-associated processes in T2DM. MRI data were analyzed from 82 patients with T2DM and 66 normal controls. Clinical, biochemical, and neuropsychological assessments were conducted in parallel with resting-state functional magnetic resonance imaging, and the cognitive status of the patients was assessed using the Montreal Cognitive Assessment-B (MoCA-B) score. Independent component analysis revealed a positive correlation between the salience network and the visual network and a negative connection between the left executive control network and the default mode network in patients with T2DM. The differences in dynamic brain network connectivity were observed in the precuneus, visual, and executive control networks. Internal network connectivity was primarily affected in the thalamus, inferior parietal lobe, and left precuneus. Hemoglobin A1c level, body mass index, MoCA-B score, and grooved pegboard (R) assessments indicated significant differences between the two groups (p < 0.05). Our findings show that key changes in functional connectivity in diabetes occur in the precuneus and executive control networks that evolve before patients develop cognitive deficits. In addition, the current study provides useful information about the role of the thalamus, inferior parietal lobe, and precuneus, which might be potential biomarkers for predicting the clinical progression, assessing the cognitive function, and further understanding the neuropathology of T2DM.

Simple and effective serum biomarkers potential for predicting status epilepticus in anti-N-methyl-D-aspartate receptor encephalitis.

BACKGROUND: Patients with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis who also present with status epilepticus (SE) often have a poor prognosis. The aim of this study is to explore simple and effective predictors for anti-NMDAR encephalitis accompanied with SE. METHODS: We retrospectively analyzed 65 anti-NMDAR encephalitis patients from January 2015 to December 2018 who admitted to the Third Affiliated Hospital of Sun Yat-sen University. Patients were divided into SE group and non-SE groups. Their pre-treatment data and 3-month follow-up data were retrospectively analyzed. RESULTS: The results showed that compared with the non-SE group, the levels of serum uric acid (UA) and high-density lipoprotein cholesterol (HDL-C) in anti-NMDAR encephalitis patients with SE decreased significantly before treatment. Additionally, the levels of serum UA and HDL-C increased while the level of C-reactive protein (CRP) decreased 3 months after treatment in the SE group. Compared with the non-SE group, the SE patients had higher modified Rankin scale (mRS) scores before (mRS1) and after treatment (mRS2). Serum UA concentrations before treatment showed significantly negative correlations with mRS1 (r = - 0.407, p < 0.01) and mRS2 (r = - 0.458, p < 0.001), while the level of serum CRP before treatment had strong positive correlations with mRS1 (r = 0.304, p < 0.05) and mRS2 (r = 0.301, p < 0.05) in anti-NMDAR encephalitis patients. The receiver operating characteristic curve demonstrated that the combined detection of UA, HDL-C and CRP before treatment had a significantly higher value (the area under the curve = 0.848; 95% confidence interval [CI], 0.74-0.957; p < 0.001) to predict anti-NMDAR encephalitis accompanied with SE than that of single detection. CONCLUSIONS: Hence, the combined detection of serum UA, HDL-C and CRP before treatment may be simple and effective indicators for predicting SE in anti-NMDAR encephalitis, which may be helpful in early stages to remind clinicians to be alert to the emergence of SE.

Chinese mothers' intent to disclose the HIV status to their children: the role of outcome expectations and self-efficacy.

The present study examined the association between outcome expectations, self-efficacy, and intention to disclose HIV status to children among HIV-positive women in China, and the moderating and mediating role of self-efficacy on the association between outcome expectations and intention to disclose. A cross-sectional survey was conducted among 179 HIV-positive mothers who had at least one living child aged >5 years and had not yet disclosed their HIV status to her oldest child. Results from hierarchical regressions revealed that after adjusting for socio-demographic and medical variables, negative outcome expectations had a negative association (ß = -0.22), while disclosure self-efficacy had a positive association (ß = 0.43) with an intention to disclose HIV. The moderation effect of self-efficacy on the association between outcome expectations and intention to disclose HIV was not significant. Results from structural equation modeling showed that self-efficacy mediated the association between negative/positive outcome expectations and intention to disclose HIV. Findings support the importance of outcome expectations and self-efficacy and also the mediating role of self-efficacy in HIV disclosure among HIV-positive mothers in the Chinese context.

Altered Hippocampal Subfields Volumes Is Associated With Memory Function in Type 2 Diabetes Mellitus.

Objective: Cognitive impairment in type 2 diabetes mellitus (T2DM) patients is related to changes in hippocampal structure and function. However, the alternation of hippocampal subfields volumes and their relationship with cognitive function are unclear. This study explored morphological alterations in the hippocampus and its subfields in T2DM patients and their relationship with cognitive function. Methods: Thirty T2DM patients and 20 healthy controls (HCs) were recruited and underwent 3-dimensional, high-resolution T1-weighted sequence (3D-T1) and a battery of cognitive tests. Freesurfer 6.0 was performed to segment the hippocampus into 12 subregions automatically. Then relationships between hippocampal subfield volumes and neurocognitive scale scores in the T2DM group were evaluated. Results: Immediate memory scores on the auditory verbal learning test (AVLT) and Montreal Cognitive Assessment (MoCA) scores in T2DM patients were lower than in the HCs. T2DM patients showed that volumes of the bilateral hippocampus were significantly reduced, mainly in the bilateral molecular layer, granule cell and molecular layer of the dentate gyrus (GC-ML-DG), cornu ammonis 4 (CA4), fimbria, and left subiculum and the right hippocampus amygdala transition area (HATA) compared to HCs. In addition, T2DM patients showed the FINS was negatively correlated with volume of left GC-ML-DG (r = -0.415, P = 0.035) and left CA4 (r = -0.489, P = 0.011); the FBG was negatively correlated with volume of right fimbria (r = -0.460, P = 0.018); the HOMA-IR was negatively correlated with volume of left GC-ML-DG (r = -0.367, P = 0.046) and left CA4(r = 0.462, P = 0.010). Partial correlation analysis found that the volume of right HATA in T2DM group was positively correlated with AVLT (immediate) scores (r = 0.427, P = 0.03). Conclusion: This study showed the volumes of multiple hippocampal subfields decreased and they were correlated with FINS, FBG and HOMA-IR in T2DM patients. We hypothesized that decreased hippocampal subfields volumes in T2DM patients was related to insulin resistance and impaired vascular function. In addition, we also found that abnormal hippocampal subfields volumes were related to memory function in T2DM patients, suggesting that reduced volumes in specific hippocampal subfields may be the potential mechanism of memory dysfunction in these patients.

Analyzing the electron trajectories in strong-field tunneling ionization with the phase-of-the-phase spectroscopy.

By numerically solving the time-dependent Schrödinger equation, we theoretically study strong-field tunneling ionization of Ar atom in the parallel two-color field which consists of a strong fundamental pulse and a much weaker second harmonic component. Based on the quantum orbits concept, we analyzed the photoelectron momentum distributions with the phase-of-the-phase spectroscopy, and the relative contributions of the two parts of the photoelectrons produced during the rising and falling edges of the adjacent quarters of the laser cycle are identified successfully. Our results show that the relative contributions of these two parts depend on both of the transverse and longitude momenta. By comparing the results from model atoms with Coulomb potential and short-range potential, the role of the long-range Coulomb interaction on the relative contributions of these two parts of electrons is revealed. Additionally, we show that the effects of Coulomb interaction on ionization time are vital for identifying their relative contributions.