Estimates of Power Shortages and Affected Populations during the Initial Period of the Ukrainian-Russian Conflict

Since the outbreak of the Ukrainian-Russian conflict on 24 February 2022, Ukraine’s economy, society, and cities have been devastated and struck on multiple fronts, with large numbers of refugees fleeing to neighboring countries. The lighting systems in Ukrainian cities have been severely restricted due to Russian missile bombing and curfew policies. The power shortages adversely affected the livelihoods of the Ukrainian residents dramatically. For a timely assessment of the power shortages’ extent and the affected population in Ukraine, this study tracked the dynamics of nighttime light emissions in Ukraine based on the newly developed daily Black Marble product (VNP46A2) from NASA. The results show that the average light radiance in Ukrainian urban areas has decreased by about 37% since the eruption of the war, with Kiev city being the most dramatic region, having a post-conflict decrease of about 51%. In addition, by introducing near-real-time population data, we have implemented a survey of the affected population in Ukraine suffering from war-induced power shortages. Estimates show that about 17.3 million Ukrainian residents were affected by power shortages. In more detail, the number of children under 10 years old was about 2.35 million (about 5.24% of the total population), while the number of elderly people over 60 years old was about 3.53 million (about 7.86% of the total population). Generally, the results of this study could contribute positively to the timely assessment of the impact of the conflict and the implementation of humanitarian relief.

The Relationship between Intimate Partner Violence and Online Help-Seeking: A Moderated Mediation Model of Emotion Dysregulation and Perceived Anonymity.

During the COVID-19 pandemic, lockdowns and isolation have limited the availability of face-to-face support services for victims of intimate partner violence (IPV). Despite the growing need for online help in supporting IPV victims, far less is known about the underlying mechanisms between IPV and online help-seeking. We studied the mediating role of emotion dysregulation (ED) and the moderating role of perceived anonymity (PA) on the internet to explain IPV victims' willingness of online help-seeking (WOHS). Through a PROCESS analysis of the questionnaire data (n = 510, 318 female, 192 male, Mage = 22.41 years), the results demonstrate that: (1) ED has been linked with the experience of IPV, and IPV significantly induces ED. (2) When IPV victims realize the symptoms of ED, they have a strong willingness to seek external intervention to support themselves. ED mediates the relationship between IPV and online help-seeking. (3) For youth growing up in the era of social networking sites (SNS), personal privacy protection is an important factor when seeking online help. The anonymity of the internet has a positive effect on victims who experience IPV and ED, and it increases WOHS. This study introduces a new perspective on the psychological mechanism behind IPV victims' help-seeking behaviors, and it suggests that the improvement of anonymity in online support can be an effective strategy for assisting IPV victims.

SARS-CoV-2 N Protein Antagonizes Stress Granule Assembly and IFN Production by Interacting with G3BPs to Facilitate Viral Replication.

SARS-CoV-2 is the causative agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19) and poses a significant threat to global health. N protein (NP), which is a major pathogenic protein among betacoronaviruses, binds to the viral RNA genome to allow viral genome packaging and viral particle release. Recent studies showed that NP antagonizes interferon (IFN) induction and mediates phase separation. Using live SARS-CoV-2 viruses, this study provides solid evidence showing that SARS-CoV-2 NP associates with G3BP1 and G3BP2 in vitro and in vivo. NPSARS-CoV-2 could efficiently suppress G3BP-mediated SG formation and potentiate viral infection by overcoming G3BP1-mediated antiviral innate immunity. G3BP1 conditional knockout mice (g3bp1fl/fL, Sftpc-Cre) exhibit significantly higher lung viral loads after SARS-CoV-2 infection than wild-type mice. Our findings contribute to the growing body of knowledge regarding the pathogenicity of NPSARS-CoV-2 and provide insight into new therapeutics targeting NPSARS-CoV-2. IMPORTANCE In this study, by in vitro assay and live SARS-CoV-2 virus infection, we provide solid evidence that the SARS-CoV-2 NP associates with G3BP1 and G3BP2 in vitro and in vivo. NPSARS-CoV-2 could efficiently suppress G3BP-mediated SG formation and potentiate viral infection by overcoming antiviral innate immunity mediated by G3BP1 in A549 cell lines and G3BP1 conditional knockout mice (g3bp1-cKO) mice, which provide in-depth evidence showing the mechanism underlying NP-related SARS-CoV-2 pathogenesis through G3BPs.

Supermeres are functional extracellular nanoparticles replete with disease biomarkers and therapeutic targets.

Extracellular vesicles and exomere nanoparticles are under intense investigation as sources of clinically relevant cargo. Here we report the discovery of a distinct extracellular nanoparticle, termed supermere. Supermeres are morphologically distinct from exomeres and display a markedly greater uptake in vivo compared with small extracellular vesicles and exomeres. The protein and RNA composition of supermeres differs from small extracellular vesicles and exomeres. Supermeres are highly enriched with cargo involved in multiple cancers (glycolytic enzymes, TGFBI, miR-1246, MET, GPC1 and AGO2), Alzheimer's disease (APP) and cardiovascular disease (ACE2, ACE and PCSK9). The majority of extracellular RNA is associated with supermeres rather than small extracellular vesicles and exomeres. Cancer-derived supermeres increase lactate secretion, transfer cetuximab resistance and decrease hepatic lipids and glycogen in vivo. This study identifies a distinct functional nanoparticle replete with potential circulating biomarkers and therapeutic targets for a host of human diseases.

CariesNet: a deep learning approach for segmentation of multi-stage caries lesion from oral panoramic X-ray image

Dental caries has been a common health issue throughout the world, which can even lead to dental pulp and root apical inflammation eventually. Timely and effective treatment of dental caries is vital for patients to reduce pain. Traditional caries disease diagnosis methods like naked-eye detection and panoramic radiograph examinations rely on experienced doctors, which may cause misdiagnosis and high time-consuming. To this end, we propose a novel deep learning architecture called CariesNet to delineate different caries degrees from panoramic radiographs. We firstly collect a high-quality panoramic radiograph dataset with 3127 well-delineated caries lesions, including shallow caries, moderate caries, and deep caries. Then we construct CariesNet as a U-shape network with the additional full-scale axial attention module to segment these three caries types from the oral panoramic images. Moreover, we test the segmentation performance between CariesNet and other baseline methods. Experiments show that our method can achieve a mean 93.64% Dice coefficient and 93.61% accuracy in the segmentation of three different levels of caries.

Full Scale Attention for Automated COVID-19 Diagnosis from CT Images.

The wide spread of coronavirus pneumonia (COVID-19) has been a severe threat to global health since 2019. Apart from the nucleic acid detection, medical imaging examination is a vital diagnostic modality to confirm and treat the disease. Thus, implementing the automatic diagnosis of the COVID-19 bears particular significance. However, the limitations of data quality and size strongly hinder the clas-sification and segmentation performance and it also result in high misdiagnosis rate. To this end, we propose a novel full scale attention mechanism (FUSA) to capture more contextual dependencies of features, which enables the model easier to classify positive cases and improve the sensitivity. Specifically, FUSA parallelly extracts the information of channel domain and spatial domain, and fuses them together. The experimental study shows FUSA can significantly improve the COVID-19 automated diagnosis performance and eliminate false negative cases compared with other state-of-the-art ones.

miR-16-5p Regulates PTPN4 and Affects Cardiomyocyte Apoptosis and Autophagy Induced by Hypoxia/Reoxygenation.

OBJECTIVES: To explore the effects of miR-16-5p and PTPN4 on the apoptosis and autophagy of AC16 cardiomyocytes after hypoxia/reoxygenation treatment. METHODS: AC16 cells were divided into the control group (NC), hypoxia/reoxygenation group (H/R), knockdown miR-16-5p negative control group (NC inhibitor), knockdown miR-16-5p group (miR-16-5p inhibitor), overexpression miR-16-5p negative control group (NC mimics), overexpression miR-16-5p group (miR-16-5p mimics), silent PTPN4 negative control group (sh-NC), silent PTPN4 group (sh-PTPN4), and silent PTPN4 + knockdown miR-16-5p group (sh-PTPN4 + miR-16-5p inhibitor). Real-time fluorescent quantitative PCR (RT-qPCR) and western blotting (WB) were used to measure the expression level of miR-16-3p, miR-16-5p, protein tyrosine phosphatase nonreceptor type 4 (PTPN4), and autophagy-related proteins (beclin-1, LC3 II/I, and P26) in AC16 cells. The apoptosis level of AC16 cells in each group was measured by flow cytometry and TUNEL. The dual-luciferase reporter gene experiment was also used to verify the targeting relationship between miR-16-5p and PTPN4. RESULTS: After H/R treatment, the levels of myocardial injury markers including LDH and CK-MB in AC16 cells were increased significantly (P < 0.05), and the levels of cell apoptosis and autophagy also increased significantly (P < 0.05). The level of miR-16-3p in AC16 cells did not change significantly after H/R treatment, whereas the level of miR-16-5p was increased significantly (P < 0.05). After miR-16-5p was knocked down, the levels of LDH and CK-MB in AC16 cells treated with H/R were significantly reduced (P < 0.05), and the rates of cell apoptosis and autophagy were also significantly reduced (P < 0.05). miR-16-5p negatively regulated the expression level of PTPN4 protein in AC16 cells (P < 0.05), and the dual-luciferase reporter gene experiment confirmed that PTPN4 was the downstream target of miR-16-5p. Silencing of PTPN4 significantly increased the damage of AC16 cells induced by H/R treatment (P < 0.05), but simultaneously inhibiting the expression of PTPN4 and miR-16-5p reversed the protective effect of miR-16-5p knockdown on AC16 cells (P < 0.05). CONCLUSIONS: The expression of miR-16-5p is upregulated in AC16 cells after H/R treatment and the knockdown which can protect AC16 cells from H/R-induced cell damage that may be due to its regulation on the expression of PTPN4.

An Antioxidant Enzyme Therapeutic for COVID-19.

The COVID-19 pandemic has taken a significant toll on people worldwide, and there are currently no specific antivirus drugs or vaccines. Herein it is a therapeutic based on catalase, an antioxidant enzyme that can effectively breakdown hydrogen peroxide and minimize the downstream reactive oxygen species, which are excessively produced resulting from the infection and inflammatory process, is reported. Catalase assists to regulate production of cytokines, protect oxidative injury, and repress replication of SARS-CoV-2, as demonstrated in human leukocytes and alveolar epithelial cells, and rhesus macaques, without noticeable toxicity. Such a therapeutic can be readily manufactured at low cost as a potential treatment for COVID-19.