Identifying and assessing the global causality among energy poverty, educational development, and public health from a novel perspective of natural resource policy optimization

With the gradual depletion of natural resources and the rapid development of renewable energy, reducing energy poverty will inevitably have a crucial impact on public health and educational development. However, the long-term cointegration link and the two-way causality among them at the global level, especially in developing countries, remain a black box, which was the initial incentive for this study. Based on annual panel data from 50 developing countries between 2000 and 2017, this study initially adopted second-generation unit root and cointegration tests to eliminate pseudo-regression. It then utilized impulse response function and Granger causality test to clearly demonstrate causality and its direction. In emerging economies and nations with high energy poverty rates, public health is positively influenced by educational development. In contrast, in non-emerging economies and countries with lower energy poverty rates, public health is negatively influenced by educational development. Thus, it is important to optimise natural resource policies to suit the local conditions. In summary, our empirical findings have implications for decreasing energy poverty, promoting educational development, and improving public health in developing countries;and for their natural resource policy formulation, especially in the post COVID-19 pandemic era.

Spatiotemporal characteristics and co-effects of air quality and carbon dioxide emissions changes during the COVID-19 epidemic lockdown measures in China.

The COVID-19 pandemic prompted several nations, including China, to enact unprecedented lockdown measures, leading to significant alterations in environmental conditions. Previous studies have solely analysed the impact of lockdown measures on air pollutants or carbon dioxide (CO2) emissions during the COVID-19 pandemic in China, but few have focused on the spatio-temporal change characteristics and synergistic effects between the two. In this study, we constructed a methodological framework to examine the spatiotemporal characteristics and co-effects of air quality (PM2.5, SO2, and NO2) and CO2 changes in 324 prefecture-level cities in China due to the COVID-19 blockade measures from January 24 to April 30, 2020, using the regression discontinuity in time method and co-effect control coordinate system. The results show that a significant improvement in air quality and CO2 emissions during the lockdown period, with notable north‒south heterogeneity. During the major lockdown period (January 24 to February 29), the measures resulted in respective reductions of 5.6%, 16.6%, and 25.1% in the concentrations of SO2, NO2, and CO2 nationwide. The proportions of cities with negative treatment effects on PM2.5, SO2, NO2, and CO2 were 39.20%, 70.99%, 84.6%, and 99.38%, respectively. Provinces where concentrations of CO2 and NO2 declined by over 30% were primarily concentrated in southern areas of the 'Yangtze River Defense Line'. Starting from March, the improvement effect of air quality and CO2 has weakened, and the concentration of air pollutants has rebounded. This study offers crucial insights into the causal effects of lockdown measures on air quality changes, and reveals the synergy between air quality and CO2, thereby providing a reference for devising effective air quality improvement and energy-saving emission reduction strategies.

Characterizing Macrophages Diversity in COVID-19 Patients Using Deep Learning.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent responsible for coronavirus disease 2019 (COVID-19), has affected the lives of billions and killed millions of infected people. This virus has been demonstrated to have different outcomes among individuals, with some of them presenting a mild infection, while others present severe symptoms or even death. The identification of the molecular states related to the severity of a COVID-19 infection has become of the utmost importance to understanding the differences in critical immune response. In this study, we computationally processed a set of publicly available single-cell RNA-Seq (scRNA-Seq) data of 12 Bronchoalveolar Lavage Fluid (BALF) samples diagnosed as having a mild, severe, or no infection, and generated a high-quality dataset that consists of 63,734 cells, each with 23,916 genes. We extended the cell-type and sub-type composition identification and our analysis showed significant differences in cell-type composition in mild and severe groups compared to the normal. Importantly, inflammatory responses were dramatically elevated in the severe group, which was evidenced by the significant increase in macrophages, from 10.56% in the normal group to 20.97% in the mild group and 34.15% in the severe group. As an indicator of immune defense, populations of T cells accounted for 24.76% in the mild group and decreased to 7.35% in the severe group. To verify these findings, we developed several artificial neural networks (ANNs) and graph convolutional neural network (GCNN) models. We showed that the GCNN models reach a prediction accuracy of the infection of 91.16% using data from subtypes of macrophages. Overall, our study indicates significant differences in the gene expression profiles of inflammatory response and immune cells of severely infected patients.

Effects of SARS-CoV-2 infection on human reproduction.

The worldwide infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) impacts human health and life on multiple levels. People infected with SARS-CoV-2 suffer from physical disorders and psychological distress. At present, no direct evidence indicates that SARS-CoV-2 negatively influences human reproduction, and the possibility that gametes and embryos are affected requires further investigation. To evaluate the potential effects of SARS-CoV-2 infection on human reproduction and fetal health, this review summarizes the basic and clinical research of SARS-CoV-2 on reproduction up to date, hoping to offer guidance and advice to people at reproductive age and provide clues for the prevention and treatment of associated diseases.

SARS-CoV-2 Entry Factors: ACE2 and TMPRSS2 Are Expressed in Peri-Implantation Embryos and the Maternal-Fetal Interface.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread throughout the world, leading to large-scale population infection. Angiotensin-converting enzyme 2 (ACE2) is the receptor of both severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2. However, it is still controversial whether vertical transmission exists. In order to investigate the potential risk of SARS-CoV-2 vertical transmission, we explored ACE2 and TMPRSS2 (encoding transmembrane protease serine 2) expression patterns in peri-implantation embryos and the maternal-fetal interface using previously published single-cell transcriptome data. The results showed that day 6 (D6) trophectoderm (TE) cells in peri-implantation embryos, as well as syncytiotrophoblast (STB) at 8 weeks of gestation (STB_8W) and extravillous trophoblast (EVT) cells at 24 weeks of gestation (EVT_24W) in the maternal-fetal interface, strongly co-expressed ACE2 and TMPRSS2, indicating a SARS-CoV-2 infection susceptibility. The ACE2 positive-expressing cells in the three cell types mentioned above were found to share common characteristics, which were involved in autophagy and immune-related processes. ACE2 showed no gender bias in post-implantation embryos but showed a significant gender difference in D6_TE, D6 primitive endoderm (PE) cells, and ACE2 positive-expressing STBs. These findings suggest that there may be different SARS-CoV-2 infection susceptibilities of D6 embryos of different genders and during the gestation of different genders. Our results reveal potential SARS-CoV-2 infection risks during embryo transfer, peri-implantation embryo development, and gestation.

Single-cell transcriptome analysis of the novel coronavirus (SARS-CoV-2) associated gene ACE2 expression in normal and non-obstructive azoospermia (NOA) human male testes.

Being infected by SARS-CoV-2 may cause damage to multiple organs in patients, such as the lung, liver and heart. Angiotensin-converting enzyme 2 (ACE2), reported as a SARS-CoV-2 receptor, is also expressed in human male testes. This suggests a potential risk in human male reproductive system. However, the characteristics of ACE2-positive cells and the expression of other SARS-CoV-2 process-related genes are still worthy of further investigation. Here, we performed singlecell RNA seq (scRNA-seq) analysis on 853 male embryo primordial germ cells (PGCs) and 2,854 normal testis cells to assess the effects of the SARS-CoV-2 virus on the male reproductive system from embryonic stage to adulthood. We also collected and constructed the scRNA-seq library on 228 Sertoli cells from three non-obstructive azoospermia (NOA) patients to assess the effects at disease state. We found that ACE2 expressing cells existed in almost all testis cell types and Sertoli cells had highest expression level and positive cells ratio. Moreover, ACE2 was also expressed in human male PGCs. In adulthood, the level of ACE2 expression decreased with the increase of age. We also found that ACE2 positive cells had high expressions of stress response and immune activation-related genes. Interestingly, some potential SARS-CoV-2 process-related genes such as TMPRSS2, BSG, CTSL and CTSB had different expression patterns in the same cell type. Furthermore, ACE2 expression level in NOA donors' Sertoli cells was significantly decreased. Our work would help to assess the risk of SARS-CoV-2 infection in the male reproductive system.