Molecular basis of nucleosomal H3K36 methylation by NSD methyltransferases.

Histone methyltransferases of the nuclear receptor-binding SET domain protein (NSD) family, including NSD1, NSD2 and NSD3, have crucial roles in chromatin regulation and are implicated in oncogenesis1,2. NSD enzymes exhibit an autoinhibitory state that is relieved by binding to nucleosomes, enabling dimethylation of histone H3 at Lys36 (H3K36)3-7. However, the molecular basis that underlies this mechanism is largely unknown. Here we solve the cryo-electron microscopy structures of NSD2 and NSD3 bound to mononucleosomes. We find that binding of NSD2 and NSD3 to mononucleosomes causes DNA near the linker region to unwrap, which facilitates insertion of the catalytic core between the histone octamer and the unwrapped segment of DNA. A network of DNA- and histone-specific contacts between NSD2 or NSD3 and the nucleosome precisely defines the position of the enzyme on the nucleosome, explaining the specificity of methylation to H3K36. Intermolecular contacts between NSD proteins and nucleosomes are altered by several recurrent cancer-associated mutations in NSD2 and NSD3. NSDs that contain these mutations are catalytically hyperactive in vitro and in cells, and their ectopic expression promotes the proliferation of cancer cells and the growth of xenograft tumours. Together, our research provides molecular insights into the nucleosome-based recognition and histone-modification mechanisms of NSD2 and NSD3, which could lead to strategies for therapeutic targeting of proteins of the NSD family.

Structural basis of DNA recognition by BEN domain proteins reveals a role for oligomerization in unmethylated DNA selection by BANP.

The BEN domain is a newly discovered type of DNA-binding domain that exists in a variety of species. There are nine BEN domain-containing proteins in humans, and most have been shown to have chromatin-related functions. NACC1 preferentially binds to CATG motif-containing sequences and functions primarily as a transcriptional coregulator. BANP and BEND3 preferentially bind DNA bearing unmethylated CpG motifs, and they function as CpG island-binding proteins. To date, the DNA recognition mechanism of quite a few of these proteins remains to be determined. In this study, we solved the crystal structures of the BEN domains of NACC1 and BANP in complex with their cognate DNA substrates. We revealed the details of DNA binding by these BEN domain proteins and unexpectedly revealed that oligomerization is required for BANP to select unmethylated CGCG motif-containing DNA substrates. Our study clarifies the controversies surrounding DNA recognition by BANP and demonstrates a new mechanism by which BANP selects unmethylated CpG motifs and functions as a CpG island-binding protein. This understanding will facilitate further exploration of the physiological functions of the BEN domain proteins in the future.

Variation characteristics of acid rain in Zhuzhou, Central China over the period 2011-2020.

Zhuzhou was one of the most polluted cities in China with the serious acid rain. Due to the implementation of air pollution control measures from 2016 to 2018, the acid rain pollution in this city has reduced. In order to understand the recent situation, a comprehensive study on the acid rain was carried out from January 2011 to December 2020. The pH values during the study period varied from 3.3 to 7.5, with a volume-weighted mean value of 4.7. The predominant acidic components of the precipitation were SO42- and NO3-, accounting for 89.3% of the total anions. The ratio of non-sea-salt SO42- to NO3- showed a decreasing trend, revealing that the pollution type of acid rain changed from sulfuric acid type to sulfuric acid and nitric acid compound type. The correlation analysis (p < 0.05) showed that SO42- was positively correlated with NH4+, Ca2+, and Mg2+; hence, it predominated in precipitation as (NH4)2SO4, NH4HSO4, CaSO4, and MgSO4. Significant positive correlation of Ca2+ with Mg2+ shows that they may originated mainly from crust. Significant positive correlation between SO42- and F- and Cl- indicate that their source may be related to the non-ferrous metal smelting industry in Zhuzhou. Further correlation analysis shows that emissions from the non-ferrous metal smelting industry in the area have a large significant on SO42- and F- in precipitation, while Cl- may still be emitted from other anthropogenic sources.

Structural basis of the human negative elongation factor NELF-B/C/E ternary complex.

Negative elongation factor (NELF) is a four-subunit transcription elongation factor that mainly functions in maintaining the paused state of RNA polymerase II in eukaryotes. Upon binding to Pol II, NELF works synergistically with DRB sensitivity-inducing factor (DSIF) and inhibits transcription elongation of Pol II, which subsequently retains a stably paused state 20-60 base pairs downstream of the promoter. The promoter-proximal pausing of Pol II caused by NELF is a general mechanism of transcriptional regulation for most signal-responsive genes. To date, structural studies have significantly advanced our understanding of the molecular mechanisms of NELF. However, a high quality structural model clarifying the interaction details of this complex is still lacking. In this study, we solved the high resolution crystal structure of the NELF-B/C/E ternary complex. We observed detailed interactions between subunits and identified residues important for the association between NELF-B and NELF-E. Our work presents a precise model of the NELF complex, which will facilitate our understanding of its in vivo function.

Potential inhibitors for the novel coronavirus (SARS-CoV-2).

The lack of a vaccine or any effective treatment for the aggressive novel coronavirus disease (COVID-19) has created a sense of urgency for the discovery of effective drugs. Several repurposing pharmaceutical candidates have been reported or envisaged to inhibit the emerging infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but their binding sites, binding affinities and inhibitory mechanisms are still unavailable. In this study, we use the ligand-protein docking program and molecular dynamic simulation to ab initio investigate the binding mechanism and inhibitory ability of seven clinically approved drugs (Chloroquine, Hydroxychloroquine, Remdesivir, Ritonavir, Beclabuvir, Indinavir and Favipiravir) and a recently designed α-ketoamide inhibitor (13b) at the molecular level. The results suggest that Chloroquine has the strongest binding affinity with 3CL hydrolase (Mpro) among clinically approved drugs, indicating its effective inhibitory ability for SARS-CoV-2. However, the newly designed inhibitor 13b shows potentially improved inhibition efficiency with larger binding energy compared with Chloroquine. We further calculate the important binding site residues at the active site and demonstrate that the MET 165 and HIE 163 contribute the most for 13b, while the MET 165 and GLN 189 for Chloroquine, based on residual energy decomposition analysis. The proposed work offers a higher research priority for 13b to treat the infection of SARS-CoV-2 and provides theoretical basis for further design of effective drug molecules with stronger inhibition.

Peripheral artery disease independently associated with significantly higher risk for COVID-19 mortality: Evidence based on adjusted effect estimates.

OBJECTIVE: To investigate the influence of peripheral artery disease (PAD) on the risk of mortality among coronavirus disease 2019 (COVID-19) patients based on adjusted effect estimates. METHODS: Systematic searches were performed through electronic databases. A random-effect model was applied to calculate the pooled effect and corresponding 95% confidence interval (CI). Inconsistency index (I2) was used to evaluate the heterogeneity across studies. Sensitivity analysis, subgroup analysis, and Begg's test were all implemented. RESULTS: On the basis of 16 eligible studies with 142,832 COVID-19 patients, the meta-analysis showed that PAD significantly increased the risk for mortality among COVID-19 patients (pooled effect = 1.29, 95% CI: 1.10-1.51). The significant association was also observed in the subgroup analysis stratified by hospitalized patients, mean age ≥ 60 years, Europe and North America. Sensitivity analysis verified the robustness of our findings. Begg's test (P = 0.15) showed there was no potential publication bias. CONCLUSIONS: COVID-19 patients with PAD may have a greater risk of mortality. Clinicians and nursing staff are supposed to identify and monitor these high-risk patients in a timely manner and provide appropriate clinical treatment for them.

3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks.

Compared to magnetic resonance imaging (MRI) and X-ray computed tomography (CT), ultrasound imaging is safer, faster, and more widely applicable. However, the use of conventional ultrasound in transcranial brain imaging for adults is predominantly hindered by the high acoustic impedance contrast between the skull and soft tissue. This study introduces a 3D AI algorithm, Brain Imaging Full Convolution Network (BIFCN), combining waveform modeling and deep learning for precise brain ultrasound reconstruction. We constructed a network comprising one input layer, four convolution layers, and one pooling layer to train our algorithm. In the simulation experiment, the Pearson correlation coefficient between the reconstructed and true images was exceptionally high. In the laboratory, the results showed a slightly lower but still impressive coincidence degree for 3D reconstruction, with pure water serving as the initial model and no prior information required. The 3D network can be trained in 8 h, and 10 samples can be reconstructed in just 12.67 s. The proposed 3D BIFCN algorithm provides a highly accurate and efficient solution for mapping wavefield frequency domain data to 3D brain models, enabling fast and precise brain tissue imaging. Moreover, the frequency shift phenomenon of blood may become a hallmark of BIFCN learning, offering valuable quantitative information for whole-brain blood imaging.

Passivating Defects at the Bottom Interface of Perovskite by Ethylammonium to Improve the Performance of Perovskite Solar Cells.

The interface of perovskite solar cells (PSCs) plays a significant role in influencing their performance, yet there is still scarce research focusing on their difficult-to-expose bottom interfaces. Herein, ethylammonium bromide (EABr) is introduced into the bottom interface and its passivation effects are studied directly. First, EABr can improve substrate wettability, which is beneficial for the perovskite-film deposition. By lifting off the perovskite film spontaneously from the substrate, it is found that EABr can significantly reduce the amount of unreacted PbI2 at the bottom interface. These PbI2 crystals have been recently identified as a major defect source and degradation site for perovskite film. Meanwhile, EABr also lifts the valence band maximum at the bottom side of perovskite from -5.38 to -5.09 eV, facilitating better hole transfer. Such a improvement is also verified by the study of charge carrier dynamics. Through introducing EABr, all photovoltaic parameters of the inverted PSCs are improved, and their power conversion efficiency (PCE) increases from 20.41% to 21.06%. The study highlights the importance of direct characterization of the bottom interface for a better passivation effect.

The association between stroke and COVID-19-related mortality: a systematic review and meta-analysis based on adjusted effect estimates.

OBJECTIVE: To investigate the association between stroke and the risk for mortality among coronavirus disease 2019 (COVID-19) patients. METHODS: We performed systematic searches through electronic databases including PubMed, Embase, Scopus, and Web of Science to identify potential articles reporting adjusted effect estimates on the association of stroke with COVID-19-related mortality. To estimate pooled effects, the random-effects model was applied. Subgroup analyses and meta-regression were performed to explore the possible sources of heterogeneity. The stability of the results was assessed by sensitivity analysis. Publication bias was evaluated by Begg's test and Egger's test. RESULTS: This meta-analysis included 47 studies involving 7,267,055 patients. The stroke was associated with higher COVID-19 mortality (pooled effect = 1.30, 95% confidence interval (CI): 1.16-1.44; I2 = 89%, P < 0.01; random-effects model). Subgroup analyses yielded consistent results among area, age, proportion of males, setting, cases, effect type, and proportion of severe COVID-19 cases. Statistical heterogeneity might result from the different effect type according to the meta-regression (P = 0.0105). Sensitivity analysis suggested that our results were stable and robust. Both Begg's test and Egger's test indicated that potential publication bias did not exist. CONCLUSION: Stroke was independently associated with a significantly increased risk for mortality in COVID-19 patients.

Sargassum fusiforme Polysaccharide-Based Hydrogel Microspheres Enhance Crystal Violet Dye Adsorption Properties.

In this study, a polysaccharide-based hydrogel microsphere (SFP/SA) was prepared using S. fusiforme polysaccharide (SFP) and sodium alginate (SA). Fourier transform infrared spectroscopy (FT-IR) demonstrated that SFP was effectively loaded onto the hydrogel microsphere. Texture profile analysis (TPA) and differential scanning calorimetry (DSC) showed that, with the increase of SFP concentration, the hardness of SFP/SA decreased, while the springiness and cohesiveness of SFP/SA increased, and the thermal stability of SFP/SA improved. The equilibrium adsorption capacity of SFP/SA increased from 8.20 mg/g (without SFP) to 67.95 mg/g (SFP accounted 80%) without swelling, and from 35.05 mg/g (without SFP) to 81.98 mg/g (SFP accounted 80%) after 24 h swelling. The adsorption of crystal violet (CV) dye by SFP/SA followed pseudo-first order and pseudo-second order kinetics (both with R2 > 0.99). The diffusion of intraparticle in CV dye was not the only influencing factor. Moreover, the adsorption of CV dye for SFP/SA (SFP accounted 60%) fit the Langmuir and Temkin isotherm models. SFP/SA exhibited good regenerative adsorption capacity. Its adsorption rate remained at > 97% at the 10th consecutive cycle while SFP accounted for 80%. The results showed that the addition of Sargassum fusiforme polysaccharide could increase the springiness, cohesiveness and thermal stability of the hydrogel microsphere, as well as improve the adsorption capacity of crystal violet dye.

Unveiling the potential of ultrasound in brain imaging: Innovations, challenges, and prospects.

Within medical imaging, ultrasound serves as a crucial tool, particularly in the realms of brain imaging and disease diagnosis. It offers superior safety, speed, and wider applicability compared to Magnetic Resonance Imaging (MRI) and X-ray Computed Tomography (CT). Nonetheless, conventional transcranial ultrasound applications in adult brain imaging face challenges stemming from the significant acoustic impedance contrast between the skull bone and soft tissues. Recent strides in ultrasound technology encompass a spectrum of advancements spanning tissue structural imaging, blood flow imaging, functional imaging, and image enhancement techniques. Structural imaging methods include traditional transcranial ultrasound techniques and ultrasound elastography. Transcranial ultrasound assesses the structure and function of the skull and brain, while ultrasound elastography evaluates the elasticity of brain tissue. Blood flow imaging includes traditional transcranial Doppler (TCD), ultrafast Doppler (UfD), contrast-enhanced ultrasound (CEUS), and ultrasound localization microscopy (ULM), which can be used to evaluate the velocity, direction, and perfusion of cerebral blood flow. Functional ultrasound imaging (fUS) detects changes in cerebral blood flow to create images of brain activity. Image enhancement techniques include full waveform inversion (FWI) and phase aberration correction techniques, focusing on more accurate localization and analysis of brain structures, achieving more precise and reliable brain imaging results. These methods have been extensively studied in clinical animal models, neonates, and adults, showing significant potential in brain tissue structural imaging, cerebral hemodynamics monitoring, and brain disease diagnosis. They represent current hotspots and focal points of ultrasound medical research. This review provides a comprehensive summary of recent developments in brain imaging technologies and methods, discussing their advantages, limitations, and future trends, offering insights into their prospects.

Deep Learning With Physics-Embedded Neural Network for Full Waveform Ultrasonic Brain Imaging.

The convenience, safety, and affordability of ultrasound imaging make it a vital non-invasive diagnostic technique for examining soft tissues. However, significant differences in acoustic impedance between the skull and soft tissues hinder the successful application of traditional ultrasound for brain imaging. In this study, we propose a physics-embedded neural network with deep learning based full waveform inversion (PEN-FWI), which can achieve reliable quantitative imaging of brain tissues. The network consists of two fundamental components: forward convolutional neural network (FCNN) and inversion sub-neural network (ISNN). The FCNN explores the nonlinear mapping relationship between the brain model and the wavefield, replacing the tedious wavefield calculation process based on the finite difference method. The ISNN implements the mapping from the wavefield to the model. PEN-FWI includes three iterative steps, each embedding the F CNN into the ISNN, ultimately achieving tomography from wavefield to brain models. Simulation and laboratory tests indicate that PEN-FWI can produce high-quality imaging of the skull and soft tissues, even starting from a homogeneous water model. PEN-FWI can achieve excellent imaging of clot models with constant uniform distribution of velocity, randomly Gaussian distribution of velocity, and irregularly shaped randomly distributed velocity. Robust differentiation can also be achieved for brain slices of various tissues and skulls, resulting in high-quality imaging. The imaging time for a horizontal cross-sectional imag e of the brain is only 1.13 seconds. This algorithm can effectively promote ultrasound-based brain tomography and provide feasible solutions in other fields.

Fingerprint authentication based on deep convolutional descent inversion tomography.

Fingerprint authentication is widely used in various areas. While existing methods effectively extract and match fingerprint features, they encounter difficulties in detecting wet fingers and identifying false minutiae. In this paper, a fast fingerprint inversion and authentication method based on Lamb waves is developed by integrating deep learning and multi-scale fusion. This method speeds up the inversion performance through deep fast inversion tomography (DeepFIT) and uses Mask R-CNN to improve authentication accuracy. DeepFIT utilizes fully connected and convolutional operations to approach the descent gradient, enhancing the efficiency of ultrasonic array reconstruction. This suppresses artifacts and accelerates sub-millimeter-level fingerprint minutia inversion. By identifying the overall morphological relationships of various minutia in fingerprints, meaningful minutia representing individual identities are extracted by the Mask R-CNN method. It segments and matches multi-scale fingerprint features, improving the reliability of authentication results. Results indicate that the proposed method has high accuracy, robustness, and speed, optimizing the entire fingerprint authentication process.

Transcriptomics analysis of the role of SdiA in desiccation tolerance of Cronobacter sakazakii in powdered infant formula.

The quorum-sensing receptor SdiA is vital for regulating the desiccation tolerance of C. sakazakii, yet the specific mechanism remains elusive. Herein, transcriptomics and phenotypic analysis were employed to explore the response of C. sakazakii wild type (WT) and sdiA knockout strain (ΔsdiA) under drying conditions. Following 20 days of drying in powdered infant formula (PIF), WT exhibited 4 log CFU/g higher survival rates compared to ΔsdiA. Transcriptome revealed similar expression patterns between csrA and sdiA, their interaction was confirmed both by protein-protein interaction analysis and yeast two-hybrid assays. Notably, genes associated with flagellar assembly and chemotaxis (flg, fli, che, mot regulon) showed significantly higher expression levels in WT than in ΔsdiA, indicating a reduced capacity for flagellar synthesis in ΔsdiA, which was consistent with cellular morphology observations. Similarly, genes involved in trehalose biosynthesis (ostAB, treYZS) and uptake (thuEFGK) exhibited similar expression patterns to sdiA, with higher levels of trehalose accumulation observed in WT under desiccation conditions compared to ΔsdiA. Furthermore, WT demonstrated enhanced protein and DNA synthesis capabilities under desiccation stress. Higher expression levels of genes related to oxidative phosphorylation were also noted in WT, ensuring efficient cellular ATP synthesis. This study offers valuable insights into how SdiA influences the desiccation tolerance of C. sakazakii, paving the way for targeted strategies to inhibit and control this bacterium.

Dual cross-linked network of the active starch film by incorporating palmitic acid and geraniol: A comprehensive evaluation of the hydrophobic mechanism and antimicrobial activity.

In this study, (3-Aminopropyl) triethoxysilane (APTES) was employed as a bridging agent to enhance the compatibility between the hydrophilic starch/pectin film and the hydrophobic palmitic acid (PA) coating through hydrogen bonding and chemical reactions. To address the insufficient antibacterial activity of starch films, geraniol was also incorporated. The intermolecular interactions among APTES, PA, and starch were confirmed using x-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), and hydrogen nuclear magnetic resonance spectroscopy (1H NMR). Notably, the inclusion of APTES and PA significantly increased the film's hydrophobicity, resulting in a water contact angle (WCA) of 95.12°, a water vapor permeability (WVP) of 2.08 × 10-10 g/(mm·s·Pa), and an oxygen permeability (OP) of 2.61 × 10-9 g·mm·mm-2·s-1. Molecular dynamics (MD) simulations revealed strong non-covalent interactions and exceptional compatibility between starch and PA. Furthermore, the integration of pectin and geraniol improved the mechanical strength and antimicrobial properties of the modified films compared to unmodified starch films. These environmentally friendly and biodegradable hydrophobic starch-based films present a promising option for sustainable packaging materials in food preservation.

Improving water resistance and mechanical properties of starch-based films by incorporating microcrystalline cellulose in a dynamic network structure.

The widespread use of starch-based films is hindered by inadequate tensile strength and high water sensitivity. To address these limitations, a novel starch film with a dynamic network structure was produced via the dehydration-condensation reaction of N, N'-methylene diacrylamide (MBA) and microcrystalline cellulose (MCC). The improvement in mechanical properties was enhanced by the incorporation of MCC, which was achieved through intermolecular hydrogen bonding and chemical crosslinking. To verify the interactions among MCC, MBA, and starch, x-ray photoelectron spectroscopy (XPS), fourier transform infrared spectroscopy (FTIR), and x-ray diffraction (XRD) were conducted. The results established the predicted interactions. The dynamic network structure of the film reduced the water absorption capacity (WAC) of starch and MCC hydroxyl groups, as confirmed by differential scanning calorimeter (DSC) and dynamic mechanical thermal analysis (DMTA). These analyses showed a restriction in the mobility of starch chains, resulting in a higher glass transition temperature (Tg) of 69.26 °C. The modified starch films exhibited excellent potential for packaging applications, demonstrating a higher contact angle (CA) of 89.63°, the lowest WAC of 4.73 g/g, and the lowest water vapor transmission rate (WVTR) of 13.13 g/m2/d, along with improved mechanical properties and identical light transmittance compared to pure starch films.

[Effects of Meteorological Conditions in Summer and Early Autumn on PM2.5 and O3 Pollution in Beijing-Tianjin-Hebei and Surrounding Areas].

PM2.5 pollution remains prominent in autumn, whereas O3 pollution gradually manifests in summer. To understand the dual high characteristics and meteorological effects of PM2.5 and O3 in the summer and early autumn of 2021 in the Beijing-Tianjin-Hebei and surrounding areas, the spatiotemporal distribution characteristics of PM2.5 and O3 concentrations, as well as meteorological conditions, subtropical high index, and weather situation in the Beijing-Tianjin-Hebei and surrounding areas were analyzed. The results showed that PM2.5 concentration and DPO3 （O3 daily maximum 8h mean minus O3 concentration at 06：00） from June to September 2021 decreased compared with those in the same period in 2020 and 2022, and high concentrations were mainly occurring in June. The overall PM2.5 concentration and DPO3 showed a gradual decrease from the middle to the north and south, with synchronous spatiotemporal changes. The hourly value of PM2.5 concentration presented a multimodal distribution, reaching the peak at 07：00-10：00 and 22：00-24：00. O3 concentration showed an opposite trend of change with PM2.5 concentration, reaching their peak from 14：00-16：00. When DPO3 and the concentration of PM2.5 were high, the characteristics of near-surface meteorological elements were characterized by temperatures ranging from 24.0-28.0℃, relative humidity concentrated at 58.4%-76.3%, and wind speeds ranging from 1.5-3 m·s-1. There was a high lag correlation between the subtropical high index and DPO3. When the subtropical high was farther and stronger from the Beijing-Tianjin-Hebei and surrounding areas, DPO3 was higher. The major weather patterns with both high PM2.5 and O3 concentrations in the study area were near surface low-pressure front, high-pressure type, and frontal type. The high altitude was controlled by high-pressure ridges, and the subtropical high ridge line was stable between 21°-28°N.

NIR-Driven Self-Healing Phase-Change Solid Slippery Surface with Stability and Promising Antifouling and Anticorrosion Properties.

Slippery liquid-infused porous surfaces (SLIPSs) have great potential to replace traditional antifouling coatings due to their efficient, green, and broad-spectrum antifouling performance. However, the lubricant dissipation problem of SLIPS severely restricts its further development and application, and the robust SLIPS continues to be extremely challenging. Here, a composite phase-change lubricant layer consisting of paraffin, silicone oil, and MXene is designed to readily construct a stable and NIR-responsive self-healing phase-change solid slippery surface (PCSSS). Collective results showed that PCSSS could rapidly achieve phase-change transformation and complete self-healing under NIR irradiation and keep stable after high-speed water flushing, centrifugation, and ultrasonic treatment. The antifouling performance of PCSSS evaluated by protein, bacteria, and algae antiadhesion tests demonstrated the adhesion inhibition rate was as high as 99.99%. Moreover, the EIS and potentiodynamic polarization experiments indicated that PCSSS had stable and exceptional corrosion resistance (|Z|0.01Hz = 3.87 × 108 Ω·cm2) and could effectively inhibit microbiologically influenced corrosion. The 90 day actual marine test reveals that PCSSS has remarkable antifouling performance. Therefore, PCSSS presents a novel, facile, and effective strategy to construct a slippery surface with the prospect of facilitating its application in marine antifouling and corrosion protection.

Significant association between HIV infection and increased risk of COVID-19 mortality: a meta-analysis based on adjusted effect estimates.

To investigate the relationship between human immunodeficiency virus (HIV) infection and the risk of mortality among coronavirus disease 2019 (COVID-19) patients based on adjusted effect estimate by a quantitative meta-analysis. A random-effects model was used to estimate the pooled effect size (ES) with corresponding 95% confidence interval (CI). I2 statistic, sensitivity analysis, Begg's test, meta-regression and subgroup analyses were also conducted. This meta-analysis presented that HIV infection was associated with a significantly higher risk of COVID-19 mortality based on 40 studies reporting risk factors-adjusted effects with 131,907,981 cases (pooled ES 1.43, 95% CI 1.25-1.63). Subgroup analyses by male proportion and setting yielded consistent results on the significant association between HIV infection and the increased risk of COVID-19 mortality. Allowing for the existence of heterogeneity, further meta-regression and subgroup analyses were conducted to seek the possible source of heterogeneity. None of factors might be possible reasons for heterogeneity in the further analyses. Sensitivity analysis indicated the robustness of this meta-analysis. The Begg's test manifested that there was no publication bias (P = 0.2734). Our findings demonstrated that HIV infection was independently associated with a significantly increased risk of mortality in COVID-19 patients. Further well-designed studies based on prospective study estimates are warranted to confirm our findings.

[Effect of Clean Heating on Carbonaceous Aerosols in PM2.5 During the Heating Period in Baoding].

In order to study the effects of clean heating measures on the concentration and source of carbonaceous aerosols in PM2.5 in Baoding, we collected PM2.5 samples in Baoding during the winter heating periods of 2014 and 2019. The concentrations of OC and EC in the samples were determined by using a DRI Model 2001A thermo-optical carbon analyzer.The results showed that the average values of ρ(OC) and ρ(EC) in the heating period in 2014 were 60.92 µg·m-3 and 18.15 µg·m-3, and the average values of ρ(OC) and ρ(EC) in the heating period in 2019 were 36.63 µg·m-3 and 6.07 µg·m-3. Compared with those in 2014, the concentrations of OC and EC decreased by 39.87% and 66.56%, respectively, in 2019; the decrease in EC was larger than that in OC, and the meteorological conditions in 2019 were more severe than those in 2014, which was not conducive to the spread of pollutants.The correlation analysis and SOC estimation of OC and EC indicated that the correlation R2 of OC and EC in Baoding in 2014 and 2019 were 0.874 and 0.811, respectively, indicating that OC and EC in Baoding had relatively consistent sources. The average values of ρ(SOC) in 2014 and 2019 were 16.59 µg·m-3 and 11.31 µg·m-3, respectively, and the contribution rates to OC were 27.23% and 30.87%, respectively. This showed that in 2019, compared with that in 2014, the primary pollution decreased, but the secondary pollution increased, and the atmospheric oxidation increased.The analysis of the pollution sources of carbonaceous aerosols revealed that in 2014 and 2019 before and after the implementation of clean heating, the carbonaceous aerosols in the atmosphere were mainly from biomass combustion, coal combustion, and vehicle exhaust emissions. However, the contribution from biomass burning and coal burning decreased in 2019 compared to that in 2014. The decrease in OC and EC concentrations was attributed to the control of coal-fired and biomass-fired sources by clean heating. At the same time, the implementation of clean heating measures reduced the contribution of primary emissions to carbonaceous aerosols in PM2.5 in Baoding City.