One new species of Pseudopoda Jäger, 2000 from Shennongjia, Central China (Araneae, Sparassidae).

Background: Pseudopoda Jäger, 2000 is currently the largest genus in the family Sparassidae Bertkau, 1872, comprising 255 species. Of these, 154 species have been recorded in China, representing 60.4% of the global species.In October 2023, a spider survey was conducted in Shennongjia National Nature Reserve, Hubei Province, China. After examination and morphological comparison, one new species of the genus Pseudopoda was identified and is described here. New information: In this paper, a new species of Pseudopoda collected in Hubei Province, China, is proposed and named Pseudopodaguanmenshan sp. nov. A detailed description, diagnosis, photographs and distribution map of the new species are provided.

Accelerating the calculation of electron-phonon coupling strength with machine learning.

The calculation of electron-phonon couplings (EPCs) is essential for understanding various fundamental physical properties, including electrical transport, optical and superconducting behaviors in materials. However, obtaining EPCs through fully first-principles methods is notably challenging, particularly for large systems or when employing advanced functionals. Here we introduce a machine learning framework to accelerate EPC calculations by utilizing atomic orbital-based Hamiltonian matrices and gradients predicted by an equivariant graph neural network. We demonstrate that our method not only yields EPC values in close agreement with first-principles results but also enhances calculation efficiency by several orders of magnitude. Application to GaAs using the Heyd-Scuseria-Ernzerhof functional reveals the necessity of advanced functionals for accurate carrier mobility predictions, while for the large Kagome crystal CsV3Sb5, our framework reproduces the experimentally observed double domes in pressure-induced superconducting phase diagrams. This machine learning framework offers a powerful and efficient tool for the investigation of diverse EPC-related phenomena in complex materials.

Regulating Surface Metal Abundance via Lattice-Matched Coordination for Versatile and Environmentally-Viable Sn-Pb Alloying Perovskite Solar Cells.

Narrow-bandgap Sn-Pb alloying perovskites showcased great potential in constructing multiple-junction perovskite solar cells (PSCs) with efficiencies approaching or exceeding the Shockley-Queisser limit. However, the uncontrollable surface metal abundance (Sn2+ and Pb2+ ions) hinders their efficiency and versatility in different device structures. Additionally, the undesired Pb distribution mainly at the buried interface accelerates the Pb leakage when devices are damaged. In this work, a novel strategy is presented to modulate crystallization kinetics and surface metal abundance of Sn-Pb perovskites using a cobweb-like quadrangular macrocyclic porphyrin material, which features a molecular size compatible with the perovskite lattice and robustly coordinates with Pb2+ ions, thus immobilizing them and increasing surface Pb abundance by 61%. This modulation reduces toxic Pb leakage rates by 24-fold, with only ∼23 ppb Pb in water after severely damaged PSCs are immersed in water for 150 h.This strategy can also enhance chemical homogeneity, reduce trap density, release tensile strain and optimize carrier dynamics of Sn-Pb perovskites and relevant devices. Encouragingly, the power conversion efficiency (PCEs) of 23.28% for single-junction, full-stack devices and 21.34% for hole transport layer-free Sn-Pb PSCs are achieved.Notably, the related monolithic all-perovskite tandem solar cell also achieves a PCE of 27.03% with outstanding photostability.

Rhodium-Catalyzed Regioselective [4 + 2] Cycloaddition of Ynamines and 2-(Cyanomethyl)phenylboronates.

A rhodium-catalyzed [4 + 2] cycloaddition of ynamines and 2-(cyanomethyl)phenylboronates has been developed, leading to efficient and excellent regioselective synthesis of valuable indole-linked aromatic compounds in a concise and flexible approach. Interestingly, this strategy was successful in the construction of C···N axially chiral indoles with high enantiocontrol by the introduction of a new phosphoramidite ligand (Xie-Phos).

Design of a Compact Multicyclic High-Performance Atmospheric Water Harvester for Arid Environments.

Water scarcity remains a grand challenge across the globe. Sorption-based atmospheric water harvesting (SAWH) is an emerging and promising solution for water scarcity, especially in arid and noncoastal regions. Traditional approaches to AWH such as fog harvesting and dewing are often not applicable in an arid environment (<30% relative humidity (RH)), whereas SAWH has demonstrated great potential to provide fresh water under a wide range of climate conditions. Despite advances in materials development, most demonstrated SAWH devices still lack sufficient water production. In this work, we focus on the adsorption bed design to achieve high water production, multicyclic operation, and a compact form factor (high material loading per heat source contact area). The modeling efforts and experimental validation illustrate an optimized design space with a fin-array adsorption bed enabled by high-density waste heat, which promises 5.826 Lwater kgsorbent -1 day-1 at 30% RH within a compact 1 L adsorbent bed and commercial adsorbent materials.

PlantSR: Super-Resolution Improves Object Detection in Plant Images.

Recent advancements in computer vision, especially deep learning models, have shown considerable promise in tasks related to plant image object detection. However, the efficiency of these deep learning models heavily relies on input image quality, with low-resolution images significantly hindering model performance. Therefore, reconstructing high-quality images through specific techniques will help extract features from plant images, thus improving model performance. In this study, we explored the value of super-resolution technology for improving object detection model performance on plant images. Firstly, we built a comprehensive dataset comprising 1030 high-resolution plant images, named the PlantSR dataset. Subsequently, we developed a super-resolution model using the PlantSR dataset and benchmarked it against several state-of-the-art models designed for general image super-resolution tasks. Our proposed model demonstrated superior performance on the PlantSR dataset, indicating its efficacy in enhancing the super-resolution of plant images. Furthermore, we explored the effect of super-resolution on two specific object detection tasks: apple counting and soybean seed counting. By incorporating super-resolution as a pre-processing step, we observed a significant reduction in mean absolute error. Specifically, with the YOLOv7 model employed for apple counting, the mean absolute error decreased from 13.085 to 5.71. Similarly, with the P2PNet-Soy model utilized for soybean seed counting, the mean absolute error decreased from 19.159 to 15.085. These findings underscore the substantial potential of super-resolution technology in improving the performance of object detection models for accurately detecting and counting specific plants from images. The source codes and associated datasets related to this study are available at Github.

Ironing out Persisters? Revisiting the Iron Chelation Strategy to Target Planktonic Bacterial Persisters Harboured in Carbapenem-Resistant Escherichia coli.

Antibiotic resistance is a global health crisis. Notably, carbapenem-resistant Enterobacterales (CRE) pose a significant clinical challenge due to the limited effective treatment options. This problem is exacerbated by persisters that develop upon antibiotic exposure. Bacteria persisters can tolerate high antibiotic doses and can cause recalcitrant infections, potentially developing further antibiotic resistance. Iron is a critical micronutrient for survival. We aimed to evaluate the utility of iron chelators, alone and in combination with antibiotics, in managing persisters. We hypothesized that iron chelators eradicate CRE persisters in vitro, when administered in combination with antibiotics. Our screening revealed three clinical isolates with bacteria persisters that resuscitated upon antibiotic removal. These isolates were treated with both meropenem and an iron chelator (deferoxamine mesylate, deferiprone or dexrazoxane) over 24 h. Against our hypothesis, bacteria persisters survived and resuscitated upon withdrawing both the antibiotic and iron chelator. Pursuing our aim, we next hypothesized that iron chelation is feasible as a post-antibiotic treatment in managing and suppressing persisters' resuscitation. We exposed bacteria persisters to an iron chelator without antibiotics. Flow cytometric assessments revealed that iron chelators are inconsistent in suppressing persister resuscitation. Collectively, these results suggest that the iron chelation strategy may not be useful as an antibiotic adjunct to target planktonic bacteria persisters.

Dimension Prediction and Microstructure Study of Wire Arc Additive Manufactured 316L Stainless Steel Based on Artificial Neural Network and Finite Element Simulation.

The dimensional accuracy and microstructure affect the service performance of parts fabricated by wire arc additive manufacturing (WAAM). Regulating the geometry and microstructure of such parts presents a challenge. The coupling method of an artificial neural network and finite element (FE) is proposed in this research for this purpose. Back-propagating neural networks (BPNN) based on optimization algorithms were established to predict the bead width (BW) and height (BH) of the deposited layers. Then, the bead geometry was modeled based on the predicted dimension, and 3D FE heat transfer simulation was performed to investigate the evolution of temperature and microstructure. The results showed that the errors in BW and BH were less than 6%, and the beetle antenna search BPNN model had the highest prediction accuracy compared to the other models. The simulated melt pool error was less than 5% with the experimental results. The decrease in the ratio of the temperature gradient and solidification rate induced the transition of solidified grains from cellular crystals to columnar dendrites and then to equiaxed dendrites. Accelerating the cooling rate increased the primary dendrite arm spacing and δ-ferrite content. These results indicate that the coupling model provides a pathway for regulating the dimensions and microstructures of manufactured parts.

Tracking the scaling of urban open spaces in China from 1990 to 2020.

Urban open spaces (UOS) are crucial for urban life, offering benefits across individual and societal levels. However, the understanding of the systematic dynamic of UOS scaling with city size and its potential non-linear performance remains a limited clarity area. This study bridges this gap by integrating urban scaling laws with remote sensing data from 1990 to 2020, creating a framework to analyze UOS trends in China. Our findings reveal that UOS growth is sub-linear scaling with city size, exhibiting economies of scale with scaling exponents between 0.55 and 0.65 and suggesting potential shortages. The distribution structure of UOS across cities is becoming increasingly balanced, as indicated by the rising Zipf's slope from 0.66 to 0.88. Southeastern coastal cities outperform, highlighting spatial variations and path dependency in UOS development. Additionally, using metrics of Scale-adjusted metropolitan indicator (SAMI) and the ratio of open space consumption to population growth rates (OCRPGR), we observe a trend towards more coordinated development between UOS and population, with a declining proportion of uncoordinated cities. Our long-term, large sample coverage study of UOS in China may offer positive significance for urban ecological planning and management in similar rapidly urbanizing countries, contributing to critical insights for quantifying and monitoring urban sustainable development.

A Rare Case of Isolated Abducens Nerve Palsy With Contemporaneous Thalamic Infarct.

We report a case of isolated left abducens nerve palsy accompanying a right thalamic infarct. The patient, a 43-year-old Malay male with newly diagnosed hypertension, diabetes mellitus, and dyslipidemia, initially reported binocular diplopia on left lateral gaze persisting for five weeks. Subsequently, he experienced acute left-sided body weakness and slurred speech for over one day. Clinical examination revealed restricted left eye lateral gaze (-3) with no relative afferent pupillary defect. Additionally, decreased power (4/5) was noted in the left upper and lower limbs. Brain magnetic resonance imaging (MRI) revealed restricted diffusion in the right thalamus extending to the right posterior internal capsule, left anterior cingulate gyrus, and left caudate nucleus. The patient was initiated on antiplatelet, antihypertensive, and oral hypoglycemic agents, resulting in symptom improvement. This rare neuroophthalmological finding has not been reported previously.

A Triggering Event of Central Retinal Artery Occlusion With Concurrent Ischemic Stroke.

We report a case of central retinal artery occlusion with concurrent ischemic stroke in a young patient. A 34-year-old Malay gentleman, an ex-smoker with underlying dyslipidemia, however, not on medication or follow-up, presented with acute, generalized, and painless right eye blurring of vision for one day. He also complained of on-and-off headaches for the past three months prior to the presentation. Visual acuity assessment demonstrated hand movement in the right eye, whereas in the left eye, it was 6/6, along with a right eye relative afferent pupillary defect. His right eye showed reduced optic nerve function and unremarkable anterior segment, with fundus examination revealing the presence of a cherry red spot, pale macula, boxcarring pattern over superior arcuate, and vascularized retina over inferior optic disc with blurred optic disc margin. The left eye examination was unremarkable. All cranial nerves were intact, except for the optic nerve. He was admitted to the ward. While in the ward, he developed a sudden onset of left-sided upper and lower limb weakness and numbness and was diagnosed with acute ischemic stroke. Blood investigations showed raised low-density lipoprotein cholesterol of 3.51 mmol/L, anti-nuclear antibody (ANA) positive, with electrocardiogram (ECG) sinus rhythm, and no atrial fibrillation. The echocardiogram was normal, and computed tomography angiography of the brain showed non-opacification at the origin and proximal part of the right ophthalmic artery, suspicious of thrombosis with distal reconstitution, with no evidence of thrombosis in the rest of neck and intracranial arteries. The patient was started on aspirin 150 mg once a day and atorvastatin 20 mg at night; subsequently, his vision improved slightly.

Flavor Characteristics, Antioxidant Activity and In Vitro Digestion Properties of Bread with Large-Leaf Yellow Tea Powder.

Foods containing tea could be widely utilized due to the addition of good tea ingredients, especially large-leaf yellow tea, which is rich with a good flavor. Applying this change to bread containing tea would improve its product quality. In this research, large-leaf yellow tea bread (LYB), possessing a special flavor, was developed using ultrafine large-leaf yellow tea powder and flour as the main raw materials. The amount of ultrafine large-leaf yellow tea powder added to bread was optimized using texture, sensation, and specific volume as comprehensive evaluation indicators. At the optimal dosage, the free amino acids, volatile flavor compounds, antioxidant activity, and in vitro starch digestibility of LYB were measured. Response surface optimization experimental results showed that the comprehensive score of bread was highest when the added amount of ultrafine large-leaf yellow tea powder was 3%. In particular, compared to blank bread (BB), adding ultrafine large-leaf yellow tea powder into bread could effectively increase its amino acid composition, enhance its volatile flavor compounds, improve the antioxidant capacity, and reduce the digestibility of starch.

Genetic and molecular characterization of metabolic pathway-based clusters in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive types of squamous cell carcinoma and represents a significant proportion of esophageal cancer. Metabolic reprogramming plays a key role in the occurrence and development of ESCC. Unsupervised clustering analysis was employed to stratify ESCC samples into three clusters: MPC1-lipid type, MPC2-amino acid type, and MPC3-energy type, based on the enrichment scores of metabolic pathways extracted from the Reactome database. The MPC3 cluster exhibited characteristics of energy metabolism, with heightened glycolysis, cofactors, and nucleotide metabolism, showing a trend toward increased aggressiveness and poorer survival rates. On the other hand, MPC1 and MPC2 primarily involved lipid and amino acid metabolism, respectively. In addition, liquid chromatography‒mass spectrometry-based metabolite profiles and potential therapeutic agents were explored and compared among ESCC cell lines with different MPCs. MPC3 amplified energy metabolism markers, especially carnitines. In contrast, MPC1 and MPC2 predominantly had elevated levels of lipids (primarily triacylglycerol) and amino acids, respectively. Furthermore, MPC3 demonstrated a suboptimal clinical response to PD-L1 immunotherapy but showed increased sensitivity to the doramapimod chemotherapy regimen, as evident from drug sensitivity evaluations. These insights pave the way for a more personalized therapeutic approach, potentially enhancing treatment precision for ESCC patients.

Drug target prediction through deep learning functional representation of gene signatures.

Many machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of OMICS datasets, including target deconvolution and mechanism of action studies, we develop an approach that represents gene signatures projected onto their biological functions, instead of their identities, similar to how the word2vec technique works in natural language processing. We develop the Functional Representation of Gene Signatures (FRoGS) approach by training a deep learning model and demonstrate that its application to the Broad Institute's L1000 datasets results in more effective compound-target predictions than models based on gene identities alone. By integrating additional pharmacological activity data sources, FRoGS significantly increases the number of high-quality compound-target predictions relative to existing approaches, many of which are supported by in silico and/or experimental evidence. These results underscore the general utility of FRoGS in machine learning-based bioinformatics applications. Prediction networks pre-equipped with the knowledge of gene functions may help uncover new relationships among gene signatures acquired by large-scale OMICs studies on compounds, cell types, disease models, and patient cohorts.

[Effects of Foliar Application of Silicon Fertilizers on Phyllosphere Bacterial Community and Functional Genes of Paddy Irrigated with Reclaimed Water].

Agricultural utilization of reclaimed water is considered to be an effective way to solve water shortage and reduce water environmental pollution. Silicon fertilizer can improve crop yield and quality and enhance crop resistance. The effect of foliar spray with silicon fertilizer on phyllosphere microbial communities remains lacking. In this study, a pot experiment was conducted to explore the effects of different types of silicon fertilizer on the composition and diversity of a phyllosphere bacterial community and the abundances of related functional genes in rice irrigated with reclaimed water. The results showed that Firmicutes, Proteobacteria, Actinobacteriota, Bacteroidota, and Verrucomicrobiota dominated the phyllosphere bacteria of rice. The relative abundance of Bacillus was higher than that of other treatments in RIS3. Reclaimed water irrigation significantly increased the relative abundances of the potential pathogens Pantoea and Enterobacter. The unclassified bacteria were also an important part of the bacterial community in the rice phyllosphere. Bacillus, Exiguobacterium, Aeromonas, and Citrobacter were significantly enriched by silicon fertilizer treatments. Functional prediction analysis showed that indicator species were mainly involved in metabolism and degradation functions, and the predicted functional groups of phyllosphere bacteria were attributed to chemoheterotrophy, aerobic chemoheterotrophy, nitrate reduction, and fermentation. Quantitative PCR results showed that AOA, AOB, and nifH genes were at low abundance levels in all treatments, and nirK genes was not significantly different among treatments. These results contribute to the in-depth understanding of the effects of foliar spray silicon fertilizer on the bacterial community structure and diversity of rice phyllosphere and provide a theoretical basis for the application of silicon fertilizer in reclaimed water irrigation agriculture.

Extreme Water Uptake of Hygroscopic Hydrogels through Maximized Swelling-Induced Salt Loading.

Hygroscopic hydrogels are emerging as scalable and low-cost sorbents for atmospheric water harvesting, dehumidification, passive cooling, and thermal energy storage. However, devices using these materials still exhibit insufficient performance, partly due to the limited water vapor uptake of the hydrogels. Here, the swelling dynamics of hydrogels in aqueous lithiumchloride solutions, the implications on hydrogel salt loading, and the resulting vapor uptake of the synthesized hydrogel-salt composites are characterized. By tuning the salt concentration of the swelling solutions and the cross-linking properties of the gels, hygroscopic hydrogels with extremely high salt loadings are synthesized, which enable unprecedented water uptakes of 1.79 and 3.86 gg-1 at relative humidity (RH) of 30% and 70%, respectively. At 30% RH, this exceeds previously reported water uptakes of metal-organic frameworks by over 100% and of hydrogels by 15%, bringing the uptake within 93% of the fundamental limit of hygroscopic salts while avoiding leakage problems common in salt solutions. By modeling the salt-vapor equilibria, the maximum leakage-free RH is elucidated as a function of hydrogel uptake and swelling ratio. These insights guide the design of hydrogels with exceptional hygroscopicity that enable sorption-based devices to tackle water scarcity and the global energy crisis.

Simple and field-adapted species identification of biological specimens combining multiplex multienzyme isothermal rapid amplification, lateral flow dipsticks, and universal primers for initial rapid screening without standard PCR laboratory.

Species identification of biological specimens can provide the valuable clues and accelerate the speed of prosecution material processing for forensic investigation, especially when the case scene is inaccessible and the physical evidence is cumbersome. Thus, establishing a rapid, simple, and field-adapted species identification method is crucial for forensic scientists, particularly as first-line technology at the crime scene for initial rapid screening. In this study, we established a new field-adapted species identification method by combining multiplex multienzyme isothermal rapid amplification (MIRA), lateral flow dipstick (LFD) system, and universal primers. Universal primers targeting COX I and COX II genes were used in multiplex MIRA-LFD system for seven species identification, and a dedicated MIRA-LFD system primer targeting CYT B gene was used to detect the human material. DNA extraction was performed by collecting DNA directly from the centrifuged supernatant. Our study found that the entire amplification process took only 15 min at 37 °C and the results of LFDs could be visually observed after 10 min. The detection sensitivity of human material could reach 10 pg, which is equivalent to the detection of single cell. Different common animal samples mixed at the ratio of 1 ng:1 ng, 10 ng:1 ng, and 1 ng:10 ng could be detected successfully. Furthermore, the damaged and degraded samples could also be detected. Therefore, the convenient, feasible, and rapid approach for species identification is suitable for popularization as first-line technology at the crime scene for initial rapid screening and provides a great convenient for forensic application.

Synchronous Elimination of Excess Photoinstable PbI2 and Interfacial Band Mismatch for Efficient and Stable Perovskite Solar Cells.

Eliminating the undesired photoinstability of excess lead iodide (PbI2 ) in the perovskite film and reducing the energy mismatch between the perovskite layer and heterogeneous interfaces are urgent issues to be addressed in the preparation of perovskite solar cells (PVSCs) by two-step sequential deposition method. Here, the 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIMBF4 ) is employed to convert superfluous PbI2 to more robust 1D EMIMPbI3 which can withstand lattice strain, while forming an interfacial dipole layer at the SnO2 /perovskite interface to reconfigure the interfacial energy band structure and accelerate the charge extraction. Consequently, the unencapsulated PVSCs device attains a champion efficiency of 24.28 % with one of the highest open-circuit voltage (1.19 V). Moreover, the unencapsulated devices showcase significantly improved thermal stability, enhanced environmental stability and remarkable operational stability accompanied by 85 % of primitive efficiency retained over 1500 h at maximum power point tracking under continuous illumination.

Lactate cross-feeding between Bifidobacterium species and Megasphaera indica contributes to butyrate formation in the human colonic environment.

Butyrate, a physiologically active molecule, can be synthesized through metabolic interactions among colonic microorganisms. Previously, in a fermenting trial of human fecal microbiota, we observed that the butyrogenic effect positively correlated with the increasing Bifidobacterium population and an unidentified Megasphaera species. Therefore, we hypothesized that a cross-feeding phenomenon exists between Bifidobacterium and Megasphaera, where Megasphaera is the butyrate producer, and its growth relies on the metabolites generated by Bifidobacterium. To validate this hypothesis, three bacterial species (B. longum, B. pseudocatenulatum, and M. indica) were isolated from fecal cultures fermenting hydrolyzed xylan; pairwise cocultures were conducted between the Bifidobacterium and M. indica isolates; the microbial interactions were determined based on bacterial genome information, cell growth, substrate consumption, metabolite quantification, and metatranscriptomics. The results indicated that two Bifidobacterium isolates contained distinct gene clusters for xylan utilization and expressed varying substrate preferences. In contrast, M. indica alone scarcely grew on the xylose-based substrates. The growth of M. indica was significantly elevated by coculturing it with bifidobacteria, while the two Bifidobacterium species responded differently in the kinetics of cell growth and substrate consumption. Coculturing led to the depletion of lactate and increased the formation of butyrate. An RNA-seq analysis further revealed the upregulation of M. indica genes involved in the lactate utilization and butyrate formation pathways. We concluded that lactate generated by Bifidobacterium through catabolizing xylose fueled the growth of M. indica and triggered the synthesis of butyrate. Our findings demonstrated a novel cross-feeding mechanism to generate butyrate in the human colon.IMPORTANCEButyrate is an important short-chain fatty acid that is produced in the human colon through microbial fermentation. Although many butyrate-producing bacteria exhibit a limited capacity to degrade nondigestible food materials, butyrate can be formed through cross-feeding microbial metabolites, such as acetate or lactate. Previously, the literature has explicated the butyrate-forming links between Bifidobacterium and Faecalibacterium prausnitzii and between Bifidobacterium and Eubacterium rectale. In this study, we provided an alternative butyrate synthetic pathway through the interaction between Bifidobacterium and Megasphaera indica. M. indica is a species named in 2014 and is indigenous to the human intestinal tract. Scientific studies explaining the function of M. indica in the human colon are still limited. Our results show that M. indica proliferated based on the lactate generated by bifidobacteria and produced butyrate as its end metabolic product. The pathways identified here may contribute to understanding butyrate formation in the gut microbiota.

Intravenous immunoglobulin for treatment of hospitalized COVID-19 patients: an evidence mapping and meta-analysis.

BACKGROUND: The clinical efficacy and safety of intravenous immunoglobulin (IVIg) treatment for COVID-19 remain controversial. This study aimed to map the current status and gaps of available evidence, and conduct a meta-analysis to further investigate the benefit of IVIg in COVID-19 patients. METHODS: Electronic databases were searched for systematic reviews/meta-analyses (SR/MAs), primary studies with control groups, reporting on the use of IVIg in patients with COVID-19. A random-effects meta-analysis with subgroup analyses regarding study design and patient disease severity was performed. Our outcomes of interest determined by the evidence mapping, were mortality, length of hospitalization (days), length of intensive care unit (ICU) stay (days), number of patients requiring mechanical ventilation, and adverse events. RESULTS: We included 34 studies (12 SR/MAs, 8 prospective and 14 retrospective studies). A total of 5571 hospitalized patients were involved in 22 primary studies. Random-effects meta-analyses of very low to moderate evidence showed that there was little or no difference between IVIg and standard care or placebo in reducing mortality (relative risk [RR] 0.91; 95% CI 0.78-1.06; risk difference [RD] 3.3% fewer), length of hospital (mean difference [MD] 0.37; 95% CI - 2.56, 3.31) and ICU (MD 0.36; 95% CI - 0.81, 1.53) stays, mechanical ventilation use (RR 0.92; 95% CI 0.68-1.24; RD 2.8% fewer), and adverse events (RR 0.98; 95% CI 0.84-1.14; RD 0.5% fewer) of patients with COVID-19. Sensitivity analysis using a fixed-effects model indicated that IVIg may reduce mortality (RR 0.76; 95% CI 0.60-0.97), and increase length of hospital stay (MD 0.68; 95% CI 0.09-1.28). CONCLUSION: Very low to moderate certainty of evidence indicated IVIg may not improve the clinical outcomes of hospitalized patients with COVID-19. Given the discrepancy between the random- and fixed-effects model results, further large-scale and well-designed RCTs are warranted.