Scbean: a python library for single-cell multi-omics data analysis.

SUMMARY: Single-cell multi-omics technologies provide a unique platform for characterizing cell states and reconstructing developmental process by simultaneously quantifying and integrating molecular signatures across various modalities, including genome, transcriptome, epigenome, and other omics layers. However, there is still an urgent unmet need for novel computational tools in this nascent field, which are critical for both effective and efficient interrogation of functionality across different omics modalities. Scbean represents a user-friendly Python library, designed to seamlessly incorporate a diverse array of models for the examination of single-cell data, encompassing both paired and unpaired multi-omics data. The library offers uniform and straightforward interfaces for tasks, such as dimensionality reduction, batch effect elimination, cell label transfer from well-annotated scRNA-seq data to scATAC-seq data, and the identification of spatially variable genes. Moreover, Scbean's models are engineered to harness the computational power of GPU acceleration through Tensorflow, rendering them capable of effortlessly handling datasets comprising millions of cells. AVAILABILITY AND IMPLEMENTATION: Scbean is released on the Python Package Index (PyPI) (https://pypi.org/project/scbean/) and GitHub (https://github.com/jhu99/scbean) under the MIT license. The documentation and example code can be found at https://scbean.readthedocs.io/en/latest/.

Therapeutic effect and mechanism of action of pterostilbene nano drugs in dry eye models.

Dry eye disease is a multifactorial dysfunction of the tear film and ocular surface, with etiology involving inflammation and oxidative stress on the ocular surface. Pterostilbene (PS) is a secondary metabolite extracted from plants, which possesses remarkable anti-inflammatory and antioxidant effects. However, its application is limited by light instability and very poor water solubility. We modified fat-soluble PS into a biparental pterostilbene-glutaric anhydride-arginine-glycine-aspartic acid (PS-GA-RGD) nanomedicine by prodrug ligation of functional peptides. The aim of this study was to explore the protective effect and potential mechanism of PS-GA-RGD on dry eye disease in vitro and in vivo. We demonstrated good long-term biocompatibility of PS-GA-RGD through rabbit eye stimulation test. Lipopolysaccharide (LPS) was used to induce murine macrophages RAW 264.7 to establish an inflammation and oxidative stress model. In this model, PS-GA-RGD effectively reduced the production of ROS and 8-OHdG, enhancing the expression of antioxidant factor Nrf2 and antioxidant enzyme heme oxygenase-1. In addition, the expression of NF-κB inflammatory pathway significantly increased in LPS-induced RAW 264.7 cells, while PS-GA-RGD could significantly reduce this pathway. Hypertonic saline was utilized to establish a hypertonic model of human corneal epithelial cells. PS-GA-RGD was found to significantly reduce the production of ROS and NLRP3 inflammasomes in this model, exhibiting superior efficacy compared to PS. Experimental dry eye animal models were co-induced with subcutaneous injection of scopolamine and an intelligently controlled environmental system. We demonstrated that PS-GA-RGD nano drugs can prevent and reduce corneal epithelial cell defects and apoptosis, protect conjunctival goblet cells, and have an excellent anti-inflammatory effect. Finally, we demonstrated that RGD sequence in PS-GA-RGD can enhance cellular uptake, corneal retention, and penetration, thereby increasing their bioavailability and efficacy by a cell uptake assay and rabbit corneal drug retention experiment. Overall, this study highlights the potential of PS-GA-RGD nanomedicines in the treatment of dry eyes.

Deciphering the impact of aging on splenic endothelial cell heterogeneity and immunosenescence through single-cell RNA sequencing analysis.

BACKGROUND: Aging is associated with significant structural and functional changes in the spleen, leading to immunosenescence, yet the detailed effects on splenic vascular endothelial cells (ECs) and their immunomodulatory roles are not fully understood. In this study, a single-cell RNA (scRNA) atlas of EC transcriptomes from young and aged mouse spleens was constructed to reveal age-related molecular changes, including increased inflammation and reduced vascular development and also the potential interaction between splenic endothelial cells and immune cells. RESULTS: Ten clusters of splenic endothelial cells were identified. DEGs analysis across different EC clusters revealed the molecular changes with aging, showing the increase in the overall inflammatory microenvironment and the loss in vascular development function of aged ECs. Notably, four EC clusters with immunological functions were identified, suggesting an Endothelial-to-Immune-like Cell Transition (EndICLT) potentially driven by aging. Pseudotime analysis of the Immunology4 cluster further indicated a possible aging-induced transitional state, potentially initiated by Ctss gene activation. Finally, the effects of aging on cell signaling communication between different EC clusters and immune cells were analyzed. CONCLUSIONS: This comprehensive atlas elucidates the complex interplay between ECs and immune cells in the aging spleen, offering new insights into endothelial heterogeneity, reprogramming, and the mechanisms of immunosenescence.

Experimental Study of Ultra-Pulsed CO 2 Fractional Laser Combined With Recombinant Human Epidermal Growth Factor Gel in the Treatment of Eyelid Keloid.

OBJECTIVE: Keloid (KD) and hypertrophic scars are prevalent and result from excessive growth of dermal tissue after skin damage. This review focused on the clinical application of the ultra-pulsed CO 2 fractional laser combined with recombinant human epidermal growth factor (rHEGF) gel in patients with eyelid KD. METHODS: Patients (N = 98) with KD who underwent surgery were randomly divided into a study group (ultra-pulsed CO 2 fractional laser combined with rHEGF gel therapy, N = 49) and a control group (ultra-pulsed CO 2 fractional laser therapy, N = 49). Besides, 5 cases dropped out of the study, including 2 cases in the study group and 3 cases in the control group. Finally, 47 cases of the study group and 46 cases of the study group were included in the analysis. The clinical baseline data such as sex, age, body mass index, scar area, etiology, Vancouver Scar Scale score, Patient and Observer Scar Assessment Scale score, four-item itch questionnaire score, serum interleukin-6 (IL-6), IL-10, and tumor necrosis factor-α level expression were recorded in the study group (N = 47) and the control group (N = 46). RESULTS: There was no significant difference in gender, age, body mass index, scar area, etiology, Vancouver Scar Scale score, Patient and Observer Scar Assessment Scale score, 4-item itch questionnaire score, IL-6, IL-10, and tumor necrosis factor-α levels between the patients treated with ultra-pulse CO 2 fractional laser + rHEGF gel and those only treated with ultra-pulse CO 2 fractional laser ( p > 0.05). Vancouver Scar Scale scores, Patient and Observer Scar Assessment Scale scores, and four-item itch questionnaire scores of patients with eyelid KD decreased to a greater extent than those treated with ultra-pulsed CO 2 fractional laser combined with rHEGF gel ( p <0.01). Compared with ultra-pulsed CO 2 fractional laser treatment, ultra-pulsed CO 2 fractional laser combined with rHEGF gel was more efficacious in treating patients with eyelid KD, with a lower incidence of adverse effects and a 1-year recurrence rate. CONCLUSIONS: Ultra-pulsed CO 2 fractional laser combined with rHEGF gel can significantly improve the scar status and scar itching in patients with eyelid KD, with an obvious therapeutic effect, a low incidence of adverse effects, a 1-year recurrence rate, and high safety, which is worthy of popularization and application.

SSCI: Self-Supervised Deep Learning Improves Network Structure for Cancer Driver Gene Identification.

The pathogenesis of cancer is complex, involving abnormalities in some genes in organisms. Accurately identifying cancer genes is crucial for the early detection of cancer and personalized treatment, among other applications. Recent studies have used graph deep learning methods to identify cancer driver genes based on biological networks. However, incompleteness and the noise of the networks will weaken the performance of models. To address this, we propose a cancer driver gene identification method based on self-supervision for graph convolutional networks, which can efficiently enhance the structure of the network and further improve predictive accuracy. The reliability of SSCI is verified by the area under the receiver operating characteristic curves (AUROC), the area under the precision-recall curves (AUPRC), and the F1 score, with respective values of 0.966, 0.964, and 0.913. The results show that our method can identify cancer driver genes with strong discriminative power and biological interpretability.

Pathway Activation Analysis for Pan-Cancer Personalized Characterization Based on Riemannian Manifold.

The pathogenesis of carcinoma is believed to come from the combined effect of polygenic variation, and the initiation and progression of malignant tumors are closely related to the dysregulation of biological pathways. Quantifying the alteration in pathway activation and identifying coordinated patterns of pathway dysfunction are the imperative part of understanding the malignancy process and distinguishing different tumor stages or clinical outcomes of individual patients. In this study, we have conducted in silico pathway activation analysis using Riemannian manifold (RiePath) toward pan-cancer personalized characterization, which is the first attempt to apply the Riemannian manifold theory to measure the extent of pathway dysregulation in individual patient on the tangent space of the Riemannian manifold. RiePath effectively integrates pathway and gene expression information, not only generating a relatively low-dimensional and biologically relevant representation, but also identifying a robust panel of biologically meaningful pathway signatures as biomarkers. The pan-cancer analysis across 16 cancer types reveals the capability of RiePath to evaluate pathway activation accurately and identify clinical outcome-related pathways. We believe that RiePath has the potential to provide new prospects in understanding the molecular mechanisms of complex diseases and may find broader applications in predicting biomarkers for other intricate diseases.

Total Synthesis of Berkeleyone A and Preaustinoid A through Epoxypolyene Cyclization.

A bioinspired Lewis acid-catalyzed epoxypolyene cyclization was developed to construct the tetracyclic framework containing a bicyclo[3.3.1]nonane core and seven chiral centers. The usage of this approach for assembling these natural products of 6/6/6/6 tetracyclic skeleton with bicyclo[3.3.1]nonane core is demonstrated by the total synthesis of highly oxidized berkeleyone A and preaustinoid A.

NIDM: network impulsive dynamics on multiplex biological network for disease-gene prediction.

The prediction of genes related to diseases is important to the study of the diseases due to high cost and time consumption of biological experiments. Network propagation is a popular strategy for disease-gene prediction. However, existing methods focus on the stable solution of dynamics while ignoring the useful information hidden in the dynamical process, and it is still a challenge to make use of multiple types of physical/functional relationships between proteins/genes to effectively predict disease-related genes. Therefore, we proposed a framework of network impulsive dynamics on multiplex biological network (NIDM) to predict disease-related genes, along with four variants of NIDM models and four kinds of impulsive dynamical signatures (IDSs). NIDM is to identify disease-related genes by mining the dynamical responses of nodes to impulsive signals being exerted at specific nodes. By a series of experimental evaluations in various types of biological networks, we confirmed the advantage of multiplex network and the important roles of functional associations in disease-gene prediction, demonstrated superior performance of NIDM compared with four types of network-based algorithms and then gave the effective recommendations of NIDM models and IDS signatures. To facilitate the prioritization and analysis of (candidate) genes associated to specific diseases, we developed a user-friendly web server, which provides three kinds of filtering patterns for genes, network visualization, enrichment analysis and a wealth of external links (http://bioinformatics.csu.edu.cn/DGP/NID.jsp). NIDM is a protocol for disease-gene prediction integrating different types of biological networks, which may become a very useful computational tool for the study of disease-related genes.

SEPA: signaling entropy-based algorithm to evaluate personalized pathway activation for survival analysis on pan-cancer data.

MOTIVATION: Biomarkers with prognostic ability and biological interpretability can be used to support decision-making in the survival analysis. Genes usually form functional modules to play synergistic roles, such as pathways. Predicting significant features from the functional level can effectively reduce the adverse effects of heterogeneity and obtain more reproducible and interpretable biomarkers. Personalized pathway activation inference can quantify the dysregulation of essential pathways involved in the initiation and progression of cancers, and can contribute to the development of personalized medical treatments. RESULTS: In this study, we propose a novel method to evaluate personalized pathway activation based on signaling entropy for survival analysis (SEPA), which is a new attempt to introduce the information-theoretic entropy in generating pathway representation for each patient. SEPA effectively integrates pathway-level information into gene expression data, converting the high-dimensional gene expression data into the low-dimensional biological pathway activation scores. SEPA shows its classification power on the prognostic pan-cancer genomic data, and the potential pathway markers identified based on SEPA have statistical significance in the discrimination of high- and low-risk cohorts and are likely to be associated with the initiation and progress of cancers. The results show that SEPA scores can be used as an indicator to precisely distinguish cancer patients with different clinical outcomes, and identify important pathway features with strong discriminative power and biological interpretability. AVAILABILITY AND IMPLEMENTATION: The MATLAB-package for SEPA is freely available from https://github.com/xingyili/SEPA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Polarization-multiplexed metasurface enabled tri-functional imaging.

Diffraction-limited focusing imaging, edge-enhanced imaging, and long depth of focus imaging offer crucial technical capabilities for applications such as biological microscopy and surface topography detection. To conveniently and quickly realize the microscopy imaging of different functions, the multifunctional integrated system of microscopy imaging has become an increasingly important research direction. However, conventional microscopes necessitate bulky optical components to switch between these functionalities, suffering from the system's complexity and unstability. Hence, solving the problem of integrating multiple functions within an optical system is a pressing need. In this work, we present an approach using a polarization-multiplexed tri-functional metasurface, capable of realizing the aforementioned imaging functions simply by changing the polarization state of the input and output light, enhancing the system structure's compactness and flexibility. This work offers a new avenue for multifunctional imaging, with potential applications in biomedicine and microscopy imaging.

Lutein targeting orbital fibroblasts attenuates fibrotic and inflammatory effects in thyroid-associated ophthalmopathy.

Lutein (LU) is a carotenoid that has recently been implicated in multiple roles in fibrosis, inflammation, and oxidative stress. Thyroid-associated ophthalmopathy (TAO) is particularly relevant to these pathological changes. We thus aim to probe the potential therapeutic effects of TAO in an in vitro model. We used LU pre-treating OFs derived from patients with TAO or not, then treated with TGF-ß1(or IL-1ß)to induce fibrosis (or inflammation). We analyzed the different expressions of related genes and proteins, and the molecular mechanism pathway on TAO OFs was screened by RNA sequencing, which is identified in vitro. We found that LU attenuates fibrotic and inflammatory effects in TAO. LU inhibited ACTA2, COL1A1, FN1, and CTGF mRNA expression and suppressed α-SMA, and FN1 protein expression induced by TGF-ß1. Besides, LU suppressed OFs migration. Besides, it is shown that LU suppressed inflammation-related genes, such as IL-6, IL-8, CXCL1, and MCP-1. Moreover, LU inhibited oxidative stress induced by IL-1ß, which is analyzed by DHE fluorescent probe staining. RNA sequencing suggested ERK/AP-1 pathway may be the molecular mechanism of LU protective effect on TAO, which is identified by RT-qPCR and western-blot. In summary, this study provides the first evidence that LU significantly attenuates the pathogenic manifestations of TAO by inhibiting the expression of fibrotic and inflammation-related genes and ROS produced by OFs. These data suggested that LU may be a potential medicine for TAO.

Nano Self-Assemblies of Caffeic Acid-Fibronectin Mimic a Peptide Conjugate for the Treatment of Corneal Epithelial Injury.

Rapid corneal re-epithelialization is important for corneal wound healing. Corneal epithelial cell motility and oxidative stress are important targets for therapeutic intervention. In this study, we covalently conjugated the antioxidant caffeic acid (CA) with a bioactive peptide sequence (PHSRN) to generate a CA-PHSRN amphiphile, which was formulated into nanoparticular eye drops with an average size of 43.21 ± 16 nm. CA-PHSRN caused minimal cytotoxicity against human corneal epithelial cells (HCECs) and RAW264.7 cells, exhibited an excellent free radical scavenging ability, and remarkably attenuated reactive oxygen species (ROS) levels in H2O2-stimulated HCECs. The antioxidant and anti-inflammatory activities of CA-PHSRN were assessed in lipopolysaccharide (LPS)-stimulated RAW264.7 cells. The results show that CA-PHSRN treatment effectively prevented LPS-induced DNA damage and significantly reduced the levels of LPS-induced pro-inflammatory cytochemokines (i.e., iNOS, NO, TNF-α, IL-6, and COX-2) in a dose-dependent manner. Moreover, using a rabbit corneal epithelial ex vivo migration assay, we demonstrated that the proposed CA-PHSRN accelerated corneal epithelial cell migration and exhibited high ocular tolerance and ocular bioavailability after topical instillation. Taken together, the proposed CA-PHSRN nanoparticular eye drops are a promising therapeutic formulation for the treatment of corneal epithelial injury.

AKAP12 inhibits esophageal squamous carcinoma cell proliferation, migration, and cell cycle via the PI3K/AKT signaling pathway.

Esophageal squamous cell carcinoma (ESCC) consistently ranks as one of the most challenging variants of squamous cell carcinomas, primarily due to the lack of effective early detection strategies. We herein aimed to elucidate the underlying mechanisms and biological role associated with A-kinase anchoring protein 12 (AKAP12) in the context of ESCC. Bioinformatic analysis had revealed significantly lower expression level of AKAP12 in ESCC tissue samples than in their non-cancerous counterparts. To gain deeper insights into the potential role of AKAP12 in the progression of ESCC, we conducted a single-gene set enrichment analysis of AKAP12 on ESCC datasets. Our findings suggested that AKAP12 exhibits functions inhibiting cell cycle progression, tumor proliferation, and epithelial-mesenchymal transition. To further validate our findings, we subjected ESCC cell lines to AKAP12 overexpression using CRISPR/Cas9-SAM. In vitro analyses demonstrated that increased expression of AKAP12 significantly reduced cell proliferation, migration, and cell cycle progression. Simultaneously, genes associated with this biological role undergo corresponding regulatory shifts. These observations provided valuable insights into the biological role played by AKAP12 in ESCC progression. In summary, AKAP12 shows promise as a new potential biomarker for early ESCC diagnosis, offering potential advantages for subsequent therapeutic intervention and disease management.

NetAUC: A network-based multi-biomarker identification method by AUC optimization.

Complex diseases are caused by a variety of factors, and their diagnosis, treatment and prognosis are usually difficult. Proteins play an indispensable role in living organisms and perform specific biological functions by interacting with other proteins or biomolecules, their dysfunction may lead to diseases, it is a natural way to mine disease-related biomarkers from protein-protein interaction network. AUC, the area under the receiver operating characteristics (ROC) curve, is regarded as a gold standard to evaluate the effectiveness of a binary classifier, which measures the classification ability of an algorithm under arbitrary distribution or any misclassification cost. In this study, we have proposed a network-based multi-biomarker identification method by AUC optimization (NetAUC), which integrates gene expression and the network information to identify biomarkers for the complex disease analysis. The main purpose is to optimize two objectives simultaneously: maximizing AUC and minimizing the number of selected features. We have applied NetAUC to two types of disease analysis: 1) prognosis of breast cancer, 2) classification of similar diseases. The results show that NetAUC can identify a small panel of disease-related biomarkers which have the powerful classification ability and the functional interpretability.

Efficacy and safety of super pulse CO2 laser-assisted punctoplasty with canalicular curettage in primary canaliculitis.

The objective of this study was to evaluate the efficacy and safety of super pulse CO2 laser-assisted punctoplasty with canalicular curettage in primary canaliculitis. In this retrospective serial case study, the clinical data of 26 patients who underwent super pulse CO2 laser-assisted punctoplasty for the treatment of canaliculitis were collected from January 2020 to May 2022. The clinical presentation, intraoperative and microbiologic findings, surgical pain severity, postoperative outcome, and complications were studied. Of the 26 patients, most were females (female:male 20:6), with a mean age of 60.1 ± 16.1 years (range, 19-93). Mucopurulent discharge (96.2%), eyelid redness and swelling (53.8%), and epiphora (38.5%) were the most common presentations. During the surgery, concretions were present in 73.1% (19/26) of the patients. The surgical pain severity scores ranged from 1 to 5, according to the visual analog scale, with a mean score of 3.2 ± 0.8. This procedure resulted in complete resolution in 22 (84.6%) patients and significant improvement in 2 (7.7%) patients, and 2 (7.7%) patients required additional lacrimal surgery with a mean follow-up time of 10.9 ± 3.7 months. The surgical procedure of super pulse CO2 laser-assisted punctoplasty followed by curettage appears to be a safe, effective, minimally invasive, and well-tolerated treatment for primary canaliculitis.

Public opinion changing patterns under the double-hazard scenario of natural disaster and public health event.

In the context of the COVID-19 epidemic, a "double-hazard scenario" consisting of a natural disaster and a public health event occurring simultaneously is likely to arise. Focusing on this double-hazard scenario, this study developed a new opinion dynamics model that verifies the effect of opinion dynamic in practical applications and extends the realistic meaning of the logic matrix. The new model can be used to quickly identify changing trends in public opinion about two co-occurring public safety events in China, helping the government to better anticipate and respond to these real double-hazard scenarios. The new model was tested with three real double-hazard scenarios involving natural disasters and public health events in China and the simulation results were analyzed. Using visualization and Pearson correlation coefficients to analyze more than a million items of network-wide public opinion data, the new model was found to show a good fit with reality. The study finally found that in China, public attention to both natural hazards and public health events was greater when these public safety events co-occurred (double-hazard scenario) than when they occurred separately (single-hazard scenarios). These results verify the coupling phenomenon of different disasters in a multi-hazard scenario at the information level for the first time, which is greatly meaningful for multi-hazard research.

A Rapid Corneal Healing Microneedle for Efficient Ocular Drug Delivery.

Fungal keratitis (FK) remains a serious clinical problem worldwide, so the ultimate goal of the treatment is to develop a minimally invasive, safe, and effective method for ocular drug delivery. Here, a minimally invasive delivery system is reported for treating FK by using a dissolving microneedle (MN)-array patch based on Poly(D,L-lactide) (PLA) and hyaluronic acid (HA). By altering the concentration of PLA, MN patches with excellent properties are modified and optimized. The 30% PLA-HA MN patches penetrate the corneal epithelial layer reversibly with no apparent ocular irritation as well as a short recovery time of less than 12 h, and increase the residence time by 2.5 h in the conjunctival sac, thereby offering higher drug bioavailability. Remarkably, the rabbit model of FK shows that the topical MN(+) patch medication exerts superior therapeutic effects compared with the conventional eye drop formulation, and also presents comparable therapeutic efficacy with that of the clinical mainstay strategy (i.e., intrastromal injection). Therefore, the MN patch, acting as an ocular drug delivery system with high efficacy and ability of rapid corneal healing, promises a cost-effective household solution for the treatment of FK, which may also lead to a new approach for treating FK in clinics.

Network-based methods for predicting essential genes or proteins: a survey.

Genes that are thought to be critical for the survival of organisms or cells are called essential genes. The prediction of essential genes and their products (essential proteins) is of great value in exploring the mechanism of complex diseases, the study of the minimal required genome for living cells and the development of new drug targets. As laboratory methods are often complicated, costly and time-consuming, a great many of computational methods have been proposed to identify essential genes/proteins from the perspective of the network level with the in-depth understanding of network biology and the rapid development of biotechnologies. Through analyzing the topological characteristics of essential genes/proteins in protein-protein interaction networks (PINs), integrating biological information and considering the dynamic features of PINs, network-based methods have been proved to be effective in the identification of essential genes/proteins. In this paper, we survey the advanced methods for network-based prediction of essential genes/proteins and present the challenges and directions for future research.

Experimental demonstration of optical trapping and manipulation with multifunctional metasurface.

Chip-scale optical tweezers, which are usually implemented in a planar format without using bulky diffractive optical elements, are recognized as a promising candidate to be integrated with a lab-on-a-chip system. However, traditional chip-scale optical tweezers are often static and allow for only one type of manipulation functionality since the geometrical parameters of the tweezers are fixed. Herein, we introduce a new, to the best of our knowledge, class of on-chip optical tweezers for diverse types of manipulation of micro-particles. Utilizing both the propagation phase and Pancharatnam-Berry phase, we experimentally demonstrate the spin-dependent trapping, moving, and circling of micro-particles with the transfer of optical gradient force and orbital angular momentum to particles. We further show that the spin angular momentum of the output beam provides an additional degree of freedom to control the spinning rotation of particles. This new type of optical tweezers paves the way for multifunctional and dynamical trapping and manipulation of particles with a lab-on-a-chip system.

Sequelae of COVID-19 among previously hospitalized patients up to 1 year after discharge: a systematic review and meta-analysis.

OBJECTIVE: Although complications and clinical symptoms of COVID-19 have been elucidated, the prevalence of long-term sequelae of COVID-19 is less clear in previously hospitalized COVID-19 patients. This review and meta-analysis present the occurrence of different symptoms up to 1 year of follow-up for previously hospitalized patients. METHODS: We performed a systematic review from PubMed and Web of Science using keywords such as "COVID-19", "SARS-CoV-2", "sequelae", "long-term effect" and included studies with at least 3-month of follow-up. Meta-analyses using random-effects models were performed to estimate the pooled prevalence for different sequelae. Subgroup analyses were conducted by different follow-up time, regions, age and ICU admission. RESULTS: 72 articles were included in the meta-analyses after screening 11,620 articles, identifying a total of 167 sequelae related to COVID-19 from 88,769 patients. Commonly reported sequelae included fatigue (27.5%, 95% CI 22.4-33.3%, range 1.5-84.9%), somnipathy (20.1%, 95% CI 14.7-26.9%, range 1.2-64.8%), anxiety (18.0%, 95% CI 13.8-23.1%, range 0.6-47.8%), dyspnea (15.5%, 95% CI 11.3-20.9%, range 0.8-58.4%), PTSD (14.6%, 95% CI 11.3-18.7%, range 1.2-32.0%), hypomnesia (13.4%, 95% CI 8.4-20.7%, range 0.6-53.8%), arthralgia (12.9%, 95% CI 8.4-19.2%, range 0.0-47.8%), depression (12.7%, 95% CI 9.3-17.2%, range 0.6-37.5%), alopecia (11.2%, 95% CI 6.9-17.6%, range 0.0-47.0%) over 3-13.2 months of follow-up. The prevalence of most symptoms reduced after > 9 months of follow-up, but fatigue and somnipathy persisted in 26.2% and 15.1%, respectively, of the patients over a year. COVID-19 patients from Asia reported a lower prevalence than those from other regions. CONCLUSIONS: This review identified a wide spectrum of COVID-19 sequelae in previously hospitalized COVID-19 patients, with some symptoms persisting up to 1 year. Management and rehabilitation strategies targeting these symptoms may improve quality of life of recovered patients.