Unveiling the potential role of virus-encoded polyphosphate kinases in enhancing phosphorus removal in activated sludge systems.

While microbial phosphate removal in activated sludge (AS) systems has been extensively studied, the role of viruses in this process remains largely unexplored. In this study, we identified 149 viral auxiliary metabolic genes associated with phosphorus cycling from 2,510 viral contigs (VCs) derived from AS systems. Notably, polyphosphate kinase 1 (ppk1) and polyphosphate kinase 2 (ppk2) genes, which are primarily responsible for phosphate removal, were found in five unclassified VCs. These genes exhibited conserved protein structures and active catalytic sites, indicating a pivotal role of viruses in enhancing phosphorus removal. Phylogenetic analysis demonstrated a close relationship between viral ppk genes and their bacterial counterparts, suggesting the occurrence of horizontal gene transfer. Furthermore, experimental assays validated that viral ppk genes enhanced host phosphate removal capabilities. VCs carrying ppk genes were observed across diverse ecological and geographical contexts, suggesting their potential to bolster host functions in varied environmental and nutrient settings, spanning natural and engineered systems. These findings uncover a previously underappreciated mechanism by which viruses enhance phosphate removal in wastewater treatment plants. Overall, our study highlights the potential for leveraging virus-encoded genes to improve the efficiency of biological phosphorus removal processes, offering new insights into the microbial ecology of AS systems and the role of viruses in biogeochemical cycling.

Veno-venous extracorporeal membrane oxygenation-assisted treatment of severe airway stenosis due to goiter: Two case reports.

RATIONALE: Extracorporeal membrane oxygenation (ECMO) is a critical care intervention that acts as a temporary substitute for the heart and lungs, facilitating adequate tissue perfusion and gas exchange. The 2 primary configurations, veno-arterial and veno-venous ECMO, are tailored to support either the heart and lungs or the lungs alone, respectively. PATIENT CONCERNS: The case report details patients with tumor-induced airway stenosis who encountered limitations with standard treatments, which were either insufficient or carried the risk of severe complications such as hypoxia and asphyxia. DIAGNOSES: Patients were diagnosed with severe airway stenosis caused by goiter, a condition that required innovative treatment approaches to prevent complications during the management process. INTERVENTIONS: Veno-venous ECMO was implemented as a bridging therapy to provide vital respiratory support during the tumor resection procedure. This intervention was crucial in reducing the risks associated with airway edema or tumor rupture. OUTCOMES: With the use of veno-venous ECMO, the patients successfully underwent tumor resection. They were subsequently weaned off the ECMO support, and after a course of treatment, they were discharged in good condition. LESSONS: The case demonstrates the efficacy of veno-venous ECMO as a bridging therapy for managing severe airway stenosis caused by goiter. Its use facilitated the successful resection of tumors and led to positive patient outcomes, highlighting its potential as a valuable treatment option in similar scenarios.

HPB-Chip: An accurate high-throughput qPCR-based tool for rapidly profiling waterborne human pathogenic bacteria in the environment.

Waterborne pathogens are threatening public health globally, but profiling multiple human pathogenic bacteria (HPBs) in various polluted environments is still a challenge due to the absence of rapid, high-throughput and accurate quantification tools. This work developed a novel chip, termed the HPB-Chip, based on high-throughput quantitative polymerase chain reactions (HT-qPCR). The HPB-Chip with 33-nL reaction volume could simultaneously complete 10,752 amplification reactions, quantifying 27 HPBs in up to 192 samples with two technical replicates (including those for generating standard curves). Specific positive bands of target genes across different species and single peak melting curves demonstrated high specificity of the HPB-Chip. The mixed plasmid serial dilution test validated its high sensitivity with the limit of quantification (LoD) of averaged 82 copies per reaction for 25 target genes. PCR amplification efficiencies and R2 coefficients of standard curves of the HPB-Chip averaged 101 % and 0.996, respectively. Moreover, a strong positive correlation (Pearson' r: 0.961-0.994, P < 0.001) of HPB concentrations (log10 copies/L) between HPB-Chip and conventional qPCR demonstrated high accuracy of the HPB-Chip. Subsequently, the HPB-Chip has been successfully applied to absolutely quantify 27 HPBs in municipal and hospital wastewater treatment plants (WWTPs) after PMA treatment. A total of 17 HPBs were detected in the 6 full-scale WWTPs, with an additional 19 in the hospital WWTP. Remarkably, Acinetobacter baumannii, Legionella pneumophila, and Arcobacter butzler were present in the final effluent of each municipal WWTP. Overall, the HPB-Chip is an efficient and accurate high-throughput quantification tool to comprehensively and rapidly quantify 27 HPBs in the environment.

Knotted Artificial Muscles for Bio-Mimetic Actuation under Deepwater.

Muscles featuring high frequency and high stroke linear actuation are essential for animals to achieve superior maneuverability, agility, and environmental adaptability. Artificial muscles are yet to match their biological counterparts, due to inferior actuation speed, magnitude, mode, or adaptability. Inspired by the hierarchical structure of natural muscles, artificial muscles are created that are powerful, responsive, robust, and adaptable. The artificial muscles consist of knots braided from 3D printed liquid crystal elastomer fibers and thin heating threads. The unique hierarchical, braided knot structure offers amplified linear stroke, force rate, and damage-tolerance, as verified by both numerical simulations and experiments. In particular, the square knotted artificial muscle shows reliable cycles of actuation at 1Hz in 3000m depth underwater. Potential application is demonstrated by propelling a model boat. Looking ahead, the knotted artificial muscles can empower novel biomedical devices and soft robots to explore various environments, from inside human body to the mysterious deep sea.

A case report of successful rescue using veno-arterial extracorporeal membrane oxygenation: managing cerebral-cardiac syndrome.

Introduction: The presence of cerebral-cardiac syndrome, wherein brain diseases coincide with heart dysfunction, significantly impacts patient prognosis. In severe instances, circulatory failure may ensue, posing a life-threatening scenario necessitating immediate life support measures, particularly effective circulatory support methods. The application of extracorporeal membrane oxygenation (ECMO) is extensively employed as a valuable modality for delivering circulatory and respiratory support in the care of individuals experiencing life-threatening circulatory and respiratory failure. This approach facilitates a critical temporal window for subsequent interventions. Consequently, ECMO has emerged as a potentially effective life support modality for patients experiencing severe circulatory failure in the context of cerebral-cardiac syndrome. However, the existing literature on this field of study remains limited. Case description: In this paper, we present a case study of a patient experiencing a critical cerebral-cardiac syndrome. The individual successfully underwent veno-arterial-ECMO (VA-ECMO) therapy, and the patient not only survived, but also received rehabilitation treatment, demonstrating its efficacy as a life support intervention. Conclusion: VA-ECMO could potentially serve as an efficacious life support modality for individuals experiencing severe circulatory failure attributable to cerebral-cardiac syndrome.

Case Report: Resuscitation of patient with tumor-induced acute pulmonary embolism by venoarterial extracorporeal membrane oxygenation.

Background: Pulmonary embolism is a condition of right cardiac dysfunction due to pulmonary circulation obstruction. Malignant tumor-induced pulmonary embolism, which has a poor therapeutic outcome and a significant impact on hemodynamics, is the cause of sudden death in patients with malignant tumors. Case description: A 38-year-old female patient, who had a medical history of right renal hamartoma, and right renal space-occupying lesion, was admitted to the hospital. During the procedure to resect the right renal malignancy, the blood pressure and end-tidal carbon dioxide level dropped, and a potential pulmonary embolism was considered as a possibility. After inferior vena cava embolectomy, the hemodynamics in the patient remained unstable. The successful establishment of venoarterial extracorporeal membrane oxygenation (VA-ECMO) resulted in the stabilization of her hemodynamics and ventilation. On Day 2 of VA-ECMO support, her respiration and hemodynamics were relatively stable, and ECMO assistance was successfully terminated following the "pump-controlled retrograde trial off (PCRTO)" test on Day 6. The patient improved gradually after the procedure and was discharged from the hospital after 22 days. Conclusion: VA-ECMO can be used as a transitional resuscitation technique for patients with massive pulmonary embolism. It is critical for the perfusion of vital organs and can assist with surgical or interventional treatment, lower right heart pressure, and hemodynamic stability. VA-ECMO has a significant impact on patient prognosis and can reduce the mortality rate.

Does international trade reduce global carbon inequality? Evidence from a producer-consumer shared responsibility.

Addressing global carbon inequality constitutes an important task for both international negotiations on climate-change mitigation and the achievement of sustainable development goals. Soaring international trade might become a vigorous modifier for reducing global carbon inequality through production reallocation and economic boosts in different countries. However, this effect remains largely unexplored, not only because of little awareness of the windfall benefits from international trade but also because of debates on quantifying global carbon inequality from both production- and consumption-based perspectives. To avoid incomplete implications from a single perspective, this study first adapted a producer-consumer shared responsibility to evaluate global carbon inequality using the technology-adjusted consumption-based accounting method for 189 countries from 2006 to 2016. A dynamic panel data model was developed to examine the different channels through which international trade affects global carbon inequality in developed and developing countries. The results demonstrate that even with increasing carbon emissions, less global carbon inequality was witnessed from 2006 to 2016. International trade plays an important role in reducing global carbon inequality, mostly by stimulating the economy and increasing household income in developing countries. However, production reallocation via international trade fails in reducing the emission responsibilities of developed countries, rendering this futile in alleviating global carbon inequality. Carbon leakage that transfers carbon-intensive production across borders can lead to this unintended result, and more stringent cross-border regulations such as the carbon border adjustment mechanism can be effective. This study not only highlights the pivotal role of international trade in reducing global carbon inequality but also the future direction of international cooperation on climate change mitigation in a globalized world.

Tailoring Bi2Se3 Topological Insulator for Visible-NIR Photodetectors with Schottky Contacts Using Liquid Phase Exfoliation.

Layered semiconductors of the V-VI group have attracted considerable attention in optoelectronic applications owing to their atomically thin structures. They offer thickness-dependent optical and electronic properties, promising ultrafast response time, and high sensitivity. Compared to the bulk, 2D bismuth selenide (Bi2Se3) is recently considered a highly promising material. In this study, 2D nanosheets are synthesized by prolonged sonication in two different solvents, such as N-methyl-2-pyrrolidone (NMP) and chitosan-acetic acid solution (CS-HAc), using the liquid-phase exfoliation (LPE) method. X-ray diffraction confirms the amorphous nature of exfoliated 2D nanosheets with maximum peak intensity at the same position (015) crystal plane as that obtained in its bulk counterpart. SEM confirms the thin 2D nanosheet-like morphology. Successful exfoliation of Bi2Se3 nanosheets up to five layers is achieved using CS-HAc solvent. The as-synthesized 2D nanosheets in different solvents are employed to fabricate the photodetector. At minimum selected power density, the photodetector fabricated using exfoliated ultrathin 2D nanosheets exhibits the highest range of responsivity, varying from 15 to 2.5 mA/W, and detectivity ranging from 2.83 × 109 to 6.37 × 107. Ultrathin 2D Bi2Se3 nanosheets have fast rise and fall times, ranging from 0.01 to 0.12 and 0.01 to 0.06 s, respectively, at different wavelengths. Ultrathin Bi2Se3 nanosheets have improved photodetection parameters as compared to multilayered nanosheets due to the high surface to volume ratio, reduced recombination and trapping of charge carrier, improved carrier confinement, and faster carrier transport due to the thin layer.

Does COVID-19 affect sperm quality in males? the answer may be yes, but only temporarily.

BACKGROUND: The Corona Virus Disease 2019 (COVID-19) pandemic has raised concerns regarding its potential impact on male reproductive health. However, the impact of COVID-19 on sperm quality remains uncertain. This retrospective study aimed to investigate the short-term and relatively long-term effects of COVID-19 infection on sperm quality. METHODS: A total of 85 males with fertility requirements, who underwent semen evaluation at Guilin People's Hospital between June 2022 and July 2023, were included in the study. Changes in semen parameters were analyzed across three specific timeframes: within 6 months before COVID-19 infection, within 3 months after COVID-19 infection, and 3-6 months after COVID-19 recovery. RESULTS: The results revealed that the sperm concentration and total sperm number were significantly lower after infection compared to before, while in the recovery period, the sperm concentration, total sperm count, progressive motility, and normal morphology significantly increased. Comparing the three periods, the most significant difference was observed in sperm concentration, which exhibited a significant decrease after infection but returned to normal levels after recovery from COVID-19. CONCLUSIONS: These findings suggest that COVID-19 may exert some impact on sperm quality, particularly evidenced by decreased sperm concentration post-infection. Fortunately, these effects on semen parameters appear to be temporary, with gradual restoration of semen parameters within 3-6 months after recovery. However, further research is needed to explore the underlying mechanisms and long-term implications of these observed changes in semen parameters.

Large-Area Soluble Covalent Organic Framework Oligomer Coating for Organic Solution Nanofiltration Membranes.

Covalent organic frameworks (COFs) are a family of engaging membrane materials for molecular separation, which remain challenging to fabricate in the form of thin-film composite membranes due to slow crystal growth and insoluble powder. Here, an additive approach is presented to construct COF-based thin-film composite membranes in 10 min via COF oligomer coating onto poly(ether ether ketone) (PEEK）ultrafiltration membranes. By the virtue of ultra-thin liquid phase and liquid-solid interface-confined assembly, the COF oligomers are fast stacked up and grow along the interface with the solvent evaporation. Benefiting from the low out-plane resistance of COFs, COF@PEEK composite membranes exhibit high solvent permeances in a negative correlation with solvent viscosity. The well-defined pore structures enable high molecular sieving ability (Mw = 300 g mol-1 ). Besides, the COF@PEEK composite membranes possess excellent mechanical integrities and steadily operate for over 150 h in the condition of high-pressure cross flow. This work not only exemplifies the high-efficiency and scale-up preparation of COF-based thin-film composite membranes but also provides a new strategy for COF membrane processing.

Evaluation of the Mechanical and Tribological Behavior of Polyether Ether Ketone Fiber-Reinforced Resin-Based Friction Materials Fabricated by Wet Granulation.

Resin-based friction materials (RBFMs) strengthened by polyether ether ketone (PEEK) fiber were designed and prepared in this study. Specimens incorporating PEEK fiber of 2-8 wt.% were fabricated based on wet granulation, and then the effects of the PEEK fiber content on the mechanical and tribological properties of RBFMs were systematically investigated. The results showed that PEEK fiber can sense the braking temperature and then effectively regulate the comprehensive properties of RBFMs. The specimen incorporating 6 wt.% PEEK fiber obtained the optimal comprehensive performance with a stable friction coefficient (COF), excellent fade resistance and recovery properties, and better wear resistance. The worn surface was inspected using a scanning electron microscope. After the friction-wear test, the specimen with 6 wt.% PEEK fiber presented a number of primary and secondary plateaus and a reduced number of pits with wear debris on the worn surface. The study indicated that PEEK fiber could not only enhance the mechanical and tribological properties of RBFMs at low temperatures because of their high strength and self-lubrication but also adhere to wear debris to reduce abrasive wear at high temperatures; furthermore, the adhered wear debris could form a secondary plateau under normal pressure, which could alleviate abrasion.

Machine learning and statistical models for analyzing multilevel patent data.

A recent surge of patent applications among public hospitals in China has aroused significant research interest. A country's healthcare innovation capacity can be measured by its number of patents. This paper explores the link between the number of patents and ten independent variables. Multicollinearity was carefully detected and removed by using the variable selection method and LASSO regression, respectively. The Poisson model and the negative binomial model were proposed to analyze the patent data. Three goodness of fit tests, the Pearson test, the deviance test, and the DHARMa non-parametric dispersion test, were conducted to investigate if the model has a good fit. After discovering four clusters by conducting agglomerative hierarchical clustering, these two models were replaced by the negative binomial mixed model. The likelihood ratio test was used to determine which model is more appropriate and the results reveal that the negative binomial mixed model outperforms both the Poisson model and the negative binomial model. Three variables, number of health technicians per 10,000 people, financial expenditure on science and technology as well as number of patent applications per 10,000 health personnel, have a significantly positive relationship with the number of patents in Chinese tertiary public hospitals.

A radiomics nomogram for preoperative prediction of nephron-sparing surgery in patients with bilateral Wilms tumor.

Background: Bilateral Wilms tumor (BWT) is a relatively rare malignant renal tumor in children. Nephron-sparing surgery (NSS) is the preferred surgical approach for treating BWT, but lacks uniform surgical indications worldwide. This study aimed to summarize the clinical and imaging features of BWT children, establish a radiomics nomogram, and predict the feasibility of NSS for improving outcomes. Methods: A 12-year retrospective single-center review was conducted on clinical data and preoperative imaging features of BWT patients. The tumor kidneys were divided into NSS and non-NSS groups. Logistic regression analysis was performed to identify independent predictors and develop a prediction model of the feasibility of NSS in BWT patients. A radiomics nomogram was constructed and internally validated by the parametric bootstrapping method. Results: A total of 58 BWT patients (115 renal units) were included in this study. After evaluations based on preoperative imaging and clinical data, 94 renal units underwent NSS with negative resection margins and were included in the NSS group, whereas 16 renal units with positive resection margins, macroscopic residual, or total nephrectomies were included in the non-NSS group. Tumor size [odds ratio (OR): 0.540, 95% confidence interval (CI): 0.308-0.945], relationship with the collecting system (OR: 0.013, 95% CI: 0.0004-0.370), and remaining renal parenchyma (RRP) proportion (OR: 71.23, 95% CI: 1.632-3108.8) were identified as independent predictors for NSS. A nomogram was constructed based on these factors, which demonstrated great consistency between the predicted and observed feasibility of NSS. The model presented with good discriminative ability [area under the curve (AUC), 0.982]. The decision curve analysis (DCA) revealed the clinical usefulness of the model. Conclusions: This study analyzed the clinical and preoperative imaging data of BWT patients and identified three independent predictors for the feasibility of NSS, including tumor size, relationship with the collecting system, and residual renal parenchyma proportion. The radiomics nomogram established in this study can provide individualized predictions to assist clinicians in making better decisions and improving patient outcomes.

Nickel hexacyanocobaltate quantum dots embedded in N-doped carbon for aqueous alkaline batteries with ultrahigh durability.

Nickel-cobalt Prussian blue analogues (Ni-Co PBAs) suffer from structural instability in neural and alkaline electrolytes due to the dissolution of metal cations and cyanide anions caused by external H2O attack, resulting in capacity degradation and restricted life span. Herein, in this work, Ni-Co PBA quantum dots embedded in N-doped carbon (CC-Ni-Co PBA) were synthesized via a facile coprecipitation method and in situ polymerization followed by calcination under a nitrogen atmosphere. The obtained electrode provided a high specific capacity of 333.7 C g-1 and still retained 188.8 C g-1 when the current density increased by 40 times. Remarkably, it exhibited outstanding cycling stability with 82% retention of capacity after 10 000 cycles in an aqueous alkaline electrolyte, which benefited from the inner Ni-Co PBA quantum dots that provided a surrounding space and significantly accommodated the volume change during the repeated charge-discharge process, and the outer carbon layer that served as a protective barrier to hinder the Ni-Co PBA from dissolving into the electrolyte, thus realizing the durability of the electrode. Furthermore, an asymmetric alkaline battery device was assembled which achieved a maximum energy density of 33.2 W h kg-1 and a power density of 3.1 kW kg-1. Our work contributed to the development of PBA-based electrode materials with improved cycling stability as battery-type electrodes in aqueous electrolytes.

Methods to Improve the Stability of Nucleic Acid-Based Nanomaterials.

Nucleic acid strands can be synthesized into various nucleic acid-based nanomaterials (NANs) through strict base pairing. The self-assembled NANs are programmable, intelligent, biocompatible, non-immunogenic, and non-cytotoxic. With the rapid development of nanotechnology, the application of NANs in the biomedical fields, such as drug delivery and biological sensing, has attracted wide attention. However, the stability of NANs is often affected by the cation concentrations, enzymatic degradation, and organic solvents. This susceptibility to degradation is one of the most important factors that have restricted the application of NANs. NANs can be denatured or degraded under conditions of low cation concentrations, enzymatic presence, and organic solvents. To deal with this issue, a lot of methods have been attempted to improve the stability of NANs, including artificial nucleic acids, modification with specific groups, encapsulation with protective structures, etc. In this review, we summarized the relevant methods to have a deeper understanding of the stability of NANs.

FB-CCNN: A Filter Bank Complex Spectrum Convolutional Neural Network with Artificial Gradient Descent Optimization.

The brain-computer interface (BCI) provides direct communication between human brains and machines, including robots, drones and wheelchairs, without the involvement of peripheral systems. BCI based on electroencephalography (EEG) has been applied in many fields, including aiding people with physical disabilities, rehabilitation, education and entertainment. Among the different EEG-based BCI paradigms, steady-state visual evoked potential (SSVEP)-based BCIs are known for their lower training requirements, high classification accuracy and high information transfer rate (ITR). In this article, a filter bank complex spectrum convolutional neural network (FB-CCNN) was proposed, and it achieved leading classification accuracies of 94.85 ± 6.18% and 80.58 ± 14.43%, respectively, on two open SSVEP datasets. An optimization algorithm named artificial gradient descent (AGD) was also proposed to generate and optimize the hyperparameters of the FB-CCNN. AGD also revealed correlations between different hyperparameters and their corresponding performances. It was experimentally demonstrated that FB-CCNN performed better when the hyperparameters were fixed values rather than channel number-based. In conclusion, a deep learning model named FB-CCNN and a hyperparameter-optimizing algorithm named AGD were proposed and demonstrated to be effective in classifying SSVEP through experiments. The hyperparameter design process and analysis were carried out using AGD, and advice on choosing hyperparameters for deep learning models in classifying SSVEP was provided.

An Analysis of Deep Learning Models in SSVEP-Based BCI: A Survey.

The brain-computer interface (BCI), which provides a new way for humans to directly communicate with robots without the involvement of the peripheral nervous system, has recently attracted much attention. Among all the BCI paradigms, BCIs based on steady-state visual evoked potentials (SSVEPs) have the highest information transfer rate (ITR) and the shortest training time. Meanwhile, deep learning has provided an effective and feasible solution for solving complex classification problems in many fields, and many researchers have started to apply deep learning to classify SSVEP signals. However, the designs of deep learning models vary drastically. There are many hyper-parameters that influence the performance of the model in an unpredictable way. This study surveyed 31 deep learning models (2011-2023) that were used to classify SSVEP signals and analyzed their design aspects including model input, model structure, performance measure, etc. Most of the studies that were surveyed in this paper were published in 2021 and 2022. This survey is an up-to-date design guide for researchers who are interested in using deep learning models to classify SSVEP signals.

Advanced Bionic Attachment Equipment Inspired by the Attachment Performance of Aquatic Organisms: A Review.

In nature, aquatic organisms have evolved various attachment systems, and their attachment ability has become a specific and mysterious survival skill for them. Therefore, it is significant to study and use their unique attachment surfaces and outstanding attachment characteristics for reference and develop new attachment equipment with excellent performance. Based on this, in this review, the unique non-smooth surface morphologies of their suction cups are classified and the key roles of these special surface morphologies in the attachment process are introduced in detail. The recent research on the attachment capacity of aquatic suction cups and other related attachment studies are described. Emphatically, the research progress of advanced bionic attachment equipment and technology in recent years, including attachment robots, flexible grasping manipulators, suction cup accessories, micro-suction cup patches, etc., is summarized. Finally, the existing problems and challenges in the field of biomimetic attachment are analyzed, and the focus and direction of biomimetic attachment research in the future are pointed out.

Effect of Wet Granulation on Tribological Behaviors of Cu-Based Friction Materials.

Because of the excellent thermal conduction, corrosion resistance, and tribological properties, copper-based friction materials (CBFMs) were widely used in airplanes, high-speed trains, and wind power generation. With operating speed continuously increasing, CBFMs are suffering more complicated and extreme working conditions, which would cause abnormal abrasion. This paper presents an experiment to investigate how the tribological behaviors of CBFMs are regulated by granulation technology. Samples were prepared by the method of granulation and cool-pressed sinter. The tribological properties of specimens with different granule sizes were studied. The results showed that granulation could improve the tribological properties of CBFMs. The friction coefficient (COF) increased first and then decreased with increasing granule size. Specimen fabricated with 5-8 mm granules obtained the lowest COF, which was reduced by 22.49% than that made of powders. Moreover, the wear rate decreased first and then increased as granule size increased. The wear rate of samples prepared by granules 3-5 mm was lower than that of all of the other samples. This is because the structured samples prepared by wet granulation can promote the formation of secondary plateaus, which are beneficial for enhancing tribological properties. This makes granulation a promising method for enhancing the tribological performances of CBFMs.

Experience summary of a COVID-19 designated community hospital and its operation model.

The aim of this study was to summarize the administration model of a COVID-19 designated hospital transformed from a community hospital to improve the emergency capacity of community hospitals and the efficiency of diagnosis and treatment of medical staff in the COVID-19 pandemic. This study analyzed the surrounding environment, ward layout, area management, treatment process, medical staff, and patient management of the designated community hospital. From February 5, 2020, to February 18, 2020, the designated community hospital has received 198 COVID-19 mild and general patients (including 41 in the hospital at the beginning of the period). Among them, 39 were transferred to module hospitals, 131 were discharged, and 28 were in the hospital at the end of the period, and none of them became severe. There were 41 medical staff, and none of them had COVID-19 infection. We have achieved excellent results in the prevention and control stratagems implemented in this new community-designated hospital that specializes in treating patients with COVID-19. Its diagnosis and treatment model has completed the treatment of COVID-19 patients successfully. After adjustment, this community hospital can shoulder the critical task of being a designated hospital for COVID-19, which includes admission, isolation, and therapy of suspected and mild COVID-19 patients, reducing the medical burden of superior hospitals. Our experience provides concepts for community hospitals to temporarily undertake medical responsibilities to reduce the spread of COVID-19 during the pandemic.