LLDSNet: Limited labeled data segmentation network for COVID-19 CT lesion segmentation

With the COVID-19 outbreak in 2019, the world is facing a major crisis and people's health is at serious risk. Accurate segmentation of lesions in CT images can help doctors understand disease infections, prescribe the right medicine and control patients' conditions. Fast and accurate diagnosis not only can make the limited medical resources get reasonable allocation, but also can control the spread of disease, and computer-aided diagnosis can achieve this purpose, so this paper proposes a deep learning segmentation network LLDSNet based on a small amount of data, which is divided into two modules: contextual feature-aware module (CFAM) and shape edge detection module (SEDM). Due to the different morphology of lesions in different CT, lesions with dispersion, small lesion area and background area imbalance, lesion area and normal area boundary blurred, etc. The problem of lesion segmentation in COVID-19 poses a major challenge. The CFAM can effectively extract the overall and local features, and the SEDM can accurately find the edges of the lesion area to segment the lesions in this area. The hybrid loss function is used to avoid the class imbalance problem and improve the overall network performance. It is demonstrated that LLDSNet dice achieves 0.696 for a small number of data sets, and the best performance compared to five currently popular segmentation networks. © 2023 SPIE.

The COVID-19 pandemic required a rapid expansion of teledermatology services

Background: The COVID-19 pandemic required a rapid expansion of tele dermatology services. Objective(s): Analyse demographic shifts in a pediatric dermatology practice session with children of colour. Method(s): A retrospective chart review of pediatric dermatology patients seen in the four practice weeks preceding the New York COVID-19 lockdown and comparable tele dermatology visits during the COVID-19 pandemic lockdown. Demographic differences (e.g., race, age, gender and household income) were analysed. Result(s): A greater proportion of patients seen were White during lockdown (59.7%), compared to pre-lockdown (43.6%), with a reduction in Asian patients seen in lockdown (6.0%) compared to prelockdown (24.5%). A lower proportion of no-show patients (4.3%, 3/70 scheduled) were noted in lockdown compared to pre-lockdown (16%, 18/112). Preferred provider organizations and higher-income zip codes were more common for children seen during lockdown. Limitation(s): The sample addresses a limited New York pediatric dermatology practice during a short time-period. Conclusion(s): White patients and patients with preferred provider organizations were more likely to access telehealth, supporting disparity in tele dermatology services. These results demonstrate reduced healthcare access for lower-income and Asian children during the COVID-19 pandemic lockdown.

Learning Social Meta-knowledge for Nowcasting Human Mobility in Disaster

Human mobility nowcasting is a fundamental research problem for intelligent transportation planning, disaster responses and management, etc. In particular, human mobility under big disasters such as hurricanes and pandemics deviates from its daily routine to a large extent, which makes the task more challenging. Existing works mainly focus on traffic or crowd flow prediction in normal situations. To tackle this problem, in this study, disaster-related Twitter data is incorporated as a covariate to understand the public awareness and attention about the disaster events and thus perceive their impacts on the human mobility. Accordingly, we propose a Meta-knowledge-Memorizable Spatio-Temporal Network (MemeSTN), which leverages memory network and meta-learning to fuse social media and human mobility data. Extensive experiments over three real-world disasters including Japan 2019 typhoon season, Japan 2020 COVID-19 pandemic, and US 2019 hurricane season were conducted to illustrate the effectiveness of our proposed solution. Compared to the state-of-the-art spatio-temporal deep models and multivariate-time-series deep models, our model can achieve superior performance for nowcasting human mobility in disaster situations at both country level and state level. © 2023 ACM.

Molecular Crowding Modulates SARS-CoV-2 Aptamer Affinity

SARS-CoV-2 aptamer is a favorable candidate for the recognition and detection of SARS-CoV-2, owing to its small size and easy synthesis. However, the issue of compromised binding affinities in real samples and targeting mutant SARS-CoV-2 hinder wide applications of the aptamer. In this study, it is discovered that molecular crowding could increase binding affinity of CoV2-6C3 aptamer against RBD (Receptor Binding Domain) of SARS-CoV-2 via increasing the absolute value of the enthalpy change. The values of the equilibrium dissociation constant in molecular crowding decrease by 70% and 150%, respectively, against wild-type and mutant RBD compared with those in buffer without crowding. Moreover, the detection limit of SARS-CoV-2 pseudovirus is up to 5 times lower under molecular crowding compared to dilute conditions. The discovery deepens the understanding of aptamer-target interaction mechanisms in crowding conditions and provides an effective way to apply SARS-CoV-2 aptamer for virus recognition and detection.

Research Report: Innovation among Businesses Across the Agri-Food Supply Chain during COVID-19

Innovation contributes critically to business recovery following major crises. Traditionally, business innovation is characterized by a series of choices and actions over time. During COVID-19, however, businesses throughout the agri-food supply chain were forced to innovate rapidly due to sudden unforeseen policy changes. To understand innovation induced by COVID-19, we analyze 297 usable responses from a survey of agri-food supply chain businesses in two distinct study regions (California and the two-state region of Minnesota-Wisconsin). Results indicate that larger agri-food businesses managed by younger owner-operators were more likely to innovate and adapt during the COVID-19 crisis. © 2023, Food Distribution Research Society. All rights reserved.

Sleep quality of first-line medical workers fighting against COVID-19 in Wuhan

[Background] Sleep is closely related to immune function and human health, and adequate sleep is an important foundation for human health. [Objective] This study investigates the sleep status of the first-line medical staff in Wuhan in a fight against the coronavirus disease 2019 (COVID-19) outbreak, provides reference for improving the sleep quality of the first-line medical staff in public health emergencies. [Methods] Through convenience sampling, 112 medical workers (first-line group) who aided the COVID-19 fight in Wuhan and 134 medical staff (non-first-line group) who did not participate in the fight were selected. The Pittsburgh Sleep Quality Index (PSQI) was employed to collect data on the incidence of sleep disorders, time to fall asleep, duration of sleep, sleep efficiency, sleep disorders, use of sleep aid, and daytime functions. In addition, a self-made questionnaire was used to investigate the common concerns and time allocation characteristics of the first-line medical workers in the context of major infectious disease outbreaks. [Results] There were no significant differences between the two groups in demographic variables such as gender, age, job title, educational background, marriage status, number of children, and working years (P > 0.05). In the first-line group, 62 medical workers (55.36%) reported sleep disorders, while in the non-first-line group, 54 medical workers (40.30%) did;the difference was statistically significant (P=0.008). Among the seven components of the PSQI, the median sleep time (component 3) score of the first-line group was 1.5, which was higher than that of the non-first-line group (median 1.0) (P < 0.001);the median sleep efficiency (component 4) score of the first-line group was 1.0, which was higher than that of the non-first-line group (median 0) (P < 0.001). The actual sleep duration of the first-line group [(5.65+/-1.15) h] was lower than that of the non-first-line group [(7.00+/-1.40) h] (P < 0.001). The distributions of common concerns were different between the two group. The top three concerns were being infected (76.79%), exhausted (37.50%), and overloaded (27.68%) in the first-line group, and family members being infected (53.73%), being infected (45.52%), and child care (33.58%) in the non-first-line group. [Conclusion] The first-line medical team members report poor sleep quality, short sleep time, low sleep efficiency, sleep disorders, and many psychological concerns. It is necessary to take appropriate measures to improve their sleep quality.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

Towards Secure and Privacy-Preserving Data Sharing for COVID-19 Medical Records: A Blockchain-Empowered Approach

COVID-19 is currently a major global public health challenge. In the battle against the outbreak of COVID-19, how to manage and share the COVID-19 Electric Medical Records (CEMRs) safely and effectively in the world, prevent malicious users from tampering with CEMRs, and protect the privacy of patients are very worthy of attention. In particular, the semi-trusted medical cloud platform has become the primary means of hospital medical data management and information services. Security and privacy issues in the medical cloud platform are more prominent and should be addressed with priority. To address these issues, on the basis of ciphertext policy attribute-based encryption, we propose a blockchain-empowered security and privacy protection scheme with traceable and direct revocation for COVID-19 medical records. In this scheme, we perform the blockchain for uniform identity authentication and all public keys, revocation lists, etc are stored on a blockchain. The system manager server is responsible for generating the system parameters and publishes the private keys for the COVID-19 medical practitioners and users. The cloud service provider (CSP) stores the CEMRs and generates the intermediate decryption parameters using policy matching. The user can calculate the decryption key if the user has private keys and intermediate decrypt parameters. Only when attributes are satisfied access policy and the user's identity is out of the revocation list, the user can get the intermediate parameters by CSP. The malicious users may track according to the tracking list and can be directly revoked. The security analysis demonstrates that the proposed scheme is indicated to be safe under the Decision Bilinear Diffie-Hellman (DBDH) assumption and can resist many attacks. The simulation experiment demonstrates that the communication and storage overhead is less than other schemes in the public-private key generation, CEMRs encryption, and decryption stages. Besides, we also verify that the proposed scheme works well in the blockchain in terms of both throughput and delay.

Scenic Beauty Evaluation of Forests with Autumn-Colored Leaves from Aerial and Ground Perspectives: A Case Study in Qixia Mountain in Nanjing, China

In recent years, on-site visitation has been strictly restricted in many scenic areas due to the global spread of the COVID-19 pandemic. "Cloud tourism”, also called online travel, uses high-resolution photographs taken by unmanned aerial vehicles (UAVs) as the dominant data source and has attracted much attention. Due to the differences between ground and aerial observation perspectives, the landscape elements that affect the beauty of colored-leaved forests are quite different. In this paper, Qixia National Forest Park in Nanjing, China, was chosen as the case study area, and the best viewpoints were selected by combining tourists' preferred viewing routes with a field survey, followed by a scenic beauty evaluation (SBE) of the forests with autumn-colored leaves in 2021 from the aerial and ground perspectives. The results show that (1) the best viewpoints can be obtained through the spatial overlay of five landscape factors: elevation, surface runoff, slope, aspect, and distance from the road;(2) the dominant factors influencing the beauty of colored-leaved forests from the aerial perspective are terrain changes, forest coverage, landscape composition, landscape contrast, the condition of the human landscape, and recreation frequency;and (3) the beauty of the ground perspective of the colored-leaved forests is strongly influenced by the average diameter at breast height (DBH), the dominant color of the leaves, the ratio of the colored-leaved tree species, the canopy width, and the fallen leaf coverage. The research results can provide scientific reference for the creation of management measures for forests with autumn-colored leaves. © 2023 by the authors.

Molecular Docking and Dynamics of Phytochemicals From Chinese Herbs With SARS-CoV-2 RdRp

The novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is causing coronavirus disease 2019 (COVID-19) pandemic. Ancient Chinese herbal formulas are effective for diseases caused by viral infection, and their effects on COVID-19 are currently being examined. To directly evaluate the role of Chinese herbs in inhibiting replication of SARS-CoV-2, we investigated how the phytochemicals from Chinese herbs interact with the viral RNA-dependent RNA polymerase (RdRP). Total 1025 compounds were screened, and then 181compounds were selected for molecular docking analysis. Four phytochemicals licorice glycoside E, diisooctyl phthalate, (-)-medicocarpin, and glycyroside showed good binding affinity with RdRp. The best complex licorice glycoside E/RdRp forms 3 hydrogen bonds, 4 hydrophobic interactions, 1 pair of Pi-cation/stacking, and 4 salt bridges. Furthermore, docking complexes licorice glycoside E/RdRp and diisooctyl phthalate/RdRp were optimized by molecular dynamics simulation to obtain the stable conformation. These studies indicate that they are promising as antivirals against SARS-CoV-2.Copyright © The Author(s) 2022.

Multi-subject collaborative prevention and control of adolescent myopia in China

Improving the system of adolescent myopia prevention and control and promoting adolescent healthy development is one of the main directions of healthy China construction in the new era. The paper reviewed national myopia policies and local practices and proposed reflections on the high burden and complex etiology of myopia among adolescents as well as unclear role and lack of coordination mandate during the COVID-19 epidemic. Based on the synergy theory through the analysis of the functional positioning of multiple subjects in the prevention and control of myopia the paper highlighted the multi-party linkage of government schools medical institutions communities families and markets profiling the resources and advantages of each subject as well as dynamic management of adolescent myopia as well as a multi-subject collaborative prevention and control system with national unity clear rights and responsibilities and long-term cooperation. © 2023 Journal of Chinese Agricultural Mechanization. All rights reserved.

USE OF ANGIOTENSIN-CONVERTING ENZYME INHIBITORS (ACEIs) AND ANGIOTENSIN-RECEPTOR BLOCKERS (ARBs) AND INCIDENCE OF PNEUMONIA OR INFLUENZA OR COVID-19: A SYSTEMATIC REVIEW AND META-ANALYSIS

Introduction: The respiratory tract infections (RTIs), including pneumonia, influenza and Coronavirus Disease 2019 (COVID-19), are the leading cause of hospitalization and mortality worldwide, contributing to elevated healthcare and societal costs. There is conflicting evidences about the effects of angiotensin converting enzyme inhibitor (ACEIs) or angiotensin II receptor blockers (ARBs) on the susceptibility of RTIs. Method(s): Systematic review of interventional and observational studies that reported use of ACEI or/and ARB on incidence of pneumonia or influenza or COVID-19. Searching was conducted in the databases of PubMed, Excerpta Medica Database (Embase), Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), including the Cochrane Library until April 2022, and references of retrieved relevant articles. We assessed the quality of included studies by using Cochrane Collaboration Risk of Bias tool for Randomized Controlled Trials and Newcastle-Ottawa Scale for observational studies. DerSimonian Laird random-effects meta-analysis was conducted to pool effects for the incidence of pneumonia, influenza and COVID-19. Subgroup analyses were carried according to baseline morbidities (hypertension or cardiovascular diseases, cerebrovascular diseases, chronic kidney disease (CKD) and other non-communicable diseases). Pooled estimates of odds ratios (OR) and corresponding 95% confidence intervals (95% CI) were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values. Result(s): 73 studies met the inclusion criteria, of which 38 studies assessed the odds of pneumonia, 32 studies assessed Covid-19 and 3 studies assessed influenza. The quality of included studies was moderate. Use of ACEIs was associated with a significantly reduced odds of pneumonia (23 studies: OR 0.74, 95% CI 0.64 to 0.85;I2=76.8%), of COVID-19 (24 studies: OR 0.87, 95% CI 0.82 to 0.92;I2=81.9%) and influenza (3 studies: OR 0.75, 95% CI 0.57 to 0.98, I2=97.7%), compared with control treatment. Use of ARBs was also associated with reduced odds of COVID-19 (25 studies: OR 0.90, 95% CI 0.83 to 0.97;I2=91.9%), but not with odds of pneumonia or influenza. These findings remain consistent in the community population, patients with history of cerebrovascular diseases or cardiovascular diseases, but not in those with CKD, diabetes and chronic obstructive pulmonary diseases. Conclusion(s): The current evidence favours a putative protective role of ACEIs, not ARB in odds of pneumonia, COVID-19 and influenza. Patient populations that may benefit most are those within the community, history of cerebrovascular diseases and cardiovascular diseases. No conflict of interestCopyright © 2023

A review on the identification of COVID-19, SARS and MERS.

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association

A review on the identification of COVID-19, SARS and MERS.

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association

A review on the identification of COVID-19, SARS and MERS.

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association

Recent progress in microfluidic biosensors with different driving forces

Microfluidic biosensors integrating fluid control, target recognition, as well as signal transduction and output, have been widely used in the field of disease diagnosis, drug screening, food safety and environmental monitoring in the past two decades. As the central part and technical characteristics of microfluidic biosensors, the fluid control is not only associated with accuracy and convenience of the sensors, but also affects the material selection and working mode of the sensors. This review summarizes the fluid driving forces for microfluidic biosensors, including gravity, capillary force, centrifugal force, pressure, light, sound, electrical, and magnetic forces. Then, the recent advances in microfluidic biosensors for the detection of viruses, cells, nucleic acids, proteins and small molecules are discussed. Finally, we propose the current challenges and future perspectives of microfluidic biosensors. We hope this review can provide readers with a new perspective to understand the technical characteristics and application potential of microfluidic biosensors.Copyright © 2022 Elsevier B.V.

Human Mobility-based Individual-level Epidemic Simulation Platform

COVID-19 has spread worldwide, and over 140 million people have been confirmed infected, over 3 million people have died, and the numbers are still increasing dramatically. The consensus has been reached by scientists that COVID-19 can be transmitted in an airborne way, and human-to-human transmission is the primary cause of the fast spread of COVID-19. Thus, mobility should be restricted to control the epidemic, and many governments worldwide have succeeded in curbing the spread by means of control policies like city lockdowns. Against this background, we propose a novel fine-grained transmission model based on real-world human mobility data and develop a platform that helps the researcher or governors to explore the possibility of future development of the epidemic spreading and simulate the outcomes of human mobility and the epidemic state under different epidemic control policies. The proposed platform can also support users to determine potential contacts, discover regions with high infectious risks, and assess the individual infectious risk. The multi-functional platform aims at helping the users to evaluate the effectiveness of a regional lockdown policy and facilitate the process of screening and more accurately targeting the potential virus carriers. © 2022 held by the owner/author(s). Publication rights licensed to ACM.

Forecast of China's Economic Growth Rate in 2023 and Policy Suggestions

China's economic growth slowed down in 2022 due to the COVID-19 pandemic and the corresponding measures. There are great uncertainties in China's economic development in 2023. It is expected that China's medium and long-term economic growth rate will show a wavy downward trend. Based on input-output technology, econometrics, prosperity analysis, expert analysis, and scenario analysis, this study proposes a systematic integrated factor prediction approach on annual GDP growth. Through analysis of China's economic growth in 2022 and the current situation worldwide, China's economic growth rate is predicted to be about 6.0% in 2023, reverting to the normal level. The policy recommendations are further put forward based on the analysis, including strengthening the adjustment of macro-policy, implementing proactive fiscal policy and prudent monetary policy, boosting domestic consumption, increasing employment and promoting investment, striving to stabilize the macro-economic market, preventing and defusing risks in major fields, and leveraging China's advantages in the global industrial chain. © 2023, Science Press. All rights reserved.