Urbanization-Related Environmental Factors and Hemorrhagic Fever with Renal Syndrome: A Review Based on Studies Taken in China.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease that has threatened Chinese residents for nearly a century. Although comprehensive prevent and control measures were taken, the HFRS epidemic in China presents a rebounding trend in some areas. Urbanization is considered as an important influencing factor for the HFRS epidemic in recent years; however, the relevant research has not been systematically summarized. This review aims to summarize urbanization-related environmental factors and the HFRS epidemic in China and provide an overview of research perspectives. The literature review was conducted following the PRISMA protocol. Journal articles on the HFRS epidemic in both English and Chinese published before 30 June 2022 were identified from PubMed, Web of Science, and Chinese National Knowledge Infrastructure (CNKI). Inclusion criteria were defined as studies providing information on urbanization-related environmental factors and the HFRS epidemic. A total of 38 studies were included in the review. Changes brought by urbanization on population, economic development, land use, and vaccination program were found to be significantly correlated with the HFRS epidemic. By changing the ecological niche of humans-affecting the rodent population, its virus-carrying rate, and the contact opportunity and susceptibility of populations-urbanization poses a biphasic effect on the HFRS epidemic. Future studies require systematic research framework, comprehensive data sources, and effective methods and models.

Analysis of Vibration Frequency and Direction for Facilitating Upper-Limb Muscle Activity.

We aimed to determine the effect of vibration frequency and direction on upper-limb muscle activation using a handheld vibrator. We recruited 19 healthy participants who were instructed to hold a handheld vibrator in their dominant hand and maintain the elbow at 90° flexion, while vertical and horizontal vibrations were applied with frequencies of 15, 30, 45, and 60 Hz for 60 s each. Surface electromyography (EMG) measured the activities of the flexor digitorum superficialis (FDS), flexor carpi radialis (FCR), extensor carpi ulnaris (ECU), extensor carpi radialis (ECR), biceps, triceps, and deltoid anterior muscles. EMG changes were evaluated as the difference in muscle activity between vibration and no-vibration (0 Hz) conditions. Muscle activity was induced under vibration conditions in both vertical and horizontal (p < 0.05) directions. At 45 Hz, FDS and FCR activities increased during horizontal vibrations, compared with those during vertical vibrations. ECU activity significantly increased under 15-Hz vertical vibrations compared with that during horizontal vibrations. Vibrations from the handheld vibrator significantly induced upper-limb muscle activity. The maximum muscle activations for FDS, ECR, ECU, biceps, and triceps were induced by 45-Hz horizontal vibration. The 60-Hz vertical and 30-Hz horizontal vibrations facilitated maximum muscle activations for the FCR and deltoid anterior, respectively.

A bibliometric analysis of the application of artificial intelligence to advance individualized diagnosis and treatment of critical illness.

Background: Artificial intelligence (AI) has been extensively applied in the individualized diagnosis and treatment of critical illness, and numerous studies have been published on this topic. Therefore, a bibliometric analysis of these publications should be performed to provide a direction of hot topics and future research trends. Methods: A bibliometric analysis was performed on the research articles to identify the hot topics and any unsolved issues regarding the use of AI in individualized diagnosis and treatment of critical illness. Articles published from January 2011 to December 2021 were retrieved from the Web of Science (WOS) core collection database for bibliometric analysis, and a cross-sectional analysis of the relevant studies that had been registered at ClinicalTrials.gov was also conducted. Results: The number of articles published showed an annually increasing trend, with a worldwide geographic distribution over the past decade. Ultimately, 427 research articles were included in the bibliometric analysis. The relevant articles were divided into four separate clusters that focused on AI application aspects, prediction model establishment, coronavirus disease 2019 (COVID-19) treatment and outcome assessments, respectively. "Machine learning" was the most frequent keyword (147 occurrences, 165 links, and 395 total link strengths) followed by "risk", "models", and "mortality". With 205 articles, the United States of America (USA) had interacted the most with other countries (20 links, and 94 total link strength), while the domestic research institutes in China had infrequently collaborated with others. Approximately 130 trials focusing on the application of AI in the intensive care unit (ICU) and emergency department (ED) had been registered at ClinicalTrial.gov, and most of them (n=71, 54.6%) were interventional. The main research objectives of these trials were to provide decision making assistance and establish prediction models. However, only 3.8% (5 trials) of them had reached exact conclusions which favored the application of AI. Conclusions: The application of AI has raised great interest in critical illness and has mainly been focused on decision making assistance and prediction model establishment. Cooperation between agencies engaged in AI research needs to be strengthened. An increasing number of trials have been registered at ClinicalTrial.gov, and the results of them are promising. Keywords: Bibliometric analysis; artificial intelligence (AI); individualized diagnosis; critical care medicine; emergency department (ED).

How agricultural economists are using big data: a review

Purpose>The purpose of this paper is to describe the main ways in which large amounts of information have been integrated to provide new measures of food consumption and agricultural production, and new methods for gathering and analyzing internet-based data.Design/methodology/approach>This study reviews some of the recent developments and applications of big data, which is becoming increasingly popular in agricultural economics research. In particular, this study focuses on applications of new types of data such as text and graphics in consumers' online reviews emerging from e-commerce transactions and Normalized Difference Vegetation Index (NDVI) data as well as other producer data that are gaining popularity in precision agriculture. This study then reviews data gathering techniques such as web scraping and data analytics tools such as textual analysis and machine learning.Findings>This study provides a comprehensive review of applications of big data in agricultural economics and discusses some potential future uses of big data.Originality/value>This study documents some new types of data that are being utilized in agricultural economics, sources and methods to gather and store such data, existing applications of these new types of data and techniques to analyze these new data.

First report of de novo assembly and annotation from brain and blood transcriptome of an anadromous shad, Alosa sapidissima.

OBJECTIVES: American shad (Alosa sapidissima) is an important migratory fish under Alosinae and has long been valued for its economic, nutritional and cultural attributes. Overfishing and barriers across the passage made it vulnerable to sustain. To protect this valuable species, aquaculture action plans have been taken though there are no published genetic resources prevailing yet. Here, we reported the first de novo assembled and annotated transcriptome of A. sapidissima using blood and brain tissues. DATA DESCRIPTION: We generated 160,481 and 129,040 non-redundant transcripts from brain and blood tissues. The entire work strategy involved RNA extraction, library preparation, sequencing, de novo assembly, filtering, annotation and validation. Both coding and non-coding transcripts were annotated against Swissprot and Pfam datasets. Nearly, 83% coding transcripts were functionally assigned. Protein clustering with clupeiform and non-clupeiform taxa revealed ~ 82% coding transcripts retained the orthologue relationship which improved confidence over annotation procedure. This study will serve as a useful resource in future for the research community to elucidate molecular mechanisms for several key traits like migration which is fascinating in clupeiform shads.

Demand shocks and supply chain resilience: an agent based modelling approach and application to the potato supply chain

The food supply chain has experienced major disruptions from both demand and supply sides during the Covid-19 pandemic. While some consequences such as food waste are directly caused by the disruption due to supply chain inefficiency, others are indirectly caused by a change in consumer's preferences. As a result, evaluating food supply chain resilience is a difficult task. With an attempt to understand impacts of demand on the food supply chain, we developed an agent-based model based on the case of Idaho's potato supply chain. Results showed that not only the magnitude but also the timing of the demand shock will have different impacts on various stakeholders of the supply chain. Our contribution to the literature is two-fold. First, the model helps explain why food waste and shortages may occur with dramatic shifts in consumer demand. Second, this paper provides a new angle on evaluating the various mitigation strategies and policy responses to disruptions beyond Covid-19.

Price and Volatility Transmissions among Natural Gas, Fertilizer, and Corn Markets: A Revisit

In this paper, we revisit price and volatility transmission among natural gas, fertilizer, and corn markets;an important issue was explored in previous work. An update of the results is urgently needed due to the recent enormous price volatility in the commodities, fertilizer, and energy markets. We followed the same methodology as previous work and used the vector error correction model and the multivariate generalized autoregressive heteroskedasticity model, but we adopted a new methodology to gather higher frequency data for fertilizer to estimate the interactions and examine the mechanisms between these market prices. Our results are consistent with previous research showing that natural gas price returns in the short-term are significantly affected by its lagged returns from itself and corn markets, and it will be affected by its lagged return sand fertilizer markets. However, we did not find a significant relationship among fertilizer, corn, and natural gas markets from May to November 2021. Moreover, the lagged conditional volatility of corn prices will affect the conditional volatility in the natural gas market but not vice versa.

Demand Shocks and Supply Chain Resilience: An Agent Based Modelling Approach and Application to the Potato Supply Chain

The food supply chain has experienced major disruptions from both demand and supply sides during the Covid-19 pandemic. While some consequences such as food waste are directly caused by the disruption due to supply chain inefficiency, others are indirectly caused by a change in consumer’s preferences. As a result, evaluating food supply chain resilience is a difficult task. With an attempt to understand impacts of demand on the food supply chain, we developed an agent-based model based on the case of Idaho’s potato supply chain. Results showed that not only the magnitude but also the timing of the demand shock will have different impacts on various stakeholders of the supply chain. Our contribution to the literature is two-fold. First, the model helps explain why food waste and shortages may occur with dramatic shifts in consumer demand. Second, this paper provides a new angle on evaluating the various mitigation strategies and policy responses to disruptions beyond Covid-19.

"Pivoting" by food industry firms to cope with COVID-19 in developing regions: E-commerce and "copivoting" delivery intermediaries.

Coronavirus disease 2019 and related lockdown policies in 2020 shocked food industry firms' supply chains in developing regions. Firms "pivoted" to e-commerce to reach consumers and e-procurement to reach processors and farmers. "Delivery intermediaries" copivoted with food firms to help them deliver and procure. This was crucial to the ability of the food firms to pivot. The pandemic was a "crucible" that induced this set of fast-tracking innovations, accelerating the diffusion of e-commerce and delivery intermediaries, and enabling food industry firms to redesign, at least temporarily, and perhaps for the long term, their supply chains to be more resilient, and to weather the pandemic, supply consumers, and contribute to food security. We present a theoretical model to explain these firm strategies, and then apply the framework to classify firms' practical strategies. We focus on cases in Asia and Latin America. Enabling policy and infrastructural conditions allowed firms to pivot and copivot fluidly.

Neurosurgery resumption in Wuhan during the early post-epidemic period: what should we pay attention to?

COVID-19 has spread globally, causing a pandemic and medical interruptions. As more countries control the epidemic, the resumption of work is imperative. However, asymptomatic carriers become the main source of infection. After several months of recovery, Wuhan had much experience with facing the challenge of work resumption. The purpose of this study was to investigate the safety of the resumption strategies, as well as the outcome of the resumption efforts, in the early post-epidemic period. A retrospective study was conducted in patients admitted between April 8 and June 30 to the neurosurgery department of Tongji Hospital, Wuhan. The medical information, past medical history, COVID-19 tests, laboratory parameters, CT results, and management were reviewed and recorded. 768 patients were admitted to the neurosurgery department at Tongji Hospital, and none of them became new infections. Our department recovered to 70% efficiency one month after the resumption of work. Two patients were found to have asymptomatic infections in the outpatient department. Two patients who recovered from COVID-19 underwent the surgery without recurrence of COVID-19. Tumor patients accounted for more than 50% of the surgery patients in the early period. It is feasible and helpful to follow our strict admission algorithm in the early post-epidemic period, even though the challenges of asymptomatic infectors exist. Two COVID-19 tests in 3 days are suggested within the early period. Protective downgrades should be based on the testing of asymptomatic patients in the area. Recovered COVID-19 patients can undergo surgery without recurrence.

An overview of functional nanoparticles as novel emerging antiviral therapeutic agents

A review. Research on highly effective antiviral drugs is essential for preventing the spread of infections and reducing losses. Recently, many functional nanoparticles have been shown to possess remarkable antiviral ability, such as quantum dots, gold and silver nanoparticles, nanoclusters, carbon dots, graphene oxide, silicon materials, polymers and dendrimers. Despite their difference in antiviral mechanism and inhibition efficacy, these functional nanoparticles-based structures have unique features as potential antiviral candidates. In this topical review, we highlight the antiviral efficacy and mechanism of these nanoparticles. Specifically, we introduce various methods for analyzing the viricidal activity of functional nanoparticles and the latest advances in antiviral functional nanoparticles. Furthermore, we systematically describe the advantages and disadvantages of these functional nanoparticles in viricidal applications. Finally, we discuss the challenges and prospects of antiviral nanostructures. This topic review covers 132 papers and will enrich our knowledge about the antiviral efficacy and mechanism of various functional nanoparticles.

Infectivity, susceptibility, and risk factors associated with SARS-CoV-2 transmission under intensive contact tracing in Hunan, China (preprint)

BackgroundSeveral parameters driving the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain unclear, including age-specific differences in infectivity and susceptibility, and the contribution of inapparent infections to transmission. Robust estimates of key time-to-event distributions remain scarce as well. MethodsWe collected individual records for 1,178 SARS-CoV-2 infected individuals and their 15,648 contacts identified by contact tracing and monitoring over the period from January 13 to April 02, 2020 in Hunan Province, China. We provide descriptive statistics of the characteristics of cases and their close contacts; we fitted distributions to time-to-key-events distributions and infectiousness profile over time; and we used generalized linear mixed model to estimate risk factors for susceptibility and transmissibility of SARS-CoV-2. ResultsWe estimated the mean serial interval at 5.5 days (95%CI -5.0, 19.9) and the mean generation time at 5.5 days (95%CI 1.7, 11.6). The infectiousness was estimated to peak 1.8 days before symptom onset, with 95% of transmission events occurring between 7.6 days before and 7.3 days after the date of symptom onset. The proportion of pre-symptomatic transmission was estimated to be 62.5%. We estimated that at least 3.5% of cases were generated asymptomatic individuals. SARS-CoV-2 transmissibility was not significantly different between working-age adults (15-59 years old) and other age groups (0-14 years old: p-value=0.16; 60 years and over: p-value=0.33), whilst susceptibility to SARS-CoV-2 infection was estimated to increase with age (p-value=0.03). In addition, transmission risk was higher for household contacts (p-value<0.001), decreased for higher generations within a cluster (second generation: odds ratio=0.13, p-value<0.001; generations 3-4: odds ratio=0.05, p-value<0.001, relative to generation 1), and decreased for infectors with a larger number of contacts (p-value=0.04). InterpretationOur findings warn of the possible relevant contribution of children to SARS-CoV-2 transmission. When lockdown interventions are in place, we found that odds of transmission are highest in the household setting but, with the relaxation of interventions, other settings (including schools) could bear a higher risk of transmission. Moreover, the estimated relevant fraction of pre-symptomatic and asymptomatic transmission highlight the importance of large-scale testing, contact tracing activities, and the use of personnel protective equipment during the COVID-19 pandemic.

Coronavirus Disease 2019 (COVID-19) During Pregnancy: A Case Series (preprint)

Background: Coronavirus disease 2019 (COVID-19) is a new viral respiratory disease and whether pregnant women are at increased risk of infection is unknown. Viral pneumonia is an important indirect cause of maternal death. Little is known about the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during pregnancy. Objective: To describe the clinical characteristics of COVID-19 in pregnancy and their newborn infant, and we sought to explored whether the SARS-CoV-2 can be intrauterine vertically transmitted. Study Design: The study was a case series study conducted in the obstetric ward of Tongji Hospital affiliated to Huazhong University of science and technology, Wuhan, China. Demographic, clinical, laboratory and radiological profiles of the SARS-CoV-2 infection case series. A systematic testing procedure for SARS-CoV-2 infection using oropharyngeal swab, placenta tissue, vaginal mucus, and breast milk of mothers. and oropharyngeal swab, umbilical cord blood, and serum of newborns was conducted. Results: We have conducted the most thorough virological assessment to date, and we include a longer clinical observation in mother-infant dyads during hospitalization. The clinical course and outcomes of three pregnant women who acquired SARS-CoV-2 infection late pregnancy are described in mother-infant dyads. Two had caesarean delivery in their third trimester. All patients showed an uneventful perinatal course, and a successful outcome. No infants became infected by vertical transmission or during delivery. Conclusion: No evidence to suggest the potential risk of intrauterine vertical transmission in the case series and further in-depth study is needed. Both the pregnancy woman and infant showed fewer adverse maternal and neonatal outcomes.