RAPID IDENTIFICATION OF ETIOLOGICAL AGENTS OF RESPIRATORY TRACT INFECTIONS DURING THE COVID-19 PANDEMIC USING THE MULTIPLEX-PCR METHOD.

Objective. Most respiratory infections have similar symptoms, so it is clinically difficult to determine their etiology. This study aimed to show the importance of molecular diagnostics in identifying the etiological agent of respiratory infections, especially during the coronavirus disease 2019 (COVID-19) pandemic. Methods. A total of 849 samples from patients hospitalized at the University Clinical Center Kragujevac (from January 1 to August 1, 2022) were examined using automated multiplex-polymerase chain reaction (PCR) tests. The BioFire-FilmArray-Respiratory Panel 2.1 test was used for 742 nasopharyngeal swabs [identification of 19 viruses (including SARS-CoV-2) and four bacteria], while the BioFire-FilmArray-Pneumonia Panel was used [identification of 18 bacteria and nine viruses] (BioMerieux, Marcy l'Etoile, France) for 107 tracheal aspirates. The tests were performed according to the manufacturer's instructions, and the results were available within an hour. Results. In 582 (78.4%) samples, the BioFire-FilmArray-Respiratory Panel 2.1 plus test identified at least one pathogen. The rhinovirus (20.6%), SARS-CoV-2 (17.7%), influenza A (17.5%), respiratory syncytial virus (12.4%), and parainfluenza 3 (10.1%) were the most common. Other viruses were found less frequently, and Bordetella parapertussis was detected in one sample. In 85 (79.4%) samples, the BioFire-FilmArray-Pneumonia Panel test identified at least one bacterium or virus. The most prevalent bacteria were Staphylococcus aureus (42.4%), Haemophilus influenzae (41.2%), Streptococcus pneumoniae (36.5%), Moraxella catarrhalis (22.3%), and Legionella pneumophila (2.4%). Among viruses, rhinovirus (36.5%), adenovirus (23.5%), influenza A (11.8%), and the genus Coronavirus (4.7%), were detected. Conclusion. Multiplex-PCR tests improved the implementation of therapeutic and epidemiological measures, preventing the spread of the COVID-19 infection and Legionnaires' disease.Copyright © 2022, Serbian Medical Society. All rights reserved.

Prevalence of multidrug-resistant Gram-negative bacteria from blood cultures and rapid detection of beta-lactamase-encoding genes by multiplex PCR assay

Introduction This study aimed to determine the prevalence of multidrug-resistant Gram-negative bacteria (GNB) from blood cultures in a tertiary-care hospital and the multiplex PCR assay's ability to detect resistance genes. Methods A total of 388 GNB isolates obtained from hospitalized patients between November 2019 and November 2021 were included in the study. Antimicrobial susceptibility testing was done by VITEK 2 system and broth microdilution method. Beta-lactamase-encoding genes were detected by multiplex PCR assays, BioFire-Blood Culture Identification 2 (BCID2) panel (bioMerieux, France). Extended-spectrum beta-lactamases (ESBLs) were detected phenotypically with VITEK AST-GN71 card (bioMerieux, France). The isolates of GNB were classified into multidrug-resistant, extensively-drug-resistant, and pandrug-resistant categories, and their prevalence and distribution in different wards, including coronavirus diseases 2019 (COVID-19) intensive care units (ICU), were calculated. Results Results revealed that all isolates of Acinetobacter baumannii and Pseudomonas aeruginosa were multidrug-resistant as well as 91.6% of Enterobacter cloacae, 80.6% of Proteus mirabilis, and 76.1% of Klebsiella pneumoniae, respectively. In fermentative bacteria, blaOXA-48-like (58.1%), blaNDM (16.1%), blaKPC (9.7%) and blaVIM (6.5%) genes were detected. More than half of Enterobacter cloacae (58.3%) and Klebsiella pneumoniae (53.7%) produced ESBLs. Among non-fermenters, the blaNDM gene was carried by 55% of Pseudomonas aeruginosa and 19.5% of Acinetobacter baumannii. In the COVID-19 ICU, Acinetobacter baumannii was the most common isolate (86.1%). Conclusions This study revealed high proportions of multidrug-resistant blood isolates and various underlying resistance genes in Gram-negative strains. The BCID2 panel seems to be helpful for the detection of the most prevalent resistance genes of fermentative bacteria.Copyright © GERMS 2022.

Umifenovir in COVID-19 therapy: a systematic review and meta-analysis.

SARS-CoV-2 has infected more than 600 million people worldwide over the last 2.5 years. So far, there efficacy of many antiviral drugs against COVID-19 has been evaluated only in small studies conducted in different countries. Objective. To assess the efficacy of umifenovir in patients with COVID-19. Materials and methods. We performed systematic search of publications in the PubMed and Google Scholar databases. Sixteen studies with a total of 1,843 patients were included in the analysis. The following endpoints were evaluated: frequencies of negative PCR test on days 7 and 14;mortality in patients with mild, moderate, and severe disease;and frequency of fever resolution on day 7. Results. We found that patients receiving umifenovir demonstrated a significantly higher frequency of negative PCR test on day 7 than patients who received no causal therapy or other antiviral drugs (odds ratio (OR) 1.69, 95% confidence interval (CI): 1.09-2.62, p = 0.02, I2 = 13%). This difference was even more significant among patients with mild to moderate COVID-19 (OR: 2.03, 95% CI: 1.24-3.32, p = 0.005, I2 = 0%), as well as on day 14 (OR: 2.02, 95% CI: 1.35-3.94, p = 0.0007, I2 = 50%). We also observed a reduced risk of death in the studies that included only patients with mild and moderate disease (JR: 0.53, 95% CI: 0.33-0.83, p = 0.006, I2 = 0). Umifenovir therapy did not affect the frequency of fever resolution by day 7 (OR: 0.87, 95% CI: 0.49-1.56, p = 0.64, I2 = 0%). Conclusion. Umifenovir significantly accelerated virus elimination by days 7 and 14 among patients with mild to moderate COVID-19. Umifenovir also reduced the risk of death compared to other antiviral drugs.Copyright © 2022, Dynasty Publishing House. All rights reserved.

Smartphone-assisted point-of-care testing of nucleic acids based on hybridization chain reaction, magnetic beads, and gold nanorods etching

Colorimetric biosensors are simple but effective tools that are gaining popularity due to their ability to provide low-cost, rapid, and accurate detection for viruses like the Novel coronavirus, Influenza A, and Dengue virus, especially in point-of-care testing (POCT) and visual detection. In this study, a smartphone-assisted nucleic acid POCT was built using hybridization chain reaction (HCR), magnetic beads (MBs), and oxidized 3,3′,5,5′-tetramethylbenzidine (TMB2+)-mediated etching of gold nanorods (GNRs). The application of HCR without enzyme isothermal characteristics and MBs with easy separation, can quickly amplify nucleic acid signal and remove other reaction components. The blue shift of longitudinal localized surface plasmon resonance (LSPR) based on GNRs showed significant differences in etching color for different concentrations of target nucleic acid, which convert the signal into a visually semi-quantitative colorimetric result, achieving quantitative analysis with the color recognition software built into smartphones. This strategy, which only takes 40 min to detect and is two-thirds less time than the PCR, was successfully applied for the detection of the Dengue target sequence with a detection limit of 1.25 nM and exhibited excellent specificity for distinguishing single-base mutations, indicating broad application prospects in clinical laboratory diagnosis and enriching the research of nucleic acid POCT.

COVID-19: comparison lung CT signs and biochemical parameters in the groups of patients with three-time positive RT-PCR and with triple negative RT-PCR test during the period of hospitalization.

Research goal. Comparative characteristics of the dynamics of CT semiotics and biochemical parameters of two groups of patients: with positive RT-PCR and with triple negative RT-PCR. Reflection of the results by comparing them with the data already available in the literature. The aim of the study is to compare the dynamics of CT semiotics and biochemical parameters of blood tests in two groups of patients: with positive RT-PCR and with triple negative RT-PCR. We also reflect the results by comparing them with the data already available in the literature. Materials and methods. We have performed a retrospective analysis of CT images of 66 patients: group I (n1 = 33) consists of patients who had three- time negative RT-PCR (nasopharyngeal swab for SARS-CoV-2 RNA) during hospitalization, and group II (n2 = 33) includes patients with triple positive RT-PCR. An important selection criterion is the presence of three CT examinations (primary, 1st CT and two dynamic examinations - 2nd CT and 3rd CT) and at least two results of biochemistry (C-reactive protein (CRP), fibrinogen, prothrombin time, procalcitonin) performed in a single time interval of +/- 5 days from 1st CT, upon admission, and +/- 5 days from 3st CT. A total of 198 CT examinations of the lungs were analyzed (3 examinations per patient). Results. The average age of patients in the first group was 58 +/- 14.4 years, in the second - 64.9 +/- 15.7 years. The number of days from the moment of illness to the primary CT scan 6.21 +/- 3.74 in group I, 7.0 (5.0-8.0) in group II, until the 2nd CT scan - 12.5 +/- 4, 87 and 12.0 (10.0-15.0), before the 3rd CT scan - 22.0 (19.0-26.0) and 22.0 (16.0-26.0), respectively. In both groups, all 66 patients (100%), the primary study identified the double-sided ground-glass opacity symptom and 36 of 66 (55%) patients showed consolidation of the lung tissue. Later on, a first follow-up CT defined GGO not in all the cases: it was presented in 22 of 33 (67%) patients with negative RT-PCR (group I) and in 28 of 33 (85%) patients with the positive one (group II). The percentage of studies showing consolidation increased significantly: up to 30 of 33 (91%) patients in group I, and up to 32 of 33 (97%) patients in group II. For the first time, radiological symptoms of "involutional changes" appeared: in 17 (52%) patients of the first group and in 5 (15%) patients of the second one. On second follow-up CT, GGO and consolidations were detected less often than on previous CT: in 1 and 27 patients of group I (3% and 82%, respectively) and in 6 and 30 patients of group II (18% and 91%, respectively), although the consolidation symptom still prevailed significantly . The peak of "involutional changes" occurred on last CT: 31 (94%) and 25 (76%) patients of groups I and II, respectively.So, in the groups studied, the dynamics of changes in lung CT were almost equal. After analyzing the biochemistry parameters, we found out that CRP significantly decreased in 93% of patients (p < 0.001) in group I;in group II, there was a statistically significant decrease in the values of C-reactive protein in 81% of patients (p = 0.005). With an increase in CT severity of coronavirus infection by one degree, an increase in CRP by 41.8 mg/ml should be expected. In group I, a statistically significant (p = 0.001) decrease in fibrinogen was recorded in 77% of patients;and a similar dynamic of this indicator was observed in group II: fibrinogen values decreased in 66% of patients (p = 0.002). Such parameters as procalcitonin and prothrombin time did not significantly change during inpatient treatment of the patients of the studied groups (p = 0.879 and p = 0.135), which may indicate that it is inappropriate to use these parameters in assessing dynamics of patients with a similar course of the disease. When comparing the outcomes of the studied groups, there was a statistically significant higher mortality in group II - 30.3%, in group I - 21.2% (p = 0.043). Conclusion. According to our data, a course of the disease does not significantly differ in the groups o patients with positive RT-PCR and three-time negative RT-PCR. A negative RT-PCR analysis may be associated with an individual peculiarity of a patient such as a low viral load of SARS-CoV-2 in the upper respiratory tract. Therefore, with repeated negative results on the RNA of the virus in the oro- and nasopharynx, one should take into account the clinic, the X-ray picture and biochemical indicators in dynamics and not be afraid to make a diagnosis of COVID-19.Copyright © 2021 ALIES. All rights reserved.

A Comprehensive Review of Sound-Based Modalities for Automatic COVID-19 Detection using Deep Learning-Based Techniques

The World Health Organization has labeled the novel coronavirus illness (COVID-19) a pandemic since March 2020. It's a new viral infection with a respiratory tropism that could lead to atypical pneumonia. Thus, according to experts, early detection of the positive cases with people infected by the COVID-19 virus is highly needed. In this manner, patients will be segregated from other individuals, and the infection will not spread. As a result, developing early detection and diagnosis procedures to enable a speedy treatment process and stop the transmission of the virus has become a focus of research. Alternative early-screening approaches have become necessary due to the time-consuming nature of the current testing methodology such as Reverse transcription polymerase chain reaction (RT-PCR) test. The methods for detecting COVID-19 using deep learning (DL) algorithms using sound modality, which have become an active research area in recent years, have been thoroughly reviewed in this work. Although the majority of the newly proposed methods are based on medical images (i.e. X-ray and CT scans), we show in this comprehensive survey that the sound modality can be a good alternative to these methods, providing faster and easiest way to create a database with a high performance. We also present the most popular sound databases proposed for COVID-19 detection. © 2022 IEEE.

Could platelet mass index (PMI) be a new prognostic biomarker for COVID-19?

Aim: Although most patients with COVID-19 experience respiratory tract infections, severe reactions to the virus may cause coagulation abnormalities that mimic other systemic coagulopathies associated with severe infections, such as disseminated intravascular coagulation and thrombotic microangiopathy. Fluctuations in platelet markers, which are an indicator of the acute phase response for COVID-19, are of clinical importance. The aim of this study is to evaluate the relationship between disease severity and Platelet Mass Index (MPI) parameters in COVID-19 patients. Material(s) and Method(s): This retrospective observational study was conducted with patients who were diagnosed with COVID-19 in a tertiary hospital. The study was continued with the remaining 280 patients. All laboratory data were scanned retrospectively from patient files and hospital information system. Result(s): A very high positive correlation was found between PMI and PLT. The PMI value in women was significantly higher than in men. It was observed that PMI did not differ significantly in terms of mortality, intubation, CPAP and comorbidity. PMI vs. Pneumonia Ct Severity Score, biochemistry parameters (AST, CRP), hemogram parameters (WBC, HGB, HCT, MCV, LYM, MPV EO) and coagulation factors (aPTT and FIB) at various levels of positive/negative, weak and strong, and significant relationship was found. There was no significant relationship between hormone and D-dimer when compared with PMI. Discussion(s): Although platelet count alone does not provide information about the prognosis of the disease, PMI may guide the clinician as an indicator of lung damage in seriously ill patients.Copyright © 2022, Derman Medical Publishing. All rights reserved.

The spread of COVID-19 in stock returns along global value chains

This paper examines the performance of industries in the trade network in international stock markets during the onset of COVID-19. In general, the value of all industries in G20 countries declines significantly in the pandemic. Stock returns of industries in the central positions of global value chains exhibit remarkable resilience despite the economic hardship caused by COVID-19. This pattern is more pronounced when the disruptions caused by social distancing requirements are considered. We postulate that this is related to the essential services provided by the central industries.

The Impact of COVID-19 on Supply Chain in UAE Food Sector

The COVID-19 outbreak has significantly impacted supply chains and has caused several supply chain disruptions in almost all industries worldwide. Moreover, increased transportation costs, labor shortages, and insufficient storage facilities have all led to food loss during the pandemic, and this disruption has affected the logistics in the food value chain. As a result, we examine the food supply chain, which is one of the key industries COVID-19 has detrimentally affected, impacting, indeed, on the entire business process from the supplier all the way to the customer. Retail businesses are thus facing supply issues, which affect consumer behavior by creating stress regarding the availability of food. This has a negative impact on the amount of food that is available as well as its quality, freshness, safety, access to markets, and affordability. This study examines the impact of COVID-19 on the United Arab Emirates food distribution systems and how consumer behavior changed in reaction to interruptions in the food supply chain and the food security problem. Hypothesis testing was used in the study's quantitative methodology to assess consumer behavior, and participants who were consumers were given a descriptive questionnaire to ascertain whether the availability and security of food had been impacted. The study used JASP 0.17.2 software to develop a model of food consumption behavior and to reveal pertinent connections between each construct. Results show that consumer food stress and consumption behavior are directly impacted by food access, food quality and safety, and food pricing. Furthermore, food stress has an impact on how consumers behave when it comes to consumption. Food stress, however, is not significantly influenced by food supply.

COVID-19: Agent-Based Simulation-Optimization to Vaccine Center Location Vaccine Allocation Problem

This paper presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epidemic outbreak. Both simulation and optimization models incorporate population health dynamics, such as susceptible (S), vaccinated (V), infected (I) and recovered (R), while their integrated utilization focuses on the COVID-19 vaccine allocation challenges. We first formulate a dynamic location-allocation mixed-integer programming (MIP) model, which determines the optimal vaccination center locations and vaccines allocated to vaccination centers, pharmacies, and health centers in a multi-period setting in each region over a geographical location. We then extend the agent-based epidemiological simulation model of COVID-19 (Covasim) by adding new vaccination compartments representing people who take the first vaccine shot and the first two shots. The Covasim involves complex disease transmission contact networks, including households, schools, and workplaces, and demographics, such as age-based disease transmission parameters. We combine the extended Covasim with the vaccination center location-allocation MIP model into one single simulation-optimization framework, which works iteratively forward and backward in time to determine the optimal vaccine allocation under varying disease dynamics. The agent-based simulation captures the inherent uncertainty in disease progression and forecasts the refined number of susceptible individuals and infections for the current time period to be used as an input into the optimization. We calibrate, validate, and test our simulation-optimization vaccine allocation model using the COVID-19 data and vaccine distribution case study in New Jersey. The resulting insights support ongoing mass vaccination efforts to mitigate the impact of the pandemic on public health, while the simulation-optimization algorithmic framework could be generalized for other epidemics. [ FROM AUTHOR] Copyright of IISE Transactions is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

COVID-19 during the Third Semester of Pregnancy: Maternal Characteristic, Possibility of Intrauterine Transmission and Neonatal Outcome in Aceh, Indonesia

BACKGROUND: Pregnant women are vulnerable against COVID-19 infection due to physiological and immunological changes. COVID-19 in pregnancy affects fetal well-being with a potential for vertical infection. AIM: This study aims to determine the incidence of vertical infection and anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in infants born to mothers with positive COVID-19 infection. MATERIALS AND METHODS: Amniotic fluid, swabs of the newborn's nasopharynx and oropharynx, and swabs of the placenta were examined using reverse transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2. Serological examination was performed by Electro-Chemiluminescence Immunoassay on infant's blood. RESULT(S): Four of 33 pregnant women gave birth to infants positive SARS-CoV-2 infection. RT-PCR examination of all amniotic fluid and placental swabs was negative for SARS-CoV-2. Four of 33 infants (12.1%) showed negative polymerase chain reaction (PCR) results but positive SARS-CoV-2 antibodies, another 4 newborns (12.1%) showed positive PCR results, but no SARS-CoV-2 antibodies detected. The remaining 25 babies (75.8%) showed both negative PCR and serologic results. CONCLUSION(S): No evidence of vertical transmission found in this study.Copyright © 2023 Cut Meurah Yeni, Zinatul Hayati, Sarjani M. Ali, Hasanuddin Hasanuddin, Rusnaidi Rusnaidi, Cut Rika Maharani.

Clinical Characteristics of Patients with Sars-Cov-2 Omicron Variant and COVID-19 Vaccination with Clinical Outcome Findings in Shanghai, China: A Single Center, Retrospective, Observational Study

Objectives: This study aimed to determine disease severity, clinical features, clinical outcome in hospitalized patients with the Omicron variant and evaluate the effectiveness of one-dose, two-dose, and three-dose inactivated vaccines in reducing viral loads, disease course, ICU admissions and severe diseases. Method(s): Retrospective cohort analysis was performed on 5,170 adult patients (>=18 years) identified as severe acute respiratory syndrome coronavirus 2 positive with Reverse Transcription Polymerase Chain Reaction admitted at Shanghai Medical Center for Gerontology between March 2022 and June 2022. COVID-19 vaccination effectiveness was assessed using logistic regression models evaluating the association between the risk of vaccination and clinical outcomes, adjusting for confounders. Result(s): Among 5,170 enrolled patients, the median age was 53 years, and 2,861 (55.3%) were male. 71.0% were mild COVID-19 cases, and cough (1,137 [22.0%]), fever (592 [11.5%]), sore throat (510 [9.9%]), and fatigue (334 [6.5%]) were the most common symptoms on the patient's first admission. Ct values increased generally over time and 27.1% patients experienced a high viral load (Ct value< 20) during their stay. 105(2.0%) of these patients were transferred to the intensive care unit after admission. 97.1% patients were cured or showed an improvement in symptoms and 0.9% died in hospital. The median length of hospital stay was 8.7+/-4.5 days. In multivariate logistic analysis, booster vaccination can significantly reduce ICU admissions and decrease the severity of COVID-19 outcome when compared with less doses of vaccine (OR=0.75, 95%CI, 0.62-0.91, P<=0.005;OR=0.99, 95%CI, 0.99-1.00, p<0.001). Conclusion(s): In summary, the most of patients who contracted SARSCoV-2 omicron variant had mild clinical features and patients with vaccination took less time to lower viral loads. As the COVID-19 pandemic progressed, an older and less vaccinated population was associated with higher risk for ICU admission and severe disease.Copyright © 2023

Blockchain Technology Based Credibility Verification in E-Journal Entities

In the industrial era 4.0, it has surpassed increasingly complex technological advances in the information system that required a very high infrastructure and facilities and prevented fraud. Counterfeiting is a procedure following an entity, statistics, or documents (observe forged documents) with plans to deceive. Falsification of extensive information certificates is exacerbated by the current economic situation in Indonesia, which is currently occurring due to the widespread epidemic, namely COVID-19. The spread of the COVID-19 outbreak has had a significant impact and changes in all sectors, especially certificate forgery in Indonesia. The imitation of busy certificates is the main focus of this journal, focusing on journal publications combined with Blockchain technology. The sophistication of blockchain technology as authentication is comparing two or more items or additional tests to ensure the accuracy, correctness, or correctness of the information. This method uses qualitative methods with data sources based on case studies in controlled supervision with the basic concept of cryptography as the basis of analysis. From the decisions made, it is hoped that this will minimize the level of forgery of certificates widely measured during the COVID-19 era. © 2022 IEEE.

Impact of Pandemic Outbreak and Targeted Required Reserve Ratio Cut Policy on Stock Return Rate: Evidence from China

This study analyzed the impact of COVID-19 outbreak and targeted required reserve ratio cut policy on stock returns of Chinese listed companies. This paper uses the data of 3,449 A-share listed companies from February 3, 2020 to December 31, 2020 for research, the empirical results showed that stock prices of private enterprises with stronger debt-paying ability and looser financing constraints, and state-owned enterprises with less supply chain credit risks performed better, in the central and western regions, enterprises with stronger solvency and looser financing constraints have better stock price performance during the early stages of pandemic. After the implementation of the targeted RRR cut policy, the stock prices of enterprises with poor solvency, private enterprises, and enterprises in central and western regions with strong financing constraints, state-owned enterprises, and enterprises in eastern region with high credit risks all showed significant reversals, and the stock prices reflected the effect of the targeted RRR cut policy in the short and medium term. Over time, the pandemic has been controlled, and the resumption of work and production has freed most enterprises from financial difficulties. However, due to sporadic outbreaks, large private enterprises and eastern enterprises with strong risk resistance and loose financing constraints enjoy better stock price performance. This study is helpful for enterprises to understand the value of financial flexibility and solvency and provides a reference for enterprises to make financial decisions: how to balance the benefits and costs of solvency. © Tian Wang, Fang Fang and Linhao Zheng, 2023.

Market development strategy and process performance of knowledge-intensive SMEs in the epidemic era: a process-oriented perspective

PurposeThis study analyzes in-depth how knowledge-intensive small and medium-sized enterprises (SMEs) can achieve higher new product development (NPD) process performance in the epidemic era and examine the internal development mechanism of knowledge-intensive SMEs in the process of continuous digital transformation.Design/methodology/approachThis issue is tested with partial least squares on data collected via a survey conducted from November 2021 to February 2022. The sample comprises 487 knowledge-intensive SMEs operating in China.FindingsThe results indicate that one form of cross-functional ambidexterity, market development strategy (MDS), plays an important role in process performance from an inside-out financial perspective and an outside-in customer perspective. Simultaneously, product innovation efficiency (PIE) mediates the relationship between MDS and the above results. Big data analytics capabilities (BDACs) positively regulate the relationship between MDS and PIE.Research limitations/implicationsThe authors do not consider other contingency factors. Future research should introduce influential factors such as leadership and competitive intensity to further distinguish the effects of MDS on NPD process performance.Practical implicationsThe study findings offer suggestions to help knowledge-intensive SME managers better manage their NPD process by making better use of their limited resources in developing countries such as China.Originality/valueThis study is one of only a few to adopt a process-oriented perspective to specifically examine how one form of cross-functional ambidexterity, MDS, impacts knowledge-intensive SME process performance in the epidemic era. This study also extends the theoretical framework of cross-functional ambidexterity to BDAC research.

Enterprises' Green Growth Model and Value Chain Reconstruction: Theory and Method

The goal of this book is to improve the ability of enterprises to implement the green growth model and value chain reconstruction. China's environmental development strategies, such as carbon peak emission and carbon neutrality, have created new challenges and requirements for enterprises to "go green.” In addition, anti-globalization and the complex dynamic uncertainty caused by COVID-19 have changed the operational environment that enterprises face. The application of new technologies, including the new generation of information technologies and the whole process management technology, provides solutions for the implementation of enterprises' green growth model and value chain reconstruction. Based on China's enterprise management cases, this book reveals the connotative features of enterprises' green growth model and their evolutionary regularities, the overall framework and decision optimization of value chain reconstruction under the green growth model, and the approach to implementing the green growth model and value chain reconstruction. The theoretical framework of the green growth model and value chain reconstruction established in this book has enriched and developed the research results in this field. Cases of enterprises implementing the green growth model can provide references for the green transformation of enterprises and help enterprises appreciate the synergy between sustainability and growth. This book can also serve as a research reference for scholars engaged in the field of sustainable operations, as well as decision-makers and managers of relevant government departments. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Demand Forecasting in SCM for Automobile Industry based on Time-series Modeling

In supply chain management (SCM), product classification and demand forecasting are crucial pillars to ensure companies to have production in the right category and quantity for long-term profitability. Due to COVID-19 from 2019, the automobile industry has been seriously negatively affected as the demand dropped dramatically. Therefore, it is necessary to make reasonable product classification and accurate demand forecasting to facilitate automobile companies in SCM to reduce unpopular product manufacture and unnecessary storage costs. In this paper, the Canada automobile market has been chosen with the period from 1946 to 2022. To classify a number of different types of motor vehicles into several categories with general characteristics, K-means Clustering method is applied. With the seasonal patterns and random generated features for auto sales, the time series models ARIMA and SARIMA are adopted for demand forecasting. According to the analysis, the automobiles fitting in the category with high demand and low price are valuable for further production. In addition, SARIMA Model is more accurate and fits better than ARIMA Model for both the training and test datasets for long-term prediction. The classification and forecasting results shed light on guiding manufacturers to adjust production schemes and ensuring auto dealers to predict more accurate sales in order to optimize the strategic planning. © 2023 SPIE.

Applying blockchain technology to ensure compliance with sustainability standards in the PPE multi-tier supply chain

Because of the Covid-19 pandemic, urgent surging demand for healthcare products such as personal protective equipment (PPE) has caused significant challenges for multi-tier supply chain management. Although a given firm may predominantly focus on an arms-length solution by targeting the first-tier supplier, the firm can still struggle with extended multi-tier suppliers it cannot choose which use unsustainable practices. One key goal is compliance across various dimensions with production, environmental and labour standards across the multi-tier supply chain, a goal that blockchain technology can be applied to manage. Based on a comprehensive literature review, this research develops a system architecture of blockchain-based multi-tier sustainable supply chain management in the PPE industry designed to identify and coordinate standards in production and social and environmental sustainability in multi-tier PPE supply chains. The architecture was validated by theoretical basis, expert opinions and technical solutions. We conclude with managerial implications for implementing blockchain technology to advance sustainable multi-tier supply chain practices.

Patient Outcomes in CMV and SARS-CoV-2 Coinfection

This study examines clinical outcomes in patients with cytomegalovirus (CMV) and SARS-CoV-2 coinfection. Between June and November 2020, previously immunocompetent patients with SARS-CoV-2 and CMV coinfection were identified at Houston Methodist Hospital as part of routine clinical correlation by a molecular pathologist. SARS-CoV-2 nasopharyngeal specimens were analyzed by real time reverse-transcriptase polymerase chain reaction (RT-PCR). All CMV tests were performed on plasma or bronchoalveolar lavage (BAL) specimens and analyzed by competitive polymerase chain reaction. 65 previously immunocompetent patients with CMV and SARS-CoV-2 coinfection were identified. Patient demographics include 41 male patients (63%) and 24 female patients (37%) ranging in age from 34 to 86 years (mean: 66.04, median 68). Documented pre-existing conditions include 27 patients with hypertension 41.5%), 19 patients with diabetes mellitus (29.2%), 9 patients with coronary artery disease (13.8%), and 3 patients with asthma (4.6%). Eight patients (12.3%) had no documented pre-existing conditions. The plasma CMV viral load ranged from <300 to 21,566 IU/mL. The CMV PCR results from bronchoalveolar lavage and bronchial wash specimens ranged from <300 to 59,127 IU/mL. CMV PCR was initially negative in 10 patients then positive on serial testing. 60 patients were critically ill requiring ventilator support (92.3%). 47 patients (72.3%) expired, 7 patients (10.8%) were transferred to a long term acute care facility, 3 patients (4.6%) were discharged to a rehabilitation facility, 3 patients (4.6%) were discharged home, and 1 patient (1.5%) remained in-patient at the time of analysis. The prevalence of CMV seropositivity and medical comorbidities increases with age. Reactivation of latent CMV is a known occurrence in critically ill patients that is associated with poor outcomes. The majority of the patients in our cohort were 50 years old, and all were severely to critically ill with a mortality rate of 72.3% These findings suggest CMV portends a worse prognosis in patients with COVID-19. These findings also demonstrate the importance of clinical correlation in molecular testing.

COVID-19 in tobacco users.

Smoking is a significant social problem threatening the population's health, especially during the coronavirus pandemic. Due to the problem's urgency, we present a clinical case of SARS-CoV-2 infection in a patient with 10 years of smoking and concomitant chronic obstructive pulmonary disease (chronic bronchitis and peribronchial pneumosclerosis). Patient L.K., 42 years old, on 13.10.2022, was hospitalized for several hours at the Emergency Hospital of the Ministry of Health of Chuvashia (Cheboksary) with a severe new coronavirus infection. Secondary diagnosis: Chronic obstructive pulmonary disease Case history: for about two to three weeks, the patient noted an increase in body temperature to 37.2-37.4 degreeC and a cough. He has smoked for about 10 years, 1 pack per day. Computed tomography showed signs of bilateral COVID-associated pneumonitis, alveolitis with 85% involvement and consolidation sites, signs of chronic bronchitis, and peribronchial pneumosclerosis. The diagnosis of COVID-19 was confirmed by a polymerase chain reaction in a nasopharyngeal smear. The NEWS2 score was 9. After the treatment started, the patient died. Histological examination showed perivascular sclerosis, peribronchial pneumosclerosis, atrophic changes in the ciliated epithelium, and structural and functional alteration of the bronchial mucosa. In addition, areas of hemorrhage and inflammatory infiltrate in the bronchial wall were found. Coronavirus is known not to cause bronchitis but bronchiolitis. In the presented case, the patient showed signs of transition of bronchitis to the acute stage. Therefore, it can be assumed that the coronavirus acts as a complicating factor. In addition to the described changes, signs of viral interstitial pneumonia, pulmonary edema, and early development of acute respiratory distress syndrome were identified.Copyright © 2023, Media Sphera Publishing Group. All rights reserved.