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Background: Intervertebral disc degeneration causing radiculopathy is driven by catabolic cytokines like IL-1β and TNFα. Autologous conditioned serum (ACS) was found to be rich in IL-1Ra (Interleukin-1 Receptor Antagonist), and thus, can impede disc degeneration. A systematic review of available literature was conducted to ascertain the potential therapeutic application of ACS in radiculopathy. Methods: Systematic literature reviews were conducted in PubMed, Scopus and Embase databases, up to September 2020. Randomised controlled trials (RCTs), prospective, retrospective studies and case series with lumbar or cervical radiculopathy and reporting use of ACS were included, with at least one of the outcome measures like VAS (Visual Analogue Scale) for pain, SF-12 (Short Form of Health Survey-12), Oswestry Disability Index, with a minimum follow up of 3 months. Animal studies, s, review articles and case reports were excluded. Results: A total of four studies, including 107 patients who received ACS were included based on the eligibility criteria. Two were RCTs and two were prospective non-comparative studies. Three studies evaluated the effect of IL-1Ra on lumbar radiculopathy and one on cervical radiculopathy. The mean age of patients in the studies ranged from 37.15 to 53.9. The dose of ACS used was 2-4 mL injection. In 1 RCT, methylprednisolone was used as control, in the other 5 mg and 10 mg triamcinolone was used. All studies reported a statistically significant reduction in pre-injection and post-injection VAS, there was also a significant difference as compared to 5 mg triamcinolone. Three studies reported significant improvement in ODI. Two studies reported statistically significant improvement in SF-12 scores post injection (p < 0.001). For cervical radiculopathy, Neck pain disability score showed a decrease of 73.76% from pre-injection to final follow up and Neck disability index showed a decrease of 74.47%. Conclusion: All of the four studies concluded that epidural perineural injection with ACS, reduced pain scores (VAS, NPDS) and improved functional scores (ODI, SF-12 and NPDS), as compared to placebo and other conventional therapeutic modalities like steroids, and analgesic-anaesthetic-steroid cocktail. Hence, ACS is a promising new therapeutic modality in both lumbar and cervical radiculopathy, and further studies can strengthen the present evidence regarding its efficacy and safety profile. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
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Information Technology (IT) has become the integral part of majority of businesses. Healthcare sector is also one such sector where IT adoption is increased in recent times. This adoption of IT has increased the internet exposure and hence increased the attack surface of the organisations working in healthcare sector. During covid outbreak, we have observed various cyber-attack and threats on organisations operating in healthcare sector. This paper focuses on cyber threat pattern in healthcare sector during covid-19 outbreak and post-covid-19 period. This research paper also aims to generate basic cyber awareness through generic cyber sanity checks to secure healthcare sector from malicious threat actors. The adaptation of proactive measures required to enhance the cyber hygiene of organisations becomes very essential in this sector. © 2023 IEEE.
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As per World Health Organization (WHO), the Corona virus Covid-19 is a pandemic disease. This virus transmits from one person to another. It has affected the whole world economy and health. It has affected not only the developing countries but also developed countries. Rural areas, as well as urban areas, have been affected by this virus. Every part of the world is affected by this disease. This decease affects to the all aged group human beings. In this pandemic situation, the government of India and many other countries have decided to lockdown. Due to this lockdown period, many industries are getting shut down. Manufacturers and industrialists have faced various problems. In this manuscript, different industry sectors have been taken for the study and focused on the challenges they have faced and the positive and negative impacts of lockdown in India. The effects of pandemics on industries for different aspects are discussed in this manuscript. © 2023 Author(s).
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Currently, there are no reliable biomarkers for identifying COVID-19 patients and no definite therapeutics to control this deadly disease. MicroRNAs (miRNA) have been explored in several human diseases for their potential role as biomarkers and their therapeutic potential. However, there is very little information available about the roles of miRNAs in COVID-19 infection. This chapter outlines the recent updates and developments of miRNAs in COVID-19 such as miRNAs as potential biomarkers for COVID-19, the molecular basis of miRNAs in COVID-19 infection, and the use of miRNAs as therapeutics targets for COVID-19. While a few potential miRNAs have been researched for the aforementioned reasons, more research is needed to determine the roles of individual miRNAs in COVID-19 infection. © 2023 Elsevier Inc. All rights reserved.
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COVID-19 has wreaked havoc on the global economy, supply chains, and government, posing an unparalleled health threat. The manufacturing sector was one of the most disruptive systems in the world at the time of the COVID-19 pandemic. Most manufacturing companies have faced a lock-down situation and are focusing on the production of essential products. Furthermore, COVID-19 has altered customer behavior. The short-term and long-term effects of COVID-19 on the manufacturing sector must be evaluated to hasten recovery and build preparedness measures should another such disruption occur. The limitations affecting the construction system during this period were discussed and prioritized in this study. The ambiguous nature of human thinking makes it difficult to evaluate the qualitative parameters;hence, it is preferred to incorporate an approach that converts the variables into triangular fuzzy numbers to better represent the values of the criteria. A fuzzy analytical hierarchical procedure (FAHP) is applied to evaluate the limitation criteria in an ambiguous environment. "Growing demand for existing products" is considered the heaviest limit after "financial stagnation" and "setback in logistics services." The study results will help the manufacturing company in formulating and implementing strategies to overcome the pandemic situation. © 2023 River Publishers. All rights reserved.
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Bell palsy is caused by impaired functioning of the 7th cranial nerve. A disparity in the stable state of the cytokine regulatory axis and a cytokine storm are observed to occur from the binding of the ACE2 to the COVID, and the subsequent functional alterations in the ACE2/AT2R suggest that COVID-19 may use direct or indirect processes to produce neurological symptoms. Increased cases of Bell palsy were reported during the CoV pandemic, so our study aimed to estimate the incidence rate of Bell palsy among COVID-19 patients in South Bangalore, India. Secondary data of patients with Bell palsy were obtained retrospectively from two multispecialty Hospitals in South Bangalore. COVID positive populations were collected between the period of March 2021 and February 2022, and many Bell palsy cases within 3 months of post-Covid period were included. Confirmatory calls were made for patients with Covid Positive who were not diagnosed to discover the occurrence of Bell palsy. A retrospective analysis of Bell palsy cases found 11 incidences between March 2021 and February 2022, when there were 1577 COVID patients in total. According to descriptive statistical analysis, the prevalence of Bell palsy increased by 0.7% during the COVID-19 pandemic. Bell palsy could be considered one of the neurological complications among COVID-19 patients, and appropriate preventative measures should be taken.Copyright © 2023 International Journal of Nutrition, Pharmacology, Neurological Diseases Published by Wolters Kluwer - Medknow.
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Theoretical and experimental studies are performed on the new organic-inorganic hybrid molecule N-(2,6-dimethylphenyl)-1-piperazineacetamide. The vibrational spectra of the molecule are characterized using FT-IR and FT-Raman in the range 4000-600 cm(-1) and 4000-100 cm(-1), respectively. Density functional theory with B3LYP/3-21G and B3LYP/cc-pVDZ basis sets is used to calculate energy, geometrical structure, and vibrational modes of stretching, bending, and torsion. The VEDA software Autodock Vina revealed a good binding is employed to calculate the detailed vibrational assignments. The theoretical and experimental vibrational data are compared to support the present study. Density functional theory is used to calculate thermodynamic parameters (heat capacity, entropy, and enthalpy) and nonlinear optical properties. The software Gaussian09W and Gaussview 6.0 are used for theoretical calculations. Molecular docking studies are carried out to investigate the effect of the titled molecule against various proteins such as SARS-CoV-2 that affect the immune system in humans. Chemical shifts are identified using carbon and proton NMR. Non-covalent interactions are studied using a reduced density gradient. The chemical reactivity and selectivity for a local reactivity site are analyzed with the help of Fukui functions.
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PurposeThis research aims to ascertain the various operational maturity challenges faced by the online food ordering and delivery enterprises (OFODE), their nature and their interactive relationships. In particular, this paper aims to (a) identify the most relevant operational maturity challenges faced by the OFODE during the COVID-19 lockdown in Oman, (b) explore and establish any likely structural relationship among these challenges and (c) put them into logical clusters. Design/methodology/approachExperts helped to reduce the 18 initially identified maturity challenges to 13 most pressing ones. Mutual relationships, dominance of interactions and their classifications were explored using fuzzy interpretive structural modeling (FISM) and fuzzy MICMAC analysis. FindingsThe study of situation-specific operational maturity challenges convinced the authors to propose a distinct FISM model that depicts the relationship among these challenges. Keeping commissions and fees reasonable emerges as the challenge which all other challenges seemingly culminate into. One of the most important situation-specific challenges (i.e. customer confidence about infection free delivery) emerges as a linkage challenge which aggravates as well as is aggravated by certain challenges. Research limitations/implicationsBesides enriching literature, the proposed model has implications for practitioners particularly when the similar lethal waves are experienced anywhere. The number of respondents, subjective approach, specific context as well as the geographical area coverage are the key limitations. Originality/valueTo the best of the authors' knowledge, this study is the first known scientific effort which attempts to model the operational maturity challenges faced by the OFODE during COVID-19 lockdown period. The authors used the FISM modeling approach to forge these interrelated challenges into a structural model.
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Coronavirus disease 2019 (COVID-19), a pandemic that is triggered by a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) or 2019-nCoV, causes primarily respiratory discomfort along with other mild symptoms/no symptoms, leading to severe illness and death, if proper care is not taken. At present, COVID-19 is the resilient reason for a large number of human casualties worldwide as well as a cause of crucial economic loss posturing global threat. There is a necessity of intensive research to elucidate the pathogenic mechanisms of COVID-19, which would assist in understating the susceptibility towards the infection as well as prompt development of effective prevention and treatment strategies. Over the years, clinical studies have indicated the risk of various pathogenic infections prejudiced due to preexisting chronic diseases as well as ABO blood group types to a larger extent. In line of this, current COVID-19 infection-associated clinical studies intensely endorse the relationship of blood group type of individual and risk of COVID-19 infection. In this chapter, various clinical studies from January 2020 to June 2020 have been summarized to highlight the eminence of ABO blood group and COVID-19 infection susceptibility in human population. These reports evidently support the fact that individuals with A histo blood group were found to be more vulnerable to COVID-19 infection whereas individuals with blood group O were less likely to get infected with virus. To get deeper insight in this fact, many more studies are desirable in order to further explicate the promising protective role of the blood group O and it will be supportive for designing and planning several additional countermeasures against COVID-19 infection. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2021.
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The heterotypic perspective of cancer depicts solid tumors as ecosystems composed of aberrant epithelium tumor cells and a multitude of cell types together referred to as stromal cells. Macrophages, which are innate immune cells, are overrepresented in certain environments. Tumor-associated macrophages (TAMs) are macrophages found in the tumor microenvironment;they are derived from the blood's monocytes and are essential for tumor progression. TAMs acquiring tumorigenic qualities is dependent on a complicated interaction between TAMs and tumor cells. Using co-culture studies, we showed that tumor-derived secretory signals promote Tams' tumor-promoting characteristics, shaping up Tams' features in ways that are advantageous to the tumor. When model human monocytes (THP-1) were co-cultured with A549 cells, the A549 cells exhibited increased proliferation, migration, and invasiveness due to the secretion of tumor-promoting cytokines from the THP-1 cells. We showed that EDA-containing Fibronectin secreted by A549 cells reliably mediates the pro-inflammatory response of THP-1 monocytes in a paracrine manner. Ablation of such responses by the treatment of THP-1 cells with TLR-4 blocking antibody implicated Fibronectin-TLR4 axis in tumor-associated inflammation and suggests a paradigm wherein lung carcinoma cell derived EDA-containing Fibronectin drives a pro-inflammatory and pro-metastatic tumor microenvironment. Interestingly, autocrine proliferation, migration, and invasion were all boosted by EDA-containing Fibronectin secreted by A549 cells. Lastly, we demonstrated that the EDA in Fibronectin activates the epithelial-mesenchymal transition pathway in A549 cells, hence granting these cells the ability to metastasize. © 2023 IEEE.
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Lung segmentation is a process of detection and identification of lung cancer and pneumonia with the help of image processing techniques. Deep learning algorithms can be incorporated to build the computer-aided diagnosis (CAD) system for detecting or recognizing broad objects like acute respiratory distress syndrome (ARDS), Tuberculosis, Pneumonia, Lung cancer, Covid, and several other respiratory diseases. This paper presents pneumonia detection from lung segmentation using deep learning methods on chest radiography. Chest X-ray is the most useful technique among other existing techniques, due to its lesser cost. The main drawback of a chest x-ray is that it cannot detect all problems in the chest. Thus, implementing convolutional neural networks (CNN) to perform lung segmentation and to obtain correct results. The 'lost' regions of the lungs are reconstructed by an automatic segmentation method from raw images of chest X-ray. © 2022 IEEE.
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Of the more than 20 studies published on SLE patients with COVID-19, none of the studies focused on lupus nephritis. We report the outcomes of renal biopsy-proven systemic lupus erythematosus (SLE) nephritis patients after COVID-19 disease. Our institute has been declared as a state COVID-19 hospital in the last week of March 2020. From then till now, we have admitted and managed COVID-19 patients from several districts of Andhra Pradesh and neighbouring states. We collected the data of patients with SLE nephritis contemporaneously from admission to the outcomes on a computerised proforma. We had identified sixteen patients with SLE nephritis who were admitted with COVID-19 disease. Of them, fourteen were females and two were males. The mean age was 29.3 years. Out of sixteen patients, seven required a mechanical ventilator and dialysis and eventually succumbed. One more patient died due to disseminated tuberculosis. Our results suggested that with an approximately 50% mortality rate, the COVID-19 disease had a calamitous effect on SLE nephritis patients. Key Points ⢠We identified the significant risk factors for mortality: younger age, higher serum creatinine at presentation, higher CT severity score and lower serum albumin. ⢠After the analysis done for this article, we decided to reduce the medications for SLE nephritis to prednisolone 10 mg/day when COVID-19 disease is contracted.
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Air quality is a global concern, with particulate matter receiving considerable attention due to its impact on human health and climate change. Recent advances in low-cost sensors allow their deployment in large number to measure spatio-temporal and real-time air quality data. Low-cost sensors need careful evaluation with both regulatory approved methods and other data sets to understand their efficacy. In this work, PM concentrations measured by deploying low-cost sensors at four regional sites are evaluated through comparison with satellite-based model MERRA-2 and the SASS reference instrument. Daily PM2.5 mass concentration variation was analyzed at four regional sites of India from January 2020 to July 2020, including pre-lockdown and six different lockdown periods. Higher PM2.5 concentration was observed at Rohtak (119 mu g m-3) compared to Mahabaleshwar (33 mu g m-3), Bhopal (45 mu g m-3) and Kashmir sites during the pre-lock down period. During the lockdown period, the PM2.5 mass concentration was reduced significantly compared to the pre-lockdown period at every location, although the PM2.5 concentration was different at each location. The air quality trend was quite similar in both the measurements, however, MERRA-2 reconstructed PM2.5 was significantly lower in the pre-lockdown period compared to the lockdown periods. Significant differences were observed between low-cost sensor measurements and MERRA-2 reanalysis data. These are attributed to the MERRA-2 modelling analysis that measures less PM2.5 concentration as compared to ground-based measurements, whereas low-cost sensor are and biases.
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Introduction This paper aims to provide an overview of the administrative and clinical preparations done in a tertiary care cancer hospital in continuing operation theatre (OT) services through the COVID pandemic.Methods Retrospective data collection, data for the past 1.5 years (COVID period) March 2020 to August 2021 were compared to surgical output for a similar duration of time before the COVID era (September 2018-February 2020).Results A total of 1,022 surgeries were done under anesthesia in the COVID period as against 1,710 surgeries done in a similar time frame in the pre-COVID era. Overall, we saw a 40%drop in the total number of cases. Thorax, abdominal, and miscellaneous surgeries (soft tissue sarcomas, urology, and gyneconcology) saw a maximum fall in numbers;however, head and neck cases saw an increase in numbers during the pandemic. Surgical morbidity and mortality were similar in the COVID and pre-COVID era. No cases of severe COVID infection were reported among the healthcare staff working in OT.Discussion We could successfully continue our anesthesia services with minimal risk to healthcare staff throughout the pandemic by adopting major guidelines in a pragmatic and practical approach with minor changes to suit our setup.
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Since 2020, the coronavirus disease 2019 (COVID-19) pandemic and lockdown policy have changed our life drastically. Due to this, companies, offices, schools, etc. are running in online mode. Therefore, the demand for internet bandwidth is very popular nowadays. Due to an increase in demand for internet bandwidth and the availability of multihomed devices, multipath TCP (MPTCP), and e-adoption of emerging technology enhanced bandwidth by utilizing the bandwidth of all available networks simultaneously. This paper analyzes the working principle of the MPTCP so that each internet device can easily use MPTCP to achieve high bandwidth. Load distribution and its performance mainly depend on the congestion control algorithm and the packet scheduler. MPTCP has various existing packet scheduling algorithms and congestion control algorithms. Here, the authors compare the performance of MPTCP with each congestion control algorithm and packet scheduler one by one and try to find out the best-performing MPTCP. This paper also shows that the MPTCP helps COVID-19 patients in various aspects.
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In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.
ABSTRACT
In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.
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Maintaining the purported Social Separating is one of the essential and greatest ways to stop the new popular episode. Legislators are enacting restrictions on the standard of private distance between people in order to concur with this restriction. In light of this real-life occurrence, it is crucial to evaluate how consistent with realistic imperatives in our lives this is, in order to ascertain the causes of any prospective cracks in such distance obstacles and determine whether this portends an anticipated risk. In order to do this, we offer the Visual Social Removing (VSD) problem, which is defined as the automatic evaluation of the difference between the depiction of connected person aggregations and the private separation from an image.When this requirement is violated, it is vital for VSD to conduct painless research to determine whether people agree to the social distance restriction and to provide assessments of the degree of wellbeing of particular places. We first draw attention to the fact that measuring VSD involves more than simply math;it also suggests a deeper comprehension of the social behavior in the setting. The goal is to genuinely identify potentially dangerous circumstances while avoiding false alerts (such as a family with children or other family members, an elderly person with their guardians), all while adhering to current security protocols. Then, at that point, we discuss how VSD links to earlier research in social sign handling and demonstrate how to investigate fresh PC vision techniques that might be able to address this issue. Future issues about the viability of VSD systems, ethical repercussions, and potential application scenarios are the result. © 2023 IEEE.
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Social distancing plays an indispensable part during the ongoing pandemic. In this period, maintaining social distancing standards between people has turned into essential insurance to dial back the spreading of COVID-19. We present an original technique to recognize matches consequently of people in a jam-packed situation individuals do not maintain the social distance restriction, which calls for about 3 ft of space between them. This project assists in restricting the spread of the coronavirus by noticing the distance between disease-spreading people. Presently, it is absurd to expect to station an individual 24 × 7 at each line to screen social separating distance violations. For instance—banks, public offices, malls, schools, theatres, and so forth typically see long lines for hours consistently. To ensure social distancing in lines, this robot aids in monitoring the social distancing. Accordingly, this robot aids in maintaining the social distance between the crowd in a public environment to assist and forestall the spread of the virus. This robot serves to be an economical solution in public places where the gathering of people is significantly high. With appropriate obstacle detection, and crowd monitoring the official are also kept updated due to the Wi-Fi and IoT technology incorporated into a robot. This robot is expected to serve as a good solution in this pandemic time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.