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The accurate analytical characterization of metastatic phenotype at primary tumor diagnosis and its evolution with time are critical for controlling metastatic progression of cancer. Here, we report a label-free optical strategy using Raman spectroscopy and machine learning to identify distinct metastatic phenotypes observed in tumors formed by isogenic murine breast cancer cell lines of progressively increasing metastatic propensities. Our Raman spectra-based random forest analysis provided evidence that machine learning models built on spectral data can allow the accurate identification of metastatic phenotype of independent test tumors. By silencing genes critical for metastasis in highly metastatic cell lines, we showed that the random forest classifiers provided predictions consistent with the observed phenotypic switch of the resultant tumors towards lower metastatic potential. Furthermore, the spectral assessment of lipid and collagen content of these tumors was consistent with the observed phenotypic switch. Overall, our findings indicate that Raman spectroscopy may offer a novel strategy to evaluate metastatic risk during primary tumor biopsies in clinical patients.

Shared understanding is essential in interorganizational projects to integrate the divergent knowledge of individual team members and support collaborative knowledge building. This can nevertheless be a challenging undertaking in interorganizational projects as team members must continuously negotiate differences in their organizational and professional backgrounds during project work. In this paper, we explore how interorganizational IT project teams deal with sources of ‘fragmentation’ in their understanding, explicating the theoretical and practical implications that these have for project management. Our study is needed to explore the increasingly complex and emergent nature of interorganizational project management today where neither goals nor the means of attainment are known with precision at a project's launch. We analyze interpretive case study findings from an 8-month IT project involving diverse organizations from industry, academia, and healthcare. Based on our findings, we develop a framework which highlights the relationship between three sources of fragmentation of understanding (interpersonal, technical, and contextual) across key project activities. We contribute towards project management literature by revealing how these sources of fragmentation might be overcome through framing project activities (the problem, method, and solution formulation) differently. While fragmentation may characterize any, or all, of these key activities, it is not without remedy.

Road accidents are incidents that should be avoided. One of the contributing factors of road accidents occurrence is drowsiness while driving due to fatigue. In this project, fatigue and drowsiness of a person can be detected by looking at the eye area. Drowsy situations are dangerous especially when driving a vehicle over long distances. When a person starts to feel drowsy, the eyes will start to blink more frequently. This characteristic can be used to monitor a driver’s fitness level. In this project the Viola-Jones algorithm using MATLAB cascade object detector was used to detect the presence of blinking eyes. The algorithm is consisted of three phases which are, selection of Haar-like characteristics, integrating a picture into the whole, and Classifiers in a cascading fashion. A number of 29 samples images consisting of the condition fatigue face and non-fatigue face was used. The obtained results obtained were calculated based on the accuracy value of the detected blinking eye. The result shows that both the total Area Under the Curve (AUC) values for faces with fatigue situations and non-fatigue situations are above acceptable values which is 0.5. This indicates both classifications are acceptable and can be used to detect the presence of blinking eyes which represent drowsiness.

E-commerce is one of the innovations that has started to become a new norm in this millennium. Due to the time-consuming physical shopping activities, the increase in living expenses, and the increase of responsibilities, people tend to find new ways to adapt to this new norm. Thus, buying groceries online has also been the preferred way for many people nowadays as it could save time and reduce daily hassles. This paper discusses the design and development of a web-based Groceries Ordering System with QR Code that was built using the web-based applications such as PHP, HTML and MySQL. The design and development of the prototype system involves three main phases, which are the system design, system development and system testing and took into consideration five criteria of the end-user satisfaction of an online shopping system, which are the system’s content, accuracy of information, format of the information displayed, ease of use and timeliness. The prototype system will also incorporate the QR code technology where it provides functions for information of products’ purchases and transactions. Upon completion of the prototype system, testing for usability among potential end-users was conducted, where it focusses on system’s usefulness, information quality and interface quality. Forty participants have completed the usability testing, and the results have showed that the Groceries Ordering System with QR Code has fulfilled all the five criteria of end user’s satisfaction

Zone-based solah times depend on the Earth's orbital movement around the sun. JAKIM has introduced zone-based solah times prescribes the times for the zones or areas. Nevertheless, the on-site calculation of zonal solah times is often informed by geographical and state Islamic affairs administrations. This study aims to survey the practices and methods employed to determine the Malaysian states' zonal solah times, using library research and interview approaches. The findings indicated that two typical methods used are the Westernmost Point and Multipoint Reference. Another alternative method provided by Falak experts is Isotime. Keywords: Zones Solah Times, Multi-Point Reference, West-most Point eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4.2918

According to the data published by JTB Tourism Research & Consulting Co., for the period beginning 1990 until 2019, the growth rate of inbound tourism in Japan has shown a steady increase which resulted in an average of 11.5% every year. This encouraging development was the result of the full-fledged ‘‘Inbound Tourism Initiative’’ campaign launched in 2003, which originally aimed at attracting 10 million foreign tourists to Japan in 2010. However, it is undeniable that there were so many challenges Japan had to overcome alongside that process due to problems that arise out of things beyond control such as natural disasters and epidemics. This article discusses in detail the volatile situation plaguing the inbound tourism industry in Japan. Analyzing from one single perspective that is why people would or would not travel to Japan, this paper seeks to observe how Japan managed to realize the inbound tourism rebound after disasters and epidemics. By employing secondary data analysis, this effort aims to present data about the determinants and factors influencing inbound tourism to Japan from as many countries as possible. This work will then examine in depth the challenges and opportunities that Japan might need to deal with in addressing the impact of COVID-19 on inbound tourism by taking Malaysia as a case study.

Purpose The appearance of the 2019 novel coronavirus (Covid-19), for which there is no treatment or a vaccine, formed a sense of necessity for new drug discovery advances. The pandemic of NCOV-19 (novel coronavirus-19) has been engaged as a public health disaster of overall distress by the World Health Organization. Different pandemic models for NCOV-19 are being exploited by researchers all over the world to acquire experienced assessments and impose major control measures. Among the standard techniques for NCOV-19 global outbreak prediction, epidemiological and simple statistical techniques have attained more concern by researchers. Insufficiency and deficiency of health tests for identifying a solution became a major difficulty in controlling the spread of NCOV-19. To solve this problem, deep learning has emerged as a novel solution over a dozen of machine learning techniques. Deep learning has attained advanced performance in medical applications. Deep learning has the capacity of recognizing patterns in large complex datasets. They are identified as an appropriate method for analyzing affected patients of NCOV-19. Conversely, these techniques for disease recognition focus entirely on enhancing the accurateness of forecasts or classifications without the ambiguity measure in a decision. Knowing how much assurance present in a computer-based health analysis is necessary for gaining clinicians’ expectations in the technology and progress treatment consequently. Today, NCOV-19 diseases are the main healthcare confront throughout the world. Detecting NCOV-19 in X-ray images is vital for diagnosis, treatment, and evaluation. Still, analytical ambiguity in a report is a difficult yet predictable task for radiologists. Method In this paper, an in-depth analysis has been performed on the significance of deep learning for Covid-19 and as per the standard search database, this is the first review research work ever made concentrating particularly on Deep Learning for NCOV-19. Conclusion The main aim behind this research work is to inspire the research community and to innovate novel research using deep learning. Moreover, the outcome of this detailed structured review on the impact of deep learning in covid-19 analysis will be helpful for further investigations on various modalities of diseases detection, prevention and finding novel solutions.

Background: The study aimed to assess the vision improvement with low vision aids (LVA) and functional vision among children learning in schools for the blind in North-East India. Material and methods: 515 students from 17 blind schools of North-East India were recruited. The comprehensive ocular examination, functional vision assessment, and vision assessment using LVA were carried out for all the subjects after determining the magnification required for each subject. Results: Of 515 children, 124 required LVA. Spectacle magnifiers were the most preferred (73 students, 58.87%), followed by magnifiers (50 students, 40.32%). A statistically significant improvement in the mean visual acuity was noted after the use of LVA (p < 0.001). Conclusion: A detailed assessment of low vision prior to admission to schools should be made mandatory in blind schools. These schools would be able to cater to really blind children, while children with low vision could attend regular schools.

This 21st century is notable for experiencing so many disturbances at economic, social, cultural, and political levels in the entire world. The outbreak of novel corona virus 2019 (COVID-19) has been treated as a Public Health crisis of global Concern by the World Health Organization (WHO). Various outbreak models for COVID-19 are being utilized by researchers throughout the world to get well-versed decisions and impose significant control measures. Amid the standard methods for COVID-19 worldwide epidemic prediction, easy statistical, as well as epidemiological methods have got more consideration by researchers and authorities. One main difficulty in controlling the spreading of COVID-19 is the inadequacy and lack of medical tests for detecting as well as identifying a solution. To solve this problem, a few statistical-based advances are being enhanced and turn into a partial resolution up-to some level. To deal with the challenges of the medical field, a broad range of intelligent based methods, frameworks, and equipment have been recommended by Machine Learning (ML) and Deep Learning. As ML and DL have the ability of identifying and predicting patterns in complex large datasets, they are recognized as a suitable procedure for producing effective solutions for the diagnosis of COVID-19. In this paper, a perspective research has been conducted in the applicability of intelligent systems such as ML, DL and others in solving COVID-19 related outbreak issues. The main intention behind this study is (i) to understand the importance of intelligent approaches such as ML and DL for COVID-19 pandemic, (ii) discussing the efficiency and impact of these methods in the prognosis of COVID-19, (iii) the growth in the development of type of ML and advanced ML methods for COVID-19 prognosis,(iv) analyzing the impact of data types and the nature of data along with challenges in processing the data for COVID-19,(v) to focus on some future challenges in COVID-19 prognosis to inspire the researchers for innovating and enhancing their knowledge and research on other impacted sectors due to COVID-19.

This research aims to investigate the effect of socio-scientific issues (SSI) based instruction on preservice science teachers’ soft skills and environmental awareness. By applying cluster random sampling, 83 preservice science teachers (PSTs) were selected from the Department of Science Education at a university in Indonesia. The participants were divided into two groups which comprised the experimental group who were taught using SSI-based instruction, while the control group received direct instruction. The quasi-experimental study was carried out through a pre- and posttest control group design. Data was gathered quantitatively using soft skills and environmental awareness questionnaires. The soft skills questionnaire comprised six sub-skills questions: communication, collaboration, problem-solving, creativity, teamwork, and social interaction. The environmental awareness questionnaire contained questions about the PSTs’ attitudes, behavior, and willingness to act. These sub-skills were developed based on literature studies and reviews of previous studies. Face validity was conducted by the experts, and Cronbach’s alpha coefficients of 0.84 (for soft skills) and 0.86 (for environmental awareness) were obtained. The data were analyzed using the Wilcoxon signed-rank test. The result showed that SSI-based instruction had a significant effect on improving preservice science teachers’ soft skills and environmental awareness. After being taught using SSI-based instruction, all the sub-skills of the soft skills of the experimental group had increased compared to before. A similar trend was also found in their scores for environmental awareness. All the components of environmental awareness, after lecturing using SSI-based instruction, showed a significant increase compared to before. These results support the claim that SSI-based instruction fosters soft skills and promotes environmental awareness.

We present 13 years old with history of cyanosis and diagnosis of congenitally corrected transposition of great arteries with ventricle septal defect and pulmonary stenosis with dextrocardia. He underwent modified Senning procedure with pulmonary root translocation. Postoperative recovery was uneventful and was extubated on postoperative day 1. Patient remained in sinus rhythm. Postoperative echocardiography showed good biventricular function with no baffle obstruction and mild pulmonary regurgitation with no significant left and right outflow tract obstruction. Patient was discharged on postoperative day 6 and remained asymptomatic on follow up at 3 months.

Increased penetration of power electronics interfaced renewable energy sources-based generation, for instance, wind farms, that displaces much of the conventional synchronous generation, has a profound effect on the inertia of modern/future power system networks. This article presents the development and validation of artificial neural network (ANN)-based tools, utilizing the power system variables measured by phasor measurement units through wide-area measurements systems, for estimation/forecasting of power system inertia with high penetration of wind farms. The development stage involves the correlation analysis to identify the best power system variables that can be nominated as inputs, and the training of the proposed inertia forecasting tools with the best-nominated inputs that are highly correlated with the power system inertia. Whereas, in the validation stage, the functionality of the trained ANN-based inertia forecasting tools have been validated using the hardware-in-the-loop testing facility developed at the University of Manchester. The development and validation procedures of the proposed inertia forecasting tools have been demonstrated on the IEEE 9-bus modified test system. The validation results revealed the effectiveness of the proposed inertia forecasting tools in estimating the inertia of modern/future power system networks with high penetration of wind farms.

A 47-year-old female underwent cardiac repair for tetralogy of Fallot at the age of 12 years. Subsequently, she was asymptomatic on follow-up. Recently, she presented elsewhere with palpitations and presyncope with documented ventricular tachycardia (VT) having left bundle branch block morphology with inferior QRS axis and late precordial transition. She was reported to have cardioverted and referred to our center for electrophysiology study (EP). She underwent EP study which induced clinical VT which was hemodynamically stable and the mechanism of VT was confirmed as re-entry. With the help of three-dimensional mapping system, VT circuit was identified in the posterior right ventricular outflow tract region between the pulmonary valve and upper end of ventricular septal defect patch. Delivery of radiofrequency energy during VT terminated the tachycardia with no further inducible VT despite aggressive pacing protocols.

Identification and classification of leukemia cells in a rapid and label-free fashion is clinically challenging and thus presents a prime arena for implementing new diagnostic tools. Quantitative phase imaging, which maps optical path length delays introduced by the specimen, has been demonstrated to discern cellular phenotypes based on differential morphological attributes. Rapid acquisition capability and the availability of label-free images with high information content have enabled researchers to use machine learning (ML) to reveal latent features. We developed a set of ML classifiers, including convolutional neural networks, to discern healthy B cells from lymphoblasts and classify stages of B cell acute lymphoblastic leukemia. Here, we show that the average dry mass and volume of normal B cells are lower than those of cancerous cells and that these morphologic parameters increase further alongside disease progression. We find that the relaxed training requirements of a ML approach are conducive to the classification of cell type, with minimal space, training time, and memory requirements. Our findings pave the way for a larger study on clinical samples of acute lymphoblastic leukemia, with the overarching goal of its broader use in hematopathology, where the prospect of objective diagnoses with minimal sample preparation remains highly desirable.

Aims and objective To study the effects of various components of "metabolic resuscitation" on the shock reversal among patients with septic shock. Introduction Sepsis is characterized by dysregulated host response to infection. Mitochondrial dysfunction which occurs early in sepsis is associated with multiorgan dysfunction. Therapies such as adequate resuscitation, early administration of antibiotics, and aggressive monitoring reduced mortality substantially but it still remains high for those with septic shock. Combination of vitamin C, hydrocortisone, and thiamine improved outcome in a retrospective study, but how effective is this therapy in isolation compared to combination has to be known before implementation. Materials and methods This study is single-center, prospective, randomized nonblinded trial done in septic shock patients admitted to the medical intensive care unit. Subjects were randomized to three groups of hydrocortisone (H), hydrocortisone, ascorbic acid (HA), hydrocortisone, ascorbic acid, thiamine (HAT). Following randomization, they received hydrocortisone 200 mg over 24 hours as infusion, intravenous ascorbic acid 1.5 g every 6 hours, thiamine 200 mg twice daily as allotted and continued till shock reversal or death. Primary outcome is time to shock reversal and secondary outcome is time to vasopressor dose reduction from hemodynamic SOFA score 4-3. Results Twenty seven subjects were randomized into 3 groups of 9 each, of which 17 (63%) patients met primary outcome and secondary outcome has been studied in 16 (59%) patients. Eight patients (29.5%) died and did not meet either outcome and two patients (7.5%) met secondary outcome but not primary outcome because of discharge to other hospital. There is no difference in time to shock reversal [mean, SD in H (7422, 8348), HA (2528, 3086), HAT (1860, 749), p value 0.17]. There is no difference in time to shock reversal from hemodynamic SOFA 4-3 [mean, SD in H (4935, 6406), HA (2310, 2515), HAT (1800, 1282), p value 0.35]. Conclusion In patients with septic shock, there is no difference in time to shock reversal comparing individual components of metabolic resuscitation. How to cite this article Reddy PR, Samavedam S, Aluru N, Yelle S, Rajyalakshmi B. Metabolic Resuscitation Using Hydrocortisone, Ascorbic Acid, and Thiamine: Do Individual Components Influence Reversal of Shock Independently? Indian J Crit Care Med 2020;24(8):649-652.

Academics and practitioners assume that knowledge sharing and knowledge integration are critical to effective team performance. However, the findings from empirical studies are at best mixed and in...

Background Fenestration of the baffle/conduit is believed to reduce pleural effusion following the Fontan operation. However, equivocal results have been observed with or without fenestration. This study aims to evaluate the efficacy of fenestration on the amount and duration of pleural effusion following the Fontan operation. Methods About 40 patients undergoing extracardiac Fontan (ECF) were randomized into two groups: one with fenestration (ECF-F; n = 20) or without fenestration (ECF-NF; n = 20). Primary outcome was the amount and duration of pleural effusions. Secondary outcomes were time to removal of the chest tubes, hospital stay, and readmission to the hospital because of recurrent pleural within 30 days of the operation. Results Mean age was 11.5 ± 5.07 (range, 8.7-13.5) years in the ECF-F group and 13.6 ± 0.4 years (range, 10.5-15.5) in the (ECF-NF) group. The total drain output was 7.89 mL/kg/d in ECF-NF compared with 6.9 mL/kg/d in the ECF-group (P = .14). Time for removal of pleural tubes was 14.6 ± 0.95 days in the ECF-NF group compared with 11.6 ± days in the ECF-F group. Total duration of hospital stay was higher but not significant in the ECF-NF group compared with the ECF-F group. Two patients in ECF-NF required readmission to the hospital within 30 days following discharge, while there were no readmissions in the ECF-F group. Conclusion Contrary to the literature, the creation of a fenestration in the ECF circuit was not clearly associated with a reduction in the amount and duration of pleural effusion compared with a non-fenestrated Fontan. These findings may be debatable in high risks versus low risk candidates. However in the present study, in a low risk canditates undergoing the Fontan operation, the daily amount of pleural drainage was no different. Larger studies are needed to confirm these findings.

Al-Istishraq is one of the subversive elements that have been corrupting Muslims into becoming radicalised, since the times of colonialism until present times. They denied the contribution of Islam in knowledge and civilizations resulting precedence in Muslim civilization becoming unclear. Al-Istishraq succeeds in misguiding and affecting integration among Muslims as Muslims blindly follow the ideologies. Prevention on such matter is challenging as scholars fail to provide comprehensive guidelines. The extremism numbers are alarming. It raises hatred and destruction of others. This article shall briefly review the impact and cause of al-Istishraq, and Muslims weaknesses in comprehend the spread. Keywords: Al-Istishraq; Islamic knowledge; Muslims, orientalism; religious extremism. eISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v5iSI1.2299

The primary aim around developing and optimizing an electronic health record is to improve patient care and population health. The objective of this study is to design and evaluate an action research approach for the optimization of the design of a summary page artefact within an electronic health record for newborn healthcare. An action research approach was chosen for its participatory democratic process for developing practical knowledge and solutions. Collaborative workshops lead by an independent graphic facilitator with a ‘bottom up’ approach, involving self-selected motivated members from multidisciplinary healthcare teams, were designed and conducted. To evaluate this approach, insights were drawn from behavioural and design science paradigms to demonstrate that knowledge and understanding of the design problem and its solution were acquired in building the optimized summary page artefact. Information system development for healthcare requires consideration not just of what we do but how and why we do things. Our analysis demonstrates that action design research represents an agile and lean approach for successful optimization and implementation of information system development in healthcare.

Aims and objectives The aim of the article was to study the safety profile of renin-angiotensin-aldosterone system (RAAS) inhibitor in COVID-19-affected Indian patients. Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for COVID-19 infection. There has been uncertainty about use of RAAS inhibitors in COVID-19. The association of RAAS inhibitors with severity of infection and clinical outcomes was addressed in this study. Materials and methods This is a single-center retrospective study from Indian intensive care unit (ICU). A total of 138 were included, who were divided into group A (RAAS inhibitor) and group B (non-RAAS inhibitor). They are followed up till ICU stay during which peak levels of ferritin, D dimer, interleukin-6 were noted (primary outcome). The number of ventilator days, ICU length of stay, and ICU outcome also compared. Results Of 138 patients, 18 are included in group A and 120, in group B. There is no difference in peak levels (mean) D dimer [5,893 vs 7,710, p 0.46], ferritin [2,388 vs 3,635, p 0.56], interleukin-6 [9,597 vs 3,625, p 0.06]. There is no difference in number of ventilator days (2.2 vs 1.78, p 0.53) and ICU length of stay (6.5 vs 6.1, p 0.74). Conclusion RAAS inhibitors can be safely continued in COVID-19 infection. It is not associated with an increase in severity of infection, ICU length of stay, and mortality. How to cite this article Reddy PR, Samavedam S, Aluru N, Rajyalakshmi B. Comparison of Severity of COVID-19 Infection among Patients Using RAAS Inhibitors and Non-RAAS Inhibitors. Indian J Crit Care Med 2021;25(4):366–368.

There are many successful interventions in medicine, especially in neurology and rehabilitation. The neurosciences represent an area of medicine with tremendous recent research innovations, one of which is virtual reality. This paper aims to discover the powerful relationship between virtual reality and rehabilitation. We assessed the effectiveness of virtual reality-based rehabilitation compared to conventional rehabilitation on motor function recovery of three patient groups: patients with a diagnosis of cerebral palsy, Parkinson's disease, or stroke. We conducted a systematic review using PubMed and included only articles that were randomized controlled trials that were published in the last five years. We used a general search in combination with a more focused Medical Subject Headings (MeSH) search. After thorough assessment and risk of bias evaluation using the Cochrane risk of bias tool, we included thirteen studies in this review. The majority of the clinical trials showed a statistically significant effect for improved motor function. More specifically, improvements in upper extremity motor function, gait, and balance in patients diagnosed with stroke were seen. Similarly, when evaluating patients with Parkinson's disease, improved gait and posture were also seen. When it came to cerebral palsy, however, there were no significant differences between the experimental group and the control. The level of improvement in motor function with a virtual reality intervention was striking, particularly since a few studies demonstrated sustained motor improvement a few months post-trial as well. Virtual reality-based rehabilitation has promising results for adult patients diagnosed with stroke or Parkinson's disease. For pediatric patients, on the other hand, a larger number of clinical trials would still need to be conducted to validate if virtual reality interventions have the capability of providing improved motor function recovery.

Purpose: The aim of this study was to describe causes of severe visual impairment and blindness (SVI/BL), and assess the mental health and quality of life of children in schools for the blind in North-East India in two phases. Methods: A total of 515 children were examined in 17 schools for the blind in the first phase of study across eight states in North-East India, 6 in Assam, 2 each in Meghalaya, Manipur, Mizoram, and Tripura, 1 each in Arunachal Pradesh, Nagaland, and Sikkim. WHO/PBL eye examination record was used to document findings. In the second phase of study, mental health and quality of life were objectively measured using depression anxiety stress scales (DASS) and low-vision quality of life (LVQOL) questionnaires in 442 children. Results: Approximately 3.1% of children had SVI and 71.84% of children were blind. Anatomical sites of SVI/BL were the whole globe in 44.85%, cornea in 17.66%, and retina in 11.65% of children. The underlying cause of visual loss was undetermined in 55% of children. Hereditary pattern was observed in 1.35% of cases. Approximately 74.94% of children were either blind or severely visually impaired since birth. DASS score revealed that 56.56% of children manifested some levels of anxiety and stress while 85.52% had some reduction in quality of life. Conclusion: A large significant number of these children suffered from potentially preventable and/or treatable cause of SVI/BL. Though nonvisual factors such as physical and mental health were strong predictors of quality of life, this study proves that visual impairment also plays a considerable role in one's quality of life in a population with low vision.

Amongst the many threats to health in our world, the most challenging ones are the ones with unknown causes. There is a mysterious epidemic of kidney disease called chronic kidney disease of unknown etiology (CKDu) that is occurring in many parts of the world. Unrelated to known risk factors such as diabetes and hypertension, CKDu mostly affects the young and middle-aged, with slight preponderance in males. It mostly occurs in people living in rural areas, especially working in agricultural jobs. Worldwide, the number of people with chronic kidney disease, and those who need dialysis and renal replacement, is increasing every year as compared to other chronic conditions like diabetes and AIDS. It's not just alarming but a great challenge to healthcare systems across the world, especially in resource-poor countries. CKDu has become a silent killer for most patients. The occurrence of end-stage renal disease (ESRD) in CKDu can be catastrophic for individuals, especially in countries with limited medical facilities, causing a significant socio-economic burden. Even within these economically developing nations, people affected by CKDu usually are from the most vulnerable and underserved populations. As a definitive etiology has not been postulated for CKDu to date, this comprehensive review was undertaken to throw light on the poorly understood epidemiologic risk factors and the course of the disease.

Hysterectomy is a commonly performed gynecologic surgery that can be associated with significant morbidity and mortality. However, the evolution of the surgical approach, from open to minimally invasive gynecologic surgery (MIGS), has substantially improved patient outcomes by reducing perioperative complications, pain, and length of hospitalization. The evident advantages and the approval of the da Vinci Surgical System by the Food and Drug Administration led to the exponential rise in the use of MIGS. In particular, robotic hysterectomy (RH) witnessed unparalleled popularity compared to other MIGS despite the lack of strong evidence demonstrating its superiority. Therefore, we conducted a systematic review of the literature to evaluate and compare various patient and surgical outcomes of RH with conventional laparoscopic hysterectomy (CLH), including operating time, estimated blood loss, length of hospitalization, overall complications, survival, and cost. Overall, the outcomes were comparable between RH and CLH except concerning cost. RH is significantly more expensive than CLH due to the higher costs of robotic equipment, including disposable instruments, equipment maintenance, and sterilization. Although RH demonstrated comparable outcomes and higher costs, its technical advantages such as improved ergonomics, three-dimensional view, a wider range of wristed mobility, mechanical lifting of robot’s hand, and greater stability might benefit patient subsets (e.g., obesity, large uterine weights >750 g). Therefore, large and multicentered randomized control trials are imperative to determine the most effective surgical approach between RH and other MIGS for different patient subsets.

Inflammatory bowel disease (IBD) is an autoimmune disease associated with dysbiosis within the gastrointestinal tract. Characteristic taxonomic shifts of microbial populations are observed in disease progression and remission; however, despite similarities, there are many differences among individuals presenting with IBD including IBD subset, clinical course, and response to therapy. Much is still unknown about how these taxonomic shifts interact with immunotherapy and how genetic variants contribute. In this systematic review, we aimed to compile information on the interactions of the gut microbiome with immunotherapy in the course of disease and treatment of IBD patients. This systematic review was conducted as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PubMed database was methodically screened for literature search including keywords and Medical Subject Headings (MeSH) terms for relevant articles. The quality appraisal was completed using the Cochrane Tool, Newcastle-Ottawa checklist, and the Scale for the Assessment of Narrative Review Articles (SANRA) checklist, as appropriate, and 11 relevant articles were included in this systematic review. Our review concludes that although there are characteristic taxonomic shifts between diseased and healthy patients, genetic variants are an important consideration in the predictive quality of disease and treatment decisions. The comparison between interactions of microbial populations and treatment in addition to the role of genetic variants may provide insight into treatment non-responders. Due to our limitations in current knowledge including the complexity of the microcosm, ethnic genetic variations among human populations, and our focus on relevant articles published in English over the past six years, we may have missed relevant studies. Future studies should focus on the comparison between Western and other cultural populations as well as further implementation of Genome-Wide Association Studies (GWAS) in clinical predictability.

BACKGROUND Pre-examination stress is a common condition faced by the students prior to exams and is emerging as a major health problem, especially in medical students. The present study was undertaken to evaluate the effect of pre-examination stress on autonomic functions like pulse rate and blood pressure in the first M.B.B.S. students. MATERIALS AND METHODS The study group consisted of 100 medical students studying 1st M.B.B.S. in Andhra Medical College, Visakhapatnam. Among them, 45 students were males, 55 students were females. Their arterial blood pressure and pulse rate were measured one month prior to examination and again one week before examination. The data was analysed using student’s paired ‘t’ test. RESULTS In the present study, the results were consistent with early clinical studies reporting that there is increase in pulse rate, systolic blood pressure, diastolic blood pressure, one week before examination compared to values of one month before examination. CONCLUSION Majority of the students were under stress prior to examination. Stress produced a significant increase in the pulse rate, systolic blood pressure and diastolic blood pressure among the students. Relaxation techniques like meditation, yoga, breathing exercises, appropriate diet and physical exercises can be recommended to students.

The widespread use of electronic Personal Health Records is considered of great importance, however, until today, there is no widely adopted application paradigm for the functional specifications of a modern ePHR due to absence of trust, inadequate data completeness and overall use complexity and “unfriendliness”. CO.R.E. (COnsolidation & Routing Engine) is an innovative approach towards the development of a health data consolidation and cloud access provision infrastructure, taking under consideration both the needs for wide adoption and the application of mission critical technologies in real production environments. The CO.R.E. infrastructure provides an environment for deploying medical record applications with central storage and individually controlled distributed access, ensuring: a) the absence of readable identifiers in any network communication among the involved systems and b) the inability (as much as modern cryptographic methods offer) of anyone - even the engineers working on the system - to correlate the stored medical data with their owner/physical person.

Graphical Abstract COVID-19 is an infectious respiratory illness caused by the virus strain severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and until now, there is no effective therapy against COVID-19. Since SARS-CoV-2 binds to angiotensin-converting enzyme 2 (ACE2) for entering into host cells, to target COVID-19 from therapeutic angle, we engineered a hexapeptide corresponding to the ACE2-interacting domain of SARS-CoV-2 (AIDS) that inhibits the association between receptor-binding domain-containing spike S1 and ACE-2. Accordingly, wild type (wt), but not mutated (m), AIDS peptide inhibited SARS-CoV-2 spike S1-induced activation of NF-κB and expression of IL-6 in human lungs cells. Interestingly, intranasal intoxication of C57/BL6 mice with recombinant SARS-CoV-2 spike S1 led to fever, increase in IL-6 in lungs, infiltration of neutrophils into the lungs, arrhythmias, and impairment in locomotor activities, mimicking some of the important symptoms of COVID-19. However, intranasal treatment with wtAIDS, but not mAIDS, peptide reduced fever, protected lungs, improved heart function, and enhanced locomotor activities in SARS-CoV-2 spike S1-intoxicated mice. Therefore, selective targeting of ACE2-to-SARS-CoV-2 interaction by wtAIDS may be beneficial for COVID-19. Supplementary Information The online version contains supplementary material available at 10.1007/s11481-020-09979-8.

United Nations Sustainable Development Goal (UN SDG) 12.6 aims to “encourage companies, especially large and transnational companies, to adopt sustainable practices and to integrate sustainability information into their reporting cycle” [43]. Using Design Science Research, GReenstreets Integrated Packaging Sustainability reporting system (“GRIPS”) is an expository artefact built using the BAO design theory for green information systems (Green IS) (c.f. Recker) [34]. The artefact aims to support organizations in overcoming sustainability challenges by providing information to help them make effective decisions around packaging sustainability and to facilitate the move from eco-efficiency to eco-effectiveness practices. This study adds to practice by helping companies to act, measure and monitor the move towards eco-effective packaging. It adds to research by providing an expository artefact based on the design theory for Green IS proposed by Recker.

Background Lithium is especially taken as a maintenance medication for Bipolar Disorder. In women with bipolar disorder, lithium is often effective during postpartum period, but breast-feeding for medicated mothers is controversial because of harmful effects for her child. At present, the biological mechanisms of lithium are not well-understood, affecting its usage and overall health implications. Procedure We developed a rat lithium and breast-feeding model at human therapeutic levels to study the effects of lithium exposure through breast-milk on pups' thyroid function. Novel laser analytical spectroscopy, along with traditional blood and immunohistochemical tests, were applied to further investigate the mechanisms behind the thyroid dysfunction. Maternal iodine supplementation was evaluated as a therapeutic method to address the pups' thyroid dysfunction. Results Pups exposed to lithium via breastmilk, even with the dam on a sub-therapeutic level, experienced weight gain, reduced blood thyroxine (T4 ), and elevated blood urea nitrogen, indicating effects on thyroid and kidney function. We show that lithium inhibited iodine uptake by thyroid follicles, initiating a mechanism that reduced iodination of tyrosine, thyroglobulin cleavage, and thyroid hormone production. Importantly, infant thyroid function can be significantly improved by administering supplementary iodine to the medicated dam's diet during breast-feeding. Conclusion These results elucidate the mechanisms of lithium in thyroid function, provide valuable information on use postpartum, and suggest a clinically applicable remedy to side-effects. The results are particularly important for patients (and their infants) who respond well to lithium and need, or choose, to breast-feed.

Purpose The study aims to provide insights in the sensemaking process and the use of business analytics (BA) for project selection and prioritisation in start-up settings. A major focus is on the various ways start-ups can understand their data through the analytical process of sensemaking. Design/methodology/approach This is a comparative case study of two start-ups that use BA in their projects. The authors follow an interpretive approach and draw from the constructivist grounded theory method (GTM) for the purpose of data analysis, whereby the theory of sensemaking functions as the sensitising device that supports the interpretation of the data. Findings The key findings lie within the scope of project selection and prioritisation, where the sensemaking process is implicitly influenced by each start-up's strategy and business model. BA helps start-ups notice changes within their internal and external environment and focus their attention on the more critical questions along the lines of their processes, operations and business model. However, BA alone cannot support decision-making around less structured problems such as project selection and prioritisation, where intuitive judgement and personal opinion are still heavily used. Originality/value This study extends the research on BA applied in organisations as tools for business development. Specifically, the authors draw on the literature of BA tools in support of project management from multiple perspectives. The perspectives include but are not limited to project assessment and prioritisation. The authors view the decision-making process and the path from insight to value, as a sensemaking process, where data become part of the sensemaking roadmap and BA helps start-ups navigate the decision-making process.

A smart city is an enhanced urban area that shines in the field of governance, economy, social capital, people and life through strong human capital. It is a novel advance to raise the effectiveness, decrease the expenses, control the difficulty of city life and enhance the standard of living of the people. These applications of smart cities hold the upcoming vision of cities, which intends at developing the information and communication technology (ICT) infrastructure, i.e., Internet of things (IoT) for worth added service delivery. Because of these raising improvements in sophisticated digital technologies, smart cities have been set with several electronic devices with the usage of IoT. In this paper, a detailed investigation has been conducted on the significance, usage levels as well as advancements of IoT-based smart cities. Also, few challenging issues along with the limitations of IoT-based smart cities are realized. Also, this paper aims to inspire and motivate researchers to innovate novel solutions for smart cities with the help of IoT technology.

Huntington's disease (HD) is a neurodegenerative disorder characterized by accumulation of mutant huntingtin protein and significant loss of neurons in striatum and cortex. Along with motor difficulties, the HD patients also manifest anxiety and loss of cognition. Unfortunately, the clinically approved drugs only offer symptomatic relief and are not free from side effects. This study underlines the importance of glyceryl tribenzoate (GTB), an FDA-approved food flavoring ingredient, in alleviating HD pathology in transgenic N171-82Q mouse model. Oral administration of GTB significantly reduced mutant huntingtin level in striatum, motor cortex as well as hippocampus and increased the integrity of viable neurons. Furthermore, we found the presence of sodium benzoate (NaB), a FDA-approved drug for urea cycle disorders and glycine encephalopathy, in the brain of GTB-fed HD mice. Accordingly, NaB administration also markedly decreased huntingtin level in striatum and cortex. Glial activation is found to coincide with neuronal death in affected regions of HD brains. Interestingly, both GTB and NaB treatment suppressed activation of glial cells and inflammation in the brain. Finally, neuroprotective effect of GTB and NaB resulted in improved motor performance of HD mice. Collectively, these results suggest that GTB and NaB may be repurposed for HD.

Lithium is a major psychiatric medication, especially as long-term maintenance medication for Bipolar Disorder. Despite its effectiveness, lithium has side-effects, such as on renal function. In this study, lithium was administered to adult rats. This animal model of renal function was validated by measuring blood lithium, urea nitrogen (BUN), and thyroxine (T4) using inductively-coupled plasma mass spectrometry and enzyme-linked immunosorbent assay. The kidneys were analyzed by laser induced breakdown spectroscopy (LIBS) with 1064 nm ablation and 300-900 nm detection. Principal components analysis (PCA), radial visualization, and random forest classification were performed on the LIBS spectra for multi-element prediction and classification. Lithium at 0.34 mmol/L was detected in the blood of lithium treated subjects only. BUN was increased (6.6 vs. 5.3 mmol/L) and T4 decreased (58.12 vs. 51.4 mmol/L) in the blood of lithium subjects compared with controls, indicating renal abnormalities. LIBS detected lithium at 2.3 mmol/kg in the kidneys of lithium subjects only. Calcium was also observed to be reduced in lithium subjects, compared with controls. Subsequent PCA observed a change in the balance of sodium and potassium in the kidneys. These are key electrolytes in the body. Importantly, partial least squares regression showed that standard clinical measurements, such as the blood tests, can be used to predict kidney electrolyte measurements, which typically cannot be performed in humans. Overall, lithium accumulates in the kidneys and adversely affects renal function. The effects are likely related to electrolyte imbalance. LIBS with machine learning analysis has potential to improve clinical management of renal side-effects in patients on lithium medication.

Since the past decades, most of the nature inspired optimization algorithms (NIOA) have been developed and become admired due to their effectiveness for resolving a variety of complex problems of dissimilar domain. Firefly algorithm (FA) is well-known, yet efficient nature inspired swarm intelligence (SI) based metaheuristic algorithm. Since from its initiation, FA has become well-liked between the researchers due to its competence and turn out to be an interesting technique for the practitioners as well as researchers for solving the problems of numerous fields of research such as classifications, clustering, neural networks, biomedical engineering, healthcare as well as other research domain. Moreover, there is an outstanding track record of FA in solving biomedical engineering (BME) and healthcare (HC) problems. Abundant complexities have been worked out with the assist of FA and its variants. By taking these particulars into concern, in this paper, a first ever in-depth analysis has been addressed on the variants, importance, applications as well as enhancements of FA in BME as well as HC. The major intention behind this investigative work is to motivate the researchers to improve and innovate new solutions for multifaceted problems of healthcare and biomedical engineering using FA.

ObjectivesTo explore and reflect on the current anticoagulation therapy offered to patients with atrial fibrillation (AF), potential challenges and the future vision for oral anticoagulants for patients with AF and healthcare professionals in Ireland.DesignA multistakeholder focus group using a World Café approach.ParticipantsNine participants from academic, clinical and health backgrounds attended the focus group together with a facilitator.ResultsEnhanced patient empowerment; more effective use of technology and developing system-based medical care pathways would provide improved supports for AF management. The challenges in providing these include cost and access issues, the doctor–patient relationship and the provision of education. While consensus for developing evidence-based pathways to maximise efficiency and effectiveness of AF treatment was evident, it would require a shared vision between stakeholders of integrated care. The benefits of embracing technological advances for clinicians and patients were evident; however, clinicians indicate this can increase pressure on already stretched resources; coupled with institutional barriers (including scarce resources) arising from the complex nature of anticoagulation for patients with AF, which emerged strongly. Including the unpredictable nature of warfarin, hidden costs associated with monitoring, adverse clinical effects, different patient cohorts (including those prescribed anticoagulant for the first time vs those switching from warfarin to a new oral anticoagulant (NOAC)), non-adherence concerns and undesirable impacts on patients’ daily lives.ConclusionsWhile anticoagulation therapy for patients with AF using NOACs has been widely adopted and is diffusing into routine practice, significant operationalisation issues and barriers to effective treatment/management persist. The reflections reported in this study are a catalyst for future discussion and research.

This study explores the factors that hinder IT departments in moving towards a consumption-based operating model (OpEx). The study explores the views of major stakeholders in a large global technology company on the possible introduction of the model. These views are triangulated with those of a select number of external experts. IT funding decisions have been complex problems for organisations. In the real world there are conflicts between the nominal IT funding practices and the actual IT operational practices currently being employed. The IT funding process skews the downstream management controls. Further research is required to understand the dynamism between the two. The study uses the lens of Behavioural Cloudonomics, which is at the intersection of psychology, economics, and the cloud and is well positioned to help us understand and address the factors that underpin the economic decision-making behaviours around the move to the Cloud.

Since its initiation, ANN became popular and also plays a key role in enhancing the latest technology. With an increase in industrial automation and the Internet of Things, now it is easier than ever to collect data and monitor food drying, extrusion, and sterilization, etc. In this industrial revolution, the uses of ANN are found successful in food processing tasks like food grading, safety, and quality check, etc. In recent years, attention on shallow learning approach (i.e. use of earlier developed ANNs) in food processing is escalating as researchers found it extensive exploitation in resolving a lot of complex real-world problems in food processing. In this row, deep learning techniques have not left any stone unturned in the context of intelligent food processing paradigm. In this paper, a detailed analysis has been reported on the advancements of food processing using ANNs, which include the details journey from shallow learning to deep learning in the applications space. Such fusion of technology with the forefront of machine learning, deep learning, and image processing for food processing, is not just the mixture of hybrid concepts, rather it provides a scope to create new dimensions and growth opportunities for each innovation.

Nature-inspired algorithms are the current state-of-the-art optimization algorithms which are quite popular due to their high employability and hence became powerful algorithms for solving unique problems of many research areas. These algorithms have been categorized into swarm intelligence, evolutionary as well as others, etc. On the basis of problem type, these algorithms have been applied to solve and to cope up with such type of complex problems. Many algorithms were simulated and inspired by nature as well as proved to be efficient are mostly swarm intelligence-based algorithms such as ACO, ABC and PSO. Also, novel algorithms are being developed and introduced day by day. Out of such developed algorithms, moth flame optimization (MFO) has gained a wider level popularity due to its significant applicability. In this paper, a comprehensive analysis is made on the applicability of MFO as well as its variants by considering the research related to MFO from its initiation up to the year 2020. The major aim of this survey is to motivate the researchers of optimization community to use MFO for solving unapplied problems.

Background Health information technology (HIT) and associated data analytics offer significant opportunities for tackling some of the more complex challenges currently facing the health care sector. However, to deliver robust health care service improvements, it is essential that HIT solutions be designed by parallelly considering the 3 core pillars of health care quality: clinical effectiveness, patient safety, and patient experience. This requires multidisciplinary teams to design interventions that both adhere to medical protocols and achieve the tripartite goals of effectiveness, safety, and experience. Objective In this paper, we present a design tool called Integrated Patient Journey Mapping (IPJM) that was developed to assist multidisciplinary teams in designing effective HIT solutions to address the 3 core pillars of health care quality. IPJM is intended to support the analysis of requirements as well as to promote empathy and the emergence of shared commitment and understanding among multidisciplinary teams. Methods A 6-month, in-depth case study was conducted to derive findings on the use of IPJM during Learning to Evaluate Blood Pressure at Home (LEANBH), a connected health project that developed an HIT solution for the perinatal health context. Data were collected from over 700 hours of participant observations and 10 semistructured interviews. Results The findings indicate that IPJM offered a constructive tool for multidisciplinary teams to work together in designing an HIT solution, through mapping the physical and emotional journey of patients for both the current service and the proposed connected health service. This allowed team members to consider the goals, tasks, constraints, and actors involved in the delivery of this journey and to capture requirements for the digital touchpoints of the connected health service. Conclusions Overall, IPJM facilitates the design and implementation of complex HITs that require multidisciplinary participation.

BACKGROUND Hearing impairment is one of the commonest congenital disabilities in the world. The prevalence of congenital hearing loss has been estimated to be 1.2-5.7 per 1,000 live births and is more among high risk neonates. Screening is one of the most important methods for early diagnosis of hearing loss. Otoacoustic emission is an easy, cost effective and reliable method of testing of large number of infants for hearing loss. The present study emphasizes the use of otoacoustic emissions as a screening tool to detect hearing loss that would otherwise go unnoticed till 2-3 years. MATERIALS AND METHODS This descriptive study was conducted on 1000 neonates during the period August 2015 to August 2016. Neonates were selected from the department of Paediatrics, the department of Obstetrics and OPD of ENT of Konaseema Institute of Medical Sciences, Amalapuram, Andhra Pradesh. Neonates between 24-72 hours of age were screened with DPOAE. Those who failed the first DPOAE screen were subjected to a second DPOAE screening after 2 to 3 months. RESULTS Out of 1000 neonates, 0.9% had persistent failure with OAE test. The factors which had significant relationship with hearing loss include prenatal risk factors like foetal distress, eclampsia, maternal infection, low birth weight, ototoxic drugs. Data was statistically analysed by McNemar’s test and Chi-square test. CONCLUSION The two staged screening protocol with Distortion Product Otoacoustic Emission was found to be a useful tool in detecting hearing loss in newborn. It is important and logical from the point of health and economy that the screening tests should become necessary for all neonates.

Studying in a foreign country is one of the ways to enhance students’ competencies in facing challenges of global competitiveness and in being marketable for future career choices. This research investigates the impact of cross-cultural adaptation among Malaysian students (N=245) who enrolled in various universities in Japan. Quantitative method was used to examine changes in the following five factors: personal changes, cross-cultural awareness, cross-cultural interaction, global mindedness and intellectual development. The findings demonstrate that studying abroad brings positive outcomes in students’ personal development. Hence, student mobility is an invaluable experience and administrators should support and encourage young people to explore “real life” globally.

BACKGROUND Thyroid carcinoma is overwhelmingly the most common type of endocrine malignancy. Clinically-recognised thyroid carcinomas constitute less than 1% of all malignant tumour. Improvements in diagnostics and understanding the pathophysiology have made the treatment more effective with good long-term results. The aim of the study is to study the clinical pattern, behaviour and management of carcinoma of thyroid. MATERIALS AND METHODS 50 patients of histopathologically-proven thyroid cancers treated during the period of 2 years from May 2006 to May 2008 were studied. Detailed history and physical findings were noted along with the investigations and treatment given. RESULTS Thyroid carcinoma formed 1.5% of all cancers treated during the period. It formed 17.45% of all thyroid swellings admitted for treatment during the same period. The ratio of female-to-male in this study was 2.9:1. Most of the cases of carcinoma (82%) were seen in the 21-50 years age group. All patients in this study had a goitre and 20% of patients presented with lymphadenopathy and hoarseness of voice. Fine-Needle Aspiration Cytology (FNAC) was the common diagnostic test done. Total thyroidectomy was the most common surgery done and papillary carcinoma was the most common histopathology seen. Transient hypocalcaemia was the most common postoperative complication seen in 20% of patients. CONCLUSION Thyroid cancers affect young adult females presenting as slow growing tumours. Majority of the tumours are papillary type in the early stage with good prognosis. FNAC is a simple test to detect cancer and total thyroidectomy is the procedure of choice for treatment.