Compact rover surveying and laser scanning for BIM development.

This paper presents a custom made small rover based surveying, mapping and building information modeling solution. Majority of the commercially available mobile surveying systems are larger in size which restricts their maneuverability in the targeted indoor vicinities. Furthermore their functional cost is unaffordable for low budget projects belonging to developing markets. Keeping in view these challenges, an economical indigenous rover based scanning and mapping system has developed using orthogonal integration of two low cost RPLidar A1 laser scanners. All the instrumentation of the rover has been interfaced with Robot Operating System (ROS) for online processing and recording of all sensorial data. The ROS based pose and map estimations of the rover have performed using Simultaneous Localization and Mapping (SLAM) technique. The perceived class 1 laser scans data belonging to distinct vicinities with variable reflective properties have been successfully tested and validated for required structural modeling. Systematically the recorded scans have been used in offline mode to generate the 3D point cloud map of the surveyed environment. Later the structural planes extraction from the point cloud data has been done using Random Sampling and Consensus (RANSAC) technique. Finally the 2D floor plan and 3D building model have been developed using point cloud processing in appropriate software. Multiple interiors of existing buildings and under construction indoor sites have been scanned, mapped and modelled as presented in this paper. In addition, the validation of the as-built models have been performed by comparing with the actual architecture design of the surveyed buildings. In comparison to available surveying solutions present in the local market, the developed system has been found faster, accurate and user friendly to produce more enhanced structural results with minute details.

Quality Metrics in Acute Stroke: Time to Own.

How to cite this article: Ahmed A. Quality Metrics in Acute Stroke: Time to Own. Indian J Crit Care Med 2023;27(11):786-787.

Omics data analysis reveals common molecular basis of small cell lung cancer and COVID-19.

The impact of COVID-19 infection on individuals with small cell lung cancer (SCLC) poses a serious threat. Unfortunately, the molecular basis of this severe comorbidity has yet to be elucidated. The present study addresses this gap utilizing publicly available omics data of COVID-19 and SCLC to explore the key molecules and associated pathways involved in the convergence of these diseases. Findings revealed 402 genes, that exhibited differential expression patterns in SCLC patients and also play a pivotal role in COVID-19 pathogenesis. Subsequent functional enrichment analyses identified relevant ontologies and pathways that are significantly associated with these genes, revealing important insights into their potential biological, molecular and cellular functions. The protein-protein interaction network, constructed under four combinatorial topological assessments, highlighted SMAD3, CAV1, PIK3R1, and FN1 as the primary components to this comorbidity. Our results suggest that these components significantly regulate this cross-talk triggering the PI3K-AKT and TGF-ß signaling pathways. Lastly, this study made a multi-step computational attempt and identified corylifol A and ginkgetin from natural sources that can potentially inhibit these components. Therefore, the outcomes of this study offer novel perspectives on the common molecular mechanisms underlying SCLC and COVID-19 and present future opportunities for drug development.Communicated by Ramaswamy H. Sarma.

Hybrid BO-XGBoost and BO-RF Models for the Strength Prediction of Self-Compacting Mortars with Parametric Analysis.

Self-compacting mortar (SCM) has superior workability and long-term durable performance compared to traditional mortar. The strength of SCM, including both its compressive and flexural strengths, is a crucial property that is determined by appropriate curing conditions and mix design parameters. In the context of materials science, predicting the strength of SCM is challenging because of multiple influencing factors. This study employed machine learning techniques to establish SCM strength prediction models. Based on ten different input parameters, the strength of SCM specimens were predicted using two different types of hybrid machine learning (HML) models, namely Extreme Gradient Boosting (XGBoost) and the Random Forest (RF) algorithm. HML models were trained and tested by experimental data from 320 test specimens. In addition, the Bayesian optimization method was utilized to fine tune the hyperparameters of the employed algorithms, and cross-validation was employed to partition the database into multiple folds for a more thorough exploration of the hyperparameter space while providing a more accurate assessment of the model's predictive power. The results show that both HML models can successfully predict the SCM strength values with high accuracy, and the Bo-XGB model demonstrated higher accuracy (R2 = 0.96 for training and R2 = 0.91 for testing phases) for predicting flexural strength with low error. In terms of compressive strength prediction, the employed BO-RF model performed very well, with R2 = 0.96 for train and R2 = 0.88 testing stages with minor errors. Moreover, the SHAP algorithm, permutation importance and leave-one-out importance score were used for sensitivity analysis to explain the prediction process and interpret the governing input variable parameters of the proposed HML models. Finally, the outcomes of this study might be applied to guide the future mix design of SCM specimens.

Musculoskeletal pain among desk-based officials of Bangladesh: Association with mental health and individual factors.

Musculoskeletal (MS) pain is widely prevalent and is an important health issue for desk-based employees which has a negative impact on both personal and work life. This study aimed to determine the MS pain status and its association with mental health and other individual factors among desk-based officials of Dhaka, Bangladesh. This cross-sectional study comprised a sample of 526 desk-based officials from Dhaka, Bangladesh. Data were collected between November 2020 to March 2021. MS pain was determined by the visual analog scale (VAS) and depression and anxiety were screened by Hospital Anxiety and Depression Scale (HADS). Logistic regression analyses were employed to estimate the adjusted effect of independent factors on MS pain. The overall prevalence of MS pain was 64% among desk-based officials. The corresponding prevalence were 19% severe, 21% moderate and 24% mild MS pain. In the adjusted model, gender (AOR: 0.19, 95% CI: 0.07-0.46), BMI (AOR: 0.28, 95% CI: 0.14-0.59), monthly income (AOR: 5.17, 95% CI: 2.18-12.25), organization type (AOR: 4.3, 95% CI:1.8-10.1), floor living (AOR: 4.7, 95% CI:2.1-10.8), physical activity (AOR: 0.16, 95% CI: 0.06-0.45), and lift facility in the house (AOR: 4.11, 95% CI: 2.06-8.23) were associated with MS pain. In addition, the prevalence of anxiety and depression was 17.7% and 16.4%, respectively. Depression was identified as a significant predictor for severe MS pain (AOR: 2.44, 95%CI:1.29-4.63). This study has revealed a relatively high prevalence of MS pain and mental health problems among Bangladeshi desk-based officials. Preventive measures need to be taken from both organizational and personal sides to delimitate MS pain and mental health problems.

Computation and memory optimized spectral domain convolutional neural network for throughput and energy-efficient inference.

Conventional convolutional neural networks (CNNs) present a high computational workload and memory access cost (CMC). Spectral domain CNNs (SpCNNs) offer a computationally efficient approach to compute CNN training and inference. This paper investigates CMC of SpCNNs and its contributing components analytically and then proposes a methodology to optimize CMC, under three strategies, to enhance inference performance. In this methodology, output feature map (OFM) size, OFM depth or both are progressively reduced under an accuracy constraint to compute performance-optimized CNN inference. Before conducting training or testing, it can provide designers guidelines and preliminary insights regarding techniques for optimum performance, least degradation in accuracy and a balanced performance-accuracy trade-off. This methodology was evaluated on MNIST and Fashion MNIST datasets using LeNet-5 and AlexNet architectures. When compared to state-of-the-art SpCNN models, LeNet-5 achieves up to 4.2× (batch inference) and 4.1× (single-image inference) higher throughputs and 10.5× (batch inference) and 4.2× (single-image inference) greater energy efficiency at a maximum loss of 3% in test accuracy. When compared to the baseline model used in this study, AlexNet delivers 11.6× (batch inference) and 5× (single-image inference) increased throughput and 25× (batch inference) and 8.8× (single-image inference) more energy-efficient inference with just 4.4% reduction in accuracy.

Anti-lung cancer drug discovery approaches by polysaccharides: an in silico study, quantum calculation and molecular dynamics study.

Lung cancer (LC) is one of the major and risky health defects even the serious cause for death in concurrent era. But no potential drugs even chemotherapeutic agents have been discovered with approval of health safety although some non-toxic biological macromolecules, such as polysaccharides and polysaccharide-protein complexes, have obtained as anti-lung cancer properties. This study conveys the anti-lung cancer properties of 45 polysaccharide derivatives collected from PubChem database. Primarily, the PASS prediction was performed to depict their anti-cancer activity, and 37 compounds showed the desired results. Next, the chemical descriptors, such as HOMO, LUMO, softness, and hardness etc, were calculated through the density functional theory (DFT) for quantum properties. Secondly, the auto molecular docking was executed to delineate the protein-ligand interactions, binding ability and inhibition of active sites of proteins. Additionally, the compounds showed docking score more than -6.40 kcal/mol, and the highest binding affinity was at -10.00 kcal/mol even 15 compounds have higher binding score (-8.6 to -10.0) than approved drugs, Gemcitabine. Succeeding, the most common protein residue, VAL 647, was blocked by ligands for the main protein (1X2J). In addition, five protein's active sites were determined to make the relative study of protein-ligand interactions. As a result, the target docking against five proteins was performed, and it was found that the targeted docking score as the binding affinity is lower than auto docking. Finally, a comparative study between auto docking and targeted docking was performed for the most common five lung cancer proteins founded in three organisms.Communicated by Ramaswamy H. Sarma.

Characterization and calibration of multiple 2D laser scanners.

This paper presents the comparative evaluation of multiple compact and lightweight 2D laser scanners for their possible backpack based scanning and mapping applications. These scanners include Hokuyo URG-04LX, Slamtec RPLidar A1-M8 and Hokuyo UTM-30LX-EW scanners. Since the technical datasheets provide general information and limited working details, this research presents a thorough study on the performance of each scanner related explicitly to indoor mapping operations. A series of scanning experiments have been performed for the characterization of each scanner using statistical analysis. During the testing, all the scanning data has been recorded using Robot Operating System (ROS) and then computed in offline processing. In initial tests, each scanner's drift effect on range measurements has been tested and presented in the relevant section of the paper. In continuation, the effect of various scanning distances on measurement accuracy has been evaluated and discussed. Later the impact of various materials typically found in indoor vicinities and their respective properties of color and smoothness have been tested and provided in the paper. Finally, a Kalman Filtering based mathematical formulation has been utilized to calibrate each scanner and to reduce the measuring uncertainties as observed in various tests for each scanner.

The Therapeutic Potential of Milk Extracellular Vesicles on Colorectal Cancer.

Colorectal cancer remains one of the leading prevalent cancers in the world and is the fourth most common cause of death from cancer. Unfortunately, the currently utilized chemotherapies fail in selectively targeting cancer cells and cause harm to healthy cells, which results in profound side effects. Researchers are focused on developing anti-cancer targeted medications, which is essential to making them safer, more effective, and more selective and to maximizing their therapeutic benefits. Milk-derived extracellular vesicles (EVs) from camels and cows have attracted much attention as a natural substitute product that effectively suppresses a wide range of tumor cells. This review sheds light on the biogenesis, methods of isolation, characterization, and molecular composition of milk EVs as well as the therapeutic potentials of milk EVs on colorectal cancer.

On-going consequences of in utero exposure of Pb: An epigenetic perspective.

Epigenetic modifications by toxic heavy metals are one of the intensively investigated fields of modern genomic research. Among a diverse group of heavy metals, lead (Pb) is an extensively distributed toxicant causing an immense number of abnormalities in the developing fetus via a wide variety of epigenetic changes. As a divalent cation, Pb can readily cross the placental membrane and the fetal blood brain barrier leading to far-reaching alterations in DNA methylation patterns, histone protein modifications, and micro-RNA expression. Over recent years, several human cohorts and animal model studies have documented hypermethylation and hypomethylation of developmental genes along with altered DNA methyl-transferase expression by in utero Pb exposure in a dose-, duration-, and sex-dependent manner. Modifications in the expression of specific histone acetyltransferase enzymes along with histone acetylation and methylation levels have been reported in rodent and murine models. Apart from these, down-regulation and up-regulation of certain microRNAs crucial for fetal development have been shown to be associated with in utero Pb exposure in human placenta samples. All these modifications in the developing fetus during the prenatal and perinatal stages reportedly caused severe abnormalities in early or adult age, such as impaired growth, obesity, autism, diabetes, cardiovascular diseases, risks of cancer development, and Alzheimer's disease. In this review, currently available information on Pb-mediated alterations in the fetal epigenome is summarized. Further research on Pb-induced epigenome modification will help to understand the mechanisms in detail and will enable us to formulate safety guidelines for pregnant women and developing children.

In-silico screening of bioactive phytopeptides for novel anti-ageing therapeutics.

A metabolic network of energy-sensing molecular pathways drives the biological ageing process. Regulating certain network elements can help decelerate the ageing process and ameliorate ageing associated disorders. Bioactive phytopeptides are a prospective avenue for anti-ageing therapeutics and rejuvenation biotechnology. The present study investigates the potential of therapeutic plant peptides against cellular senescence by targeting three key proteins in the ageing network - target of rapamycin (mTOR), adenosine monophosphate-activated protein kinase (AMPK) and sirtuin 1 (SIRT1). This investigation screened a library of reported bioactive peptides using standard cheminformatic methods including in-silico ADMET, molecular docking, molecular dynamics simulation and molecular mechanics calculation. The retrieved simulation data predict 25 diverse phytopeptides as potential safe and drug-like anti-ageing biologics with half-lives >20 h and bioavailability scores >0.40. The best docked peptide, Cycloleonuripeptide B, exhibited strong binding affinity and stable complex formation with mTOR (-17.5 kCal/mol), SIRT1 (-28.54 kCal/mol) and two active sites in AMPK (-41.8 kCal/mol; -36.0 kCal/mol) during molecular dynamics simulations. The computational study acts as a foundation for future laboratory and clinical research into the potential of repurposing therapeutic phytopeptides against cellular senescence and associated pathophysiology. Communicated by Ramaswamy H. Sarma.

The impact of COVID-19 on pregnancy and therapeutic drug development.

Emerging data show that pregnant women with COVID-19 are at significantly higher risk of severe outcomes compared with non-pregnant women of similar age. This review discusses the invaluable insight revealed from vaccine clinical trials in women who were vaccinated and inadvertently became pregnant during the trial period. It further explores a number of clinical avenues in their management and proposes a drug development strategy in line with clinical trials for vaccines and drug treatments for the drug development community. Little is known of the long-term effects of COVID-19 on the mother and the baby. Our hypothesis that COVID-19 predisposes pregnant women to pre-eclampsia or hypertensive disorders during pregnancy is supported by a clinical study, and this may also adversely impact a woman's cardiovascular disease risk later in life. It may also increase a woman's risk of pre-eclampsia in subsequent pregnancy. This is an ever-evolving landscape, and early knowledge for healthcare providers and drug innovators is offered to ensure benefits outweigh the risks. COVID-19 mRNA vaccines appear to generate robust humoral immunity in pregnant and lactating women. This novel approach to vaccination also offers new ways to therapeutically tackle disorders of many unmet medical needs. LINKED ARTICLES: This article is part of a themed issue on The second wave: are we any closer to efficacious pharmacotherapy for COVID 19? (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.10/issuetoc.

Predicting multi-enzyme inhibition in the arachidonic acid metabolic network by Heritiera fomes extracts.

Heritiera fomes is a mangrove plant with a rich history of ethnomedicinal usage against chronic inflammation. Biochemical analyses of H. fomes have exposed a plethora of bioactive phytochemicals that contribute to this therapeutic effect by perturbing enzymes of a complex inflammatory network mediated by arachidonic acid (AA) metabolism. This study is the first instance of utilizing cheminformatic approaches to elucidate a molecular linkage between these phytochemical interventions and the multi-enzyme AA metabolic network regulation. Analysis of the simulations reflects H. fomes as a functional reservoir of multiple safe and potent natural anti-inflammatory compounds. The investigation suggests two phytocompounds extracted from the plant: a sesquiterpene lactone and a flavone glycoside, as candidate inhibitors of multiple catalytic checkpoints of the inflammatory network. The outcomes of this research act as a primary guideline for future laboratory and clinical testing of anti-inflammatory potentials of H. fomes as an exploitable source of safe and potent drug-like molecules.Communicated by Ramaswamy H. Sarma.

Novel mutations in PDE6A and CDHR1 cause retinitis pigmentosa in Pakistani families.

AIM: To investigate the genetic basis of autosomal recessive retinitis pigmentosa (arRP) in two consanguineous/ endogamous Pakistani families. METHODS: Whole exome sequencing (WES) was performed on genomic DNA samples of patients with arRP to identify disease causing mutations. Sanger sequencing was performed to confirm familial segregation of identified mutations, and potential pathogenicity was determined by predictions of the mutations' functions. RESULTS: A novel homozygous frameshift mutation [NM_000440.2:c.1054delG, p. (Gln352Argfs*4); Chr5:g.149286886del (GRCh37)] in the PDE6A gene in an endogamous family and a novel homozygous splice site mutation [NM_033100.3:c.1168-1G>A, Chr10:g.85968484G>A (GRCh37)] in the CDHR1 gene in a consanguineous family were identified. The PDE6A variant p. (Gln352Argfs*4) was predicted to be deleterious or pathogenic, whilst the CDHR1 variant c.1168-1G>A was predicted to result in potential alteration of splicing. CONCLUSION: This study expands the spectrum of genetic variants for arRP in Pakistani families.

Microwave power penetration enhancement inside an inhomogeneous human head.

The penetration of microwave power inside a human head model is improved by employing a dielectric loaded rectangular waveguide as the transmission source. A multi-layer reflection model is investigated to evaluate the combined material characteristics of different lossy human head tissues at 2.45 GHz. A waveguide loaded with a calculated permittivity of 3.62 is shown to maximise the microwave power penetration at the desired frequency. A Quartz (SiO2) loaded rectangular waveguide fed by a microstrip antenna is designed to validate the power penetration improvement inside an inhomogeneous human head phantom. A measured 1.33 dB power penetration increment is observed for the dielectric loaded waveguide over a standard rectangular waveguide at 50 mm inside the head, with an 81.9% reduction in the size of the transmission source.

Hyperglycaemia up-regulates placental growth factor (PlGF) expression and secretion in endothelial cells via suppression of PI3 kinase-Akt signalling and activation of FOXO1.

Placenta growth factor (PlGF) is a pro-inflammatory angiogenic mediator that promotes many pathologies including diabetic complications and atherosclerosis. Widespread endothelial dysfunction precedes the onset of these conditions. As very little is known of the mechanism(s) controlling PlGF expression in pathology we investigated the role of hyperglycaemia in the regulation of PlGF production in endothelial cells. Hyperglycaemia stimulated PlGF secretion in cultured primary endothelial cells, which was suppressed by IGF-1-mediated PI3K/Akt activation. Inhibition of PI3K activity resulted in significant PlGF mRNA up-regulation and protein secretion. Similarly, loss or inhibition of Akt activity significantly increased basal PlGF expression and prevented any further PlGF secretion in hyperglycaemia. Conversely, constitutive Akt activation blocked PlGF secretion irrespective of upstream PI3K activity demonstrating that Akt is a central regulator of PlGF expression. Knock-down of the Forkhead box O-1 (FOXO1) transcription factor, which is negatively regulated by Akt, suppressed both basal and hyperglycaemia-induced PlGF secretion, whilst FOXO1 gain-of-function up-regulated PlGF in vitro and in vivo. FOXO1 association to a FOXO binding sequence identified in the PlGF promoter also increased in hyperglycaemia. This study identifies the PI3K/Akt/FOXO1 signalling axis as a key regulator of PlGF expression and unifying pathway by which PlGF may contribute to common disorders characterised by endothelial dysfunction, providing a target for therapy.

Medicated multi-targeted alginate-based dressings for potential treatment of mixed bacterial-fungal infections in diabetic foot ulcers.

Recently developed medicated dressings target either bacterial or fungal infection only, which is not effective for the treatment of mixed infections common in diabetic foot ulcers (DFUs). This study aimed to develop advanced bioactive alginate-based dressings (films and wafers) to deliver therapeutically relevant doses of ciprofloxacin (CIP) and fluconazole (FLU) to target mixed bacterial and fungal infections in DFUs. The alginate compatibility with the drugs was confirmed by SEM, XRD, FTIR and texture analysis, while the medicated wafers showed better fluid handling properties than the films in the presence of simulated wound fluid. The dressings showed initial fast release of FLU followed by sustained release of CIP which completely eradicated E. coli, S. aureus, P. aeruginosa and reduced fungal load (C. albicans) by 10-fold within 24 h. Moreover, the medicated dressings were biocompatible (>70% cell viability over 72 h) with human primary adult keratinocytes and in-vitro scratch assay showed 65-68% wound closure within 7 days.

Corona Collateral Damage Syndrome: Perception of the Damage.

How to cite this article: Ahmed A. Corona Collateral Damage Syndrome: Perception of the Damage. Indian J Crit Care Med 2021;25(4):358-359.

USH2A gene variants cause Keratoconus and Usher syndrome phenotypes in Pakistani families.

BACKGROUND: Retinitis pigmentosa (RP) is the most common inherited retinal dystrophy, affecting approximately 1 in 4000 individuals worldwide. The most common form of syndromic RP is Usher syndrome (USH) accounting for approximately 20-30 % of RP cases. Mutations in the USH2A gene cause a significant proportion of recessive non-syndromic RP and USH type II (USH2). This study aimed to determine the causative role of the USH2A gene in autosomal recessive inherited ocular diseases and to establish genotype-phenotype correlation associated with USH2A variants. METHODS: We performed direct Sanger sequencing and co-segregation analysis of the USH2A gene to identify disease causing variants in a non-syndromic RP family, two USH2 families and two Keratoconus (KC) families. RESULTS: Disease causing variants in the USH2A gene were identified in two families displayed KC and USH2 phenotypes. A novel variant c.4029T > G, p.Asn1343Lys in the USH2A gene was detected in a Pakistani family with KC phenotype. In addition, a missense variant (c.7334 C > T, p. Ser2445Phe) in the USH2A gene was found segregating in another Pakistani family with USH2 phenotype. Homozygosity of identified missense USH2A variants was found associated with autosomal recessive inherited KC and USH2 phenotypes in investigated families. These variants were not detected in ethnically matched healthy controls. Moreover, the USH2A variants were predicted to be deleterious or potentially disease causing by PolyPhen-2, PROVEAN and SIFT. CONCLUSIONS: This study provided first evidence for association of a novel USH2A variant with KC phenotype in a Pakistani family as well as established the phenotype-genotype correlation of a USH2A variant (c.7334 C > T, p. Ser2445Phe) with USH2 phenotype in another Pakistani family. The phenotype-genotype correlations established in present study may improve clinical diagnosis of affected individuals for better management and counseling.

Potential detrimental role of soluble ACE2 in severe COVID-19 comorbid patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the host cell by binding to angiotensin-converting enzyme 2 (ACE2) receptor. Other important proteins involved in this process include disintegrin and metalloproteinase domain-containing protein 17 (ADAM17) also known as tumour necrosis factor-α-converting enzyme and transmembrane serine protease 2. ACE2 converts angiotensin II (Ang II) to angiotensin (1-7), to balance the renin angiotensin system. Membrane-bound ACE2 ectodomain shedding is mediated by ADAM17 upon viral spike binding, Ang II overproduction and in several diseases. The shed soluble ACE2 (sACE2) retains its catalytic activity, but its precise role in viral entry is still unclear. Therapeutic sACE2 is claimed to exert dual effects; reduction of excess Ang II and blocking viral entry by masking the spike protein. Nevertheless, the paradox is why SARS-CoV-2 comorbid patients struggle to attain such benefit in viral infection despite having a high amount of sACE2. In this review, we discuss the possible detrimental role of sACE2 and speculate on a series of events where protease primed or non-primed virus-sACE2 complex might enter the host cell. As extracellular virus can bind many sACE2 molecules, sACE2 level could be reduced drastically upon endocytosis by the host cell. A consequential rapid rise in Ang II level could potentially aggravate disease severity through Ang II-angiotensin II receptor type 1 (AT1R) axis in comorbid patients. Hence, monitoring sACE2 and Ang II level in coronavirus disease 2019 comorbid patients are crucial to ensure safe and efficient intervention using therapeutic sACE2 and vaccines.