A graph neural network approach for predicting drug susceptibility in the human microbiome.

Recent studies have illuminated the critical role of the human microbiome in maintaining health and influencing the pharmacological responses of drugs. Clinical trials, encompassing approximately 150 drugs, have unveiled interactions with the gastrointestinal microbiome, resulting in the conversion of these drugs into inactive metabolites. It is imperative to explore the field of pharmacomicrobiomics during the early stages of drug discovery, prior to clinical trials. To achieve this, the utilization of machine learning and deep learning models is highly desirable. In this study, we have proposed graph-based neural network models, namely GCN, GAT, and GINCOV models, utilizing the SMILES dataset of drug microbiome. Our primary objective was to classify the susceptibility of drugs to depletion by gut microbiota. Our results indicate that the GINCOV surpassed the other models, achieving impressive performance metrics, with an accuracy of 93% on the test dataset. This proposed Graph Neural Network (GNN) model offers a rapid and efficient method for screening drugs susceptible to gut microbiota depletion and also encourages the improvement of patient-specific dosage responses and formulations.

Exploring fractional-order new coupled Korteweg-de Vries system via improved Adomian decomposition method.

This paper aims to extend the applications of the projected fractional improved Adomian Decomposition method (fIADM) to the fractional order new coupled Korteweg-de Vries (cKdV) system. This technique is significantly recognized for its effectiveness in addressing nonlinearities and iteratively handling fractional derivatives. The approximate solutions of the fractional-order new cKdV system are obtained by employing the improved ADM in fractional form. These solutions play a crucial role in designing and optimizing systems in engineering applications where accurate modeling of wave phenomena is essential, including fluid dynamics, plasma physics, nonlinear optics, and other mathematical physics domains. The fractional order new cKdV system, integrating fractional calculus, enhances accuracy in modeling wave interactions compared to the classical cKdV system. Comparison with exact solutions demonstrates the high accuracy and ease of application of the projected method. This proposed technique proves influential in resolving fractional coupled systems encountered in various fields, including engineering and physics. Numerical results obtained using Mathematica software further verify and demonstrate its efficacy.

Insight into the interaction of isochroman with bovine serum albumin: extensive experimental and computational investigations.

The way therapeutic compounds interact with serum protein provides valuable information on their pharmacokinetics, toxicity, effectiveness, and even their structural-related information. Isochroman (IC) is a phytochemical compound obtained from the leaves of Olea europea plant. The derivatives of IC have various pharmacological properties including antidepressants, antihistamines, antiinflammation, anticonvulsants, appetite depressants, etc. The binding of small molecules to bovine serum albumin (BSA) is useful to ensure their efficacy. Thus, in this study, we have found out the binding mode of IC with BSA using several spectroscopic and in silico studies. UV and fluorescence spectroscopy suggested the complex formation between IC and BSA with a binding constant of 103 M-1. IC resulted in fluorescence quenching in BSA through static mechanism. The microenvironmental and conformational changes in BSA were confirmed using synchronous and three-dimensional studies. Site marker experiment revealed the IC binding in site-III of BSA. The influence of vitamins, metals and ß-cyclodextrin (ß-CD) on binding constant of IC-BSA complex was also examined. Circular dichroism spectra showed that α-helical of BSA decreased upon interaction with IC. Computational and experimental results were complimentary with one another and assisted in determining the binding sites, nature of bonds and amino acids included in the IC-BSA complex formation.Communicated by Ramaswamy H. Sarma.

Cis-regulatory control of mammalian Trps1 gene expression.

TRPS1 serves as the causative gene for tricho-rhino phalangeal syndrome, known for its craniofacial and skeletal abnormalities. The Trps1 gene encodes a protein that represses Wnt signaling through strong interactions with Wnt signaling inhibitors. The identification of genomic cis-acting regulatory sequences governing Trps1 expression is crucial for understanding its role in embryogenesis. Nevertheless, to date, no investigations have been conducted concerning these aspects of Trps1. To identify deeply conserved noncoding elements (CNEs) within the Trps1 locus, we employed a comparative genomics approach, utilizing slowly evolving fish such as coelacanth and spotted gar. These analyses resulted in the identification of eight CNEs in the intronic region of the Trps1 gene. Functional characterization of these CNEs in zebrafish revealed their regulatory potential in various tissues, including pectoral fins, heart, and pharyngeal arches. RNA in-situ hybridization experiments revealed concordance between the reporter expression pattern induced by the identified set of CNEs and the spatial expression pattern of the trps1 gene in zebrafish. Comparative in vivo data from zebrafish and mice for CNE7/hs919 revealed conserved functions of these enhancers. Each of these eight CNEs was further investigated in cell line-based reporter assays, revealing their repressive potential. Taken together, in vivo and in vitro assays suggest a context-dependent dual functionality for the identified set of Trps1-associated CNE enhancers. This functionally characterized set of CNE-enhancers will contribute to a more comprehensive understanding of the developmental roles of Trps1 and can aid in the identification of noncoding DNA variants associated with human diseases.

Preliminary anticancer evaluation of new Pd(II) complexes bearing NNO donor ligands.

In this study we presented a novel series of NNO tridentate ligands generating imino, amido and oxo donor pocket for Pd(II) coordination. All the compounds were meticulously characterized by elemental analysis and advanced spectroscopic techniques, including FTIR, proton and carbon NMR. The synthesized compounds underwent rigorous evaluation for their potential as anti-cancer agents, utilizing the aggressive breast cancer cell lines MDA-MB (ATCC) and MCF-7 as a crucial model for assessing growth inhibition in cancer cells. Remarkably, the MTT assay unveiled the robust anti-cancer activity for all palladium complexes against MDA-MB-231 and MCF-7 cells. Particularly, complex [Pd(L1)(CH3CN)] exhibited exceptional potency with an IC50 value of 25.50 ± 0.30 µM (MDA-MB-231) and 20.76 ± 0.30 µM (MCF-7), compared to respective 27.00 ± 0.80 µM and 24.10 ± 0.80 µM for cisplatin, underscoring its promising therapeutic potential. Furthermore, to elucidate the mechanistic basis for the anti-cancer effects, molecular docking studies on tyrosine kinases, an integral target in cancer research, were carried out. The outcome of these investigations further substantiated the remarkable anticancer properties inherent to these innovative compounds. This research offers a compelling perspective on the development of potent anti-cancer agents rooted in the synergy between ligands and Pd(II) complexes and presenting a promising avenue for future cancer therapy endeavors.

Identification of ancestral gnathostome Gli3 enhancers with activity in mammals.

Abnormal expression of the transcriptional regulator and hedgehog (Hh) signaling pathway effector Gli3 is known to trigger congenital disease, most frequently affecting the central nervous system (CNS) and the limbs. Accurate delineation of the genomic cis-regulatory landscape controlling Gli3 transcription during embryonic development is critical for the interpretation of noncoding variants associated with congenital defects. Here, we employed a comparative genomic analysis on fish species with a slow rate of molecular evolution to identify seven previously unknown conserved noncoding elements (CNEs) in Gli3 intronic intervals (CNE15-21). Transgenic assays in zebrafish revealed that most of these elements drive activities in Gli3 expressing tissues, predominantly the fins, CNS, and the heart. Intersection of these CNEs with human disease associated SNPs identified CNE15 as a putative mammalian craniofacial enhancer, with conserved activity in vertebrates and potentially affected by mutation associated with human craniofacial morphology. Finally, comparative functional dissection of an appendage-specific CNE conserved in slowly evolving fish (elephant shark), but not in teleost (CNE14/hs1586) indicates co-option of limb specificity from other tissues prior to the divergence of amniotes and lobe-finned fish. These results uncover a novel subset of intronic Gli3 enhancers that arose in the common ancestor of gnathostomes and whose sequence components were likely gradually modified in other species during the process of evolutionary diversification.

Tomato maturity recognition with convolutional transformers.

Tomatoes are a major crop worldwide, and accurately classifying their maturity is important for many agricultural applications, such as harvesting, grading, and quality control. In this paper, the authors propose a novel method for tomato maturity classification using a convolutional transformer. The convolutional transformer is a hybrid architecture that combines the strengths of convolutional neural networks (CNNs) and transformers. Additionally, this study introduces a new tomato dataset named KUTomaData, explicitly designed to train deep-learning models for tomato segmentation and classification. KUTomaData is a compilation of images sourced from a greenhouse in the UAE, with approximately 700 images available for training and testing. The dataset is prepared under various lighting conditions and viewing perspectives and employs different mobile camera sensors, distinguishing it from existing datasets. The contributions of this paper are threefold: firstly, the authors propose a novel method for tomato maturity classification using a modular convolutional transformer. Secondly, the authors introduce a new tomato image dataset that contains images of tomatoes at different maturity levels. Lastly, the authors show that the convolutional transformer outperforms state-of-the-art methods for tomato maturity classification. The effectiveness of the proposed framework in handling cluttered and occluded tomato instances was evaluated using two additional public datasets, Laboro Tomato and Rob2Pheno Annotated Tomato, as benchmarks. The evaluation results across these three datasets demonstrate the exceptional performance of our proposed framework, surpassing the state-of-the-art by 58.14%, 65.42%, and 66.39% in terms of mean average precision scores for KUTomaData, Laboro Tomato, and Rob2Pheno Annotated Tomato, respectively. This work can potentially improve the efficiency and accuracy of tomato harvesting, grading, and quality control processes.

Deep learning for plant bioinformatics: an explainable gradient-based approach for disease detection.

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a combination of these omics data to learn crucial plant disease detection characteristics. We trained our model with multiple hyperparameters, such as the learning rate, number of hidden layers, and dropout rate, and attained a test set accuracy of 95.5%. We also conducted a sensitivity analysis to determine the model's resistance to hyperparameter variations. Our analysis revealed that our model exhibited a notable degree of resilience in the face of these variations, resulting in only marginal changes in performance. Furthermore, we conducted a comparative examination of the time efficiency of our EG-CNN model in relation to baseline models, including SVM, Random Forest, and Logistic Regression. Although our model necessitates additional time for training and validation due to its intricate architecture, it demonstrates a faster testing time per sample, offering potential advantages in real-world scenarios where speed is paramount. To gain insights into the internal representations of our EG-CNN model, we employed saliency maps for a qualitative analysis. This visualization approach allowed us to ascertain that our model effectively captures crucial aspects of plant disease, encompassing alterations in gene expression, metabolite levels, and spectral discrepancies within plant tissues. Leveraging omics data and hyperspectral images, this study underscores the potential of deep learning methods in the realm of plant disease detection. The proposed EG-CNN model exhibited impressive accuracy and displayed a remarkable degree of insensitivity to hyperparameter variations, which holds promise for future plant bioinformatics applications.

Preparation of nanoformulation of 5-fluorouracil to improve anticancer efficacy: integrated spectroscopic, docking, and MD simulation approaches.

Nanoformulations (NFs) can be used as a novel drug delivery system to treat all cancer types. One of the major drawbacks of conventional anticancer drugs is that they have poor specificity and higher toxicity towards normal cells. 5-fluorouracil (5-FU) is a well-studied anticancer drug that has a significant role in various cancers, specifically colorectal cancer therapy. This study was performed to determine the functional groups, particle size, surface charge, heterogeneity, and stability of the NF. The NFs of 5-FU were prepared through the ultrasonication technique by increasing the surfactant (Tween-80) concentrations. Among all three NFs, nanoformulated 5-FU (n5-FU) showed the most effective particle size (10.72 nm) with a zeta potential of (-4.57 mV). The cytotoxicity and apoptosis profiles confirmed that n5-FU enhanced the anticancer effect of the pure drug in HCT-116 cells, as evident from MTT assay, fluorescence microscopy, and FACS analysis. In HCT-116 cells, the IC50 values of pure and n5-FU were obtained as 41.3 µM and 18.8 µM, respectively, indicating that n5-FU was more effective against the cancer cell line. The cellular uptake study was performed to check the intake of NF in cancer cells. However, the microtubule-affinity regulating kinase-4 (MARK-4), a cancer-target protein, was purified to study the inhibition and interaction studies. The inhibition assay confirmed the inhibitory potential of 5-FU against MARK-4 protein. the multi-spectroscopic, molecular docking and MD simulation studies were performed to analyse the conformational changes, binding studies, intermolecular interactions, and stability of MARK-4 protein upon binding 5-FU. This demonstrates that NF can enhance the effectiveness of anticancer drugs.Communicated by Ramaswamy H. Sarma.

Lyophilization Based Isolation of Exosomes.

Exosomes are nanoscale extracellular vesicles which regulate intercellular communication. They have great potential for application in nanomedicine. However, techniques for their isolation are limited by requirements for advanced instruments and costly reagents. In this study, we developed a lyophilization-based method for isolating exosomes from cultured cells. The isolated exosomes were characterized for protein content using Bradford assay, and for size distribution and shape using scanning electron microscopy (SEM) and nanoparticles tracking analysis (NTA). In addition, CD63, CD9, CD81, HSP70 and TSG101 were evaluated as essential exosomal surface markers using Western blot. Drug loading and release studies were performed to confirm their drug delivery properties using an in vitro model. Exosomes were also loaded with commercial dyes (Cy5, Eosin) for the evaluation of their drug delivery properties. All these characterizations confirmed successful exosome isolation with measurements of less than 150 nm, having a typical shape, and by expressing the known exosome surface protein markers. Finally, tyrosine kinase inhibitors (dasatinib and ponatinib) were loaded on the exosomes to evaluate their anticancer effects on leukemia cells (K562 and engineered Ba/F3-BCR-ABL) using MTT and Annexin-PI assays. The expression of MUC1 protein on the exosomes isolated from MCF-7 cells also indicated that their potential diagnostic properties were intact. In conclusion, we developed a new method for exosome isolation from cultured cells. These exosomes met all the essential requirements in terms of characterization, drug loading and release ability, and inhibition of proliferation and apoptosis induction in Ph+ leukemia cells. Based on these results, we are confident in presenting the lyophilization-based exosome isolation method as an alternative to traditional techniques for exosome isolation from cultured cells.

Evolutionary relevance of single nucleotide variants within the forebrain exclusive human accelerated enhancer regions.

BACKGROUND: Human accelerated regions (HARs) are short conserved genomic sequences that have acquired significantly more nucleotide substitutions than expected in the human lineage after divergence from chimpanzees. The fast evolution of HARs may reflect their roles in the origin of human-specific traits. A recent study has reported positively-selected single nucleotide variants (SNVs) within brain-exclusive human accelerated enhancers (BE-HAEs) hs1210 (forebrain), hs563 (hindbrain) and hs304 (midbrain/forebrain). By including data from archaic hominins, these SNVs were shown to be Homo sapiens-specific, residing within transcriptional factors binding sites (TFBSs) for SOX2 (hs1210), RUNX1/3 (hs563), and FOS/JUND (hs304). Although these findings suggest that the predicted modifications in TFBSs may have some role in present-day brain structure, work is required to verify the extent to which these changes translate into functional variation. RESULTS: To start to fill this gap, we investigate the SOX2 SNV, with both forebrain expression and strong signal of positive selection in humans. We demonstrate that the HMG box of SOX2 binds in vitro with Homo sapiens-specific derived A-allele and ancestral T-allele carrying DNA sites in BE-HAE hs1210. Molecular docking and simulation analysis indicated highly favourable binding of HMG box with derived A-allele containing DNA site when compared to site carrying ancestral T-allele. CONCLUSION: These results suggest that adoptive changes in TF affinity within BE-HAE hs1210 and other HAR enhancers in the evolutionary history of Homo sapiens might. have brought about changes in gene expression patterns and have functional consequences on forebrain formation and evolution. METHODS: The present study employ electrophoretic mobility shift assays (EMSA) and molecular docking and molecular dynamics simulations approaches.

Proprioception and Exteroception of a Soft Robotic Finger Using Neuromorphic Vision-Based Sensing.

Equipping soft robotic grippers with sensing and perception capabilities faces significant challenges due to their high compliance and flexibility, limiting their ability to successfully interact with the environment. In this work, we propose a sensorized soft robotic finger with embedded marker pattern that integrates a high-speed neuromorphic event-based camera to enable finger proprioception and exteroception. A learning-based approach involving a convolutional neural network is developed to process event-based heat maps and achieve specific sensing tasks. The feasibility of the sensing approach for proprioception is demonstrated by showing its ability to predict the two-dimensional deformation of three points located on the finger structure, whereas the exteroception capability is assessed in a slip detection task that can classify slip heat maps at a temporal resolution of 2 ms. Our results show that our proposed approach can enable complete sensorization of the finger for both proprioception and exteroception using a single camera without negatively affecting the finger compliance. Using such sensorized finger in robotic grippers may provide safe, adaptive, and precise grasping for handling a wide category of objects.

In vitro and in silico binding studies of phytochemical isochroman with calf thymus DNA using multi-spectroscopic and computational modelling techniques.

A wide range of therapeutic molecules uses deoxyribonucleic acid (DNA) as an intracellular target. The interaction of small molecules to DNA is a key feature in pharmacology and plays a vital role in the development of novel and more efficient drugs with increased selective activity and enhanced therapeutic effectiveness. Isochroman (IC) is a constituent of Olea europea plant, which has been shown to exhibit several beneficial pharmacological activities. At present, its interaction studies using calf thymus DNA (ct-DNA) have not been explained. A set of multi-spectroscopic techniques has been performed to determine the interaction mechanism of isochroman with ct-DNA. Absorption spectra and quenching in fluorescence studies show that isochroman and ct-DNA form a complex. The static mode of quenching was determined by the Stern-Volmer plot. The value of binding constant, Kb = 4.0 × 103 M-1 revealed moderate type of binding. Effects of single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) and ionic strength were studied to examine the isochroman binding to ct-DNA. Potassium iodide (KI) quenching effects and competitive binding studies clearly showed that isochroman binds in the minor groove of ct-DNA. Circular dichroic and DNA melting experiments also confirmed these results. The experimental outputs were further corroborated via in silico computational modelling studies. Lipinski's rule of 5 and SwissADME showed drug-likeness and oral bioavailability scores. Protox ІІ online software predicts oral and organ toxicity.Communicated by Ramaswamy H. Sarma.

A Framework for Determining the Performance and Requirements of Cable-Driven Mobile Lower Limb Rehabilitation Exoskeletons.

The global increase in the number of stroke patients and limited accessibility to rehabilitation has promoted an increase in the design and development of mobile exoskeletons. Robot-assisted mobile rehabilitation is rapidly emerging as a viable tool as it could provide intensive repetitive movement training and timely standardized delivery of therapy as compared to conventional manual therapy. However, the majority of existing lower limb exoskeletons continue to be heavy and induce unnecessary inertia and inertial vibration on the limb. Cable-driven exoskeletons can overcome these issues with the provision of remote actuation. However, the number of cables and routing can be selected in various ways posing a challenge to designers regarding the optimal design configuration. In this work, a simulation-based generalized framework for modelling and assessment of cable-driven mobile exoskeleton is proposed. The framework can be implemented to identify a 'suitable' configuration from several potential ones or to identify the optimal routing parameters for a given configuration. For a proof of concept, four conceptual configurations of cable-driven exoskeletons (one with a spring) were developed in a manner where both positive and negative moments could be generated for each joint (antagonistic configuration). The models were analyzed using the proposed framework and a decision metric table has been developed based on the models' performance and requirements. The weight of the metrics can be adjusted depending on the preferences and specified constraints. The maximum score is assigned to the configuration with minimum requirement or error, maximum performance, and vice versa. The metric table indicated that the 4-cable configuration is a promising design option for a lower limb rehabilitation exoskeleton based on tracking performance, model requirements, and component forces exerted on the limb.

Exploring the binding mechanism of ß-resorcylic acid with calf thymus DNA: Insights from multi-spectroscopic, thermodynamic and bioinformatics approaches.

ß-resorcylic acid (BR) is a phytochemical which is widely used in the food industry as a flavouring agent and preservative. It has also been found to exhibit antibacterial action against several types of food-borne bacteria. DNA is the main molecular target for many small molecules of therapeutic importance. Hence, the interest is rapidly growing among the researchers to elucidate the interaction between small molecules and DNA. Thus, paving the way to design novel DNA-specific drugs. In this study, an attempt was made to examine the mechanism of binding of BR with calf thymus DNA (ctDNA) with the help of various experiments based on spectroscopy and in silico studies. The spectroscopic studies like UV absorption and fluorescence affirmed the complex formation between BR and ctDNA. The observed binding constant was in the order of 103 M-1 which is indicative of the groove binding mechanism. These findings were further verified by dye-displacement assay, potassium iodide quenching, urea denaturation assay, the study of the effect of ssDNA, circular dichroism and DNA thermal denaturing studies. Different temperature-based fluorescence and isothermal titration calorimetry (ITC) experiments were employed to evaluate thermodynamic parameters. The analysis of thermodynamic parameters supports the enthalpically driven, exothermic and spontaneous nature of the reaction between BR and ctDNA. The forces involved in the binding process were mainly found to be hydrogen bonding, van der Waals and hydrophobic interactions. The results obtained from the molecular docking and molecular dynamics (MD) simulation were consistent with the in vitro experiments, which support the groove binding mode of BR with ctDNA.

Molecular signatures of selection on the human GLI3 associated central nervous system specific enhancers.

The zinc finger-containing transcription factor Gli3 is a key mediator of Hedgehog (Hh) signaling pathway. In vertebrates, Gli3 has widespread expression pattern during early embryonic development. Along the anteroposterior axes of the central nervous system (CNS), dorsoventral neural pattern elaboration is achieved through Hh mediated spatio-temporal deployment of Gli3 transcripts. Previously, we and others uncovered a set of enhancers that mediate many of the known aspects of Gli3 expression during neurogenesis. However, the potential role of Gli3 associated enhancers in trait evolution has not yet received any significant attention. Here, we investigate the evolutionary patterns of Gli3 associated CNS-specific enhancers that have been reported so far. A subset of these enhancers has undergone an accelerated rate of molecular evolution in the human lineage in comparison to other primates/mammals. These fast-evolving enhancers have acquired human-specific changes in transcription factor binding sites (TFBSs). These human-unique changes within subset of Gli3 associated CNS-specific enhancers were further validated as single nucleotide polymorphisms through 1000 Genome Project Phase 3 data. This work not only infers the molecular evolutionary patterns of Gli3 associated enhancers but also provides clues for putative genetic basis of the population-specificity of gene expression regulation.

Comparative genomic analysis of human GLI2 locus using slowly evolving fish revealed the ancestral gnathostome set of early developmental enhancers.

BACKGROUND: The zinc finger-containing transcription factor Gli2, is a key mediator of Hedgehog (Hh) signaling and participates in embryonic patterning of various organs including the central nervous system (CNS) and limbs. Abnormal expression of Gli2 can impede the transcription of Hh target genes through disruption of proper balance between Gli2 and Gli3 functions. Therefore, delineation of enhancers that are required for complementary roles of Glis would allow the interrogation of those pathogenic variants that cause gene dysregulation, and a corresponding abnormal phenotype. Previously, we reported tissue-specific enhancers for Gli family including Gli2 through direct tetrapod-teleost comparisons. RESULTS: Here, we employed the sequence alignments of slowly evolving spotted gar and elephant shark and have identified six novel conserved noncoding elements in human GLI2 containing locus. Zebrafish-based transgenic assays revealed that combined action of these autonomous CNEs reflects many aspects of Gli2 specific endogenous transcriptional activity, including CNS and pectoral fins. CONCLUSION: Taken together with our previous findings, this study suggests that Hh-signaling controlled deployment of Gli2 activity in embryonic patterning arose in the common ancestor of gnathostomes. These GLI2 specific cis-regulatory modules will help to identify DNA variants that probably reside outside of coding intervals and are associated with congenital anomalies.

Effects of Awake Prone Positioning in Non-intubated Spontaneously Breathing COVID-19 Patients Requiring High Flow Oxygen Therapy in High Dependency Unit (HDU): An Observational Study.

Background and Aims: Prone positioning increases oxygenation by recruiting dorsal lung regions and draining airway secretions and improves gas exchange and survival in ARDS. We describe the efficacy of prone positioning in awake non-intubated spontaneously breathing COVID-19 positive patients with hypoxemic acute respiratory failure. Methods: We studied 26 awake non-intubated spontaneously breathing patients with hypoxemic respiratory failure treated with prone positioning. Patients were kept in prone position for two hours in each session and four such sessions were given to patients in 24 hours. SPO2, PaO, 2RR and haemodynamics were measured before prone positioning (PRE), 60 minutes of prone positioning (PRONE), and one hour after the completion of each session (POST). Results: 26 patients (12 males and 14 females) non-intubated spontaneously breathing with SPO2 <94% on 0.4 FiO2 were treated with prone positioning. One patient required intubation and was shifted to ICU, the rest (25 patients) were discharged from HDU. Mean hours of prone positioning were 19.4 ± 2.06 hr. There was significant improvement in oxygenation (increase in PaO2 from 53.15 ± 6.0 mmHg to 64.23 ± 6.96 mmHg in PRE and POST sessions respectively, likewise there was increase in SPO2). No complications were noted with various sessions. Conclusion: Prone positioning was feasible and improved oxygenation in awake non-intubated, spontaneously breathing COVID-19 patients with hypoxemic acute respiratory failure.

Evolutionary and structural analysis of SARS-CoV-2 specific evasion of host immunity.

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading fast worldwide. There is a pressing need to understand how the virus counteracts host innate immune responses. Deleterious clinical manifestations of coronaviruses have been associated with virus-induced direct dysregulation of innate immune responses occurring via viral macrodomains located within nonstructural protein-3 (Nsp3). However, no substantial information is available concerning the relationship of macrodomains to the unusually high pathogenicity of SARS-CoV-2. Here, we show that structural evolution of macrodomains may impart a critical role to the unique pathogenicity of SARS-CoV-2. Using sequence, structural, and phylogenetic analysis, we identify a specific set of historical substitutions that recapitulate the evolution of the macrodomains that counteract host immune response. These evolutionary substitutions may alter and reposition the secondary structural elements to create new intra-protein contacts and, thereby, may enhance the ability of SARS-CoV-2 to inhibit host immunity. Further, we find that the unusual virulence of this virus is potentially the consequence of Darwinian selection-driven epistasis in protein evolution. Our findings warrant further characterization of macrodomain-specific evolutionary substitutions in in vitro and in vivo models to determine their inhibitory effects on the host immune system.