Radiological Patterns of Lung Injury on HRCT in COVID-19 Patients: An Experience From Tertiary Care Centre in India.

INTRODUCTION: During the outbreak of the COVID-19 pandemic, radiological examinations became crucial in assessing the severity and progression of lung injuries in COVID-19 patients. AIM: This study was done to identify radiological patterns of lung injuries in COVID-19 patients, assess lobar involvement, and perform CT severity scoring on symptomatic patients on a baseline scan. METHODS AND MATERIAL: All the RT-PCR-positive patients were retrospectively enrolled in the study from August 16, 2020 to October 12, 2020. The final heart-resolution computed tomographic (HRCT) thorax data of a total of 119 COVID-19 patients was analyzed using simple statistical methods. A p-value of less than 0.05 (p < 0.05) was considered statistically significant. RESULTS: A total of 119 HRCT thorax scans of symptomatic indoor RT-PCR-positive patients were reviewed. Over 50% of the patients were under 50 (n = 66; 25 = 5; 25-50 = 61). Males > females: 3.25:1 (M = 91; F = 28). Peripheral involvement dominated (n = 90). Both lungs were affected equally, but the right lower lobe was more involved (n = 103) than the left (n = 98). Inpatient care was needed for 64.70% of CT severity score (CTSS) 10 COVID-19 patients (n = 77). Most positive CT scans (n = 115) revealed ground glass opacities (n = 112; 97.39%). Vascular dilatation or vasculitis (n = 65; 56.62%) and organizing pneumonia-like changes (n = 61; 53.04%) were also common. Vascular enlargement (56.53 percent, n = 65) and reverse halo (52.17%, n = 60) were the most common CT signs. CONCLUSION:  The most common chest CT finding in COVID-19 was ground-glass opacity in peripheral distribution with extensive lung involvement. These ground glass opacities may coalesce into consolidations. Vascular dilatation, organizing pneumonia, interlobular septal thickening, and crazy paving were other important imaging characteristics.

Color Doppler ultrasound in high-low risk pregnancies and its relationship to fetal outcomes: a cross-sectional study.

Objective: To calculate the multivessel color Doppler indices in high-risk and low-risk pregnancies and relate these to fetal outcomes. Methods: The investigation involved 60 patients who were pregnant. The patients were separated into groups according to assessment of low and high risk. The patients underwent color Doppler ultrasonography to detect the maternal and fetal blood vessels, and the measured Doppler indices were then analyzed for any association with fetal outcomes. Results: The gestational stages (in weeks) of the participants at the respective times of investigation and delivery were 32.06 ± 2.98 and 36.2 ± 1.78 in the low-risk group and 29.21 ± 1.95 and 29.83 ± 1.86 in the high-risk group. The pulsatility index (PI), resistive index (RI), and systolic/diastolic ratio (SD) decreased with gestation length in the low-risk group, whereas in the high-risk group, these values increased in the uterine and umbilical arteries. With increased gestational stage, MCA-PSV (peak systolic velocity) in the middle cerebral artery (MCA) increased, while PI decreased. Pulsatile and reversal flow of the uterine vein, the vein of Galen, and the umbilical vein were noted in high-risk pregnancies, and these negatively affected the fetal outcome. The fetal venous parameters were more specific and sensitive for predicting an unfavorable fetal outcome than the arterial factors, with a greater negative predictive value. Conclusion: The results of our study indicate that abnormal Doppler indices of the blood vessels in high-risk pregnant patients will result in adverse clinical outcomes. Therefore, the patients can be monitored and managed accordingly using Doppler ultrasonography.

Classifying COVID-19 and Viral Pneumonia Lung Infections through Deep Convolutional Neural Network Model using Chest X-Ray Images.

Context: Automated detection of COVID-19 in real time can greatly help clinicians to handle increasing number of cases for preliminary screening. Deep CNN models trained with sufficiently large datasets may become best candidates to meet the purpose. Aims: This study aims for automated detection and classification of COVID-19 and viral pneumonia diseases by applying deep CNN model using chest X-ray images. The proposed model performs multiclass classification to meet the purpose. Settings and Design: The proposed model is built on top of VGG16 architecture with pretrained ImageNet weights. The model was fine-tuned using additional custom layers to deliver better performance specific to the target. Subjects and Methods: A total of 15,153 samples are used in this work. These samples include chest X-ray images of COVID-19, viral pneumonia, and normal cases. The entire dataset was split into train and test sets, with a ratio of 80:20 before training the model. To enhance important image features, image preprocessing and augmentation were applied before feeding the image batches to the model. Statistical Analysis Used: Performance of the model is evaluated through accuracy, precision, recall, and F1 score performance metrics. The results produced by the model are also compared with other recent leading studies. Results: The proposed model has achieved a classification accuracy of 98% with 98% precision, 96% recall, and 97% F1 score on the test dataset for multiclass classification. The area under receiver operating characteristic curve score was 0.99 for all three cases of multiclass classification. Conclusions: The proposed classification model may be highly useful for the preliminary diagnosis of COVID-19 and viral pneumonia cases, especially during heavy workloads and large quantities.

Evaluation of Platelet and Red Blood Cell Parameters with Proposal of Modified Score as Discriminating Guide for Iron Deficiency Anemia and ß-Thalassemia Minor.

INTRODUCTION: Iron Deficiency Anaemia (IDA) and ß-Thalassaemia Minor (BTM) are considered to be important cause of microcytic hypochromic anaemia. Studies have evaluated various red cell parameters which are easily available on electronic cell counters for discrimination of IDA and BTM in different ethnic populations. The analysis of previously established red cell discriminative indices with new cut-off have also been done by studies which may be relevant in their set of population for differentiation. AIM: The study was conducted to propose a modified score considering the established red blood cell indices with a new cut off and to formulate index taking into consideration Red Blood Cell (RBC) and platelet parameters for early differentiation of IDA and BTM. MATERIALS AND METHODS: The prospective study included cases with MCV< 80 fl and new modified score of 11 was proposed by statistically analysing the previous discriminative indices with new cut-off by giving score 0 for IDA and score 1 for BTM. The summation of all scores gave modified 11 T score. A new cut off for differentiation of IDA and BTM was proposed in the study by using ROC curve and analysing AUC which statistically corresponded to highest accuracy. An attempt to formulate a new index using the RBC and platelet parameters was also made for initial discrimination. RESULTS: The study included 153 cases and in addition to red blood cell parameters, mean platelet volume and platelet distribution width also showed statistical significant difference between IDA and BTM (p<0.05). Modified new 11 T score was 87.6% specific for BTM while proposed index showed 80.4% negative predictive value for BTM and correctly identified 75% of cases. CONCLUSION: The proposed new index and modified 11T score may be used for initial discrimination of BTM and IDA especially in resource limited regions. Apart from RBC parameters, mean platelet volume and platelet distribution width may also be useful in early differentiation. It is essential to determine cut off of every index in given population for differentiation of these two conditions.

Scrub typhus in children at a tertiary hospital in north India: clinical profile and complications.

OBJECTIVE: To study the clinical profile and complications of childhood scrub typhus. METHODS: Prospective observational study of 66 children with scrub typhus, admitted to a tertiary hospital in north India, during the period between January 2011 and December 2012. The diagnosis was confirmed by serology. Findings : All children presented with fever. Other common symptoms were vomiting (56%), facial swelling (52%), cough (35%), abdominal pain (33%), breathlessness (29%) and decreased urine output (29%). High grade fever (>101 (o)F) was recorded in 91% of children. Other common signs were hepatomegaly, splenomegaly, edema, tender lymphadenopathy and hypotension, observed in 82%, 59%, 39%, 38% and 36% of cases, respectively. An eschar and a maculopapular rash each were observed in 20% of patients. Meningoencephalitis (30.3%), severe thrombocytopenia (27.2%), shock (25.8%), acute kidney injury (16.7%) and hepatitis (13.6%) were the most common complications observed in these children. Other common complications were acute respiratory distress syndrome, respiratory failure requiring ventilation, bronchopneumonia and myocarditis. Ninety percent of children became afebrile within 48 hours of initiating an appropriate antibiotic. Median time to defervescence was 22 hours. The overall mortality rate was 7.5%. Causes of death were refractory shock, meningoencephalitis, acute respiratory distress syndrome, bronchopneumonia, acute kidney injury and myocarditis. CONCLUSION: Pediatricians should keep a high index of suspicion for scrub typhus in any febrile child having a maculopapular rash, hepatosplenomegaly, tender lymphadenopathy, thrombocytopenia and features suggestive of capillary leak. Pending serological confirmation, empirical therapy with doxycycline or azithromycin should be started, as delay in treatment would result in life threatening complications.

Prevalence and pattern of congenital heart disease in Uttarakhand, India.

OBJECTIVE: To find the prevalence and pattern of congenital heart disease (CHD) at a tertiary care hospital in Uttarakhand, India. METHODS: A thorough history and clinical examination was done for all the live births and children up to 18 y of age who presented to the institute over a period of 3 y from July 2008 through June 2011. Those suspected of having a CHD, were further evaluated with ECG, chest radiography and the diagnosis was confirmed by color Doppler echocardiography. RESULTS: Of the 36541 children examined, 312 were identified as having congenital heart defects, thus giving a prevalence of 8.54 per 1000 children attending hospital. Only one fifth cases were diagnosed in neonatal period and the diagnosis was delayed beyond infancy in more than half of the cases. Ventricular septal defect (30.45%), atrial septal defect (17.63%), patent ductus arteriosus (9.62%), pulmonary stenosis (6.41%), tetralogy of Fallot (5.45%) and transposition of great arteries (5.13%) were the commonest defects observed. Only 9.29% of children with CHD underwent definitive treatment. CONCLUSION: The prevalence of CHD at a tertiary referral hospital in Uttarakhand India is 8.54 per 1000 children. VSD and TOF are the most common acyanotic and cyanotic congenital heart defects respectively.

Identification of Escherichia coli through analysis of 16S rRNA and 16S-23S rRNA internal transcribed spacer region sequences.

A bacterial strain, designated BzDS03 was isolated from water sample, collected from Dal Lake Srinagar. The strain was characterized by using 16S ribosomal RNA gene and 16S-23S rRNA internal transcribed spacer region sequences. Phylogenetic analysis showed that 16S rRNA sequence of the isolate formed a monophyletic clade with genera Escherichia. The closest phylogenetic relative was Escherichia coli with 99% 16S rRNA gene sequence similarity. The result of Ribosomal database project's classifier tool revealed that the strain BzDS03 belongs to genera Escherichia.16S rRNA sequence of isolate was deposited in GenBank with accession number FJ961336. Further analysis of 16S-23S rRNA sequence of isolate confirms that the identified strain BzDS03 be assigned as the type strain of Escherichia coli with 98% 16S-23S rRNA sequence similarity. The GenBank accession number allotted for 16S-23S rRNA intergenic spacer sequence of isolate is FJ961337.

A ClpP protein model as tuberculosis target for screening marine compounds.

ATP-dependent Clp protease (ClpP) is a core unit of a major bacterial protease complex employing as a new attractive drug target for that isolates, which are resistant to antibiotics. Mycobacterium tuberculosis, a gram-positive bacterium, is one of the major causes of hospital acquired infections. ClpP in Mycobacterium tuberculosis is usually tightly regulated and strictly requires a member of the family of Clp-ATPase and often further accessory proteins for proteolytic activation. Inhibition of ClpP eliminates these safeguards and start proteolytic degradation. Such uncontrolled proteolysis leads to inhibition of bacterial cell division and eventually cell death. In order to inhibit Clp protease, at first three dimensional structure model of ClpP in Mycobacterium tuberculosis was determined by comparative homology modeling program MODELLER based on crystal structure of the proteolytic component of the caseinolytic Clp protease (ClpP) from E. coli as a template protein and has 55%sequence identity with ClpP protein. The computed model's energy was minimized and validated using PROCHECK to obtain a stable model structure and is submitted in Protein Model Database (PMDB-ID: PM0075741). Stable model was further used for virtual screening against marine derived bioactive compound database through molecular docking studies using AutoDock 3.05. The docked complexes were validated and enumerated based on the AutoDock Scoring function to pick out the best marine inhibitors based on docked Energy. Thus from the entire 186 Marine compounds which were Docked, we got best 5 of them with optimal docked Energy (Ara-A: -14.31 kcal/mol, Dysinosin C: - 14.90kcal/mol, Nagelamide A: -20.49 kcal/mol, Strobilin: -8.02 kcal/mol, Manoalide: -8.81 kcal/mol). Further the five best-docked complexes were analyzed through Python Molecular Viewer software for their interaction studies. Thus from the Complex scoring and binding ability its deciphered that these Marine compounds could be promising inhibitors for ClpP as Drug target yet pharmacological studies have to confirm it.

Virtual screening and pharmacophore studies for ftase inhibitors using Indian plant anticancer compounds database.

Farnesyl transferase (FTase) is an enzyme responsible for post-translational modification in proteins having a carboxy-terminal CaaX motif in human. It catalyzes the attachment of a lipid group in proteins of RAS superfamily, which is essential in signal transduction. FTase has been recognized as an important target for anti cancer therapeutics. In this work, we performed virtual screening against FTase with entire 125 compounds from Indian Plant Anticancer Database using AutoDock 3.0.5 software. All compounds were docked within binding pocket containing Lys164, Tyr300, His248 and Tyr361 residues in crystal structure of FTase. These complexes were ranked according to their docking score, using methodology that was shown to achieve maximum accuracy. Finally we got three potent compounds with the best Autodock docking Score (Vinorelbine: -21.28 Kcal/mol, Vincristine: -21.74 Kcal/mol and Vinblastine: -22.14 Kcal/mol) and their energy scores were better than the FTase bound co-crystallized ligand (L- 739: -7.9 kcal/mol). These three compounds belong to Vinca alkaloids were analyzed through Python Molecular Viewer for their interaction studies. It predicted similar orientation and binding modes for these compounds with L-739 in FTase.Thus from the complex scoring and binding ability it is concluded that these Vinca alkaloids could be promising inhibitors for FTase. A 2-D pharmacophore was generated for these alkaloids using LigandScout to confirm it. A shared feature pharmacophore was also constructed that shows four common features (one hydogen bond Donar, Two hydrogen bond Acceptor and one ionizable area) help compounds to interact with this enzyme.

Identification of Comamonas species using 16S rRNA gene sequence.

A bacterial strain Bz02 was isolated from a water sample collected from river Gomti at the Indian city of Lucknow. We characterized the strain using 16S rRNA sequence. Phylogenetic analysis showed that the strain formed a monophyletic clade with members of the genus Comamonas. The closest phylogenetic relative was Comamonas testosteroni with 95% 16S rRNA gene sequence similarity. It is proposed that the identified strain Bz02 be assigned as the type strain of a species of the genus Comamonas (Comamonas sp Bz02) based on 16S rRNA gene sequence search in Ribosomal Database Project, small subunit rRNA and large subunit rRNA databases together with the phylogenetic tree analysis. The sequence is deposted in GenBank with the accession number FJ211417.

A molecular model for diacylglycerol acyltransferase from Mortierella ramanniana var. angulispora.

Acyl CoA diacylglycerol acyltransferase (DGAT, EC 2.3.120) is recognized as a key player of cellular diacylglycerol metabolism. It catalyzes the terminal, yet the committed step in triacylglycerol synthesis using diacylglycerol and fatty acyl CoA as substrates. The protein sequence of diacylglycerol acyltransferse (DGAT) Type 2B in Moretierella ramanniana var. angulispora (Protein_ID = AAK84180.1) was retrieved from GenBank. However, a structure is not yet available for this sequence. The 3D structure of DGAT Type 2B was modeled using a template structure (PDB ID: 1K30) obtained from Protein databank (PDB) identified by searching with position specific iterative BLAST (PSI-BLAST). The template (PDB ID: 1K30) describes the structure of DGAT from Cucurbita moschata. Modeling was performed using Modeller 9v2 and protein model is hence generated. The DGAT type 2B protein model was subsequently docked with six inhibitors (sphingosine; trifluoroperazine; phosphatidic acid; lysophospatidylserine; KCl; 1, 2-diolein) using AutoDock (a molecular docking program). The binding of inhibitors to the protein model of DGAT type 2B is discussed.

Identification of regulatory elements in 16S rRNA gene of Acinetobacter species isolated from water sample.

A bacterial strain, designated AcBz01, was isolated from a water sample collected from Gomti River, Lucknow, India, and identified using a molecular approach. On the basis of the bacterial 16S rRNA gene sequence phylogeny and comparison of this gene sequence with sequences in Ribosomal Database project II, evidence given in this study, it is proposed that isolate is closely related to members of the genus Acinetobacter. Identification and annotation of regulatory elements in the 16S rRNA gene and characterization of their interaction with the respective transcription factor can provide basis for better understanding of the mechanism of network of gene interaction of functionally related genes. The identification of such sites is relevant for locating promoter boundary of a gene and it also allows the prediction of specific gene expression pattern and response to disturbances in a known signaling pathway. Computational identification of regulatory elements and Transcription Factor with their binding sites in 16S rRNA gene of Acinetobacter sp. was performed using BPROM tool. We predicted the regulatory elements are TSS, -10 box, -35 box and three Transcription Factor (narP, ompR and fadR) with their binding sites in the upstream region of 16S rRNA gene of Acinetobacter sp. AcBz01. The GenBank accession number for 16S rRNA gene of Acinetobacter sp. AcBz01 is EU931637.