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Article: Post-extubation Dysphagia-Early Detection by Serial Tongue Pressure Measurements: Is it Practical?

Paul, Subhankar / Pande, Rajesh Kumar

Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine

2023 Volume 26, Issue 12, Page(s) 1233–1234

Abstract: How to cite this article: ...

Abstract	How to cite this article:
Language	English
Publishing date	2023-01-21
Publishing country	India
Document type	Editorial
ZDB-ID	2121263-6
ISSN	1998-359X ; 0972-5229
ISSN (online)	1998-359X
ISSN	0972-5229
DOI	10.5005/jp-journals-10071-24374
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Comparing Functional Efficacy of Transforaminal vs Interlaminar Epidural Steroid Injection for Lumbar Disc Disease!! Do We Really Need Transforaminal Epidural Route Injections?

Gharu, Eman M P / Singh, Noel S / Paul, Rajesh / Osahan, Narjeet K

Journal of pharmacy & bioallied sciences

2024 Volume 16, Issue Suppl 1, Page(s) S437–S439

Abstract: This study compared the functional efficacy of therapeutic transforaminal versus interlaminar epidural steroid injection. Adult patients were selected and randomized using an online research randomizer website and assigned into two groups and were given ... ...

Abstract	This study compared the functional efficacy of therapeutic transforaminal versus interlaminar epidural steroid injection. Adult patients were selected and randomized using an online research randomizer website and assigned into two groups and were given epidural injection either via transforaminal route or interlaminar route. The outcome was measured based on the Modified Japanese Orthopedic Association back index score (mJOA), Oswestry disability index (ODI), and visual analog scale (VAS) over a follow-up on 1
Language	English
Publishing date	2024-02-29
Publishing country	India
Document type	Journal Article
ZDB-ID	2573569-X
ISSN	0975-7406 ; 0976-4879
ISSN (online)	0975-7406
ISSN	0976-4879
DOI	10.4103/jpbs.jpbs_658_23
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Article ; Online: Correction: A Machine Learning Approach to Identify Potential miRNA-Gene Regulatory Network Contributing to the Pathogenesis of SARS-CoV-2 Infection.

Das, Rajesh / Sinnarasan, Vigneshwar Suriya Prakash / Paul, Dahrii / Venkatesan, Amouda

Biochemical genetics

2023 Volume 62, Issue 2, Page(s) 1007

Language	English
Publishing date	2023-09-05
Publishing country	United States
Document type	Published Erratum
ZDB-ID	2168-4
ISSN	1573-4927 ; 0006-2928
ISSN (online)	1573-4927
ISSN	0006-2928
DOI	10.1007/s10528-023-10511-9
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Article: Safety and Evaluation of the Immune Response of Coronavirus Nosode (BiosimCovex) in Healthy Volunteers: A Preliminary Study Extending the Homeopathic Pathogenetic Trial.

Herscu, Paul / Talele, Gitanjali / Vaidya, Shashikant / Shah, Rajesh

Medicines (Basel, Switzerland)

2022 Volume 10, Issue 1

Abstract: ... ...

Abstract	Objectives
Language	English
Publishing date	2022-12-30
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2777965-8
ISSN	2305-6320
ISSN	2305-6320
DOI	10.3390/medicines10010008
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Article ; Online: Is surgical risk of aortic arch aneurysm repair underestimated? A novel perspective based on 30-day versus 1-year mortality.

Rajesh, Kavya / Levine, Dov / Murana, Giacomo / Castagnini, Sabrina / Bianco, Edoardo / Childress, Patra / Zhao, Yanling / Kurlansky, Paul / Pacini, Davide / Takayama, Hiroo

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery

2024 Volume 65, Issue 3

Abstract: Objectives: The decision to undergo aortic aneurysm repair balances the risk of operation with the risk of aortic complications. The surgical risk is typically represented by perioperative mortality, while the aneurysmal risk relates to the 1-year risk ... ...

Abstract	Objectives: The decision to undergo aortic aneurysm repair balances the risk of operation with the risk of aortic complications. The surgical risk is typically represented by perioperative mortality, while the aneurysmal risk relates to the 1-year risk of aortic events. We investigate the difference in 30-day and 1-year mortality after total arch replacement for aortic aneurysm. Methods: This was an international two-centre study of 456 patients who underwent total aortic arch replacement for aneurysm between 2006 and 2020. Our primary end-point of interest was 1-year mortality. Our secondary analysis determined which variables were associated with 1-year mortality. Results: The median age of patients was 65.4 years (interquartile range 55.1-71.1) and 118 (25.9%) were female. Concomitantly, 91 (20.0%) patients had either an aortic root replacement or aortic valve procedure. There was a drop in 1-year (81%, 95% confidence interval (CI) 78-85%) survival probability compared to 30-day (92%, 95% CI 90-95%) survival probability. Risk hazards regression showed the greatest risk of mortality in the first 4 months after discharge. Stroke [hazard ratio (HR) 2.54, 95% CI (1.16-5.58)], renal failure [HR 3.59 (1.78-7.25)], respiratory failure [HR 3.65 (1.79-7.42)] and reoperation for bleeding [HR 2.97 (1.36-6.46)] were associated with 1-year mortality in patients who survived 30 days. Conclusions: There is an increase in mortality up to 1 year after aortic arch replacement. This increase is prominent in the first 4 months and is associated with postoperative complications, implying the influence of surgical insult. Mortality beyond the short term may be considered in assessing surgical risk in patients who are undergoing total arch replacement.
MeSH term(s)	Humans ; Female ; Aged ; Male ; Aortic Dissection ; Aneurysm, Aortic Arch ; Aortic Aneurysm/surgery ; Aorta/surgery ; Vascular Surgical Procedures ; Reoperation ; Postoperative Complications/etiology ; Treatment Outcome ; Retrospective Studies ; Risk Factors ; Aortic Aneurysm, Thoracic ; Blood Vessel Prosthesis Implantation/methods
Language	English
Publishing date	2024-03-01
Publishing country	Germany
Document type	Journal Article
ZDB-ID	639293-3
ISSN	1873-734X ; 1010-7940 ; 1567-4258
ISSN (online)	1873-734X
ISSN	1010-7940 ; 1567-4258
DOI	10.1093/ejcts/ezae041
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Zs.A 2303: Show issues

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Article ; Online: Identification of prolactin receptor variants with diverse effects on receptor signalling.

Gorvin, Caroline M / Newey, Paul J / Thakker, Rajesh V

Journal of molecular endocrinology

2023 Volume 70, Issue 3

Abstract: The prolactin receptor (PRLR) signals predominantly through the JAK2-STAT5 pathway regulating multiple physiological functions relating to fertility, lactation, and metabolism. However, the molecular pathology and role of PRLR mutations and signalling ... ...

Abstract	The prolactin receptor (PRLR) signals predominantly through the JAK2-STAT5 pathway regulating multiple physiological functions relating to fertility, lactation, and metabolism. However, the molecular pathology and role of PRLR mutations and signalling are incompletely defined, with progress hampered by a lack of reported disease-associated PRLR variants. To date, two common germline PRLR variants are reported to demonstrate constitutive activity, with one, Ile146Leu, overrepresented in benign breast disease, while a rare activating variant, Asn492Ile, is reported to be associated with an increased incidence of prolactinoma. In contrast, an inactivating germline heterozygous PRLR variant (His188Arg) was reported in a kindred with hyperprolactinaemia, while an inactivating compound heterozygous PRLR variant (Pro269Leu/Arg171Stop) was identified in an individual with hyperprolactinaemia and agalactia. We hypothesised that additional rare germline PRLR variants, identified from large-scale sequencing projects (ExAC and GnomAD), may be associated with altered in vitro PRLR signalling activity. We therefore evaluated >300 previously uncharacterised non-synonymous, germline PRLR variants and selected 10 variants for in vitro analysis based on protein prediction algorithms, proximity to known functional domains and structural modelling. Five variants, including extracellular and intracellular domain variants, were associated with altered responses when compared to the wild-type receptor. These altered responses included loss- and gain-of-function activities related to STAT5 signalling, Akt and FOXO1 activity, as well as cell viability and apoptosis. These studies provide further insight into PRLR structure-function and indicate that rare germline PRLR variants may have diverse modulating effects on PRLR signalling, although the pathophysiologic relevance of such alterations remains to be defined.
MeSH term(s)	Female ; Humans ; Receptors, Prolactin/genetics ; Receptors, Prolactin/metabolism ; STAT5 Transcription Factor/genetics ; STAT5 Transcription Factor/metabolism ; Hyperprolactinemia ; Signal Transduction ; Prolactin/metabolism ; Carrier Proteins/metabolism
Chemical Substances	Receptors, Prolactin ; STAT5 Transcription Factor ; Prolactin (9002-62-4) ; Carrier Proteins
Language	English
Publishing date	2023-01-25
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	645012-x
ISSN	1479-6813 ; 0952-5041
ISSN (online)	1479-6813
ISSN	0952-5041
DOI	10.1530/JME-22-0164
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Zs.A 2406: Show issues

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Article ; Online: MLDSPP: Bacterial Promoter Prediction Tool Using DNA Structural Properties with Machine Learning and Explainable AI.

Paul, Subhojit / Olymon, Kaushika / Martinez, Gustavo Sganzerla / Sarkar, Sharmilee / Yella, Venkata Rajesh / Kumar, Aditya

Journal of chemical information and modeling

2024 Volume 64, Issue 7, Page(s) 2705–2719

Abstract: Bacterial promoters play a crucial role in gene expression by serving as docking sites for the transcription initiation machinery. However, accurately identifying promoter regions in bacterial genomes remains a challenge due to their diverse architecture ...

Abstract	Bacterial promoters play a crucial role in gene expression by serving as docking sites for the transcription initiation machinery. However, accurately identifying promoter regions in bacterial genomes remains a challenge due to their diverse architecture and variations. In this study, we propose MLDSPP (Machine Learning and Duplex Stability based Promoter prediction in Prokaryotes), a machine learning-based promoter prediction tool, to comprehensively screen bacterial promoter regions in 12 diverse genomes. We leveraged biologically relevant and informative DNA structural properties, such as DNA duplex stability and base stacking, and state-of-the-art machine learning (ML) strategies to gain insights into promoter characteristics. We evaluated several machine learning models, including Support Vector Machines, Random Forests, and XGBoost, and assessed their performance using accuracy, precision, recall, specificity, F1 score, and MCC metrics. Our findings reveal that XGBoost outperformed other models and current state-of-the-art promoter prediction tools, namely Sigma70pred and iPromoter2L, achieving F1-scores >95% in most systems. Significantly, the use of one-hot encoding for representing nucleotide sequences complements these structural features, enhancing our XGBoost model's predictive capabilities. To address the challenge of model interpretability, we incorporated explainable AI techniques using Shapley values. This enhancement allows for a better understanding and interpretation of the predictions of our model. In conclusion, our study presents MLDSPP as a novel, generic tool for predicting promoter regions in bacteria, utilizing original downstream sequences as nonpromoter controls. This tool has the potential to significantly advance the field of bacterial genomics and contribute to our understanding of gene regulation in diverse bacterial systems.
MeSH term(s)	Tool Use Behavior ; Bacteria/genetics ; DNA/genetics ; Machine Learning ; Promoter Regions, Genetic
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2024-01-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	190019-5
ISSN	1549-960X ; 0095-2338
ISSN (online)	1549-960X
ISSN	0095-2338
DOI	10.1021/acs.jcim.3c02017
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Zs.A 1230: Show issues

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Article ; Online: Gastric Cancer Biomarker Candidates Identified by Machine Learning and Integrative Bioinformatics: Toward Personalized Medicine.

Sinnarasan, Vigneshwar Suriya Prakash / Paul, Dahrii / Das, Rajesh / Venkatesan, Amouda

Omics : a journal of integrative biology

2023 Volume 27, Issue 6, Page(s) 260–272

Abstract: Gastric cancer (GC) is among the leading causes of cancer-related deaths worldwide. The discovery of robust diagnostic biomarkers for GC remains a challenge. This study sought to identify biomarker candidates for GC by integrating machine learning (ML) ... ...

Abstract	Gastric cancer (GC) is among the leading causes of cancer-related deaths worldwide. The discovery of robust diagnostic biomarkers for GC remains a challenge. This study sought to identify biomarker candidates for GC by integrating machine learning (ML) and bioinformatics approaches. Transcriptome profiles of patients with GC were analyzed to identify differentially expressed genes between the tumor and adjacent normal tissues. Subsequently, we constructed protein-protein interaction networks so as to find the significant hub genes. Along with the bioinformatics integration of ML methods such as support vector machine, the recursive feature elimination was used to select the most informative genes. The analysis unraveled 160 significant genes, with 88 upregulated and 72 downregulated, 10 hub genes, and 12 features from the variable selection method. The integrated analyses found that
MeSH term(s)	Humans ; Biomarkers, Tumor/genetics ; Gene Regulatory Networks ; Precision Medicine ; Stomach Neoplasms/diagnosis ; Stomach Neoplasms/genetics ; Computational Biology/methods ; Machine Learning ; ATPases Associated with Diverse Cellular Activities/genetics ; Cell Cycle Proteins/genetics
Chemical Substances	Biomarkers, Tumor ; TRIP13 protein, human (EC 3.6.4.-) ; ATPases Associated with Diverse Cellular Activities (EC 3.6.4.-) ; Cell Cycle Proteins
Language	English
Publishing date	2023-05-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2030312-9
ISSN	1557-8100 ; 1536-2310
ISSN (online)	1557-8100
ISSN	1536-2310
DOI	10.1089/omi.2023.0015
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Article ; Online: Antiviral Peptides in Antimicrobial Surface Coatings-From Current Techniques to Potential Applications.

Jabeen, Mahe / Biswas, Payel / Islam, Md Touhidul / Paul, Rajesh

Viruses

2023 Volume 15, Issue 3

Abstract: The transmission of pathogens through contact with contaminated surfaces is an important route for the spread of infections. The recent outbreak of COVID-19 highlights the necessity to attenuate surface-mediated transmission. Currently, the disinfection ... ...

Abstract	The transmission of pathogens through contact with contaminated surfaces is an important route for the spread of infections. The recent outbreak of COVID-19 highlights the necessity to attenuate surface-mediated transmission. Currently, the disinfection and sanitization of surfaces are commonly performed in this regard. However, there are some disadvantages associated with these practices, including the development of antibiotic resistance, viral mutation, etc.; hence, a better strategy is necessary. In recent years, peptides have been studied to be utilized as a potential alternative. They are part of the host immune defense and have many potential in vivo applications in drug delivery, diagnostics, immunomodulation, etc. Additionally, the ability of peptides to interact with different molecules and membrane surfaces of microorganisms has made it possible to exploit them in ex vivo applications such as antimicrobial (antibacterial and antiviral) coatings. Although antibacterial peptide coatings have been studied extensively and proven to be effective, antiviral coatings are a more recent development. Therefore, this study aims to highlight antiviral coating strategies and the current practices and application of antiviral coating materials in personal protective equipment, healthcare devices, and textiles and surfaces in public settings. Here, we have presented a review on potential techniques to incorporate peptides in current surface coating strategies that will serve as a guide for developing cost-effective, sustainable and coherent antiviral surface coatings. We further our discussion to highlight some challenges of using peptides as a surface coating material and to examine future perspectives.
MeSH term(s)	Humans ; Antiviral Agents/pharmacology ; COVID-19/prevention & control ; Anti-Infective Agents/pharmacology ; Anti-Bacterial Agents/chemistry ; Peptides/pharmacology
Chemical Substances	Antiviral Agents ; Anti-Infective Agents ; Anti-Bacterial Agents ; Peptides
Language	English
Publishing date	2023-02-27
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v15030640
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Article ; Online: A Machine Learning Approach to Identify Potential miRNA-Gene Regulatory Network Contributing to the Pathogenesis of SARS-CoV-2 Infection.

Das, Rajesh / Sinnarasan, Vigneshwar Suriya Prakash / Paul, Dahrii / Venkatesan, Amouda

Biochemical genetics

2023 Volume 62, Issue 2, Page(s) 987–1006

Abstract: Worldwide, many lives have been lost in the recent outbreak of coronavirus disease. The pathogen responsible for this disease takes advantage of the host machinery to replicate itself and, in turn, causes pathogenesis in humans. Human miRNAs are seen to ... ...

Abstract	Worldwide, many lives have been lost in the recent outbreak of coronavirus disease. The pathogen responsible for this disease takes advantage of the host machinery to replicate itself and, in turn, causes pathogenesis in humans. Human miRNAs are seen to have a major role in the pathogenesis and progression of viral diseases. Hence, an in-silico approach has been used in this study to uncover the role of miRNAs and their target genes in coronavirus disease pathogenesis. This study attempts to perform the miRNA seq data analysis to identify the potential differentially expressed miRNAs. Considering only the experimentally proven interaction databases TarBase, miRTarBase, and miRecords, the target genes of the miRNAs have been identified from the mirNET analytics platform. The identified hub genes were subjected to gene ontology and pathway enrichment analysis using EnrichR. It is found that a total of 9 miRNAs are deregulated, out of which 2 were upregulated (hsa-mir-3614-5p and hsa-mir-3614-3p) and 7 were downregulated (hsa-mir-17-5p, hsa-mir-106a-5p, hsa-mir-17-3p, hsa-mir-181d-5p, hsa-mir-93-3p, hsa-mir-28-5p, and hsa-mir-100-5p). These miRNAs help us to classify the diseased and healthy control patients accurately. Moreover, it is also found that crucial target genes (UBC and UBB) of 4 signature miRNAs interact with viral replicase polyprotein 1ab of SARS-Coronavirus. As a result, it is noted that the virus hijacks key immune pathways like various cancer and virus infection pathways and molecular functions such as ubiquitin ligase binding and transcription corepressor and coregulator binding.
MeSH term(s)	Humans ; Gene Regulatory Networks ; COVID-19/genetics ; SARS-CoV-2/genetics ; SARS-CoV-2/metabolism ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Machine Learning
Chemical Substances	MicroRNAs
Language	English
Publishing date	2023-07-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	2168-4
ISSN	1573-4927 ; 0006-2928
ISSN (online)	1573-4927
ISSN	0006-2928
DOI	10.1007/s10528-023-10458-x
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