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Article: Unveiling the Role of Biomarkers in Cardiovascular Risk Assessment and Prognosis.

Bhatnagar, Sumit / Jain, Mohit

2024 Volume 16, Issue 1, Page(s) e51874

Abstract: Cardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality, necessitating innovative approaches for accurate risk assessment and prognosis. This review explores the evolving role of biomarkers in advancing cardiovascular risk ...

Abstract	Cardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality, necessitating innovative approaches for accurate risk assessment and prognosis. This review explores the evolving role of biomarkers in advancing cardiovascular risk evaluation and prognostication. Utilizing cardiac biomarkers that represent diverse pathophysiological pathways has the potential to enhance risk stratification for CVD. We delve into the intricate molecular signatures indicative of cardiovascular health, focusing on established biomarkers such as troponins, natriuretic peptides, and lipid profiles while also examining emerging candidates like microRNAs and inflammatory markers. This review provides a holistic perspective on the current landscape of cardiovascular biomarkers, offering insights into their applications in risk assessment and prognosis. In evaluating the risk and prognosis of heart failure (HF), the measurement of natriuretic peptides (B-type natriuretic peptide [BNP] or N-terminal pro-B-type natriuretic peptide [NT-proBNP]) or markers of myocardial injury (cardiac troponin I [TnI] or T [TnT]) has demonstrated utility. By elucidating the synergistic interplay between traditional markers and cutting-edge technologies, this work aims to guide future research endeavors and clinical practices, ultimately contributing to more effective strategies for risk assessment and prognosis of cardiovascular disease.
Language	English
Publishing date	2024-01-08
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.51874
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A comprehensive forced degradation studies of Cariprazine hydrochloride using LC-HRMS/MS and in silico toxicity predictions of its degradation products.

Jain, Mohit / Khan, Shahnawaz

Journal of pharmaceutical and biomedical analysis

2022 Volume 219, Page(s) 114955

Abstract: Cariprazine hydrochloride is a second-generation antipsychotic drug and has been approved by the US Food and Drug Administration and the European Medicines Agency. Herein, we have reported a stability-indicating assay method for the Cariprazine ... ...

Abstract	Cariprazine hydrochloride is a second-generation antipsychotic drug and has been approved by the US Food and Drug Administration and the European Medicines Agency. Herein, we have reported a stability-indicating assay method for the Cariprazine hydrochloride and characterization of its major degradation products using LC-HRMS/MS. The drug substance Cariprazine hydrochloride was subjected to acid, base, oxidation, thermal and photolytic stress degradation. A total of five novel degradation products (DP-1 to DP-5) of Cariprazine hydrochloride drug substance were formed under various acid, base and oxidative conditions. In silico toxicity of the degradation products was evaluated using Leadscope prediction platform. We successfully separated Cariprazine Hydrochloride peak from degradation products (DP-1 to DP-5) by using gradient elution on an Inertsil C18 column (150 × 4.6 mm, 5 µm). The drug substance was found to be labile to acidic, alkaline hydrolytic, and oxidative conditions and stable to photolytic and thermal stress conditions. The degradation pathways were delineated by explaining the putative mechanism of degradation in various conditions. The stability-indicating assay method was validated according to the ICH guideline and hence can be used for routine quality control and stability study analysis of Cariprazine hydrochloride in pharmaceutical industries and research laboratories.
MeSH term(s)	Chromatography, High Pressure Liquid/methods ; Chromatography, Liquid/methods ; Drug Stability ; Hydrolysis ; Mass Spectrometry/methods ; Oxidation-Reduction ; Photolysis ; Piperazines
Chemical Substances	Piperazines ; cariprazine (F6RJL8B278)
Language	English
Publishing date	2022-07-21
Publishing country	England
Document type	Journal Article
ZDB-ID	604917-5
ISSN	1873-264X ; 0731-7085
ISSN (online)	1873-264X
ISSN	0731-7085
DOI	10.1016/j.jpba.2022.114955
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Book ; Online: Understanding Journalists' Workflows in News Curation

Atreja, Shubham / Srinath, Shruthi / Jain, Mohit / Pal, Joyojeet

2023

Abstract: With the increasing dominance of the internet as a source of news consumption, there has been a rise in the production and popularity of email newsletters compiled by individual journalists. However, there is little research on the processes of ... ...

Abstract	With the increasing dominance of the internet as a source of news consumption, there has been a rise in the production and popularity of email newsletters compiled by individual journalists. However, there is little research on the processes of aggregation, and how these differ between expert journalists and trained machines. In this paper, we interviewed journalists who curate newsletters from around the world. Through an in-depth understanding of journalists' workflows, our findings lay out the role of their prior experience in the value they bring into the curation process, their use of algorithms in finding stories for their newsletter, and their internalization of their readers' interests and the context they are curating for. While identifying the role of human expertise, we highlight the importance of hybrid curation and provide design insights on how technology can support the work of these experts. Comment: accepted at CHI'23
Keywords	Computer Science - Computers and Society ; Computer Science - Human-Computer Interaction
Publishing date	2023-03-31
Publishing country	us
Document type	Book ; Online
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Article: Neoantigen Cancer Vaccines: Generation, Optimization, and Therapeutic Targeting Strategies.

Reynolds, Carson R / Tran, Son / Jain, Mohit / Narendran, Aru

Vaccines

2022 Volume 10, Issue 2

Abstract: Alternatives to conventional cancer treatments are highly sought after for high-risk malignancies that have a poor response to established treatment modalities. With research advancing rapidly in the past decade, neoantigen-based immunotherapeutic ... ...

Abstract	Alternatives to conventional cancer treatments are highly sought after for high-risk malignancies that have a poor response to established treatment modalities. With research advancing rapidly in the past decade, neoantigen-based immunotherapeutic approaches represent an effective and highly tolerable therapeutic option. Neoantigens are tumor-specific antigens that are not expressed in normal cells and possess significant immunogenic potential. Several recent studies have described the conceptual framework and methodologies to generate neoantigen-based vaccines as well as the formulation of appropriate clinical trials to advance this approach for patient care. This review aims to describe some of the key studies in the recent literature in this rapidly evolving field and summarize the current advances in neoantigen identification and selection, vaccine generation and delivery, and the optimization of neoantigen-based therapeutic strategies, including the early data from pivotal clinical studies.
Language	English
Publishing date	2022-01-26
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2703319-3
ISSN	2076-393X
ISSN	2076-393X
DOI	10.3390/vaccines10020196
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Article: Orthodontic Treatment of a Case With Palatally Impacted Canine and Missing Molars: A Case Report.

Mavani, Kinjal J / Jain, Mohit J / Pai, Vikram / Naik, Vijay

Cureus

2022 Volume 14, Issue 5, Page(s) e24741

Abstract: Interdisciplinary care provides a comprehensive method for the management of impacted teeth. Careful planning is necessary to achieve the desired treatment goals. This article highlights the importance of diagnosis as well as adequate treatment planning ... ...

Abstract	Interdisciplinary care provides a comprehensive method for the management of impacted teeth. Careful planning is necessary to achieve the desired treatment goals. This article highlights the importance of diagnosis as well as adequate treatment planning for the eruption of impacted teeth and the management of missing molars to achieve a balanced occlusion in circumstances when an ideal occlusion cannot be achieved. Here, we have presented a case report of an impacted maxillary canine with lost molars of a 15-year-old female patient.
Language	English
Publishing date	2022-05-04
Publishing country	United States
Document type	Case Reports
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.24741
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Article ; Online: RespireNet: A Deep Neural Network for Accurately Detecting Abnormal Lung Sounds in Limited Data Setting.

Gairola, Siddhartha / Tom, Francis / Kwatra, Nipun / Jain, Mohit

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

2021 Volume 2021, Page(s) 527–530

Abstract: Auscultation of respiratory sounds is the primary tool for screening and diagnosing lung diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in enabling tele-screening of fatal lung diseases. Deep neural networks ( ... ...

Abstract	Auscultation of respiratory sounds is the primary tool for screening and diagnosing lung diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in enabling tele-screening of fatal lung diseases. Deep neural networks (DNNs) have shown potential to solve such problems, and are an obvious choice. However, DNNs are data hungry, and the largest respiratory dataset ICBHI has only 6898 breathing cycles, which is quite small for training a satisfactory DNN model. In this work, RespireNet, we propose a simple CNN-based model, along with a suite of novel techniques- device specific fine-tuning, concatenation-based augmentation, blank region clipping, and smart padding-enabling us to efficiently use the small-sized dataset. We perform extensive evaluation on the ICBHI dataset, and improve upon the state-of-the-art results for 4-class classification by 2.2%.Code: https://github.com/microsoft/RespireNet.
MeSH term(s)	Auscultation ; Humans ; Lung ; Neural Networks, Computer ; Respiratory Sounds/diagnosis ; Stethoscopes
Language	English
Publishing date	2021-12-10
Publishing country	United States
Document type	Journal Article
ISSN	2694-0604
ISSN (online)	2694-0604
DOI	10.1109/EMBC46164.2021.9630091
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Article: Outcome of individuals with alcoholic cirrhosis hospitalized with first decompensation and their predictors.

Giri, Suprabhat / Ingawale, Sushrut / Harindanath, Sidharth / Jain, Mohit / Garg, Pranav / Darak, Harish / Kumar, Sanjay / Kale, Aditya / Shukla, Akash

The Indian journal of medical research

2024 Volume 159, Issue 2, Page(s) 213–222

Abstract: Background objectives: Alcohol is one of most common aetiologies of cirrhosis and decompensated cirrhosis is linked to higher morbidity and death rates. This study looked at the outcomes and mortality associated risk variables of individuals with ... ...

Abstract	Background objectives: Alcohol is one of most common aetiologies of cirrhosis and decompensated cirrhosis is linked to higher morbidity and death rates. This study looked at the outcomes and mortality associated risk variables of individuals with alcoholic cirrhosis who had hospitalization with their first episode of decompensation. Methods: Individuals with alcoholic cirrhosis who were hospitalized with the first episode of decompensation [acute decompensation (AD) or acute-on-chronic liver failure (ACLF)] were included in the study and were prospectively followed up until death or 90 days, whichever was earlier. Results: Of the 227 study participants analyzed, 167 (73.56%) and 60 (26.43%) participants presented as AD and ACLF, respectively. In the ACLF group, the mortality rate at 90 days was higher than in the AD group (48.3 vs 32.3%, P=0.02). In the AD group, participants who initially presented with ascites as opposed to variceal haemorrhage had a greater mortality rate at 90 days (36.4 vs 17.1%, P=0.041). The chronic liver failure-consortium AD score and the lactate-free Asian Pacific Association for the study of the Liver-ACLF research consortium score best-predicted mortality in individuals with AD and ACLF. Interpretation conclusions: There is significant heterogeneity in the type of decompensation in individuals with alcoholic cirrhosis. We observed significantly high mortality rate among alcoholic participants hospitalized with initial decompensation; deaths occurring in more than one-third of study participants within 90 days.
MeSH term(s)	Humans ; Liver Cirrhosis, Alcoholic/complications ; Liver Cirrhosis, Alcoholic/epidemiology ; Esophageal and Gastric Varices ; Prospective Studies ; Gastrointestinal Hemorrhage ; Liver Cirrhosis/complications ; Liver Cirrhosis/epidemiology ; Acute-On-Chronic Liver Failure/epidemiology ; Acute-On-Chronic Liver Failure/therapy ; Prognosis
Language	English
Publishing date	2024-04-04
Publishing country	India
Document type	Journal Article
ZDB-ID	390883-5
ISSN	0971-5916 ; 0019-5340
ISSN	0971-5916 ; 0019-5340
DOI	10.4103/ijmr.ijmr_1690_22
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Article ; Online: Development and validation of a 21-gene prognostic signature in neuroblastoma.

Gupta, Mehul / Kannappan, Sunand / Jain, Mohit / Douglass, David / Shah, Ravi / Bose, Pinaki / Narendran, Aru

Scientific reports

2023 Volume 13, Issue 1, Page(s) 12526

Abstract: Survival outcomes for patients with neuroblastoma vary markedly and reliable prognostic markers and risk stratification tools are lacking. We sought to identify and validate a transcriptomic signature capable of predicting risk of mortality in patients ... ...

Abstract	Survival outcomes for patients with neuroblastoma vary markedly and reliable prognostic markers and risk stratification tools are lacking. We sought to identify and validate a transcriptomic signature capable of predicting risk of mortality in patients with neuroblastoma. The TARGET NBL dataset (n = 243) was used to develop the model and two independent cohorts, E-MTAB-179 (n = 478) and GSE85047 (n = 240) were used as validation sets. EFS was the primary outcome and OS was the secondary outcome of interest for all analysis. We identified a 21-gene signature capable of stratifying neuroblastoma patients into high and low risk groups in the E-MTAB-179 (HR 5.87 [3.83-9.01], p < 0.0001, 5 year AUC 0.827) and GSE85047 (HR 3.74 [2.36-5.92], p < 0.0001, 5 year AUC 0.815) validation cohorts. Moreover, the signature remained independent of known clinicopathological variables, and remained prognostic within clinically important subgroups. Further, the signature was effectively incorporated into a risk model with clinicopathological variables to improve prognostic performance across validation cohorts (Pooled Validation HR 6.93 [4.89-9.83], p < 0.0001, 5 year AUC 0.839). Similar prognostic utility was also demonstrated with OS. The identified signature is a robust independent predictor of EFS and OS outcomes in neuroblastoma patients and can be combined with clinically utilized clinicopathological variables to improve prognostic performance.
MeSH term(s)	Humans ; Prognosis ; Gene Expression Profiling ; Transcriptome ; Neuroblastoma/diagnosis ; Neuroblastoma/genetics ; Biomarkers, Tumor/genetics
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2023-08-02
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-37714-9
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Article ; Online: Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors.

Nicolas Sundqvist / Nina Grankvist / Jeramie Watrous / Jain Mohit / Roland Nilsson / Gunnar Cedersund

PLoS Computational Biology, Vol 18, Iss 4, p e

2022 Volume 1009999

Abstract: Accurate measurements of metabolic fluxes in living cells are central to metabolism research and metabolic engineering. The gold standard method is model-based metabolic flux analysis (MFA), where fluxes are estimated indirectly from mass isotopomer data ...

Abstract	Accurate measurements of metabolic fluxes in living cells are central to metabolism research and metabolic engineering. The gold standard method is model-based metabolic flux analysis (MFA), where fluxes are estimated indirectly from mass isotopomer data with the use of a mathematical model of the metabolic network. A critical step in MFA is model selection: choosing what compartments, metabolites, and reactions to include in the metabolic network model. Model selection is often done informally during the modelling process, based on the same data that is used for model fitting (estimation data). This can lead to either overly complex models (overfitting) or too simple ones (underfitting), in both cases resulting in poor flux estimates. Here, we propose a method for model selection based on independent validation data. We demonstrate in simulation studies that this method consistently chooses the correct model in a way that is independent on errors in measurement uncertainty. This independence is beneficial, since estimating the true magnitude of these errors can be difficult. In contrast, commonly used model selection methods based on the χ2-test choose different model structures depending on the believed measurement uncertainty; this can lead to errors in flux estimates, especially when the magnitude of the error is substantially off. We present a new approach for quantification of prediction uncertainty of mass isotopomer distributions in other labelling experiments, to check for problems with too much or too little novelty in the validation data. Finally, in an isotope tracing study on human mammary epithelial cells, the validation-based model selection method identified pyruvate carboxylase as a key model component. Our results argue that validation-based model selection should be an integral part of MFA model development.
Keywords	Biology (General) ; QH301-705.5
Subject code	310
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: "Can't Take the Pressure?"

Mehta, Suril / Kwatra, Nipun / Jain, Mohit / McDuff, Daniel

Examining the Challenges of Blood Pressure Estimation via Pulse Wave Analysis

2023

Abstract: The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such technology can have a significant impact on health screening, chronic ... ...

Abstract	The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such technology can have a significant impact on health screening, chronic disease management and remote monitoring. A common approach is to collect sensor data and corresponding labels from a clinical grade device (e.g., blood pressure cuff), and train deep learning models to map one to the other. Although well intentioned, this approach often ignores a principled analysis of whether the input sensor data has enough information to predict the desired metric. We analyze the task of predicting blood pressure from PPG pulse wave analysis. Our review of the prior work reveals that many papers fall prey data leakage, and unrealistic constraints on the task and the preprocessing steps. We propose a set of tools to help determine if the input signal in question (e.g., PPG) is indeed a good predictor of the desired label (e.g., blood pressure). Using our proposed tools, we have found that blood pressure prediction using PPG has a high multi-valued mapping factor of 33.2% and low mutual information of 9.8%. In comparison, heart rate prediction using PPG, a well-established task, has a very low multi-valued mapping factor of 0.75% and high mutual information of 87.7%. We argue that these results provide a more realistic representation of the current progress towards to goal of wearable blood pressure measurement via PPG pulse wave analysis.
Keywords	Electrical Engineering and Systems Science - Signal Processing ; Computer Science - Artificial Intelligence ; Computer Science - Human-Computer Interaction ; Computer Science - Machine Learning
Subject code	306
Publishing date	2023-04-23
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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