Publications by authors named "Arpit Jain"

Background Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal malignancy with limited effective systemic therapies. Modified FOLFIRINOX (mFOLFIRINOX) and gemcitabine plus nab-paclitaxel (GN) are commonly used first-line regimens. The purpose of this study is to evaluate real-world efficacy (response rates, progression-free survival (PFS) and overall survival (OS)) and toxicity (grade 3/4 hematologic and non-hematologic toxicities) of first-line mFOLFIRINOX and gemcitabine plus nab-paclitaxel in patients with advanced pancreatic ductal adenocarcinoma.

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Harnessing quantum interference among bosons provides opportunities due to their longer coherence time than fermions. Fano resonance, an example of quantum interference between discrete and continuous states, is marked by an asymmetric lineshape. While photon-based Fano resonance has enabled high-sensitivity molecule sensing, phonon-based Fano resonance remains underexplored because of ineffective interference between discrete phonons and electronic continuum.

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Background Muscle-invasive bladder cancer (MIBC) involves a high risk of progression and death. Neoadjuvant chemotherapy (NAC), prior to radical cystectomy (RC), has been shown to improve survival. Gemcitabine-cisplatin (GC) has emerged as a preferred NAC regimen based on its favorable toxicity profile, while dose-dense methotrexate, vinblastine, doxorubicin, and cisplatin (ddMVAC) may yield better pathologic complete response (pCR) rates, as reported in some studies.

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Graphene and zinc oxide (ZnO) nanowires (NWs)-based photodetectors demonstrate excellent photodetection performance in the ultraviolet (UV) spectrum regime. This paper presents the design and analysis of a heterostructure model of p-few-layer graphene (p-FLG)/n-ZnO NWs-based UV photodetector. The design utilizes the unique properties of few-layer graphene to enhance light absorption and improve photodetector performance.

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Introduction: Afatinib, a second-generation EGFR TKI, was approved in 2015 for the treatment of metastatic NSCLC in India. We aimed to evaluate the clinical outcomes of Afatinib therapy in a real-world setting.

Patients And Methods: Electronic medical records of 43 patients who received Afatinib for advanced EGFR-mutant advanced NSCLC were retrospectively reviewed.

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Semantic segmentation of high-resolution images from remote sensing is crucial across various sectors. However, due to limitations in computational resources and the complexity of network architectures, many sophisticated semantic segmentation models struggle with efficiency in real-world applications, leading to an interest in developing lightweight model like borders. These models often employ a dual-branch structure, which balances processing speed and performance effectively.

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This research explores the design of an infrared (IR) photodetector using mercury cadmium telluride (HgCdTe). It proposes two- and three-dimensional homojunction models based on p-HgCdTe/n-HgCdTe, focusing on applications in the long-wavelength infrared range. The photodetector's performance is analyzed using Silvaco ATLAS TCAD software and compared with analytical calculations based on drift-diffusion, tunneling, and Chu's approximation techniques.

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Heart failure (HF) stands as a formidable challenge in global healthcare casting a long shadow over both morbidity and mortality. A significant interplay between HF and type 2 diabetes (T2DM) manifests an elevated risk of adverse cardiovascular events in T2DM patients. Glucagon-like peptide 1 emerges as a pivotal player in T2DM, which is released in response to meals rich in glucose and lipids.

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Background: Patients with chronic obstructive pulmonary disease (COPD) have an increased risk of cardiovascular involvement, which is among the leading causes of morbidity and mortality worldwide. Echocardiography (ECHO) could be a reliable, non-invasive tool for predicting the risk of cardiovascular modalities in patients with COPD. Combining the ECHO parameters with highly selective cardiac troponin could predict the severity and outcome of patients with COPD.

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Graphene-enhanced Raman scattering (GERS) offers great opportunities to achieve optical sensing with a high uniformity and superior molecular selectivity. The GERS mechanism relies on charge transfer between molecules and graphene, which is difficult to manipulate by varying the band alignment between graphene and the molecules. In this work, we synthesized a few atomic layers of metal termed two-dimensional (2D) metal to precisely and deterministically modify the graphene Fermi level.

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Background: Hypertriglyceridemia is a common cause of acute pancreatitis (AP). This literature review compared the effectiveness and adverse events of insulin therapy, with or without heparin, and plasmapheresis, in reducing triglyceride levels in patients with hypertriglyceridemia-induced AP.

Methods: Systematic reviews, meta-analyses, evidence syntheses, editorials, commentaries, protocols, abstracts, theses and preprints were excluded.

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Small microscopic entities known as microbes, having a population of hundreds of billions or perhaps even in trillions, reside in our gastrointestinal tract. A healthy immune system, digestion, and creation of vitamins and enzymes are all thanks to these microbes. However, new research has shown a hitherto unrecognized connection between the microbiota of the intestines and the genesis of neurodegenerative diseases.

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Acute lymphoblastic leukemia (ALL) is a life-threatening hematological malignancy that requires early and accurate diagnosis for effective treatment. However, the manual diagnosis of ALL is time-consuming and can delay critical treatment decisions. To address this challenge, researchers have turned to advanced technologies such as deep learning (DL) models.

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This study proposes an intelligent health prediction and fault prognosis of the endodontic file during the root canal treatment. Root canal treatment is the procedure of disinfecting the infected pulp through the canal with the help of an endodontic instrument. Force signals are acquired with the help of a dynamometer during the canal preparation, and statistical features are extracted.

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Background: Improving basic infection control (IC) practices, diagnostics and anti-microbial stewardship (AMS) are key tools to handle antimicrobial resistance (AMR).

Materials And Methods: This is a retrospective study done over 6 years (2016-2021) in an oncology centre in North India with many on-going interventions to improve IC practices, diagnostics and AMS. This study looked into AMR patterns from clinical isolates, rates of hospital acquired infections (HAI) and clinical outcomes.

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Recent studies have focused on treating heart failure, primarily mitigating symptoms and reducing the risk of mortality and other cardiovascular complications. A promising new treatment approach involves using LCZ696, an angiotensin receptor-neprilysin inhibitor (ARNI) comprising sacubitril and valsartan. This treatment is superior to the conventional drugs enalapril or valsartan in patients diagnosed with heart failure.

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The process of examining the data flow over the internet to identify abnormalities in wireless network performance is known as network traffic analysis. When analyzing network traffic data, traffic classification becomes an important task. The traffic data classification is used to determine whether data in network traffic is in real-time or not.

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This work provides an innovative endodontic instrument fault detection methodology during root canal treatment (RCT). Sometimes, an endodontic instrument is prone to fracture from the tip, for causes uncertain the dentist's control. A comprehensive assessment and decision support system for an endodontist may avoid several breakages.

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Background: Ondansetron is a selective 5-hydroxytryptamine type 3 serotonin-receptor antagonist with antiemetic properties used inadvertently in the emergency department for controlling nausea. However, ondansetron is linked with a number of adverse effects, including prolongation of the QT interval. Therefore, the purpose of this meta-analysis was to assess the occurrence of QT prolongation in pediatric, adult, and elderly patients receiving oral or intravenously administered ondansetron.

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Background: Diabetes mellitus (DM) is one of the fastest-growing public health problems in the twenty-first century. The ignorance among people about their disease may be related to their low socioeconomic status and lack of quality education available to them about the disease. It is a serious condition leading to several complications if the individual does not follow up regularly for check-ups and blood sugar monitoring.

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In the field of medical imaging, the classification of brain tumors based on histopathological analysis is a laborious and traditional approach. To address this issue, the use of deep learning techniques, specifically Convolutional Neural Networks (CNNs), has become a popular trend in research and development. Our proposed solution is a novel Convolutional Neural Network that leverages transfer learning to classify brain tumors in MRI images as benign or malignant with high accuracy.

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Introduction Pregnancy-induced hypertension (PIH) is a hypertensive disorder in pregnancy that occurs after 20 weeks of pregnancy in the absence of previously known hypertension. PIH is a common and serious complication accompanying pregnancy. Pre-eclampsia and eclampsia are multisystem disorders that can involve end organs like kidneys, liver, eyes, haematopoietic system and placenta.

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Scheuermann kyphosis, also known as Scheuermann disease, juvenile kyphosis, or juvenile discogenic disease, is a condition involving an abnormal, excessive curvature of the spine. It involves both the vertebral bodies and discs of the spine and is characterized by anterior wedging of greater than or equal to 5 degrees in three or more adjacent vertebral bodies. Type 1 Scheuermann's disease involves the thoracic spine, whereas type 2 involves both the thoracic and lumbar spine.

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Synopsis of recent research by authors named "Arpit Jain"

  • - Arpit Jain's recent research focuses on the intersection of cardiovascular health, diabetes management, and advanced diagnostic technologies, particularly in the context of heart failure, COPD, and hypertriglyceridemia-related acute pancreatitis.
  • - Notable findings include the efficacy of semaglutide in heart failure patients, the potential of echocardiography and cardiac biomarkers to assess cardiovascular risk in COPD, and the effectiveness of insulin versus plasmapheresis for managing high triglyceride levels causing pancreatitis.
  • - Additionally, Jain explores innovative approaches such as using two-dimensional metals for improving graphene-based molecular detection, and advances in artificial intelligence for diagnosing conditions like acute lymphoblastic leukemia, highlighting a commitment to bridging medical research with cutting-edge technology.