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Liver cancer ranks as the third most common cause of cancer-related death rate, resulting in an estimated 830,180 deaths globally. Recent, 2023 estimation of the American Cancer Society predicted around 29,380 deaths due to this disease in America alone. However, with early detection and proper drug management the survival rate can be greatly extended. Significantly, the noteworthy observation pertains to the absence of consistent drug responses among patients with identical cancer types at the same stage. Hence the need of the hour is the precision medicine that predict patient specific drug response based on molecular data genome expression. In this regard, we propose drug response system that uses deep learning framework that predicts drug response in new cell lines or patient with the aim of accurate prediction and suggesting précised medicine to that particular cancer patient. The prediction of the framework is on the lines of recommended system’s projection of drugs and cell lines into latent pharmacogenomic space. During our experimentation, we utilized the Genomics of Drug Sensitivity in Cancer dataset and observed that Cancer Drug Response and Patient Specific Recommender System (CDRP-PRS) consistently delivers robust predictions and effective response, even when applied to previously unseen patient-derived cell line datasets. CDRP-PRS inferences in the pharmacogenomic space are helpful to understand the drug mechanism to identify the cellular subtypes and their categorized associations. Further it is aimed is to predict the accuracy of drug responses for patients and suggest precise medications tailored to their specific cancer.

Identification of markers associated with fertility restoration (Rf) genes is essential because they can streamline the breeding of new CMS lines and production of commercial hybrid seeds. Therefore, in the present study, F2 populations (M31‐2A × DSMR 8) was utilized to identify markers linked to Rf loci on maldandi (A4) cytoplasm through bulk segregant analysis (BSA). The F2 population was analysed for seed set percentage. Chi‐square (χ2) analysis showed that the fertility restoration trait followed expected digenic ratio. By BSA, simple sequence repeats (SSRs) markers, namely, Xtxp 34 and Xtxp 69 located on chromosome 3 and SB 3956 and Xtxp 312 located on chromosome 7, showed clear polymorphism between two groups of fertile and sterile bulks. The genomic region harbouring Rf locus on chromosome 3 (2.61 Mbp) predicted to encode five pentatricopeptide repeat (PPR) genes whereas, on chromosome 7, the gene SORBI_3007G047400 predicted to encode MYB (myeloblastosis) domain containing proteins. These predicted genes could be the candidate for restoring fertility on A4 cytoplasm. This finding will be fundamental in the production and rapid selection of novel restorer lines. [ABSTRACT FROM AUTHOR]

Ultrasonic gauging and defect detection of metallic pipes is a multi-disciplinary task, as it has to be performed in situ and involves several difficulties due to their curvature, limited access and corroded/eroded surface roughness due to harsh operating conditions. This research paper focuses on the investigation of employing a focused piezoelectric transducer in an immersion pulse-echo (PE) mode to measure the wall thickness (WT) from the inner side of the metallic pipes and to detect defects in the pipes. This paper also provides advances for understanding ultrasonic wave propagation in metallic pipes by simulation study using modern finite element technology and validating the results experimentally using battery-operated, water-immersible, IP67-grade stand-alone two-channel ultrasonic instrumentation that can move inside the pipe under test in flowing liquids such as water or oil. A simulation model has been established for time-of-flight (TOF) measurements for metallic pipes with various wall thicknesses, detection of standard defects and wall-thinning by inspecting the inner diameter (ID) surface of pipes and the pipe filled with water. The simulated results for the metallic pipes are in good agreement with the experimental data, providing an accurate and quantitative assessment of WT in the presence or absence of defects. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 2019 (COVID-19) pandemic outbreak created a challenge to manage the health, especially the mental health of various care providers involved in treating the patients infected with the virus. Previously published literature has shown a significant effect of the pandemic on the psychological health of healthcare workers (HCWs) globally; so, this study aimed to describe the psychological health outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among Indian HCWs. Methods: An extensive literature search was conducted in databases including PubMed and Google Scholar. The search was restricted from the COVID-19 outbreak until June 2022. Cross-sectional studies and other studies (telephonic interviews and survey-based studies) reported the prevalence of anxiety and depression among frontline HCWs since the onset of the COVID-19 pandemic. All the studies were critically evaluated by two individual authors in terms of screening and methodological quality evaluation. A total of 16 studies were included in the final meta-analysis. Results: The prevalence of depression among n = 12231 participants of 14 studies was 0.37 CI 95% [0.28–0.48]; the prevalence of anxiety among n = 9467 participants of 12 studies was 0.39 CI 95% [0.29–0.49]. The results of the overall meta-analysis indicate that 37% and 39% of HCWs in this study experienced mild-to-severe depression and anxiety, respectively. During the COVID-19 pandemic, a significant number of HCWs developed mental health issues, with a reported prevalence of depression (37%) and anxiety (39%). Conclusion: Frontline HCWs’ mental health should get full consideration during public health emergencies, screening should be actively conducted, and specific steps should be taken to lower the fear associated with the risk of infections.

Colossal magnetoresistance materials have demonstrated large changes in resistance in the presence of magnetic fields. In the current work, a group of such materials, with the compositional formula La0.67Ba0.33MnO3 and 10% Fe, Co, Ni, Zn doped La0.67Ba0.33MnO3 have been prepared by conventional solid-state method. Structural analysis has been carried out by X-Ray diffraction method followed by Rietveld analysis. Magnetic transition between ferromagnetism to paramagnetism has been observed from the magnetic characterizations. Parameters such as Curie temperature (θP) and effective magnetic moment (µeff) are obtained from susceptibility analysis subject to Curie–Weiss law. Furthermore, magnetocaloric nature of the samples is examined from the M-H isotherms. Using Maxwell's relations, isothermal entropy change, ∆Smax are determined to check whether the prepared samples can be used for magnetic refrigeration around the room temperature. [ABSTRACT FROM AUTHOR]

In this study, the sol–gel method was used to synthesize calcium titanate (CaTiO3) at different calcination temperatures (400–800 °C). The main objective of this work is to find, using various characterization techniques, how the calcination temperature influences the optical, structural, and photocatalytic properties of CaTiO3. According to the DTA/TGA analysis, 600 °C was the ideal calcination temperature for the synthesis of CaTiO3 nanoparticles. The photocatalytic treatment of simulated wastewater demonstrates its potential application in wastewater treatment. For all calcination temperatures, the percentage of Chemical Oxygen Demand (COD) removed after treatment was 100 % for the initial COD of 700 mg/L, more than 83 % for the initial COD of 5000 mg/L, and more than 71 % for the initial COD of 16000 mg/l.

We investigated how BCG vaccination affects the levels of certain eicosanoids, namely Leukotriene B4, 15-epimer of LXA4, prostaglandin F2, Lipoxin A4, Prostaglandin E2 and Resolvin D1 in the plasma of healthy elderly individuals (aged 60–80) before vaccination, one month post-vaccination (M1), and six months post-vaccination (M6). This study is part of the clinical trial ''BCG Vaccine Study: Reducing COVID-19 Impact on the Elderly in Indian Hotspots,'' registered in the clinical trial registry (NCT04475302). While some primary outcomes have been previously reported, this analysis delves into the immunological outcomes. Our findings indicate that BCG vaccination leads to reduced plasma levels of 15-epi-LXA4, LXA4, PGE2, and Resolvin D1 at both M1 and M6. In contrast, there is a notable increase in circulating levels of LTB4 at these time points following BCG vaccination. This underscores the immunomodulatory effects of BCG vaccination and hints at its potential to modulate immune responses by dampening inflammatory reactions.

Background: The SDM-Q-9 is a widely used and reliable tool for assessing patient involvement in shared decision-making. However, there is a dearth of validated information regarding this tool among the Indian population. Therefore, the current study aimed to evaluate the validity and reliability of the Hindi version of the SDM-Q-9 questionnaire in Indian oncology patients. Method: ology: This study was conducted between August 2022 to March 2023 at a tertiary cancer care hospital in India. The sample comprised 150 patients. The scale was initially translated into the Hindi language and later back-translated by experts. Item characteristics were measured using the difficulty index, corrected item-total item correlation, and internal consistency. Factor analysis was conducted using both exploratory factor analysis and confirmatory factor analysis to validate the scale in SPSS v.27 and IBM AMOS v.26. Results: The Cronbach alpha value was found to be significantly good (0.841), indicating high internal consistency. Additionally, the Kaiser-Mayer-Olkin value was 0.825, which suggested that the sample adequacy was satisfactory. Bartlett's test (x2 = 461.209 (df = 36), p = 0.000) also showed that the data were suitable for factor analysis. EFA resulted in an uni-factorial model extraction similar to the developed version, with acceptable model fit indices including CFI (0.861), GFI (0.891), AGFI (0.818), RMSEA (0.122), SRMR (0.119), and TLI (0.815). The CFA resulted in better model fit indices. Conclusion: The study suggests that the Hindi version of the SDM-Q-9 questionnaire is a suitable tool for measuring patient-reported involvement in clinical decision-making among Indian oncology patients.

Abstract Background Severe Acute Respiratory Syndrome Coronavirus‐2 (SARS‐CoV‐2), a causative pathogen of the COVID‐19 pandemic, affects all age groups. However, various studies have shown that COVID‐19 presentation and severity vary considerably with age. We, therefore, wanted to examine the differences between the immune responses of children with COVID‐19 and elderly COVID‐19 individuals. Methods We analyzed cytokines, chemokines, growth factors, and acute phase proteins in acute and convalescent COVID‐19 children and the elderly with acute and convalescent COVID‐19. Results We show that most of the pro‐inflammatory cytokines (interferon [IFN]γ, interleukin [IL]‐2, tumor necrosis factor‐α [TNFα], IL‐1α, IFNα, IFNβ, IL‐6, IL‐12, IL‐3, IL‐7, IL‐1Ra, IL‐13, and IL‐10), chemokines (CCL4, CCL11, CCL19, CXCL1, CXCL2, CXCL8, and CXL10), growth factors (vascular endothelial growth factor and CD40L) and acute phase proteins (C‐reactive protein, serum amyloid P, and haptoglobin) were decreased in children with acute COVID 19 as compared with elderly individuals. In contrast, children with acute COVID‐19 exhibited elevated levels of cytokines‐ IL‐1β, IL‐33, IL‐4, IL‐5, and IL‐25, growth factors—fibroblast growth factor‐2, platelet‐ derived growth factors‐BB, and transforming growth factorα as compared with elderly individuals. Similar, differences were manifest in children and elderly with convalescent COVID‐19. Conclusion Thus, COVID‐19 children are characterized by distinct cytokine/chemokine/growth factor/acute phase protein markers that are markedly different from elderly COVID‐19 individuals.