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The sinonasal tract harbors a diverse spectrum of high-grade neoplasms, many of which have considerable overlapping morphologic features owing to their poorly differentiated or undifferentiated appearance. (1,2) Some of these [...], * Context.--Molecular analysis of poorly differentiated/ undifferentiated sinonasal neoplasms has resulted in identification of a growing number of genetically defined tumors. SMARCA4-deficient sinonasal carcinoma is one such recently described entity that emerged from within sinonasal undifferentiated carcinoma (SNUC), neuroendocrine carcinoma (NEC), and teratocarcinosarcoma (TCS). Objective.--To identify SMARCA4-deficient sinonasal carcinomas from a large institutional cohort of poorly differentiated/undifferentiated carcinomas and evaluate their clinicopathologic features. Design.--SMARCA4/BRG1 immunohistochemistry was performed on all tumors diagnosed as SNUC, poorly differentiated carcinoma, NEC, and TCS during a 12-year period. SMARCA2/BRM and INSM1 immunostaining was performed in SMARCA4-deficient cases. Results.--Twelve SMARCA4-deficient sinonasal carcinomas were identified among 299 cases. Morphologically, 5 cases were large cell NEC, 2 cases were small cell NEC, and 5 were TCS. SMARCA4 loss was diffuse and complete in 10 cases, while 2 cases showed focal retention. Most cases showed diffuse cytokeratin staining accompanied by weak, usually focal staining for chromogranin and synaptophysin. INSM-1 showed negativity in most cases. All cases showed retained SMARCA2 expression. IDH1/2 mutation was absent in all cases analyzed. Four of 7 patients died of disease, and aggressive multimodality treatment provided better outcome. Conclusions.--SMARCA4-deficient sinonasal carcinomas are morphologically akin to sinonasal poorly differentiated NECs and TCS, display cytokeratin positivity and only focal staining for neuroendocrine markers, and have aggressive biological behavior. Inclusion of SMARCA4 in the immunohistochemical panel for diagnostic workup of all sinonasal NEC and TCS phenotypes will facilitate their early recognition. Comprehensive germline and somatic mutational analyses of these tumors are necessary for further insights into their molecular pathogenesis. (Arch Pathol Lab Med. 2022;146:1122-1130; doi: 10.5858/arpa.2021-0001-OA)

Abstract Linear Regression (LR), as one of the essential Machine Learning (ML) models, incurs massive data crunching during the training phase based on many data points. Considering the computationally intensive nature in the LR models, an optimized dedicated hardware IP core design can be very effective. This paper proposes the following novelties: (a) an optimized hardware IP core design of linear regression‐based machine learning model using high‐level synthesis (HLS). More specifically, independent application specific datapath architectures of hardware IP for computing optimal bias and intercepts and cost function in LR‐ML are presented here; (b) an optimized hardware IP core design of LR based ML model by deducing dependency graph from its corresponding mathematical foundation; (c) register transfer level (RTL) design, using HLS, of the optimized LR based ML hardware IP core for computing cost function; (d) linear regression IP core design using multi‐layered tree‐height transformation (THT) and swarm intelligence based architectural exploration for optimized HLS design.

Modern technology is relying on hardware accelerators to achieve enhanced performance of computing systems. In the modern computing paradigm, floating point representation of numbers has gained popularity owing to its wide dynamic range. Rounding of floating point numbers to integer is used in modern processor architectures e.g., ARM and Intel's architecture (IA) as well as in specific applications such as multimedia. However, the academic literature lacks discussion on hardware designs for rounding binary floating point numbers to integer in different rounding modes. This article presents novel efficient algorithms and hardware architecture designs for rounding binary floating point numbers to the integer for the following rounding modes: round towards zero, round up (towards positive infinity), round down (towards negative infinity), round to the nearest integer, and round to nearest even. The article also proposes an integrated multi-mode rounding (IMR) algorithm and hardware design which can be configured to a specific rounding mode among the above-mentioned five modes. This article proposes a mantissa bit of rounding (MBR) to determine the condition of rounding for the various modes. The MBR is identified on the basis of the dynamic range and precision features of floating point representation. To the best of our knowledge, we present the individual as well as an integrated hardware design for the various rounding modes for the first time in the literature. The proposed designs have been implemented on an FPGA platform to analyze the design metrics such as area, delay, and power. The results imply that the proposed designs are suitable to aid the intended hardware accelerators as they are efficient in terms of the design parameters. Moreover, this article presents the integration of the proposed rounding hardware design with the compression processor and evaluates the integration overhead which is found to be nominal (<1%). [ABSTRACT FROM AUTHOR]

The role of end-of-life care is fundamental for end-stage renal disease (ESRD) patients, who are known to have a high morbidity and mortality rate despite being on dialysis. This requires effective communication and shared decision-making. Thus, exploring patients' knowledge and perceptions is essential to improve the gaps in delivering end-of-life care. This study aimed to describe the knowledge and perceptions of end-of-life care among ESRD patients on hemodialysis (HD). This was a cross-sectional study involving 14 outpatient HD centers in Kuantan, Malaysia. Patients were recruited from March to June 2019. A validated questionnaire was delivered via interview-based surveys by the researcher or trained interviewers. The majority of the respondents had poor knowledge of the disease and end-of-life care. However, more than 70% of the respondents felt that it was important for them to be actively involved in medical decision-making, as well as being prepared and planning for death. End-of-life needs, which included management of symptoms and psychological, social, and spiritual support, were important to most respondents. Additionally, patients with higher educational backgrounds were observed to have higher scores for both knowledge and perceptions (P

Abstract Background Cisplatin is a frontline anticancer drug routinely used as part of concurrent chemoradiation administered at 3-weekly (100 mg/m2) dose. However, its role as fractionated weekly dose has achieved favorable outcome in patients with locally advanced squamous cell carcinoma of head and neck (LA-SCCHN) during induction chemotherapy (IC). We therefore sought to compare the toxicity outcomes of patients with LA-SCCHN treated with platinum-based IC at a single institution study using split-dose cisplatin chemotherapy. We compared the hematological and renal toxicity profile between the weekly cisplatin (30 mg/m2) (group A) versus 3-weekly (100 mg/m2) (group B) dosage schedule in this setting. Results The median age of the patients in groups A and B were 49.1 years and 48.27 years respectively with male:female ratio of 4:1. Most of the patients were of oropharyngeal cancers. Group A patients showed greater neutropenia (40.2%) than group B (20.6%). There was statistically significant fall in Hb% level in group A (13.9%) than in group B (11.9%). Renal profile showed greater rise in serum urea and serum creatinine (52.7%) in group B than in group A (52.29%) with statistically significant difference. Conclusions Since toxicities induced by high-dose cisplatin are irreversible and reduce quality of life in patients, the weekly regimen may be preferred owing to less renal toxicity, lesser hospitalization and more feasible in situations with high patient load and limited resources.

Parkinson’s disease (PD) is one of the most common neurodegenerative disorders. The management of PD is a challenging aspect for general physicians and neurologists. It is characterized by the progressive loss of dopaminergic neurons. Impaired α-synuclein secretion and dopamine release may cause mitochondrial dysfunction and perturb energy metabolism, subsequently altering the activity and survival of dopaminergic neurons, thus perpetuating the neurodegenerative process in PD. While the etiology of PD remains multifactorial, emerging research indicates a crucial role of circadian dysfunction in its pathogenesis. Researchers have revealed that circadian dysfunction and sleep disorders are common among PD subjects and disruption of circadian rhythms can increase the risk of PD. Hence, understanding the findings of circadian biology from translational research in PD is important for reducing the risk of neurodegeneration and for improving the quality of life. In this review, we discuss the intricate relationship between circadian dysfunction in cellular metabolism and PD by summarizing the evidence from animal models and human studies. Understanding the metabolic basis of circadian dysfunction in PD may shed light on novel therapeutic approaches to restore circadian rhythm, preserve dopaminergic function, and ameliorate disease progression. Further investigation into the complex interplay between circadian rhythm and PD pathogenesis is essential for the development of targeted therapies and interventions to alleviate the burden of this debilitating neurodegenerative disorder.

Poloidal asymmetries in neutral and impurity ion temperatures and particle and impurity transports have been observed in many tokamaks. To investigate these asymmetries, space-resolved visible spectroscopic diagnostic of the ADTIYA-U tokamak has been upgraded to measure the spatial profile of Hα and impurities spectral line profile, ion temperature, and plasma rotation from both low and high field sides of the plasma, simultaneously with a better spatial resolution. This has been done by developing a linear array of 15 optical fibers as compared to the present linear array of nine fibers having a core diameter of 400 μm and coupling it to the entrance slit of a 1 m long high-resolution spectrometer of the existing diagnostic. A sCMOS detector with a larger height has also been employed to record 15 tracks as compared to the nine tracks when the spectrometer was coupled to a CCD detector having a size of 26.6 × 6.6 mm. The spatial profile of the Hα spectral line from the low and high field sides of the ADITYA-U plasma has been now recorded at every 20 ms to investigate neutral particle dynamics. [ABSTRACT FROM AUTHOR]

ABSTRACT: Introduction: With increased urbanization the prevalence of important public health problems like road traffic accidents (RTA) and depression are surging. This study was aimed to determine the association between RTA and depression among Indian population aged ≥45 years. Methods: Using Longitudinal Aging Study in India (LASI) dataset (April 2017–December 2018), we have conducted this study among older adults (45–59 years) and elderly (≥60 years) Indians. Bivariate analysis was conducted to estimate the prevalence of RTA and depression nationally and across aspirants, achievers, and front runner states. Multivariable logistic regression was conducted between RTA and depression, adjusted with demographic and socioeconomic; health related and behavioral factors. P value <0.05 was considered as statistically significant. Results: Prevalence of RTA was 1.84 (1.74-1.94)% nationally, highest among achiever states (2.04 (1.82–2.30)%). Prevalence of depression was 6.08 (5.90–6.26)% nationally, highest among aspirant states (7.02 (6.74–7.30)%). The adjusted odds of having accident was significantly 1.75 times higher among depressed (aOR 1.75, 95% CI 1.44–2.13) than non-depressed participants which was highest across front runners (aOR 1.86, 95%CI 1.26–2.72) followed by aspirant states (aOR 1.79, 95%CI 1.37–2.33). Conclusion: This study established the association between depression and road traffic accidents among older adults and elderly. Therefore, efforts must be taken to address mental health issues specially focusing on depression in them with proper policy implication more focused on front runners followed by aspirant states. [ABSTRACT FROM AUTHOR]

ABSTRACT: Introduction: Anemia is an important public health disorder. There is a significant chunk of India's population residing in poor housing quality with inadequate sanitation and hygiene, which might lead to higher anemia prevalence. The objective was to determine the association between anemia with poor housing quality among the older Indian adult population (≥45 years) as per residence. Methods: This study analyzed the nationally representative dataset of the Longitudinal Ageing Study in India (LASI 2017–18, Wave-1). Bivariate analysis and logistic regression were conducted to show the association of anemia (outcome variable) with poor housing quality (explanatory variable). Multivariable logistic regression was conducted by adjusting for covariates as per their models. P value <0.05 was considered statistically significant. STATA version 17 was used for analysis. Results: Our study found that higher adjusted odds of having anemia among older Indian adults were observed among participants with overcrowding (AOR 1.30, 95%CI 1.19–1.42), having access to open/nonsanitary toilet facility (AOR 1.56, 95%CI 1.41–1.72), no electric supply (AOR 1.31, 95%CI 1.12–1.53), and overall poor housing quality (AOR 1.34, 95%CI 1.21–1.48). All of these associations were even higher in urban areas except for having access to open/nonsanitary toilet facilities, which was much higher in rural areas (AOR 1.61, 95%CI 1.45–1.79). Conclusion: Through a nationally representative large dataset, this study generated compelling evidence despite several obstacles indicating a positive association between anemia and poor housing quality among older Indian adults. It might raise awareness and assist individuals in steering clear of the negative effects of overcrowding, using open/nonsanitary toilet facilities, lack of electric supply, and overall housing quality on anemia status. It is advised to conduct additional research to determine temporality and causation. [ABSTRACT FROM AUTHOR]

Context: Salt stress is one of the major, ever-increasing abiotic stresses that hinders rice production across arable land around the world. In order to sustain the production of rice (Oryza sativa) in these salt-affected areas, high-yielding stable salt tolerant genotypes must be identified. Aims: The additive main effects and multiplicative interaction (AMMI) model was carried out to identify high-yielding stable rice genotypes under both saline and alkali stress. Methods: Nineteen promising rice genotypes including five standard checks were evaluated using randomized block design under nine salt stress environments using three replications in 2017 and 2018. Key results: The AMMI model II is thought to be the best model for genotype identification based on prediction accuracy with high GEIS and low GEIN (genotype and environment interaction noise). According to AMMI model II, six genotypes were identified as the top performers under salt stress: one genotype (CSR RIL-01-IR 165) yielded the best in three environments; another genotype (CSR 2711-17) yielded highly in in two environments; and the remaining three genotypes (RP5989-2-4-8-15-139-62-6-9, RP 6188-GSR IR1-8-S6-S3-S1, RP6189-HHZ17-Y16-Y3-SAL1) as well as one control genotype (CHK2) yielded well in single environments. Conclusions: Based on AMMI stability study, genotypes RP5989-2-4-8-15-139-62-6-9, CSR2711-17, CSR RIL-01-IR 165, CSR-2748-4441-195, CSR-2748-4441-193), and CSRRIL-01-IR 75 were determined to be higher yielding and more stable than the national control genotype (CSR23). Implications: The high-yielding stable genotypes identified in this study could be planted for salt-affected areas to sustain the production of rice. Salt tolerant varieties with stable performance can be used to address productivity in salt-affected land. Five rice (Oryza sativa) genotypes (RP 5989-2-4-8-15-139-62-6-9, CSR RIL-01-IR 75, CSR-2748-4441-193, CSR-2748-4441-195, and CSR 2711-17) were highly stable across salt-affected environments with yielded 5% more than the national control genotype (CSR23). These high yielding genotypes identified could be used as potential parental lines for breeding varieties for salt-affected conditions to enhance the productivity of salt-affected soils. This article belongs to the collection: Abiotic Stress Tolerance vs Climate Change. [ABSTRACT FROM AUTHOR]

Background: Vitamin D deficiency is thought to increase the likelihood of insulin resistance (IR) and diabetes onset. The objective of this study was to examine the association between the triglyceride glucose (TyG) index and vitamin D levels in individuals with prediabetes and type 2 diabetes mellitus (T2DM) in the tribal community of India. Methods: This study included 270 participants, consisting of 90 individuals with prediabetes, 90 individuals with T2DM, and 90 control patients. Anthropometric and biochemical characteristics were evaluated in all participants. 25-hydroxyvitamin D [25(OH)D] levels were measured using a chemiluminescent immunoassay. The TyG index was computed as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)]/2. Spearman correlation analysis and linear regression analysis were performed to assess the relationship between the TyG index and 25(OH)D levels in people diagnosed with prediabetes and T2DM. The optimum cut-off value of the TyG index for detecting vitamin D deficiency was determined by receiver operating characteristic (ROC) curve analysis. Results: We observed a significant reduction in vitamin D levels in individuals with prediabetes and T2DM compared to those in the control group. However, the TyG index was significantly greater in individuals with prediabetes and T2DM than in controls. Statistical analysis revealed a significant negative correlation between the TyG index and 25(OH)D in both prediabetes and T2DM. Conclusions: The TyG index demonstrated a negative association with vitamin D levels and was identified as an independent predictor of vitamin D deficiency in individuals with prediabetes and T2DM. [ABSTRACT FROM AUTHOR]