879,022 results match your criteria: "India; Dr. K.C.Patel Research and Development Center[Affiliation]"

Incidence of postoperative pain after single-visit and multiple-visit root canal therapy: a systematic review.

BMC Oral Health

January 2025

Department of Conservative Dentistry and Endodontics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600077, Tamil Nadu, India.

AIM- The objective of the systematic review is to evaluate the incidence of postoperative pain after single-visit and multiple-visit root canal therapy. METHODS- Published research indexed in PubMed or Scopus or Cochrane or DOAJ or Web of Science evaluating the frequency percentage of postoperative aching after one and several root canal therapy appointments through randomized controlled trials or prospectively were included. RESULT- Most surveys utilized VAS (Visual Analogue Scale) to estimate the degree of pain among the participants.

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Background: Postoperative pain remains a significant problem in patients undergoing donor nephrectomy despite reduced tissue trauma following laparoscopic living donor nephrectomy (LLDN). Inadequately treated pain leads to physiological and psychological consequences, including chronic neuropathic pain.

Materials And Methods: This randomized controlled double-blinded trial was conducted in sixty-nine (n = 69) participants who underwent LLDN under general anesthesia.

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Background: Placenta accreta spectrum (PAS) disorder is a fatal condition responsible for obstetric haemorrhage, which contributes to increased feto-maternal morbidity and mortality. The main contributing factor is a scarred uterus, often from a previous cesarean delivery, myomectomy, or uterine instrumentation. The occurrence of PAS in an unscarred uterus is extremely rare, with only anecdotal cases reported so far in the literature.

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Effective BCDNet-based breast cancer classification model using hybrid deep learning with VGG16-based optimal feature extraction.

BMC Med Imaging

January 2025

Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.

Problem: Breast cancer is a leading cause of death among women, and early detection is crucial for improving survival rates. The manual breast cancer diagnosis utilizes more time and is subjective. Also, the previous CAD models mostly depend on manmade visual details that are complex to generalize across ultrasound images utilizing distinct techniques.

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Background: Children with Autism exhibit impairment of fine motor co-ordination and sensory sensibilities and hence can directly affect the toothbrushing leading to poor oral hygiene.

Aim: This current systematic review and meta-analysis (SRMA) aims to evaluate the effectiveness of Video-based intervention of toothbrush training over other methods on improvement of oral hygiene in children with autism spectrum disorders (ASD) MATERIALS AND METHODS: Prospero no: (CRD42023450168). 'PubMed', 'Cochrane', 'Ovid' databases were searched from 1 January 1980 to 1 August 2023 using pre-defined search strategy.

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Background: Surveys based on capillary blood show that anaemia is rampant in India, but capillary blood haemoglobin (Hb) may not accurately reflect venous blood Hb concentrations. Further, iron deficiency (ID) is thought to be the main cause of anaemia, there are no venous blood-based surveys to confirm this.

Methods: A community-based (urban, slum and rural) cross-sectional, venous blood survey was conducted in eight Indian states to estimate anaemia and ID prevalences from Hb and inflammation-corrected plasma ferritin concentrations in adolescents, adults, and elderly.

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In recent years, the healthcare data system has expanded rapidly, allowing for the identification of important health trends and facilitating targeted preventative care. Heart disease remains a leading cause of death in developed countries, often leading to consequential outcomes such as dementia, which can be mitigated through early detection and treatment of cardiovascular issues. Continued research into preventing strokes and heart attacks is crucial.

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The Indian scad, Decapterus russelli is one of the most exploited pelagic resources of India. Population genetic analyses using mitochondrial and nuclear markers indicated a lack of genetic structuring among populations from Indian waters. As this species is highly migratory, it is also important to establish the environmental influence on its population structure.

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An experiment was conducted for 60 days in a 500L capacity FRP tank containing inland ground saline water (fortified to a level of 50% potassium) with one control (sediment) and three treatments; T1(Paddy Straw Biochar (PSB) in sediment), T2 (Banana Peduncle Biochar (BPB) in sediment), and T3 (PSB + BPB in sediment). Biochar (100 g) was amended with sediment (25 kg) at 9 tons/ha. Shrimps of average weight 5 ± 0.

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Carbon dots doped with metals and non-metals have gained much popularity due to the enhancement in their optical and electronic properties. In this study, polyethyleneimine-functionalized transition metal (nickel or copper) doped carbon dots (CD, NiCD and CuCD) were synthesized through hydrothermal method. The carbon dots exhibited a blue fluorescence at 470 nm when excited at 350 nm.

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Herbicide paraquat dichloride, a potent redox agent found its way to natural water bodies and influences their health; however, its impact on the reproductive health of fish is potentially less studied and requires clear investigation. This study was conducted to elucidate its effect on the gonadal health of female fish, Channa punctatus over 60 days. The 96-h LC of test herbicide was calculated as 0.

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Freshwater ecosystems are highly biodiverse and important for livelihoods and economic development, but are under substantial stress. To date, comprehensive global assessments of extinction risk have not included any speciose groups primarily living in freshwaters. Consequently, data from predominantly terrestrial tetrapods are used to guide environmental policy and conservation prioritization, whereas recent proposals for target setting in freshwaters use abiotic factors.

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Wind energy assessment and hybrid micro-grid optimization for selected regions of Saudi Arabia.

Sci Rep

January 2025

Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.

This study investigates the optimization of wind energy integration in hybrid micro grids (MGs) to address the rising demand for renewable energy, particularly in regions with limited wind potential. A comprehensive assessment of wind energy potential was conducted, and optimal sizing of standalone MGs incorporating photovoltaic (PV) systems, wind turbines (WT), and battery storage (BS) systems was performed for six regions in the Kingdom Saudi Arabia. Wind resource analysis utilizing the Weibull distribution function shows that all regions exhibited Class 1 wind energy characteristics, with average annual wind power densities ranging from 36.

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An approach for load frequency control enhancement in two-area hydro-wind power systems using LSTM + GA-PID controller with augmented lagrangian methods.

Sci Rep

January 2025

Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.

This paper proposes an advanced Load Frequency Control (LFC) strategy for two-area hydro-wind power systems, using a hybrid Long Short-Term Memory (LSTM) neural network combined with a Genetic Algorithm-optimized PID (GA-PID) controller. Traditional PID controllers, while extensively used, often face limitations in handling the nonlinearities and uncertainties inherent in interconnected power systems, leading to slower settling time and higher overshoot during load disturbances. The LSTM + GA-PID controller mitigates these issues by utilizing LSTM's capacity to learn from historical data by using gradient descent to forecast the future disturbances, while the GA optimizes the PID parameters in real time, ensuring dynamic adaptability and improved control precision.

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Boosting skin cancer diagnosis accuracy with ensemble approach.

Sci Rep

January 2025

School of Information and Electronic Engineering and Zhejiang Key Laboratory of Biomedical Intelligent Computing Technology, Zhejiang University of Science and Technology, No. 318, Hangzhou, Zhejiang, China.

Skin cancer is common and deadly, hence a correct diagnosis at an early age is essential. Effective therapy depends on precise classification of the several skin cancer forms, each with special traits. Because dermoscopy and other sophisticated imaging methods produce detailed lesion images, early detection has been enhanced.

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Economic burden of breast cancer in India, 2000-2021 and forecast to 2030.

Sci Rep

January 2025

Faculty of Life and Allied Health Sciences, MS Ramiah University of Applied Sciences (RUAS), MSR Nagar, New BEL Road, Bangalore, 560054, India.

Background Breast cancer represents a significant public health concern in India, accounting for 28% of all cancer diagnoses and imposing a substantial economic burden. This study introduces a novel approach to forecasting the number of breast cancer cases (based on prevalence rates) and estimating the associated economic impact in India using the autoregressive integrated moving average (ARIMA) model. Methods Data on the prevalence of breast cancer in India from 2000 to 2021 were obtained from the Global Burden of Disease (GBD) database.

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The q-RASPR approach for predicting the property and fate of persistent organic pollutants.

Sci Rep

January 2025

Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, via Mario Negri 2, Milano, 20156, Italy.

This study presents a quantitative read-across structure-property relationship (q-RASPR) approach that integrates the chemical similarity information used in read-across with traditional quantitative structure-property relationship (QSPR) models. This novel framework is applied to predict the physicochemical properties and environmental behaviors of persistent organic pollutants, specifically polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs). By utilizing a curated dataset and incorporating similarity-based descriptors, the q-RASPR approach improves the accuracy of predictions, particularly for compounds with limited experimental data.

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Metabolic reprogramming, vital for cancer cells to adapt to the altered microenvironment, remains a topic requiring further investigation for different tumor types. Our study aims to elucidate shared metabolic reprogramming across breast (BRC), colorectal (CRC), and lung (LUC) cancers. Leveraging gene expression data from the Gene Expression Omnibus and various bioinformatics tools like MSigDB, WebGestalt, String, and Cytoscape, we identified key/hub metabolism-related genes (MRGs) and their interactions.

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The most common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) is an intronic GC repeat expansion in C9orf72. The repeats undergo bidirectional transcription to produce sense and antisense repeat RNA species, which are translated into dipeptide repeat proteins (DPRs). As toxicity has been associated with both sense and antisense repeat-derived RNA and DPRs, targeting both strands may provide the most effective therapeutic strategy.

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Biopsy is considered the gold standard for diagnosing brain tumors, but its invasive nature can pose risks to patients. Additionally, tissue analysis can be cumbersome and inconsistent among observers. This research aims to develop a cost-effective, non-invasive, MRI-based computer-aided diagnosis tool that can reliably, accurately and swiftly identify brain tumor grades.

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Microneedles (MNs) appear as a transformative and minimally invasive platform for transdermal drug delivery, representing a highly promising strategy in wound healing therapeutics. This technology, entailing the fabrication of micron-scale needle arrays, enables the targeted and efficient delivery of bioactive agents into the epidermal and dermal layers without inducing significant pain or discomfort. The precise penetration of MNs facilitates localized and sustained drug release, which significantly enhances tissue regeneration and accelerates wound closure.

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A simple, fast, and cost-effective colorimetric nitrite (NO) sensor based on ZIF-67-derived CoO nanocomposite (ZCo-2 NC) structure has been developed. The prepared colorimetric sensor (ZCo-2 NC) was employed to sensitively detect NO in drinking water system by the exhibition of promising peroxidase-mimicking nanozyme-like features. The sensor manifest well-determined sensing response with excellent linear and wide range of NO sensitivity (0.

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Heterocyclic compounds are increasingly used in medicinal chemistry because they are the main components of many biological processes and materials. Benzimidazole remains the core center of the heterocyclic chemical group, with essential traits such as six-five-member connected rings and two nitrogen atoms at the 1,3 position in a six-membered benzene and five-membered imidazole- fused ring system. Molecules with benzimidazole derivatives serve important functions as therapeutic agents and have shown excellent results in clinical and biological research.

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Introduction: Squamous cell carcinoma is a major public health concern, with traditional treatments such as surgery, chemotherapy, and radiation therapy frequently resulting in significant side effects. Immunotherapy targeting checkpoints such as PD-1, CTLA-4, and B7- H3 provides a more specific approach but incurs high costs due to monoclonal antibodies.

Aim And Objective: This study aims to investigate the potential of natural flavonoids as lowtoxicity, small molecule-based alternatives targeting the PD-1 immunological checkpoint for SCC treatment.

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Colorectal cancer (CRC) is one of the most common and deadly forms of cancer worldwide, necessitating accurate and early detection to improve treatment outcomes. Traditional diagnostic methods often rely on manual examination of pathological images, which can be time-consuming and prone to human error. This study presents an advanced approach for colorectal cancer detection using a Random Hinge Exponential Distribution coupled Attention Network (RHED-CANet) on pathological images.

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