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Background Treatment modalities for cancer including surgery, radiotherapy and chemotherapy, have some complications even in the oral cavity. The literature describes oral lesions that may arise as a result of chemotherapy. However, information regarding oral symptoms in advanced cancer patients is poor. Objective To identify the oral manifestations like oral mucositis, dry mouth and loss of taste in patients undergoing chemotherapy treatment. Methods We evaluated 60 patients affected by malignancy undergoing chemotherapy treatment. The clinical and pathological data such as age, gender, diagnosis of malignancy and types of treatments with anticancer chemotherapeutic drug treatment, were obtained. Patients were routinely evaluated for the presence of oral mucositis based on the Common Terminology Criteria for Adverse Events (CTCAE) v5.0 scale for adverse effects and graded. Other findings like dry mouth and loss of taste were recorded. Results Of the 60 patients, 40 (66.6%) were male, and 20 (33.3%) females with a mean age of 53.7 years. Most patients about 63% and 83% were diagnosed with dry mouth and loss of taste, respectively and 71% of patients had mucositis. Chemotherapy drugs like Cyclophosphamide, carboplatin, nanoxel, paclitaxel, oxaliplatin, docetaxel and doxorubicin, were directly associated with oral mucositis. Conclusion Patients treated with chemotherapy for cancer most often suffer from a multitude of intense and debilitating oral dysfunctions. Oral lesions found in patients undergoing chemotherapy were mucositis, dry mouth and loss of taste. These adverse effects and an appropriate symptomatic therapy need to be discussed with the patients. Chemotherapy has a significant but transient effect on the oral symptoms.

Objective: To determine the incidence, clinical characteristics, and survival outcomes of patients with multiple primary malignancies at a tertiary care cancer centre. Methods: A retrospective analysis of 28 patients (11 males, 17 females) with histologically confirmed multiple primary malignancies was conducted from 2020 to 2022. Data on demographic characteristics, tumour sites, histopathology, staging, and survival were collected. Kaplan-Meier method was used for survival analysis with log-rank tests for group comparisons. Results: The incidence of multiple primary malignancies was 0.73%. Metachronous tumours (67.9%) were more common than synchronous tumours (32.1%). Breast cancer was the most frequent primary (32.1%) and secondary (28.6%) malignancy. Mean survival time significantly differed between males (198.0 months, 95% CI: 76.8-122.4) and females (125.2 months, 95% CI: 88.5-162.0, p=0.093). Advanced stage presentation was common, with 42% of primary and 25% of secondary tumours diagnosed at stage III. The event-free survival was higher for metachronous than synchronous malignancies (log-rank p<0.05). Among patients, 28.6% had a positive family history, and 17.9% reported substance addiction. Conclusion: Multiple primary malignancies show distinct patterns in incidence, tumour site distribution, and survival outcomes, with metachronous presentations and breast cancer predominance being key characteristics in our population. [ABSTRACT FROM AUTHOR]

The increasing computational demand for real-time mobile applications has led to the development of mobile edge computing (MEC), with support from unmanned aerial vehicles (UAVs), as a promising paradigm for constructing high-throughput line-of-sight links for ground users and pushing computational resources to network edges. Users can reduce processing latency and the load on their local computers by delegating tasks to the UAV in its role as an edge server. The coverage capacity of a single UAV is, however, very limited. Moreover, it will be easy to intercept the data that is transferred to the unmanned aerial vehicle. Thus, for UAV-assisted mobile edge computing, we proposed a transmission technique based on multi-agent deep reinforcement learning in this study. The recommended approach to maximize UAV deployment first applies the particle swarm optimization algorithm. Then, deep reinforcement learning is utilized to optimize the secure offloading to maximize the system utility and minimize the quantity of information eavesdropping, taking into consideration different user task types with diverse preferences for processing time and residual energy of computing equipment. The results of the simulation demonstrate that, in comparison to the single-agent strategy and the benchmark, the multi-agent approach can optimize offloading more successfully and produce higher system utility. [ABSTRACT FROM AUTHOR]

Background: Dietary adherence during chemotherapy is crucial for managing side effects and maintaining nutritional status. However, there is a lack of validated tools to measure dietary adherence in this context. The aim of this study was to develop and validate the Chemotherapy Dietary Adherence Scale (CDAS) for assessing dietary adherence among cancer patients undergoing chemotherapy. Methods: A cross-sectional study was conducted over 2 months. The CDAS was developed through a literature review and expert consultation. Face and content validation were performed with 25 experts in oncology, dietetics, and community medicine. The Content Validity Index (CVI) was calculated at both the item (I-CVI) and scale (S-CVI) levels. Results: The expert panel comprised diverse professionals (40% public health experts, 20% medical oncologists, and 20% dietitians). Face validation showed 85% agreement on grammar, clarity, and content. The I-CVI was 0.81, and the S-CVI was 0.83, indicating strong content validity. Conclusion: The CDAS demonstrated robust content validity and relevance for assessing dietary adherence in cancer chemotherapy patients. Further research is needed to evaluate its psychometric properties and clinical utility. [ABSTRACT FROM AUTHOR]

In this research, we explore the latest advancements in the domains of vehicle detection, recognition, and tracking through vision-based methodologies. Spanning from traditional techniques to cutting-edge deep learning models, the paper provides a thorough analysis of their strengths, limitations, and real-world applications. We examine the evolution of detection methods, including edge-based approaches and motion segmentation techniques like frame differencing, background subtraction, and optical flow, showcasing their efficacy in identifying moving vehicles. Convolutional neural networks (CNNs), in particular, are highlighted for the integration of appearance-based approaches due to their transformative impact on accuracy, particularly in difficult settings. In addition, we explore vehicle recognition and classification methods, highlighting their applications in traffic analysis, security, and urban planning. These methods include color recognition, license plate recognition, logo recognition, and vehicle type classification. In addition to comparing tracking algorithms based on accuracy, computing economy, and adaptability, the evaluation includes methodologies for tracking vehicles that include model-based, shape-based, and feature-based approaches. In conclusion, this research provides a thorough examination of the development of vision-based vehicle analysis, making it a useful tool for academics, professionals, and decision-makers working to improve traffic surveillance systems and plan for the future of urban transportation. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to assess the risk of malnutrition in cancer chemotherapy patients and identify the associated factors. Materials and Methods: It is a cross-sectional study. Purposive sampling was used to collect data from a tertiary care cancer centre. The study collected data from 101 participants and used a malnutrition screening tool (MST) to assess the risk of malnutrition. Results: The majority of participants in the study were female (61.4%) and in the 3rd or 4th stage of cancer (57.4% and 41.6%, respectively). Of the participants, 63.4% experienced weight loss without trying chemotherapy, and 60.4% were at risk for malnutrition. Cancer stage was associated with malnutrition risk, but other clinical variables were not. Conclusion: Malnutrition is a significant issue among cancer chemotherapy patients in the study's population. The findings of this study can be used to develop interventions to prevent and manage malnutrition in patients with cancer and improve the effectiveness of cancer treatment in the Indian population. [ABSTRACT FROM AUTHOR]

Introduction: In India in 2020, there were an estimated 1.39 million cancers present in the country. Chemotherapy patients experience several problems such as ADRs (adverse drug reactions), and because of this, many dropouts have been happening. Also, there is a lack of communication between the patient and care providers (doctors). Objectives: Development and validation of a comprehensive needs assessment tool to assess the burden of chemotherapy on patients attending tertiary level health care facilities. Materials and Methods: Development and validation of comprehensive needs assessment in cancer chemotherapy involve several steps, including problem statement and literature review regarding the problem, domain generation, development of the preliminary questionnaire, face validation, statistical validation, and final draft of the tool. Results: A total of 10 experts are involved in face validation. The majority (80%) of the experts agreed with the grammar, clarity, and content of the tool. A few experts (20%) disagreed regarding the construction of the questionnaire, the appropriate level of understanding for the participants, and the content of the tool and suggested changes in the physical and psychological domains. The questionnaire has been re-structured according to the expert's suggestion before going for statistical validation. Internal consistency of the CNAT-CC was optimal, with a satisfactory Cronbach's alpha of 0.7 for the total scale. Discussion: The current study was focused on the development and validation of needs assessment in cancer chemotherapy patients. The CNAT-CC promises to be a comprehensive needs assessment tool that applies to a comparatively vast majority of patients undergoing cancer chemotherapy. [ABSTRACT FROM AUTHOR]

Background: Autologous HCT in multiple myeloma is done as upfront treatment in newly diagnosed transplant eligible patients after induction chemotherapy. In addition, it is standard for relapsed, aggressive non-Hodgkin lymphoma (NHL) and classical Hodgkin lymphoma (HL), and is curative in ~40% to 45% of patients. Over a decade, many efforts were made to find helpful parameters to predict an optimal time for initiating an efficient peripheral blood stem cell collection so that adequate stem cells are collected. It has been well accepted that CD34+ cell count in peripheral blood before leukapheresis is the best parameter to predict CD34 cell yield. However, white blood cell count, mononuclear cell count, and other easily obtained parameters are still used to guide the clinical practice of peripheral blood stem cell mobilization and collection. Materials and Methods: In the present study, we analyzed the correlation between peripheral blood MNC and Apheresis CD34 levels and also between peripheral blood CD34 by flow cytometry and apheresis CD34 levels. Results: We found that there was a statistically insignificant weak correlation between peripheral MNC and apheresis CD34. There was a statistically significant strong correlation between peripheral CD34 and apheresis CD34. Conclusion: The results show that peripheral blood MNC was analogous indicating that no reliable prediction can be done for CD34 cells collected in apheresis while peripheral CD34 by flow cytometry is the strongest predictor for initiating stem cell collection. [ABSTRACT FROM AUTHOR]

Pregnancy-related death is defined by the International Classification of Diseases, Tenth Revision (ICD-10) as the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death. A six year retrospective hospital record-based research regarding maternal deaths conducted at Department of Obstetrics & Gynecology, AJ Institute of Medical Sciences, Mangalore, situated in coastal Karnataka, South India. It included the data regarding age, parity, status of the patient on admission mode of delivery and cause of death. Of the total 3621 females delivered 17 maternal deaths were reported. The majority (29.4%) of the cases were from age group of 21-25 years. Multigravida and in antepartum state had a greater number (10) of deaths. Majority (29.3%) of the patient succumbed for sepsis. Sepsis and obstetrical haemorrhage are still major causes of maternal deaths. Most maternal deaths are preventable. The provision of timely management of complications can lower maternal mortality. [ABSTRACT FROM AUTHOR]

This study reports on an investigation of the antecedents of customer loyalty in an academic library setting. A structural model is presented to test the relationships between web-based library service quality, service value, customer satisfaction and customer loyalty based on theoretical underpinnings in the literature on service quality and customer loyalty. The study provides empirical data on library users' behavioral intentions, which helps understand the nature of customers' loyalty towards web-based library services. Participants included postgraduates and academic staff from four research intensive universities in Malaysia. Structural equation modeling was carried out to test the modeled relationships between the four construct in this study. This study provides insights into the antecedents of customer satisfaction and customer loyalty as findings revealed that service quality and service value have a direct effect on customer satisfaction, which then directly impacts customer loyalty. [ABSTRACT FROM AUTHOR]

Abstract: Kimura''s disease (KD) is a rare chronic inflammatory disorder that involves the subcutaneous tissues and occurs predominantly in the head and neck region, frequently associated with regional lymphadenopathy or salivary gland involvement. Although, not an uncommon condition in the Asian countries, it is quite rare among the occidental civilization and in the western countries is more commonly diagnosed among Asian migrants. Kimura''s disease is sometimes confused with angiolymphoid hyperplasia with eosinophilia, which occurs in the superficial skin of the head and neck region. The classical features of angiolymphoid hyperplasia with eosinophilia are characterized by a triad of painless subcutaneous masses in the head and neck region, blood and tissue eosinophilia, and markedly elevated immunoglobulin E (IgE) levels. Here, we report a case of a 33-year-old Indian male with KD who presented with unilateral nodular swelling in the right parotid region. The diagnosis was based on characteristic histopathologic findings in conjunction with peripheral eosinophilia and elevated serum IgE levels [Copyright &y& Elsevier]