Levofloxacin induced psychosis: a rare case report

Levofloxacin is a commonly prescribed antibiotic for treating bacterial infections in routine clinical practice. A wide range of side-effects have been ascribed to the quinolone group of drugs, the most common being gastrointestinal. Central nervous system is rarely involved; neuropsychiartic complications are among the least reported adverse reactions. We report a rare case of levofloxacin induced acute psychosis in a young male presenting in out-patient department with signs of urinary tract infection along with pneumonitis

Borderline phyllodes tumor of breast in a premenarchal girl: A relatively common tumor at an uncommon age

Phyllodes tumors are relatively rare breast lesions that usually occur in the age group of 35 ‒ 55 years. It is a very rare diagnosis in young girls, particularly at prepubertal age. Because of the uncommon nature of this tumor in children, it may be misdiagnosed leading to inappropriate management. We report a case of a 9–year-old girl who was diagnosed as a case of borderline phyllodes tumor left breast. Simple mastectomy without axillary staging was performed. She has recovered well and is on follow up

Combining ability and heterosis studies for grain iron and zinc concentrations in pearl millet [Cenchrus americanus (L). Morrone]

Iron (Fe) and zinc (Zn) deficiency has been identified as a major food-related health issue, affecting two billion people globally. Efforts to enhance the Fe and Zn content in food grains through plant breeding are an economic and sustainable solution to combat micronutrient deficiency in resource-poor populace of Asia and Africa. Pearl millet, Cenchrus americanus (L). Morrone, considered as a hardy nutri-cereal, is the major food crop for millions of people of these nations. As an effort to enhance its grain mineral content, an investigation was conducted using line × tester analysis to generate information on the extent of heterosis, gene action, combining ability for grain yield potential, and grain mineral nutrients (Fe and Zn). The partitioning of variance attributable to parents indicated that the lines and testers differed significantly for the traits studied. For most of the attributes, hybrids that were superior to the parents in the desired direction in terms of per se performance were identified. The analysis of combining ability variance indicated the preponderance of both additive and non-additive genetic effects. Thus, reciprocal recurrent selection can be used to develop a population with high–grain Fe and Zn contents. The Fe and Zn content in grain exhibited a highly significant and positive association between them, whereas the Fe and Zn contents individually showed a negative, albeit weak, correlation with grain yield and a moderate positive relation with grain weight. This indicates that mineral nutrient contents in grains can be improved without significant compromise on yield. The consistency of these trends across the environment suggests that these findings could be directly used as guiding principles for the genetic enhancement of Fe and Zn grain content in pearl millet

Borderline phyllodes tumor of breast in a premenarchal girl: A relatively common tumor at an uncommon age

Phyllodes tumors are relatively rare breast lesions that usually occur in the age group of 35 ‒ 55 years. It is a very rare diagnosis in young girls, particularly at prepubertal age. Because of the uncommon nature of this tumor in children, it may be misdiagnosed leading to inappropriate management. We report a case of a 9–year-old girl who was diagnosed as a case of borderline phyllodes tumor left breast. Simple mastectomy without axillary staging was performed. She has recovered well and is on follow up.</p

A cast partial obturator with hollow occlusal shim and semi-precision attachment

A maxillofacial patient's quality of life is distorted and social integration becomes difficult. An obturator is a maxillofacial prosthesis used to close a congenital or acquired tissue defect, primarily of the hard palate and/or contiguous alveolar/soft-tissue structures. Subsequently, it restores the esthetics, speech, and function. The present clinical report aimed for the prosthetic rehabilitation of a maxillectomy defect by the incorporation of a semi-precision attachment as PRECI-SAGIX – male part of 2.2 mm on fixed partial denture (#22 and #23 teeth) and matrix – plastic female part of size 2.2 mm and height 4.2 mm of yellow on cast partial in polymer base. It aids in the retention of a hollow lightweight obturator. The technique also described the method to make a bulbless obturator with a hollow self-cured acrylic resin occlusal shim. A patient is quite satisfied with bulb less, lightweight cast partial and hollow shim palatal obturator

Analysis of outcomes and prognostic factors of acute lymphoblastic leukemia patients treated by MCP841 protocol: A regional cancer center experience

Background: A dramatic improvement in the survival of acute lymphoblastic leukemia (ALL) patients in the last three decades has been observed. MCP 841 protocol is an old but effective tool with tolerable toxicities. The objective of this study was to estimate the relapse-free survival of ALL patients treated uniformly with MCP 841 protocol on the basis of various prognostic factors. Materials and Methods: The study design was retrospective and it was conducted in a regional cancer center of Northwest India. Three hundred and ten ALL patients who underwent treatment with MCP 841 protocol and regular follow-up for up to 5 years were selected for this study. Relapse-free survival was calculated by Kaplan-Meier analysis and Cox regression analysis was used to calculate the hazards ratio (HR) using Statistical Package for the Social Sciences (SPSS) software for windows version 20.0. Results: Fifty-four percent patients were 1 lakh/cmm had 41% survival [HR 2.14 (1.76-2.48) with, P < 0.001]. Conclusion: MCP 841 protocol is a useful tool for the treatment of ALL in children when more aggressive protocols can not be used

Optimized Stacking Ensemble Learning Model for Breast Cancer Detection and Classification Using Machine Learning

Breast cancer is the most frequently encountered medical hazard for women in their forties, affecting one in every eight women. It is the greatest cause of death worldwide, and early detection and diagnosis of the disease are extremely challenging. Breast cancer currently exceeds all other female cancers, including ovarian cancer. Researchers can use access to healthcare records to find previously unknown healthcare trends. According to the National Cancer Institute (NCI), breast cancer mortality rates can be lowered if the disease is detected early. The novelty of our work is to develop an optimized stacking ensemble learning (OSEL) model capable of early breast cancer prediction. A dataset from the University of California, Irvine repository was used, and comparisons to modern classifier models were undertaken. The implementation analyses reveal the unique approach’s efficacy and superiority when compared to existing contemporary categorization models (AdaBoostM1, gradient boosting, stochastic gradient boosting, CatBoost, and XGBoost). In every classification task, predictive models may be used to predict the class level, and the current research explores a range of predictive models. It is better to integrate multiple classification algorithms to generate a set of prediction models capable of predicting each class level with 91–99% accuracy. On the breast cancer Wisconsin dataset, the suggested OSEL model attained a maximum accuracy of 99.45%, much higher than any single classifier. Thus, the study helps healthcare professionals find breast cancer and prevent it from happening

Optimized Stacking Ensemble Learning Model for Breast Cancer Detection and Classification Using Machine Learning

Breast cancer is the most frequently encountered medical hazard for women in their forties, affecting one in every eight women. It is the greatest cause of death worldwide, and early detection and diagnosis of the disease are extremely challenging. Breast cancer currently exceeds all other female cancers, including ovarian cancer. Researchers can use access to healthcare records to find previously unknown healthcare trends. According to the National Cancer Institute (NCI), breast cancer mortality rates can be lowered if the disease is detected early. The novelty of our work is to develop an optimized stacking ensemble learning (OSEL) model capable of early breast cancer prediction. A dataset from the University of California, Irvine repository was used, and comparisons to modern classifier models were undertaken. The implementation analyses reveal the unique approach&rsquo;s efficacy and superiority when compared to existing contemporary categorization models (AdaBoostM1, gradient boosting, stochastic gradient boosting, CatBoost, and XGBoost). In every classification task, predictive models may be used to predict the class level, and the current research explores a range of predictive models. It is better to integrate multiple classification algorithms to generate a set of prediction models capable of predicting each class level with 91&ndash;99% accuracy. On the breast cancer Wisconsin dataset, the suggested OSEL model attained a maximum accuracy of 99.45%, much higher than any single classifier. Thus, the study helps healthcare professionals find breast cancer and prevent it from happening

Addition of magnetic resonance imaging to computed tomography-based three-dimensional conformal radiotherapy planning for postoperative treatment of astrocytomas: Changes in tumor volume and isocenter shift

Introduction: Postoperative radiotherapy is the current gold standard treatment in astrocytomas. Computed tomography (CT)-based radiotherapy planning leads to either missing of the tumor volume or underdosing. The aim of this prospective study was to study the changes in tumor volume on addition of magnetic resonance imaging (MRI) to CT-based three-dimensional radiotherapy treatment planning of astrocytomas. Materials and Methods: Twenty-five consecutive patients of astrocytoma (WHO grades I-IV) for postoperative three-dimensional conformal radiotherapy were included in this prospective study. Postoperative tumor volumes were contoured on CT-based images and recontoured on CT-MRI images after automated MRI co-registration on treatment planning system Eclipse 8.9.15 as per ICRU-50 report. Tumor volumes were compared with each other. Result: The MRI-based mean and median tumor volume was 24.24 cc ± 13.489 and 18.72 cc (range 5.6-46.48 cc), respectively, while for CT it was 19.4 cc ± 11.218 and 16.24 cc (range: 5.1-38.72 cc), respectively. The mean and median isocenter shift between CT and MRI was 4.05 mm and 4.39 mm (range 0.92-6.32 mm), respectively. There is a linear relationship between MRI and CT volume with a good correlation coefficient of R2 = 0.989, and MRI-based tumor volume was 1.208 times as compared to CT volume. Statistical analysis using paired sample t-test for the difference in CT and MRI tumor volume was highly significant (P < 0.001). Conclusion: Addition of MRI to the CT-based three-dimensional radiation treatment planning reduces the chances of geographical miss or tumor under dosing. Thus, MRI should be an integral part of three-dimensional planning of astrocytomas

Cancer related fatigue: A ubiquitous problem yet so under reported, under recognized and under treated

Background: Cancer related fatigue (CRF) is a problem that is highly under reported, under recognized and thus, under treated. About 80% of patients receiving chemotherapy/radiotherapy experience CRF, making it the most common side effect of cancer treatment. Functional assessment of chronic illness therapy fatigue (FACIT-F) version-4 is a 13 item questionnaire that has been used to measure the level of fatigue of cancer patients during their daily activities over the past 7 days. Materials and Methods: 92 patients of age 18 years and above attending the oncology Out Patient Department (OPD) of a regional cancer center were recruited in this study and were given FACIT-F questionnaire. The relevant sociodemographic parameters were obtained from the medical records of the patients. The internal consistency of the 13 items was measured using the Cronbach′s alpha. Results: The Cronbach alpha coefficient for FACIT-F scale in our study was found to be 0.74. Kendall′s coefficient of concordance was estimated to be 0.080. The correlation between Eastern Cooperative Oncology Group (ECOG) performance status and mean score of FACIT-F was studied, Pearson correlation coefficient was estimated to be 0.271 (P = 0.009). Conclusions: FACIT-F is a brief, simple, easy to administer and patient friendly tool to measure the fatigue in last 7 days. CRF should be given adequate attention from the beginning of the treatment to improve the quality of life of cancer patients