Bhaktapur Cancer Hospital

Mushrooms are recognized for their therapeutic qualities in addition to their nutritional value. Numerous substances with therapeutic properties are present even in inedible mushrooms. These substances can be used to make potent medications once they have been refined and examined. The present study aims to explore the biological activities of the extracts of Microporous xanthopus and Phylloporia pectinata , collected from Gulmi District, Nepal. The methanolic and ethyl acetate extracts of both species were subjected to phytochemical screening, total phenolic content (TPC), total flavonoid content (TFC), and antioxidant and antibacterial activity. The LC–MS analysis was performed to identify the compounds present in the extract by detecting and analyzing their molecular ion peaks. The TPC (611.89 and 319.16 mg GAE/g) and TFC (57.18 and 142.37 mg QE/g) were found highest in the ethyl acetate extract of P. pectinata and M. xanthopus, respectively. The antioxidant activity (DPPH radical scavenging %) of the methanolic extract and the ethyl acetate extract of M. xanthopus was found to be 41.7% and 21.6%, whereas that for P. pectinata was found to be 78.6% and 55.4%, respectively. Those extracts were found to inhibit the growth of S. aureus, E. coli , and S. typhi . The LC–MS analysis of the extract of P. pectinata showed eight important secondary metabolites present in the extract. These mushrooms, with their rich content of bioactive compounds, demonstrate significant antioxidant and antibacterial properties, indicating their potential for medicinal applications.

Cervical cancer, a prevalent malignancy linked to HPV infection, necessitates accurate and timely diagnosis to mitigate its high mortality rate. Traditional diagnostic methods, such as Pap smears and colposcopy, are often laborious and subjective, highlighting the need for advanced computational approaches. This study covers machine learning (ML) to enhance cervical cancer detection, evaluating models including Multi- Layer Perceptron (MLP), Gaussian Naive Bayes (GaussianNB), Bagging, Random Forest (RF) and K-Nearest Neighbors (KNN). The MLP classifier achieved 99.59% accuracy, while other algorithms surpassed 97% AUC, underscoring their clinical viability. To ensure interpretability, Explainable AI (XAI) techniques – SHAP, LIME and ELI5, are used, explaining feature contributions and decision pathways, thus nurturing clinician trust. The integration of high-accuracy ML models with transparent XAI frameworks not only improves diagnostic precision, but also facilitates the ethical deployment of AI in healthcare, paving the way for reliable, data-driven clinical decision making.

Nepal has practiced a high fertility rate drop and marginalized and indigenous groups are more fertile and reproduce earlier interaction of reproductive timing and socio-economic elements. The Fertility was measured by cross-sectional survey in terms of a quantitative survey of the 289 Women of Danuwar in Lalitpur District (Mean fertility) in terms of Fertility Knowledge (FK), and Children Ever Born (CEB) as a measure of the Total fertility rate (TFR), descriptive statistics, ANOVA, multiple linear regression to determine the effects of education, employment, child mortality experience, singulate mean age at marriage (SMAM) and timing of childbearing. TFR was estimated and the socio-demographic variation was large and was 2.41. The factors associated with increased fertility included low education, not part of the working population, lost children, married young and the birth spacing was low. The regression equation was also significant (R2 = 0.153; p < 0.01). The reproduction behavior, education, child survival, and economic participation determine fertility of Danuwar women as a transitory period. The absence of equitable improvement of fertility and better reproduction health among the marginalized groups in Nepal requires late marriage, increased female involvement in the labor force, better education and better child-survival programs.

ABSTRACT This study aimed to predict daily runoff using three machine learning models: artificial neural networks (ANNs), random forests (RFs), and extreme gradient boosting (XGBoost). Thirty-five years of discharge records and remote-sensing climate data were used to develop and validate the models, demonstrating the potential of satellite data for machine-learning-based runoff prediction, especially in data-poor regions like Nepal. The study identified 1-day lagged discharge (lag_1), average temperature, and maximum temperature as the three most important input variables. The developed ANN model demonstrates high accuracy in streamflow prediction, achieving an R2 of 0.928, a root-mean-square error (RMSE) of 435.43 m3/s, a Nash–Sutcliffe efficiency (NSE) of 0.93, and a Kling–Gupta efficiency (KGE) of 0.944 for the Narayani River Basin. When applied to the Trishuli River, a major tributary of the Narayani, the model demonstrated strong performance, with an R2 of 0.895, an RMSE of 425.92 m3/s, an NSE of 0.89, and a KGE of 0.908. Nonetheless, RF outperformed ANN in capturing low-flow conditions in the Narayani River. Overall, the models provide valuable tools for retrospective streamflow prediction, gap-filling in hydrological records, and supporting effective and sustainable water management.

Introduction: Breast cancer is one of the common malignancy among women in Nepal, with a rise in incidence among younger, premenopausal patients. A significant proportion are hormone receptor positive (HR+), where ovarian function suppression (OFS) remains a cornerstone of systemic therapy. Bilateral salpingo-oophorectomy (BSO) provides a permanent, compliance-free method of OFS, particularly relevant for metastatic disease, recurrence, or risk reduction in BRCA mutation carriers. Traditionally considered the domain of gynaecologists, laparoscopic BSO can also be safely performed by surgical oncologists with laparoscopic skills, thereby avoiding interdepartmental delays and maintaining continuity of care. This study reports the experience of implementing laparoscopic BSO for breast cancer patients in a surgical oncology unit. Methods: All consecutive patients undergoing laparoscopic BSO between January 2020 and December 2024 in a surgical oncology unit at Bhaktapur Cancer Hospital were included. Data were extracted from a prospectively maintained departmental database. Clinical variables, indications, perioperative details, complications, and histopathology findings were analysed. Data analysis was descriptive, using Microsoft Excel (Microsoft Corporation, Redmond, WA, USA). Results: Thirty patients underwent laparoscopic BSO, with a median age of 37 years (IQR: 32–43). The most common indications were metastatic disease (n=14), recurrence (n=8), BRCA mutation pathogenic status (n=5), high-risk disease (n=2) and progression on neoadjuvant chemotherapy (n=1). The median operative duration was 60 minutes (IQR: 53–80). There were no conversions to open surgery, reexplorations, or readmissions. The mean hospital stay was 2.6 days. Histopathological evaluation revealed ovarian metastases in six cases (20%), fallopian tube tuberculosis in one case, mature cystic teratoma in one case, and unremarkable findings in the remaining 22 patients. Conclusion: Laparoscopic BSO performed by surgical oncologists is a safe, feasible, and effective procedure in the continuum of care for breast cancer. It provides definitive ovarian suppression with low morbidity, avoids delays associated with referrals, and ensures continuity of care. These findings support the role of surgical oncologists in integrating laparoscopic BSO into comprehensive breast cancer management.

Introduction: This study aims to analyze the epidemiological risk factors and management outcomes of vulvar cancer in histologically confirmed cases based on tumor stage. Vulvar cancer is an uncommon form of cancer and presents a public health issue comparable to other types of malignancies. Cost associated with diagnosis, medical treatment, and psychological well-being of female. Methods: This was a hospital-based retrospective descriptive study conducted over one month. Women with diagnosed case of vulvar carcinoma between 2021 to 2023 who were undergoing treatment at Bhaktapur Cancer Hospital in the Department of Gynecologic Oncology were included in this study. The risk factors, symptoms, stage, histological type, and treatment were recorded. The categorical variables obtained were summarized using frequency and percentage. Results: total of 25 patients with biopsy confirmed vulvar malignancy were included in the study. The majority of the patients were postmenopausal, with ages exceeding 50 years, accounting for 18 (72%) cases, and were multiparous. Squamous cell carcinoma constituted 18 (72%) cases of the total histological types and was most common histological variant. The most frequently performed procedure was radical vulvectomy combined with bilateral pelvic lymphadenectomy which accounted for 14 (56%) of totalprocedure. Conclusion: Vulvar carcinoma is a rare type of gynaecological malignancy in Nepal, and mainly affects women in their postmenopausal stage. The commonest type is the squamous cell carcinoma that is usually diagnosed in early cases. Risk factors were commonly parity and smoking. The primary therapy was surgery, particularly radical vulvectomy and lymphadenectomy.

Students often face difficulties while learning mathematics at primary level. To obtain the obstacles of the students in the mathematical progress and outcomes, this study was conducted systematically. This is the quantitative study with the involvement of 24 students of class two from primary five schools in the Lalbandi municipality. On the basis of result of the Progress Monitoring Test and CAS of respective schools, the students were identified with mathematical difficulties. Students, here participants, were chosen with the help of the quartile (lower quartile or the first quartile (Q1) to involve in the progress monitoring test of the intervention program. After the result of the Progress Monitoring Test, a small group of four participants was chosen for the intervention program to measure the progress of those participants. It was difficult to manage the intervention program with optimal group size. The tests of the intervention program were conducted for seven times with the participants. These tests were taken after every 7 days to measure the progress in number and other mathematical concepts. T-test was used to determine the significant difference between the achievements of the both pre-tests and post-tests. The participants of grade two were found to have faced many types of the mathematical difficulties, viz. low level of understanding, lack of permanent learning, numerical figure confusion, delivery of subject matters and lack of concentrations.

Penelitian ini bertujuan untuk menganalisis pengaruh kepemimpinan transformasional terhadap motivasi dan kinerja karyawan housekeeping di Grand Keisha Hotel Yogyakarta serta dampaknya terhadap kualitas layanan dan kepuasan tamu. Latar belakang penelitian ini didasari oleh pentingnya peran sumber daya manusia dalam industri perhotelan, khususnya pada departemen housekeeping yang bertanggung jawab atas kebersihan dan kenyamanan fasilitas hotel. Penelitian ini menggunakan pendekatan kualitatif dengan teknik pengumpulan data melalui wawancara mendalam, observasi, dan dokumentasi. Hasil penelitian menunjukkan bahwa kepemimpinan transformasional yang diterapkan oleh manajemen hotel mampu meningkatkan motivasi kerja karyawan melalui perhatian personal, apresiasi, dan keterlibatan dalam pengambilan keputusan. Selain itu, kepemimpinan transformasional juga berdampak positif terhadap kinerja karyawan dengan membentuk sikap disiplin, komunikasi dua arah, serta pencapaian standar kerja yang tinggi. Motivasi dan kinerja karyawan yang meningkat dapat memberikan dampak terhadap peningkatan kualitas layanan dan kepuasan tamu, yang pada akhirnya berkontribusi terhadap citra dan daya saing hotel.