Search

Melanotic neuroectodermal tumor of infancy also known as progonoma is an exceedingly rare neoplasm occurring within first two years of life with around 550 cases reported so far. It is predominantly a benign neoplasm but clinical suspicion of malignancy is always high owing to its rapid progression. Thus, it is a cause of concern to the parents and clinicians alike. It mostly involves the craniofacial bones and mean age of occurrence is 5 months. On radiology, well-defined lytic lesions are encountered. Histopathology is the gold standard for diagnosis wherein a biphasic tumor is seen. It comprises larger polygonal cells with melanin pigment and smaller round blue cells. Surgical excision is the preferred modality of treatment. However, the recurrence rates vary from 15 to 27%. Very few cases with metastasis have been reported. We present two interesting cases of this rare neoplasm along with a comprehensive clinical and pathological review of this rare entity.

ABSTRACTIntegrated farming system (IFS), comprising various enterprises such as crop, horticulture, dairy, poultry and fishery optimally, uses farm resources to suit small and medium farms of India. In this study, 55 IFSs with different sizes and several enterprises were assessed in terms of their environment impact, eco-efficiency and technical efficiency (TE). The households, which own these IFS, were grouped into four major categories based on farm size viz., marginal (2.0 ha). Among the farm size category, the highest eco-efficiency was recorded for marginal farms, whereas the lowest eco-efficiency was observed for small farms. The highest eco-efficiency was recorded for farm having five enterprises (INR195 kg CO2eq. ha−1) followed by four enterprises (INR190 kg CO2eq.ha−1). Among the enterprises, the highest eco-efficiency was recorded in fruits, whereas the lowest eco-efficiency was observed in dairy. The TE scores estimated using stochastic frontier analysis decreased with increasing farm size and the highest TE score was recorded for marginal farms, whereas medium and large farms recorded the lowest TE scores. The findings indicated the necessity for imparting training and demonstrations and funding support as well as subsidy for larger adoption of IFS to reap higher returns.

Introduction: The availability of essential medicines in health facilities in Jur River County (JRC), South Sudan, is below expectations. This is despite the requirement that all citizens should be provided with adequate quality health care services. The objective of the study was to assess the availability of essential medicines and inventory management practices in JRC. Method: This was a cross sectional study conducted in 31 of the 51 health facilities in JRC. These were 23 primary health care units (PHCUs) and eight primary health care centres (PHCCs). Data were collected using a structured questionnaire, logistics management information system (LMIS) data reports and checklist forms. All the completed checklists and questionnaires were analysed using IBM SPSS statistics version 20.0 and LMIS data was analysed using excel spreadsheet. Results: The main findings were stockouts and overstocking of essential medicines, low skilled health workers (HWs) and ineffective rotation of medicines in the health facilities. From January – August 2021, the stockouts of essential medicines in PHCUs and PHCCs were 44% and 34% respectively, whereas the incidences of over stockings were 22% and 31% respectively. Almost all (97%) of the health facilities kept records of essential medicines, revealing stockouts of 90.3% on the day of the visit. Of the 31 HWs interviewed 23 (74.9%) were community health workers (CHWs), four (12.9%) nurses and four (12.9%) pharmacy technicians; most (87.1%) had attained secondary education. Conclusion: The quantities of essential medicines were inadequate and able to cover only two months. The major reasons were inadequate supply of essential medicines; recruitment of CHWs and nurses, instead of pharmacy technicians in the management of supplies; ineffective rotation of medicines within and other health facilities. More research is needed on the factors affecting the availability of medicines at the health facilities in JRC.

Despite the availability of factor replacement therapy, including prophylaxis, to treat and prevent bleeding, haemophilic arthropathy continues to be the most common complication of haemophilia and significantly impairs the quality of life in people with haemophilia (PwH). Regular periodic assessment of joint status in PwH is essential to identify early arthropathic changes and prevent the development or progression of haemophilic arthropathy. Kinematic and kinetic assessment are preferable and MRI is the gold standard for diagnosing haemophilic arthropathy, but availability is limited in developing countries. HJHS and ultrasound in conjunction with HEAD-US have been shown to effective in assessing changes indicating arthropathy.

Cotton (Gossypium spp.), a crucial cash crop in the United States, requires the constant monitoring of growth parameters for informed decision-making. Recently, forecasting models have gained prominence for predicting canopy indicators, aiding in-season planning and management decisions to optimize cotton production. This study employed unmanned aerial system (UAS) technology to collect canopy cover (CC) data from a 40-hectare cotton field in Driscoll, Texas, in 2020 and 2021. Long short-term memory (LSTM) models, trained using 2020 data, were subsequently applied to forecast the CC values for 2021. These models were compared with real-time auto-regressive integrated moving average (ARIMA) models to assess their effectiveness in predicting the CC values up to 14 days in advance, starting from the 28th day after crop emergence. The results showed that multiple-input multi-step output LSTM models achieved higher accuracy in predicting the in-season CC values during the early growth stages (up to the 56th day), with an average testing RMSE of 3.86, significantly lower than other single-input LSTM models. Conversely, when sufficient testing data are available, single-input stacked-LSTM models demonstrated precision in CC predictions for later stages, achieving an average RMSE of 3.06. These findings highlight the potential of LSTM models for in-season CC forecasting, facilitating effective management strategies in cotton production.

Oleogels, which are traditionally utilized to reduce saturated and trans fats in bakery foods, have recently shown promising applications in non-bakery foods, particularly in the enhancement of their food texture and cooking qualities. This study investigates the impact of incorporating stearic acid-containing candelilla wax–groundnut oil oleogel in various proportions on the production of whole wheat pasta. Five different pasta samples were prepared by replacing water with oleogels in varying concentrations (2.5%, 5%, 10%, and 15%), and their physicochemical attributes were evaluated using a range of analytical methods for both cooked and uncooked pasta (like microscopy, colorimetry, dimensional analysis, texture, cooking qualities, moisture content, and FTIR). Significant differences in width, thickness, and color properties were observed between the control sample (0% oleogel) and those containing oleogel, with notable variations in surface texture and color intensities, particularly with the higher oleogel content (p < 0.05). Cooked pasta exhibited lower L* values and higher a* values than uncooked pasta. Stereo zoom microscope and field emission scanning electron microscope (FESEM) micrographs demonstrated a change in the pasta surface topology and microstructures. Dark spots on the pasta with greater oleogel concentrations (samples with 10% and 15% oleogel replacement) suggest the formation of starch–lipid complexes. Cooking induced pore formation, which was more pronounced when the oleogel content was increased, impacted the water absorption capacity, swelling index, and moisture content. The cooked samples exhibited higher moisture content and improved polymer network stability compared to the uncooked ones, indicating the potential of oleogel incorporation to modulate pasta properties in a concentration-dependent manner. These findings underscore the versatility of oleogels when their applications are diversified in non-bakery foods to enhance food texture and quality.

Background: Neonatal sepsis remains a significant cause of morbidity and mortality globally, particularly in developing countries like India. Early and late onset sepsis present unique challenges in diagnosis and management, with maternal and neonatal factors playing crucial roles in the manifestation of the condition. Methodology: Data were collected from tertiary care hospitals affiliated with Kasturba Medical College, Mangaluru. A structured proforma was used to gather information on maternal factors, birth history, neonatal conditions, and complications. Statistical analysis was performed using Chi- square test and student’s ‘t’ test. Results: Out of 132 cases, 50.75% were early onset sepsis (EOS) and 49.25% were late onset sepsis (LOS). Blood culture reports were positive in 46.1% cases. Maternal comorbidities included gestational diabetes mellitus (GDM), antepartum hemorrhage (APH), and pregnancy-induced hypertension (PIH). Neonatal comorbidities such as convulsions, congenital malformations, neonatal jaundice, preterm birth, and low birth weight were observed. Positive blood culture reports correlated with low birth weight and preterm births. Staphylococcus aureus was the most common organism, followed by Citrobacter Spp., Enterobacter Spp., and Pseudomonas aeruginosa. Sensitivity analysis revealed varying degrees of susceptibility to different antibiotics. Conclusion: Maternal factors like GDM, APH, and PIH showed no significant correlation with neonatal sepsis, whereas neonatal factors such as low birth weight and preterm birth were associated with an increased risk. Consanguinity also emerged as a potential risk factor. Staphylococcus aureus was the predominant causative organism, with varying antibiotic sensitivities. This study underscores the importance of understanding maternal and neonatal factors in the prevention and management of neonatal sepsis.

Objectives: To evaluate the loss of crestal bone height around dental implants placed in various tissue biotypes. Materials and Methods: 20 patients with single edentulous sites were allocated randomly, with 10 samples in each into Group I (implants were placed in thick tissue biotype) and Group II (implants were placed in thin tissue biotype). Baseline cone-beam computed tomography (CBCT) was performed after implant placement in both groups, and follow-up CBCT was taken at the time of cementation prior to occlusal loading to assess the crestal bone loss around the mesial and distal side of implants in both groups. Result: A significant loss of crestal bone at both the distal and mesial sides of the implants at the time of cementation was observed in both groups but Group II showed more crestal bone loss as compared to Group I. Conclusion: Mean crestal bone loss was more in Group II (thin tissue biotype) in comparison to Group I (thick tissue biotype). The thick biotype causes less crestal bone changes than the thin biotype, which evokes more loss of crestal bone during the period of peri-implant healing.