Adenocarcinoma of sweat gland: case report and review of literature

Sweat gland carcinoma is a rare malignant tumour, first described in 1865, with approximately 220 cases reported in last 30 years. Lower limbs are the most common site of involvement, followed by the upper extremities, and the head. Trunk is rarely involved. Five histological types have been described, most common being porocarcinomas followed by ductal carcinomas, adenoid cystic carcinomas, syringomatous carcinomas and mucinous carcinomas. These are aggressive tumours with potential for distant metastasis. Wide surgical excision is the treatment of choice and the overall prognosis is poor. Here we report another case of sweat gland adenocarcinoma with no evidence of metastasis.

Psychrotrophic yeast Yarrowia lipolytica NCYC 789 mediates the synthesis of antimicrobial silver nanoparticles via cell-associated melanin

A psychrotrophic marine strain of the ascomycetous yeast Yarrowia lipolytica (NCYC 789) synthesized silver nanoparticles (AgNPs) in a cell-associated manner. These nanostructures were characterized by UV-Visible spectroscopy and scanning electron microscope-energy dispersive spectrometer (SEM-EDS) analysis. The brown pigment (melanin) involved in metal-interactions was obtained from the cells. This extracted pigment also mediated the synthesis of silver nanoparticles that were characterized by a variety of analytical techniques. The melanin-derived nanoparticles displayed antibiofilm activity. This paper thus reports the synthesis of AgNPs by the biotechnologically important yeast Y. lipolytica; proposes a possible mechanism involved in the synthetic process and describes the use of the bio-inspired nanoparticles as antibiofilm agents

Preparing faculty for problem-based learning curriculum at Patan Academy of Health Sciences, Nepal

Introduction: Patan Academy of Health Sciences (PAHS) in Nepal has adopted problem-based learning (PBL) as principal pedagogy to foster attributes predefined for its medical graduates. This study evaluates reaction of participants in PBL tutor-training program focused on PBL process and its assessment. Methods: An orientation program was organized separately for 24 faculty members and 45 higher secondary science majoring students prior to conduction of real-time PBL tutorial sessions. Faculty’s reaction as PBL tutors was collected before and after the orientation program using a 13-item self-administered questionnaire. Internal consistency reliability of the questionnaire items and outcome of the training program were assessed using Cronbach’s alpha, coefficient of variation, Shapiro-Wilk test, paired t-test and adjusted effect size for dependent samples. Results: The pre-test internal consistency reliability was high (0.89) whereas it was acceptable (0.69) for post-test. The average score increased from 26.50 to 34.55 and standard deviation decreased from 5.39 to 2.70 between pre- and post-test. Difference between post- and pre-tests total scores followed normal distribution and suitable parametric test (paired t-test) revealed the difference was highly significant (p< 0.0001). The adjusted effect size was high (1.65) for small dependent samples. Conclusions: The faculty training for PBL and assessment was helpful  in implementing PBL pedagogy at PAHS.  Keywords: Nepal, PAHS, Problem based learning, Process assessment, Tutor training program Â

Validating a problem-based learning process assessment tool in a Nepalese medical school

Introductions: The newly established Patan Academy of Health Sciences (PAHS) has incorporated the measurement of non-cognitive skills and behaviors into the summative assessment in the setting of problem based learning (PBL). This study was conducted to validate a PBL process assessment tool for PAHS.Methods: A list of 72 items of student behaviors observable in PBL tutorials was compiled from literature review. They were categorized under ten broad dimensions consistent with predefined PAHS Graduate Attributes. A series of PBL project committee meetings and expert inputs refined the list of 72 items to 47 and categorized them under eight dimensions. These 47 items, each with a 4-point rating scale, formed the Tutor Assessment of Student Tool (TAS-Tool). Twenty-four trained faculty members used the TAS-Tool to evaluate the performance of 41 senior high school students in PBL tutorials. Results: The internal-consistency of the TAS-Tool was very high rona’s .. eoal of to inonsistent ites furter increased it to 0.975. Principal components analysis with varimax rotation applied to the remaining 45 items gave seven components and explained 69.47% of the variation between the components. These seven components (% variation) were: Immersed in the Tutorial Process (20.16%); Professional (12.71%); Communicator and Team Leader (11.25%); Critical Thinker (8.77%); Reflector (6.22%); Creative (5.95%), and Sensitive (4.41%).Conclusions: TAS-Tool was found to be reliable and valid instrument deemed applicable in formative PBL process assessment at PAHS starting with the pioneer cohort of medical students. Further validation of TASTool through longitudinal study with PAHS students is required for summative purpose.Keywords: factor analysis, problem based learning, summative assessment, tool validation, Nepa

Combined effect of boron and salt on polypeptide resolutions in wheat (Triticum aestivum) varieties differing in their tolerance

Salinity aggravates toxicity symptoms of boron in wheat. Four wheat (Triticum aestivum L.) varieties differing in tolerance to these stresses were subjected to five stress treatments [control (2.5 ppm B), 50 ppm B + 6 dS/m, 100 ppm B + 6 dS/m, 50 ppm B + 10 dS/m and 100 ppm B + 10 dS/m]. Higher reductions for root length, fresh and dry weight were observed in Schomburgk and HD 2009 varieties at 100 ppm B + 10 dS/m NaCl in comparison to KRL 35 and BTSchomburgk. Results indicated that combined boron and salt stresses significantly increased soluble B and proline concentrations in the roots. At the highest level of stress (100 ppm B + 10 dS/m), maximum proline accumulation was evident in HD 2009 (18.6 mg/g) and minimum in KRL 35 (13.5 mg/g). Protein profile expressions of boron tolerant and intolerant varieties of wheat showed de novo synthesis of two specific polypeptides (35.73 and 31.10 KDa) in boron tolerant variety and one (16.98 kDa) in boron intolerant variety. Likewise, KRL 35 (salt tolerant) showed 4 specific polypeptides of 89.13, 58.4, 46.21 and 31.10 kDa, whereas three specific polypeptides (24.05, 19.13 and 17.52 kDa) appeared in the salt intolerant variety (HD 2009). Appearance of 5 common polypeptides bands of MW 89.13, 53.4, 46.21. 31.10 and 25.12 kDa in both the tolerant varieties, i.e. BT-Schomburgk (boron tolerant) and KRL 35 (salt tolerant) is of special interest and could have possible use as markers for tolerance. The synthesis of common polypeptide of MW 25.12 kDa was observed in all the four varieties with increase in stress treatments

Sequential herbicide application coupled with mulch enhances the productivity and quality of winter onion (Allium cepa L.) while effectively controlling the mixed weed flora

Weed control poses substantial difficulties for winter season onion (Allium cepa L.) cultivation in the north-western Indo-Gangetic Plains, primarily due to the constrained efficacy of the existing herbicides. To address this issue, a 2-year field study was conducted to assess the efficacy of pre- and post-emergence herbicides (pendimethalin, ethoxysulfuron, imazethapyr, and quizalofop-p-ethyl) individually and in combination with crop residue mulch for weed control in winter onion. The results revealed that using herbicides or mulches in isolation did not provide satisfactory weed control. However, the integration of natural mulch with pendimethalin followed by quizalofop-p-ethyl application proved to be the most effective weed control strategy, resulting in the least reduction in bulb yield (10.3%) compared to other treatments. On the contrary, combinations of pendimethalin with ethoxysulfuron or imazethapyr showed adverse effects on the onion crop and inflicted the highest yield losses among all treatments (78.6 and 83.4%, respectively). However, the combination of pendimethalin with quizalofop-p-ethyl coupled with crop mulch resulted in season-long weed control and over 80% bulb yield (36.58 t/ha) gains compared to the weed-free condition. These findings emphasize the efficacy of combining herbicides and mulches as an integrated weed management strategy for onions. By adopting such integrated approaches, farmers could improve weed control while maintaining bulb yield and quality, reducing the risks associated with herbicide resistance, and promoting sustainable onion production in the north-western Indo-Gangetic Plains

Impact of an International Nosocomial Infection Control Consortium multidimensional approach on central line-associated bloodstream infection rates in adult intensive care units in eight cities in India

SummaryObjectiveTo evaluate the impact of the International Nosocomial Infection Control Consortium (INICC) multidimensional infection control approach on central line-associated bloodstream infection (CLABSI) rates in eight cities of India.MethodsThis was a prospective, before-and-after cohort study of 35650 patients hospitalized in 16 adult intensive care units of 11 hospitals. During the baseline period, outcome surveillance of CLABSI was performed, applying the definitions of the CDC/NHSN (US Centers for Disease Control and Prevention/National Healthcare Safety Network). During the intervention, the INICC approach was implemented, which included a bundle of interventions, education, outcome surveillance, process surveillance, feedback on CLABSI rates and consequences, and performance feedback. Random effects Poisson regression was used for clustering of CLABSI rates across time periods.ResultsDuring the baseline period, 9472 central line (CL)-days and 61 CLABSIs were recorded; during the intervention period, 80898 CL-days and 404 CLABSIs were recorded. The baseline rate was 6.4 CLABSIs per 1000 CL-days, which was reduced to 3.9 CLABSIs per 1000 CL-days in the second year and maintained for 36 months of follow-up, accounting for a 53% CLABSI rate reduction (incidence rate ratio 0.47, 95% confidence interval 0.31–0.70; p=0.0001).ConclusionsImplementing the six components of the INICC approach simultaneously was associated with a significant reduction in the CLABSI rate in India, which remained stable during 36 months of follow-up

Diversity-oriented synthesis of analogues of the novel macro- cyclic peptide FR-225497 through late stage functionalization

Abstract A concise synthetic approach to a class of biologically interesting cyclic tetrapeptides is reported which involves a late-stage functionalization of a macrocyclic scaffold through cross metathesis in an attempt to create diversity. The utility of this protocol is demonstrated through the preparation of three structural analogues of the important naturally occurring histone deacetylase inhibito

Machine learning methods for predicting cancer drug effects from signaling and cell fate data

An important area of research within the discipline of the Computational Systems Biology is to investigate the mechanisms of determination of cell fate. As the cellular development progresses, a cell goes through several phenotypes (e.g. Apoptosis, Proliferation, G1, S, G2 and M). Apoptosis, which is a process of programmed cell death in case of a healthy cell, is a special case of cell fate. For example, development of fingers in human embryo occurs due the apoptotic cell death of the cells between digits. Regulatory networks such as transcriptional regulatory network for regulating cell differentiation in the embryonic development, signaling networks for regulating activity level of proteins, etc., determine the course of cell fate and lineage commitment. Signaling pathways play important regulatory roles in apoptosis. However, in cancer cells signaling pathways are in an atypical forms that lead to continuous survival, growth and proliferation of tumor cells. A major objective in cancer research is to investigate the dynamics of signaling pathways that influence the apoptosis of tumor cells. The changes in signaling pathways supporting uncontrolled cell growth, termed as rewiring, can lead to dysregulation of cell fates. Hence comparative analysis of normal and oncogenic signal transduction pathways may provide insights into dynamics of cancer drug induced signaling changes and enable the discovery of novel and effective anti-cancer therapies. A better understanding of rewiring is essential for developing effective anti-cancer therapeutic strategies. In this thesis, we first demonstrate how rewiring of signaling pathways regulate diverse signaling molecules in an apoptotic network. We use a simple yet intuitive differential equation based computational model to understand the roles played by certain essential regulatory proteins in the regulation of programmed cell death. Inspired by the success of dynamical modeling and data analysis in cancer biology, we propose a hybrid modeling approach combining computational models with experimental phosphoproteomics data. We use a hybrid modeling approach based on ordinary differential equation (ODE) models and machine learning techniques to map network rewiring in the apoptotic pathways that may be responsible for the increase of drug sensitivity of tumour cells in triple-negative breast cancer. Our method employs Genetic Algorithm to search for the most likely network topologies by iteratively generating simulated protein phosphorylation data using ODEs and the rewired network and then fitting the simulated data with real data of cancer signaling and cell fate. Most of our predictions are consistent with experimental evidence from literature. Combining the strengths of knowledge-driven and data-driven approaches, our hybrid model can help uncover molecular mechanisms of cancer cell fate at the systems level. Secondly, we investigate the context-specific drug effects on diverse cancer cell lines. We construct a knowledge-based model of ordinary differential equations (ODEs) for the apoptotic signaling network and subsequently infer model parameters (e.g. reaction rates) from real phosphoproteomics data for three breast tumor cell lines, i.e. BT-20, MCF7 and MDA-MB-453 using a Bayesian framework of inference. The model is used to predict apoptosis in response to various perturbations such as caspase knockdown for each of the three cell lines which can be validated using the experimental literature. The inferred changes of the parameters reveal drug effects on diverse cell lines under the treatment with the drug of Erlotinib. Despite having a limited amount of real data, we believe that our in silico apoptosis model is able to capture several dynamic characteristics of drug sensitivity of tumor cells in a coherent way. We hope that as new and larger datasets become available in future, our proposed model can be used to gain more in-depth and quantitative understanding about the regulation of cancer cell death. Our studies offer a novel method of hybrid modeling for linking the computational model with biological data. It is demonstrated to be promising for explaining and predicting the impact of anti-cancer therapies on cancer cells at the systems level.Doctor of Philosophy (SCE