Understanding the economics of inclusion: a perspective on Nepal

Missing infrastructure is inhibiting the connection between rural homes and businesses and urban customers and suppliers in Nepal. Ashutosh Mani Dixit suggests that a policy rethink is needed to ensure economic inclusion for rural populations

Strengthening infrastructure governance in Nepal

The development narrative in Nepal often focusses almost exclusively on how to raise funds for Nepal’s considerable infrastructure needs. Ashutosh Mani Dixit and Bishal K Chalise supplement this with robust framework to ensure resources are used efficiently

Biometric properties of onion seedlings relevant to the development of onion seedling transplanter

A study was conducted to investigate biometric properties of seedlings of three common varieties of onion viz. Pusa Red, Set-126 and Pusa Ridhi (50, 60, 70 days old). The parameters determined were weight of seedling without and with de-topping, bulb diameter, stem diameter, height, moisture content, compressive strength and coefficient of static friction. The weight of seedlings without de-topping ranged from 0.53 to 3.05 g while with de-topping ranged from 0.47 to 1.68 g for all the three cultivars. The bulb and stem diameter for all varieties ranged from 3.13 to 5.76 g for bulb and 2.44 to 4.33 g for stem whereas height varied from 14.48 cm to 34.65 cm, among all Pusa red was taller than Set-126 and Pusa Ridhi. The moisture content at different age and for all cultivars ranged from 84.89 to 91.63 % (wb). The average coefficient of static friction for mild steel (MS), aluminum and galvanized iron (GI) varied from 0.63 to 0.79. The compressive strength of bulb and stem of seedlings were 9.76 to 19.54 N for bulb and 4.08 to 8.17 N for stem respectively for 50 to 70 days seedlings. This information was not available but is critical in designing and selection of different components of onion seedling transplanter

Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer

Colorectal cancer (CRC) is a common cause of cancer-related deaths worldwide. The CRC mRNA gene expression dataset containing 644 CRC tumor and 51 normal samples from the cancer genome atlas (TCGA) was pre-processed to identify the significant differentially expressed genes (DEGs). Feature selection techniques Least absolute shrinkage and selection operator (LASSO) and Relief were used along with class balancing for obtaining features (genes) of high importance. The classification of the CRC dataset was done by ML algorithms namely, random forest (RF), K-nearest neighbour (KNN), and artificial neural networks (ANN). The significant DEGs were 2933, having 1832 upregulated and 1101 downregulated genes. The CRC gene expression dataset had 23,186 features. LASSO had performed better than Relief for classifying tumor and normal samples through ML algorithms namely RF, KNN, and ANN with an accuracy of 100%, while Relief had given 79.5%, 85.05%, and 100% respectively. Common features between LASSO and DEGs were 38, from them only 5 common genes namely, VSTM2A, NR5A2, TMEM236, GDLN, and ETFDH had shown statistically significant survival analysis. Functional review and analysis of the selected genes helped in downsizing the 5 genes to 2, which are VSTM2A and TMEM236. Differential expression of TMEM236 was statistically significant and was markedly reduced in the dataset which solicits appreciation for assessment as a novel biomarker for CRC diagnosis

Prognostic model development for classification of colorectal adenocarcinoma by using machine learning model based on feature selection technique boruta

Colorectal cancer (CRC) is the third most prevalent cancer type and accounts for nearly one million deaths worldwide. The CRC mRNA gene expression datasets from TCGA and GEO (GSE144259, GSE50760, and GSE87096) were analyzed to find the significant differentially expressed genes (DEGs). These significant genes were further processed for feature selection through boruta and the confirmed features of importance (genes) were subsequently used for ML-based prognostic classification model development. These genes were analyzed for survival and correlation analysis between final genes and infiltrated immunocytes. A total of 770 CRC samples were included having 78 normal and 692 tumor tissue samples. 170 significant DEGs were identified after DESeq2 analysis along with the topconfects R package. The 33 confirmed features of importance-based RF prognostic classification model have given accuracy, precision, recall, and f1-score of 100% with 0% standard deviation. The overall survival analysis had finalized GLP2R and VSTM2A genes that were significantly downregulated in tumor samples and had a strong correlation with immunocyte infiltration. The involvement of these genes in CRC prognosis was further confirmed on the basis of their biological function and literature analysis. The current findings indicate that GLP2R and VSTM2A may play a significant role in CRC progression and immune response suppression

Correlating multi-functional role of cold shock domain proteins with intrinsically disordered regions

Cold shock proteins (CSPs) are an ancient and conserved family of proteins. They are renowned for their role in response to low-temperature stress in bacteria and nucleic acid binding activities. In prokaryotes, cold and non -cold inducible CSPs are involved in various cellular and metabolic processes such as growth and development, osmotic oxidation, starvation, stress tolerance, and host cell invasion. In prokaryotes, cold shock condition re-duces cell transcription and translation efficiency. Eukaryotic cold shock domain (CSD) proteins are evolved form of prokaryotic CSPs where CSD is flanked by N-and C-terminal domains. Eukaryotic CSPs are multi-functional proteins. CSPs also act as nucleic acid chaperons by preventing the formation of secondary structures in mRNA at low temperatures. In human, CSD proteins play a crucial role in the progression of breast cancer, colon cancer, lung cancer, and Alzheimer's disease. A well-defined three-dimensional structure of intrinsically disordered re-gions of CSPs family members is still undetermined. In this article, intrinsic disorder regions of CSPs have been explored systematically to understand the pleiotropic role of the cold shock family of proteins

Cathepsins B and D drive hepatic stellate cell proliferation and promote their fibrogenic potential

El pdf del artículo es el manuscrito de autor.-- PubMed: PMCID:PMC2670444Cathepsins have been best characterized in tumorigenesis and cell death and implicated in liver fibrosis; however, whether cathepsins directly regulate hepatic stellate cell (HSC) activation and proliferation, hence modulating their fibrogenic potential, is largely unknown. Here, we show that expression of cathepsin B (CtsB) and cathepsin D (CtsD) is negligible in quiescent HSCs but parallels the increase of -smooth muscle actin and transforming growth factor- during in vitro mouse HSC activation. Both cathepsins are necessary for HSC transdifferentiation into myofibroblasts, because their silencing or inhibition decreasedHSC proliferation and the expression of phenotypicmarkers ofHSC activation, with similar results observed with the human HSC cell line LX2. CtsB inhibition blunted AKT phosphorylation in activated HSCs in response to platelet-derived growth factor.Moreover, during in vivo liver fibrogenesis caused by CCl4 administration, CtsB expression increased in HSCs but not in hepatocytes, and its inactivation mitigated CCl4-induced inflammation, HSC activation, and collagen deposition. Conclusion: These findings support a critical role for cathepsins inHSC activation, suggesting that the antagonismof cathepsins inHSCsmay be of relevance for the treatment of liver fibrosis.Financial support: The work was supported by CIBEREHD and grant PI070193 (Instituto de Salud Carlos III); by grant SAF2006-06780 (Plan Nacional de I+D), Spain; and by grant P50-AA-11999 (Research Center for Liver and Pancreatic Diseases, US National Institute on Alcohol Abuse and Alcoholism).Peer reviewe

Predictive Modeling Techniques in Prostate Cancer

A number of new predictive modeling techniques have emerged in the past several years. These methods can be used independently or in combination with traditional modeling techniques to produce useful tools for the management of prostate cancer. Investigators should be aware of these techniques and avail themselves of their potentially useful properties. This review outlines selected predictive methods that can be used to develop models that may be useful to patients and clinicians for prostate cancer management.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63147/1/10915360152745812.pd

Racial differences in serum prostate-specific antigen (PSA) doubling time, histopathological variables and long-term PSA recurrence between African-American and white American men undergoing radical prostatectomy for clinically localized prostate cancer

To determine if there are significant differences in biochemical characteristics, biopsy variables, histopathological data, and rates of prostate-specific antigen (PSA) recurrence between African-American (AA) and white American (WA) men undergoing radical prostatectomy (RP), as AA men are twice as likely to die from prostate cancer than their white counterparts. PATIENTS AND METHODS We established a cohort of 1058 patients (402 AA, 646 WA) who had RP and were followed for PSA recurrence. Age, race, serum PSA, biopsy Gleason score, clinical stage, pathological stage, and PSA recurrence data were available for the cohort. The chi-square test of proportions and t -tests were used to assess basic associations with race, and log-rank tests and Cox regression models for time to PSA recurrence. Forward stepwise variable selection was used to assess the effect on the risk of PSA recurrence for race, adjusted by the other variables added one at a time. RESULTS The AA men had higher baseline PSA levels, more high-grade prostatic intraepithelial neoplasia (HGPIN) in the biopsy, and more HGPIN in the pathology specimen than WA men. The AA men also had a shorter mean (sd) PSA doubling time before RP, at 4.2 (4.7) vs 5.2 (5.9) years. However, race was not an independent predictor of PSA recurrence ( P  = 0.225). Important predictors for PSA recurrence in a multivariable model were biopsy HGPIN ( P  < 0.014), unilateral vs bilateral cancer ( P  < 0.006), pathology Gleason score and positive margin status (both P  < 0.001). CONCLUSIONS This study indicates that while there are racial differences in baseline serum PSA and incidence of HGPIN, race is not an independent risk factor for PSA recurrence. Rather, other variables such as pathology Gleason score, bilateral cancers, HGPIN and margin positivity are independently associated with PSA recurrence. The PSA doubling time after recurrence may also be important, leading to the increased mortality of AA men with prostate cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74706/1/j.1464-410X.2005.05561.x.pd