Pancreatic cancer (PC) is considered a silent killer because it does not show specific symptoms at an early stage. Thus, identifying suitable biomarkers is important to avoid the burden of PC. Stratifin (SFN) encodes the 14-3-3σ protein, which is expressed in a tissue-dependent manner and plays a vital role in cell cycle regulation. Thus, SFN could be a promising therapeutic target for several types of cancer. This study was aimed at investigating, using online bioinformatics tools, whether SFN could be used as a diagnostic and prognostic biomarker in PC. SFN expression was explored by utilizing the ONCOMINE, UALCAN, GEPIA2, and GENT2 tools, which revealed that SFN expression is higher in PC than in normal tissues. The clinicopathological analysis using the ULCAN tool showed that the intensity of SFN expression is commensurate with cancer progression. GEPIA2, R2, and OncoLnc revealed a negative correlation between SFN expression and survival probability in PC patients. The ONCOMINE, UCSC Xena, and GEPIA2 tools showed that cofilin 1 is strongly coexpressed with SFN. Moreover, enrichment and network analyses of SFN were performed using the Enrichr and NetworkAnalyst platforms, respectively. Receiver operating characteristic (ROC) curves revealed that tissue-dependent expression of the SFN gene could serve as a diagnostic and prognostic biomarker. However, further wet laboratory studies are necessary to determine the relevance of SFN expression as a biomarker.

The pandemic situation of novel coronavirus disease 2019 (COVID-19) is a global threat on our current planet, with its rapid spread and high mortality rate. Sarcoidosis patients are at high risk to COVID-19 severity for having lung injuries as well as treating with immunosuppressive agents. So, physicians are in dilemma whether they should use immunosuppressive agents or not for the patients with sarcoidosis history and COVID-19 infection. Therefore, common factors should be identified to provide effective treatment. For determining the common genes between COVID-19 and sarcoidosis, GSE164805 and GSE18781 were retrieved from the Gene Expression Omnibus (GEO) database. Common upregulated genes were identified by using R language to investigate their involved pathways and gene ontologies (GO). With the aid of the STRING Cytoscape plugin tool, protein-protein interactions (PPIs) network was constructed. From the PPIs network, Hub genes and essential modules were detected by using Cytohubba, and MCODE respectively. For hub genes, TFs, TFs-miRNA, and drug, interaction networks were built through the NetworkAnalyst web platform. A total of 34 common upregulated genes were identified and among them, five hub genes, including TET2, MUC5AC, VDR, NFE2L2, and BCL6 were determined. In addition, a cluster having VDR and NFE2L2 was detected from the PPIs network. Moreover, 32 transcription factors and 9 miRNA were recognized for hub genes. Furthermore, vitamin D and some of its analogous compounds were obtained from the drug interaction network. In conclusion, hub genes identified in this study might have potential roles in modulating COVID-19 infection and sarcoidosis. However, further studies are required to corroborate this study.

Background and Aims: Occupational exposure to wood dust leads to lung function abnormalities that are prominent causes of morbidity and disability of sawmill workers. The adverse respiratory effects of wood dust in sawmills have not been studied thoroughly in Bangladesh. This study aimed to investigate the effect of wood dust on the respiratory health of sawmill workers compared to controls as well as to determine the association of wood dust-exposing effects with inflammatory blood biomarkers, such as immunoglobulin E (IgE), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP).Methods: This cross-sectional study included 100 sawmill workers from 25 distinct sawmills in various areas of Tangail, Bangladesh as well as 100 healthy volunteers who were adopted as a control group. Questionaries' survey and pulmonary function tests were performed face to face. Furthermore, after performing lung function tests, blood was drawn for further IgE, ESR, and CRP analyses.Results: Respiratory symptoms including breathlessness (32%), coughing (39%), sneezing (43%), chest tightness (30%), and itching (40%) were significantly higher in sawmill workers compared with control. Besides, sawmill workers' exposure to wood dust revealed a significantly lower level of spirometry parameters (forced vital capacity [FVC], FVC (%), forced expiratory volume in 1 s [FEV1], FEV1 (%), peak expiratory flow [PEF], PEF (%), FEV1/FVC (%), FEF25, FEF75, and FEF2575) compared with control and these spirometry parameters decreased with the increasing length of service. Moreover, a significantly higher level of IgE was observed in sawmill workers (290.90 ± 39.49) than in the control (120.95 ± 23.00).The high level of IgE suggests that the lower pulmonary function may be linked to allergic responses to wood dust among sawmill workers.

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Problem statement: How a host (the code consumer) can determine with certainty that a downloaded program received from untrusted source (the code producer) will maintain the confidentiality of the data it manipulates and it is safe to install and execute. Approach: The approach adopted for verifying that a downloaded program will not leak confidential data to unauthorized parties was based on the concept of Proof-Carrying Code (PCC). A mobile program (in its assembly form) was analyzed for information flow security based on the concept of proof-carrying code. The security policy was centered on a type system for analyzing information flows within assembly programs based on the notion of noninterference. Results: A verification tool for verifying assembly programs for information flow security was built. The tool certifies SPARC assembly programs for secure information flow by statically analyzing the program based on the idea of Proof-Carrying Code (PCC). The tool operated directly on the machine-code requiring only the inputs and outputs of the code annotated with security levels. The tool provided a windows user interface enabling the users to control the verification process. The proofs that untrusted program did not leak sensitive information were generated and checked on the host machine and if they are valid, then the untrusted program can be installed and executed safely. Conclusion: By basing proof-carrying code infrastructure on information flow analysis type-system, a sufficient assurance of protecting confidential data manipulated by the mobile program can be obtained. This assurance was come due to the fact that type systems provide a sufficient guarantee of protecting confidentiality.