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Objective: A year after the emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as a new crisis in respiratory infections, there remain many uncertainties and unknowns about SARS-CoV-2 and the disease it causes, called coronavirus disease (COVID-19). Although COVID-19 is known as a respiratory disease, some atypical manifestations have been seen, different from those seen in other types of viral respiratory infections. This paper aims to describe designing, launching, and implementing a data collection system for all respiratory diseases, with a focus on SARS-CoV-2 from the onset of this pandemic. Method: The current registry is designed in compliance with the standard Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, along with the declaration of Helsinki principles. Results: A respiratory disease registry, with an emphasis on COVID-19 and other co-infections, was developed. Data consisted of demographic, clinical, and supporting information about SARS-CoV-2 and other respiratory viral diseases. Conclusion: It is hoped that the current data registry will facilitate patient evaluation and improve the outcomes of cases of respiratory infection defined by a particular condition, disease, or exposure. Moreover, the registry can harmonize data about the treatment, outcomes, and well-being of patients who receive care over time, and identify best practices. [ABSTRACT FROM AUTHOR]

A life-threatening respiratory disease, coronavirus 2019 (COVID-19), has spread across the globe since December 2019. Many prognostic factors have already been put forward to predict the risk of death and other outcomes. The current study is evaluating the survival rate between hypertensive and non-hypertensive infected patients. Patients who were included in this study were admitted between 20 February to 1 March 2020 in Fars (southwest of Iran) province hospitals. Data were collected from the electronic base registry which contained demographic information, medical symptoms, and signs, underlying diseases, CT scan results, and final outcome. Of all 1239 positive cases, 159 (12.83%) had known with hypertension ant this group was significantly older than non-hypertensive patients (66.1 years Vs 48.95 years, p <.001). According to Kaplan–Meier survival curve and log-rank test, it was seen hypertensive patients deteriorated more rapidly than non-hypertensive group (p =.032). Moreover, HIV, cardiovascular, and kidney disease were diagnosed as factors that increase the risk of death in hypertensive patients. The current study about the survival rate of COVID-19 patients had shown hypertensive patents are in danger of disease severity, although it may be related to their age. Moreover, the probability of other complications like diabetes, smoking, asthma, kidney, and cardiovascular diseases, and either some other infections such as HIV can make the condition complicated and need more consideration to prevent noxious outcomes. [ABSTRACT FROM AUTHOR]

In this research, the effects of heat treatment are studied on the microstructure and mechanical properties of the explosive bonding of 304 stainless steel plates and CK45 carbon steel with a constant explosive load and various standoff distances. The samples are heat treated in a furnace for 2-h and 4-h at 250℃ and 350℃. The results imply that by increasing the standoff distance from 4 to 5 mm, the impact kinetic energy increases and severe plastic deformation occurs in the bonding interface. The metallography results indicate the wave-vortex nature of the interface with the increase of standoff distance. In addition, heat treatment for 2 h at 350℃ leads to an increase in the thicknesses of intermetallic compounds in the interface. Also, the hardness decreases from 271 to 171 Vickers, and from 279 to 195 Vickers with 2 h of heat treatment at 350℃ in samples with standoff distances of 4 and 5 mm, respectively. Furthermore, the strengths of the samples decrease from 449 to 371 MPa, and from 510 to 433 MPa, respectively. Hardness and strength changes occur due to changes in the thickness of the intermetallic area and an increase in grain sizes. [ABSTRACT FROM AUTHOR]

Background: Introduction of therapeutic genes into the injured site of nervous system can be achieved using transplantation of cellular vehicles containing desired gene. To transfer exogenous genes into the cellular vehicles, lentiviral vectors are one of interested vectors because of advantages such high transduction efficiency of dividing and non-dividing cells. Unrestricted somatic stem cells are subclasses of umbilical cord blood derived stem cells which are appreciate candidates to use as cellular vehicles for ex vivo gene therapy of nervous system. Objectives: In current study we investigated the effect of lentiviral vector transduction on the neuronal related features of unrestricted somatic stem cells to indicate the probable and unwanted changes related to transduction procedure. Materials and Methods: In this experimental study, lentiviral vector containing green fluorescent protein (GFP) were transduced into unrestricted somatic stem cells and its effect was investigated with using MTT assay, qPCR and immunohistochemistry techniques. For statistical comparison of real time PCR results, REST software (2009, Qiagen) was used. Results: Obtained results showed lentiviral vector transduction did not have cytotoxic effects on unrestricted somatic stem cells and did not change neuronal differentiation capacity of them as well the expression of some neuronal related genes and preserved them in multilineage situation. Conclusions: In conclusion, we suggested that lentiviral vectors could be proper vectors to transfer therapeutic gene into unrestricted somatic stem cells to provide a cellular vehicle for ex vivo gene therapy of nervous system disorders. [ABSTRACT FROM AUTHOR]

Sustainable management of orchard fields requires detailed information about the tree types, which is a main component of precision agriculture programs. To this end, hyperspectral imagery can play a major role in orchard tree species mapping. Efficient use of hyperspectral data in combination with field measurements requires the development of optimized band selection strategies to separate tree species. In this study, field spectroscopy (350 to 2500 nm) was performed through scanning 165 spectral leaf samples of dominant orchard tree species (almond, walnut, and grape) in Chaharmahal va Bakhtiyari province, Iran. Two multivariable methods were employed to identify the optimum wavelengths: the first includes three-step approach ANOVA, random forest classifier (RFC) and principal component analysis (PCA), and the second employs partial least squares (PLS). For both methods we determined whether tree species can be spectrally separated using discriminant analysis (DA) and then the optimal wavelengths were identified for this purpose. Results indicate that all species express distinct spectral behaviors at the beginning of the visible range (from 350 to 439 nm), the red edge and the near infrared wavelengths (from 701 to 1405 nm). The ANOVA test was able to reduce primary wavelengths (2151) to 792, which had a significant difference (99% confidence level), then the RFC further reduced the wavelengths to 118. By removing the overlapping wavelengths, the PCA represented five components (99.87% of variance) which extracted optimal wavelengths were: 363, 423, 721, 1064, and 1388 nm. The optimal wavelengths for the species discrimination using the best PLS-DA model (100% accuracy) were at 397, 515, 647, 1386, and 1919 nm. [ABSTRACT FROM AUTHOR]