Economic and environmental impact assessments of a stand-alone napier grass-fired combined heat and power generation system in the southeastern US

The International Journal of Life Cycle Assessment - Napier grass, one of the high yield perennial energy crops can be grown on marginal lands with minimal inputs, but with increased soil carbon...     

Flooding or drought which one is more offensive on pepper physiology and growth?

Molecular Biology Reports - Both extreme usage of water in agriculture i.e., drought and flooding affect physiological and growth aspects of the plant as well as gene expression undertaken in water...     

Comparison of PCR-RFLP with 21-plex PCR and rDNA Sequencing for Identification of Clinical Yeast Isolates

Non-albicans Candida species and other rare yeasts have emerged as major opportunistic pathogens in fungal infections. Identification of opportunistic yeasts in developing countries is mainly performed by phenotypic assay, which are time-consuming and prone to errors. The aim of the present study was to evaluate PCR-RFLP as a routinely used identification technique for the most clinically important Candida species in Iran and make a comparison with a novel multiplex PCR, called 21-plex PCR. One hundred and seventy-three yeast isolates from clinical sources were selected and identified with sequence analysis of the D1/D2 domains of rDNA (LSU rDNA) sequencing as the gold standard method. The results were compared with those obtained by PCR-RFLP using MspI restriction enzyme and the 21-plex PCR. PCR-RFLP correctly identified 93.4% of common pathogenic Candida species (C. albicans, C. glabrata, C. parapsilosis, C. tropicalis, and P. kudriavsevii (=?C. krusei)) and was able to identify 45.5% of isolates of the uncommon yeast species compared to the D1/D2 rDNA sequencing. Compared with PCR-RFLP, all common Candida species and 72.7% of uncommon yeast species were correctly identified by the 21-plex PCR. The application of the 21-plex PCR assay as a non-sequence-based molecular method for the identification of common and rare yeasts can reduce turnaround time and costs for the identification of clinically important yeasts and can be applied in resource-limited settings.

     

Silver-coated magnetic nanoparticles as an efficient delivery system for the antibiotics trimethoprim and sulfamethoxazole against E. Coli and S. aureus: release kinetics and antimicrobial activity

BioMetals - Trimethoprim and sulfamethoxazole are prescribed for a broad spectrum of bacteria. However, the use of these medicines is restricted due to the risk of microbial resistance in the body....     

Real-time observation of structure and dynamics during the liquid-to-solid transition of FUS LC

A subset of the proteins found in pathological protein fibrils also exhibit tendencies for liquid-liquid phase separation (LLPS) both in vitro and in cells. The mechanisms underlying the connection between these phase transitions have been challenging to study due to the heterogeneous and dynamic nature of the states formed during the maturation of LLPS protein droplets into gels and solid aggregates. Here, we interrogate the liquid-to-solid transition of the low-complexity domain of the RNA-binding protein FUS (FUS LC), which has been shown to adopt LLPS, gel-like, and amyloid states. We employ magic-angle-spinning NMR spectroscopy, which has allowed us to follow these transitions in real time and with residue-specific resolution. We observe the development of β-sheet structure through the maturation process and show that the final state of FUS LC fibrils produced after LLPS is distinct from that grown from fibrillar seeds. We also apply our methodology to FUS LC G156E, a clinically relevant FUS mutant that exhibits accelerated fibrillization rates. We observe significant changes in dynamics during the transformation of the FUS LC G156E construct and begin to unravel the sequence specific contributions to this phenomenon with computational studies of the phase-separated state of FUS LC and FUS LC G156E.     

Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologists in early diagnosis of mental disorders and preventing severe trauma. Major Depression Disorder (MDD) is a common and serious medical condition whose exact manifestations are not fully understood. So, early discovery of MDD patients helps to cure or limit the adverse effects. Electroencephalogram (EEG) is prominently used to study brain diseases such as MDD due to having high temporal resolution information, and being a noninvasive, inexpensive and portable method. This paper has proposed an EEG-based deep learning framework that automatically discriminates MDD patients from healthy controls. First, the relationships among EEG channels in the form of effective brain connectivity analysis are extracted by Generalized Partial Directed Coherence (GPDC) and Direct directed transfer function (dDTF) methods. A novel combination of sixteen connectivity methods (GPDC and dDTF in eight frequency bands) was used to construct an image for each individual. Finally, the constructed images of EEG signals are applied to the five different deep learning architectures. The first and second algorithms were based on one and two-dimensional convolutional neural network (1DCNN–2DCNN). The third method is based on long short-term memory (LSTM) model, while the fourth and fifth algorithms utilized a combination of CNN with LSTM model namely, 1DCNN-LSTM and 2DCNN-LSTM. The proposed deep learning architectures automatically learn patterns in the constructed image of the EEG signals. The efficiency of the proposed algorithms is evaluated on resting state EEG data obtained from 30 healthy subjects and 34 MDD patients. The experiments show that the 1DCNN-LSTM applied on constructed image of effective connectivity achieves best results with accuracy of 99.24% due to specific architecture which captures the presence of spatial and temporal relations in the brain connectivity. The proposed method as a diagnostic tool is able to help clinicians for diagnosing the MDD patients for early diagnosis and treatment.     

Dental stem cell banking: Techniques and protocols

Dental tissue-derived stem cells (DSCs) provide an easy, accessible, relatively noninvasive promising source of adult stem cells (ASCs), which brought encouraging prospective for their clinical applications. DSCs provide a perfect opportunity to apply for a patient's own ASC, which poses a low risk of immune rejection. However, problems associated with the long-term culture of stem cells, including loss of proliferation and differentiation capacities, senescence, genetic instability, and the possibility of microbial contamination, make cell banking necessary. With the rapid development of advanced cryopreservation technology, various international DSC banks have been established for both research and clinical applications around the world. However, few studies have been published that provide step-by-step guidance on DSCs isolation and banking methods. The purpose of this review is to present protocols and technical details for all steps of cryopreserved DSCs, from donor selection, isolation, cryopreservation, to characterization and quality control. Here, the emphasis is on presenting practical principles in accordance with the available valid guidelines.     

Competition and overlap of Oryzaephilus surinamensis and Plodia interpunctella populations under condition of stored date fruits

Plodia interpunctella and Oryzaephilus surinamensis are found in food storehouses including dates and palm storages. The current study aimed to determine competition and overlap potentials of the two pests of date fruits. Time series models were used to study two species populations and logistic growth model to estimate the effect of density of the species. The results revealed the environmental capacities of O. surinamensis and P. interpunctella were 433 and 1610 (maximum number per 20 g), respectively, and the population growth rates (r) were 1.2 and 1.3, respectively. Ecological balances of the two species were close to each other from the first to the third week. The population of O. surinamensis decreased in the fourth week of the competition. The highest population balance of the two species was in the 14th week. The potential of exploitable ecological niches (e_ij) and the amount of non-exploited ecological niches by any species (z_ij) for O. surinamensis was higher than for P. interpunctella from the 8th week untill the end of sampling period. The overlap of ecological niches in the two species (D) ranged from 0.94 to 1, indicating a complete overlap of temporal activity in the two populations on date palm. The current results of this study can be used by integrated pest management specialists. Information over the effects of species competition on population dynamics and their coexistence can be used to predict population status and to adopt simple pest control methods.     

Heat-Induced Conformational Unfolding of Fatty Acid-Free and Fatted Camel Serum Albumin: A Comparative Study

Albumin is a multifunctional non-glycosylated, negatively charged plasma protein, with extraordinary ligand-binding and transport properties, antioxidant functions, and enzymatic activities. Physiologically, albumin transports free fatty acids in plasma and contributes in maintaining colloid osmotic pressure. Recent progresses in using albumin as a versatile protein carrier for drug targeting and for improving the pharmacokinetic profile of peptide or protein-based drugs, increased the attempts for improving albumin stability. Studying the thermal stability of camel albumin may provide us not only new clues for designing recombinant albumins, but also molecular insights on camel physiology. This study aims to determine the thermal stability of camel albumin. Fatted camel serum albumin (FCSA) was purified from blood via combination of Cohn’s method and anion-exchange chromatography. Activated charcoal treatment was used to obtain defatted camel serum albumin (CSA). Fluorescence spectroscopy and differential scanning calorimetry (DSC) were used to study thermal denaturation of this protein. The set of fluorescence spectra were deconvoluted using the convex constraint analysis method (CCA). The results from deconvolution of fluorescence spectroscopy and DSC showed three and two components for CSA and FCSA, respectively. The bimodal DSC transition can be attributed to a crevice between domains I and II and formation of two independent thermodynamic domains. The crevice formation can be prevented by fatty acid binding between domains I and II. The calculated values of ?H _v/?H _cal, approximately 0.4 for CSA and near 1 for FCSA, confirmed the presence of at least one intermediate in thermal unfolding of CSA and the absence of the intermediate for FCSA. The obtained midpoint transition temperature (T _m) of FCSA was about 20 °C higher than that of CSA. Such enormous stabilizing effect may be attributed to the fact that fatty acid serves as glue which preserves different domains beside each other and prevents formation of the mentioned intermediate.