Identification of an Immunoglobulin M (IgM) Antibody Against Enolase 1 Protein (ENO1) Derived from HEK-293 Cells in Patients with Kidney Failure

Kidney failure is one of the most important challenges in medicine. In this study, we used HEK-293 kidney cells to evaluate and compare changes in the expr     

Diagnostic and prognostic value of circular RNA CDR1as/ciRS‐7 for solid tumours: A systematic review and meta‐analysis

The circular RNA, CDR1as/ciRS‐7, functions as a vital regulator in various cancers; however, the predictive value of CDR1as remains controversial. Therefore, a comprehensive analysis for clarifying the precise diagnostic and prognostic value of CDR1as in solid tumours is needed. A literature review of several databases was conducted for identifying potential studies. Pooled odds ratios (ORs) and hazard ratios (HRs) were used for evaluating the diagnostic accuracy variables and survival. Overall, 15 studies (1787 patients) and 11 studies (1578 patients) were included for diagnostic and prognostic outcome syntheses, respectively. Up‐regulated CDR1as expression was found to be correlated with worse clinicopathological characteristics, including the T status, N status, histological grade, TNM stage and distant metastasis. The synthesized sensitivity was 0.72 (95% confidence interval [CI], 0.65‐0.79), and the specificity was 0.80 (95% CI, 0.74‐0.86). The positive likelihood ratio (LR), negative LR and diagnostic odds ratio (DOR) were 3.70, 0.34 and 10.80, respectively. The area under the receiver operator characteristic curve was 0.84 (95% CI, 0.80‐0.87). In the pooled prognostic analysis, patients with high CDR1as expression had worse overall survival (HR = 2.40, P < 0.001) and disease‐free survival (HR = 1.74, P < 0.001). These results suggest that CDR1as is a reliable diagnostic and prognostic biomarker with high accuracy and efficiency, which may potentially facilitate clinical decisions on solid tumours in the future.     

The alteration of PLCζ protein expression in unexplained infertile and asthenoteratozoospermic patients: A potential effect on sperm fertilization ability

Failed oocyte activation has been observed in unexplained infertile (UI) and asthenoteratozoospermic (AT) men. The deficiency of phospholipase C‐zeta (PLCζ) could be a possible reason for such failures and has not been studied yet. We investigated the expression and localization of PLCζ protein in the sperms of patients with UI and AT conditions. The relationships between PLCζ‐related parameters with male age, sperm characteristics, DNA integrity, and cellular maturity were assessed. Semen samples were collected from fertile (n = 40), UI (n = 40), and AT (n = 40) men. Subsequently, semen analysis, DNA fragmentation, hyaluronic acid‐binding ability, and PLCζ level along with its distribution were evaluated using computer‐assisted sperm analyzer, sperm chromatin structure assay (SCSA), hyaluronic acid‐binding assay (HBA), western blot analysis and immunofluorescence microscopy, respectively. Unlike SCSA, the values of HBA, and PLCζ expression were significantly reduced in UI and AT patients compared to fertile men, whereas no significant differences were observed among the experimental groups in terms of PLCζ localization patterns. The regression analysis also showed that HBA is the only variable associated with PLCζ levels. Furthermore, the correlation of male age with PLCζ localization in postacrosomal, equatorial, and acrosomal+postacrosomal+equatorial (A+PA+E) patterns, as well as the relation of normal morphology, with the (A+PA+E) pattern, remained in the regression model. Our findings indicated that reduced PLCζ level along with the increased DNA fragmentation and impaired maturation may be possible etiologies of decreased fertilization in the studied subjects.     

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...     

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.