Notes

miR-133a-5p inhibits stomach cancer by means of TCF4 down-regulation.
Nitrogen doping and amino group functionalization through chemical modification lead to strong electron donation. Applying these processes to a large π-conjugated system of graphene quantum dot (GQD)-based materials as electron donors increases the charge transfer efficiency of nitrogen-doped amino acid-functionalized GQDs (amino-N-GQDs), resulting in enhanced two-photon absorption, post-two-photon excitation (TPE) stability, TPE cross-sections, and two-photon luminescence through the radiative pathway when the lifetime decreases and the quantum yield increases. Additionally, it leads to the generation of reactive oxygen species through two-photon photodynamic therapy (PDT). The sorted amino-N-GQDs prepared in this study exhibited excitation-wavelength-independent two-photon luminescence in the near-infrared region through TPE in the near-infrared-II region. The increase in size resulted in size-dependent photochemical and electrochemical efficacy, increased photoluminescence quantum yield, and efficient two-photon PDT. Therefore, the sorted amino-N-GQDs can be applicable as two-photon contrast probes to track and localize analytes in in-depth two-photon imaging executed in a biological environment along with two-photon PDT to eliminate infectious or multidrug-resistant microbes.Aging can be defined as the progressive deterioration of cellular, tissue, and organismal function over time. Alterations in protein homeostasis, also known as proteostasis, are a hallmark of aging that lead to proteome imbalances and protein aggregation, phenomena that also occur in age-related diseases. Among the various proteostasis regulators, microRNAs (miRNAs) have been reported to play important roles in the post-transcriptional control of genes involved in maintaining proteostasis during the lifespan in several organismal tissues. In this review, we consolidate recently published reports that demonstrate how miRNAs regulate fundamental proteostasis-related processes relevant to tissue aging, with emphasis on the two most studied tissues, brain tissue and skeletal muscle. We also explore an emerging perspective on the role of miRNA regulatory networks in age-related protein aggregation, a known hallmark of aging and age-related diseases, to elucidate potential miRNA candidates for anti-aging diagnostic and therapeutic targets.The repair of DNA damage is a crucial process for the correct maintenance of genetic information, thus, allowing the proper functioning of cells. Among the different types of lesions occurring in DNA, double-strand breaks (DSBs) are considered the most harmful type of lesion, which can result in significant loss of genetic information, leading to diseases, such as cancer. DSB repair occurs through two main mechanisms, called non-homologous end joining (NHEJ) and homologous recombination repair (HRR). There is evidence showing that miRNAs play an important role in the regulation of genes acting in NHEJ and HRR mechanisms, either through direct complementary binding to mRNA targets, thus, repressing translation, or by targeting other genes involved in the transcription and activity of DSB repair genes. Therefore, alteration of miRNA expression has an impact on the ability of cells to repair DSBs, which, in turn, affects cancer therapy sensitivity. This latter gives account of the importance of miRNAs as regulators of NHEJ and HRR and places them as a promising target to improve cancer therapy. Here, we review recent reports demonstrating an association between miRNAs and genes involved in NHEJ and HRR. We employed the Web of Science search query TS ("gene official symbol/gene aliases*" AND "miRNA/microRNA/miR-") and focused on articles published in the last decade, between 2010 and 2021. We also performed a data analysis to represent miRNA-mRNA validated interactions from TarBase v.8, in order to offer an updated overview about the role of miRNAs as regulators of DSB repair.Preclinical and clinical evidence supports melatonin and its analogues as potential treatment for diseases involving cognitive deficit such as Alzheimer's disease. In this work, we evaluated by in silico studies a set of boron-containing melatonin analogues on MT1 and MT2 receptors. Then, we synthesized a compound (borolatonin) identified as potent agonist. After chemical characterization, its evaluation in a rat model with cognitive deficit showed that it induced ameliorative effects such as those induced by equimolar administration of melatonin in behavioral tests and in neuronal immunohistochemistry assays. Our results suggest the observed effects are by means of action on the melatonin system. Further studies are required to clarify the mechanism(s) of action, as the beneficial effects on disturbed memory by gonadectomy in male rats are attractive.As the global SARS-CoV-2 pandemic continues to plague healthcare systems, it has become clear that opportunistic pathogens cause a considerable proportion of SARS-CoV-2-associated mortality and morbidity cases. Of these, Covid-Associated Pulmonary Aspergilliosis (CAPA) is a major concern with evidence that it occurs in the absence of traditional risk factors such as neutropenia and is diagnostically challenging for the attending physician. In this review, we focus on the immunopathology of SARS-CoV-2 and how this potentiates CAPA through dysregulation of local and systemic immunity as well as the unintended consequences of approved COVID treatments including corticosteroids and IL-6 inhibitors. Finally, we will consider how knowledge of the above may aid in the diagnosis of CAPA using current diagnostics and what treatment should be instituted in probable and confirmed cases.Cells sense a variety of extracellular signals balancing their metabolism and physiology according to changing growth conditions. Plasma membranes are the outermost informational barriers that render cells sensitive to regulatory inputs. Membranes are composed of different types of lipids that play not only structural but also informational roles. Hormones and other regulators are sensed by specific receptors leading to the activation of lipid metabolizing enzymes. These enzymes generate lipid second messengers. Among them, phosphatidic acid (PA) is a well-known intracellular messenger that regulates various cellular processes. This lipid affects the functional properties of cell membranes and binds to specific target proteins leading to either genomic (affecting transcriptome) or non-genomic responses. The subsequent biochemical, cellular and physiological reactions regulate plant growth, development and stress tolerance. In the present review, we focus on primary (genome-independent) signaling events triggered by rapid PA accumulation in plant cells and describe the functional role of PA in mediating response to hormones and hormone-like regulators. The contributions of individual lipid signaling enzymes to the formation of PA by specific stimuli are also discussed. E-64 We provide an overview of the current state of knowledge and future perspectives needed to decipher the mode of action of PA in the regulation of cell functions.Considering the challenges related to antimicrobial resistance, other strategies for controlling infections have been suggested, such as antimicrobial photodynamic therapy (aPDT) and antimicrobial peptides (AMP). This study aims to perform a systematic review and meta-analysis to obtain evidence on the antimicrobial effectiveness of aPDT associated with AMP and establish in vitro knowledge on this topic for further study designs. The PubMed, Scopus, Web of Science, Science Direct, Scielo, and Cochrane Library databases were searched. Two independent and calibrated researchers (Kappa = 0.88) performed all the systematic steps according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The odds ratio (OR) was used as the effect measure. The Peto method was used to perform the meta-analysis due to the sparse data. Twenty studies were included in the present review. The result was significant (OR = 0.14/p = 0.0235/I-squared = 0%), showing better outcomes of aPDT associated with peptides than those of aPDT alone for controlling the microbial load. Only 20% of the studies included evaluated this approach in a biofilm culture. Combined treatment with aPDT and AMP highly increased the ability of microbial reduction of Gram-positive and Gram-negative bacteria. However, additional blind studies are required to evaluate the efficacy of this therapy on microbial biofilms.Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), a member of the TNF protein superfamily, represents a multifaceted cytokine with unique biological features including both proapoptotic and pro-survival effects in different cell types depending on receptor interactions and local stimuli. Beyond its extensively studied anti-tumor and immunomodulatory properties, a growing body of experimental and clinical evidence over the past two decades suggests a protective role of TRAIL in the development of type 1 (T1DM) and type 2 (T2DM) diabetes mellitus. This evidence can be briefly summarized by the following observations (i) acceleration and exacerbation of T1DM and T2DM by TRAIL blockade or genetic deficiency in animal models, (ii) prevention and amelioration of T1DM and T2DM with recombinant TRAIL treatment or systemic TRAIL gene delivery in animal models, (iii) significantly reduced circulating soluble TRAIL levels in patients with T1DM and T2DM both at disease onset and in more advanced stag delineate its therapeutic implications in metabolic disease.Flow cytometry is widely used within the manufacturing of cell and gene therapies to measure and characterise cells. Conventional manual data analysis relies heavily on operator judgement, presenting a major source of variation that can adversely impact the quality and predictive potential of therapies given to patients. Computational tools have the capacity to minimise operator variation and bias in flow cytometry data analysis; however, in many cases, confidence in these technologies has yet to be fully established mirrored by aspects of regulatory concern. Here, we employed synthetic flow cytometry datasets containing controlled population characteristics of separation, and normal/skew distributions to investigate the accuracy and reproducibility of six cell population identification tools, each of which implement different unsupervised clustering algorithms Flock2, flowMeans, FlowSOM, PhenoGraph, SPADE3 and SWIFT (density-based, k-means, self-organising map, k-nearest neighbour, deterministic k-means, and model-based clustering, respectively). We found that outputs from software analysing the same reference synthetic dataset vary considerably and accuracy deteriorates as the cluster separation index falls below zero. Consequently, as clusters begin to merge, the flowMeans and Flock2 software platforms struggle to identify target clusters more than other platforms. Moreover, the presence of skewed cell populations resulted in poor performance from SWIFT, though FlowSOM, PhenoGraph and SPADE3 were relatively unaffected in comparison. These findings illustrate how novel flow cytometry synthetic datasets can be utilised to validate a range of automated cell identification methods, leading to enhanced confidence in the data quality of automated cell characterisations and enumerations.
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