Using focused ultrasound to modulate microglial structure and function

Transcranial focused ultrasound (FUS) has the unique ability to target regions of the brain with high spatial precision, in a minimally invasive manner. Neuromodulation studies have shown that FUS can excite or inhibit neuronal activity, demonstrating its tremendous potential to improve the outcome of neurological diseases. Recent evidence has also shed light on the emerging promise that FUS has, with and without the use of intravenously injected microbubbles, in modulating the blood-brain barrier and the immune cells of the brain. As the resident immune cells of the central nervous system, microglia are at the forefront of the brain's maintenance and immune defense. Notably, microglia are highly dynamic and continuously survey the brain parenchyma by extending and retracting their processes. This surveillance activity aids microglia in performing key physiological functions required for brain activity and plasticity. In response to stressors, microglia rapidly alter their cellular and molecular profile to help facilitate a return to homeostasis. While the underlying mechanisms by which both FUS and FUS + microbubbles modify microglial structure and function remain largely unknown, several studies in adult mice have reported changes in the expression of the microglia/macrophage marker ionized calcium binding adaptor molecule 1, and in their phagocytosis, notably of protein aggregates, such as amyloid beta. In this review, we discuss the demonstrated and putative biological effects of FUS and FUS + microbubbles in modulating microglial activities, with an emphasis on the key cellular and molecular changes observed in vitro and in vivo across models of brain health and disease. Understanding how this innovative technology can modulate microglia paves the way for future therapeutic strategies aimed to promote beneficial physiological microglial roles, and prevent or treat maladaptive responses.

Genomic Biomarker Heterogeneities between SARS-CoV-2 and COVID-19

Genes functionally associated with SARS-CoV-2 infection and genes functionally related to the COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in the transcriptional response to SARS-CoV-2 infection with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with another gene in predicting disease status to achieve better-indicating accuracy than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. These two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction with their exceptional predicting accuracy. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in our earlier work, the genes and their transcriptional response and functional effects on SARS-CoV-2 infection, and the genes and their functional signature patterns on COVID-19 antibodies, are significantly different. We will use a total of fourteen cohort studies (including breakthrough infections and omicron variants) with 1481 samples to justify our results. Such significant findings can help explore the causal and pathological links between SARS-CoV-2 infection and the COVID-19 disease, and fight against the disease with more targeted genes, vaccines, antiviral drugs, and therapies.

Lift the Veil of Breast Cancers Using 4 or Fewer Critical Genes

Known genes in the breast cancer study literature could not be confirmed whether they are vital to breast cancer formations due to lack of convincing accuracy, although they may be biologically directly related to breast cancer based on present biological knowledge. It is hoped vital genes can be identified with the highest possible accuracy, for example, 100% accuracy and convincing causal patterns beyond what has been known in breast cancer. One hope is that finding gene-gene interaction signatures and functional effects may solve the puzzle. This research uses a recently developed competing linear factor analysis method in differentially expressed gene detection to advance the study of breast cancer formation. Surprisingly, 3 genes are detected to be differentially expressed in TNBC and non-TNBC (Her2, Luminal A, Luminal B) samples with 100% sensitivity and 100% specificity in 1 study of triple-negative breast cancers (TNBC, with 54 675 genes and 265 samples). These 3 genes show a clear signature pattern of how TNBC patients can be grouped. For another TNBC study (with 54 673 genes and 66 samples), 4 genes bring the same accuracy of 100% sensitivity and 100% specificity. Four genes are found to have the same accuracy of 100% sensitivity and 100% specificity in 1 breast cancer study (with 54 675 genes and 121 samples), and the same 4 genes bring an accuracy of 100% sensitivity and 96.5% specificity in the fourth breast cancer study (with 60 483 genes and 1217 samples). These results show the 4-gene-based classifiers are robust and accurate. The detected genes naturally classify patients into subtypes, for example, 7 subtypes. These findings demonstrate the clearest gene-gene interaction patterns and functional effects with the smallest numbers of genes and the highest accuracy compared with findings reported in the literature. The 4 genes are considered to be essential for breast cancer studies and practice. They can provide focused, targeted researches and precision medicine for each subtype of breast cancer. New breast cancer disease types may be detected using the classified subtypes, and hence new effective therapies can be developed.

Effects of atorvastatin combined with bivalirudin on coagulation function, cardiac function, and inflammatory factors of percutaneous coronary intervention in elderly patients with acute myocardial infarction

BACKGROUND

Acute myocardial infarction (AMI) occurs when atherosclerotic lesions which present in the coronary arteries cause the intravascular plate to rupture and with the result of myocardial ischemia, hypoxia, and infarct. The preferred treatment for AMI is currently percutaneous coronary intervention (PCI), for which the key to the success is the choice of anticoagulant and thrombolytic drugs during surgery. Here, we aim to explore the effects of atorvastatin combined with bivalirudin on coagulation function, cardiac function, and inflammatory factors in elderly patients with AMI who underwent PCI.

METHODS

The clinical data of 86 AMI patients who were admitted to our hospital between February 2016 and May 2018 were retrospectively analyzed. Based on different treatments, the patients were divided into the control group and the observation group, with 43 patients in each group. The control group patients were treated with bivalirudin, and the observation group was treated with bivalirudin plus atorvastatin. Both groups of patients underwent PCI and the clinical efficacy, coagulation function, cardiac function, inflammatory factor levels and cardiovascular events (MACE), and other clinical data were compared between the groups.

RESULTS

The total clinical effective rate in the observation group was significantly higher than that in the control group (90.90% vs. 72.09%) (P<0.05). Fibrinogen (Fg) and D-dimer (D-D) levels were significantly decreased after treatment in both groups but were significantly lower in the observation group than in the control group. The prothrombin time (PT) was significantly prolonged after treatment in both groups but was significantly longer in the observation group than in the control group after treatment (P<0.05). Meanwhile, the left ventricular end-diastolic diameter (LVEDD) and left ventricular end-systolic diameter (LVESD) were significantly reduced after treatment in both groups but were significantly lower in the observation group than in the control group, whereas the left ventricular ejection fraction (LVEF) was significantly higher in the observation group compared with the control group after treatment (P<0.05). After treatment, serum levels of transforming growth factor-β1 (TGF-β1), tumor necrosis factor-α (TNF-α), and IL-6 were significantly reduced in both groups but the levels were significantly lower in the observation group than in the control group (P<0.05). The overall incidence of MACE in the observation group was significantly lower than that in the control group (9.30% vs. 30.23%) (P<0.05).

CONCLUSIONS

Atorvastatin combined with bivalirudin can improve the efficiency of clinical treatment in elderly AMI patients who undergo PCI, while simultaneously improving blood coagulation function and reducing the occurrence of bleeding, compared with bivalrudin alone. It can also decrease the level of inflammatory factors, promote vascular recanalization, and improve myocardial ischemia, thereby reducing the incidence of MACE and improving patient prognosis.

The impact of thioredoxin reduction of allosteric disulfide bonds on the therapeutic potential of monoclonal antibodies

Therapeutic mAbs are used to manage a wide range of cancers and autoimmune disorders. However, mAb-based treatments are not always successful, highlighting the need for a better understanding of the factors influencing mAb efficacy. Increased levels of oxidative stress associated with several diseases are counteracted by the activities of various oxidoreductase enzymes, such as thioredoxin (Trx), which also reduces allosteric disulfide bonds in proteins, including mAbs. Here, using an array of in vitro assays, we explored the functional effects of Trx-mediated reduction on the mechanisms of action of six therapeutic mAbs. We found that Trx reduces the interchain disulfide bonds of the mAbs, after which they remain intact but have altered function. In general, this reduction increased antigen-binding capacity, resulting in, for example, enhanced tumor necrosis factor (TNF) neutralization by two anti-TNF mAbs. Conversely, Trx reduction decreased the antiproliferative activity of an anti-tyrosine kinase-type cell-surface receptor HER2 mAb. In all of the mAbs, Fc receptor binding was abrogated by Trx activity, with significant loss in both complement-dependent cytotoxicity and antibody-dependent cellular cytotoxicity (ADCC) activity of the mAbs tested. We also confirmed that without alkylation, Trx-reduced interchain disulfide bonds reoxidize, and ADCC activity is restored. In summary, Trx-mediated reduction has a substantial impact on the functional effects of an mAb, including variable effects on antigen binding and Fc function, with the potential to significantly impact mAb efficacy in vivo.

Extending in Silico Protein Target Prediction Models to Include Functional Effects

In silico protein target deconvolution is frequently used for mechanism-of-action investigations; however existing protocols usually do not predict compound functional effects, such as activation or inhibition, upon binding to their protein counterparts. This study is hence concerned with including functional effects in target prediction. To this end, we assimilated a bioactivity training set for 332 targets, comprising 817,239 active data points with unknown functional effect (binding data) and 20,761,260 inactive compounds, along with 226,045 activating and 1,032,439 inhibiting data points from functional screens. Chemical space analysis of the data first showed some separation between compound sets (binding and inhibiting compounds were more similar to each other than both binding and activating or activating and inhibiting compounds), providing a rationale for implementing functional prediction models. We employed three different architectures to predict functional response, ranging from simplistic random forest models ('Arch1') to cascaded models which use separate binding and functional effect classification steps ('Arch2' and 'Arch3'), differing in the way training sets were generated. Fivefold stratified cross-validation outlined cascading predictions provides superior precision and recall based on an internal test set. We next prospectively validated the architectures using a temporal set of 153,467 of in-house data points (after a 4-month interim from initial data extraction). Results outlined Arch3 performed with the highest target class averaged precision and recall scores of 71% and 53%, which we attribute to the use of inactive background sets. Distance-based applicability domain (AD) analysis outlined that Arch3 provides superior extrapolation into novel areas of chemical space, and thus based on the results presented here, propose as the most suitable architecture for the functional effect prediction of small molecules. We finally conclude including functional effects could provide vital insight in future studies, to annotate cases of unanticipated functional changeover, as outlined by our CHRM1 case study.

Potential functional applications of extracellular vesicles: a report by the NIH Common Fund Extracellular RNA Communication Consortium

The NIH Extracellular RNA Communication Program's initiative on clinical utility of extracellular RNAs and therapeutic agents and developing scalable technologies is reviewed here. Background information and details of the projects are presented. The work has focused on modulation of target cell fate by extracellular vesicles (EVs) and RNA. Work on plant-derived vesicles is of intense interest, and non-mammalian sources of vesicles may represent a very promising source for different therapeutic approaches. Retro-viral-like particles are intriguing. Clearly, EVs share pathways with the assembly machinery of several other viruses, including human endogenous retrovirals (HERVs), and this convergence may explain the observation of viral-like particles containing viral proteins and nucleic acid in EVs. Dramatic effect on regeneration of damaged bone marrow, renal, pulmonary and cardiovascular tissue is demonstrated and discussed. These studies show restoration of injured cell function and the importance of heterogeneity of different vesicle populations. The potential for neural regeneration is explored, and the capacity to promote and reverse neoplasia by EV exposure is described. The tremendous clinical potential of EVs underlies many of these projects, and the importance of regulatory issues and the necessity of general manufacturing production (GMP) studies for eventual clinical trials are emphasized. Clinical trials are already being pursued and should expand dramatically in the near future.

Neurobiological effects of transcranial direct current stimulation: a review

Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation technique that is affordable and easy to operate compared to other neuromodulation techniques. Anodal stimulation increases cortical excitability, while the cathodal stimulation decreases it. Although tDCS is a promising treatment approach for chronic pain as well as for neuropsychiatric diseases and other neurological disorders, several complex neurobiological mechanisms that are not well understood are involved in its effect. The purpose of this systematic review is to summarize the current knowledge regarding the neurobiological mechanisms involved in the effects of tDCS. The initial search resulted in 171 articles. After applying inclusion and exclusion criteria, we screened 32 full-text articles to extract findings about the neurobiology of tDCS effects including investigation of cortical excitability parameters. Overall, these findings show that tDCS involves a cascade of events at the cellular and molecular levels. Moreover, tDCS is associated with glutamatergic, GABAergic, dopaminergic, serotonergic, and cholinergic activity modulation. Though these studies provide important advancements toward the understanding of mechanisms underlying tDCS effects, further studies are needed to integrate these mechanisms as to optimize clinical development of tDCS.