Hydrophilic Random Cationic Copolymers as Polyplex-Formation Vectors for DNA

Research on the improvement and fabrication of polymeric systems as non-viral gene delivery carriers is required for their implementation in gene therapy. Random copolymers have not been extensively utilized for these purposes. In this regard, double hydrophilic poly[(2-(dimethylamino) ethyl methacrylate)-co-(oligo(ethylene glycol) methyl ether methacrylate] [P(DMAEMA-co-OEGMA)] random copolymers were synthesized via reversible addition-fragmentation chain transfer (RAFT) polymerization. The copolymers were further modified by quaternization of DMAEMA tertiary amine, producing the cationic P(QDMAEMA-co-OEGMA) derivatives. Fluorescence and ultraviolet–visible (UV–vis) spectroscopy revealed the efficient interaction of copolymers aggregates with linear DNAs of different lengths, forming polyplexes, with the quaternized copolymer aggregates exhibiting stronger binding affinity. Light scattering techniques evidenced the formation of polyplexes whose size, molar mass, and surface charge strongly depend on the N/P ratio (nitrogen (N) of the amine group of DMAEMA/QDMAEMA over phosphate (P) groups of DNA), DNA length, and length of the OEGMA chain. Polyplexes presented colloidal stability under physiological ionic strength as shown by dynamic light scattering. In vitro cytotoxicity of the empty nanocarriers was evaluated on HEK293 as a control cell line. P(DMAEMA-co-OEGMA) copolymer aggregates were further assessed for their biocompatibility on 4T1, MDA-MB-231, MCF-7, and T47D breast cancer cell lines presenting high cell viability rates.     

Locomotor recovery after spinal cord injury: intimate dependence between axonal regeneration and re-connection

Traumatic spinal cord injuries(SCI) are characterized by damage in the integrity of the spinal cord,which results in either temporary or permanent alterations in the locomotor,sensory and/or autonomic functions(Yezierski,2009).The traumatic event leads to impairments in voluntary control of movement below the injury by affecting the connection between the brain and the neurons localized in the spinal cord.     

Suicide Biomarkers to Predict Risk,Classify Diagnostic Subtypes,and Identify Novel Therapeutic Targets: 5 Years of Promising Research

BackgroundSuicide is a global health crisis. However, no objective biomarkers of suicide risk currently exist, and self-reported data can be unreliable, which limits prediction, diagnostic, and treatment efforts. Reliable biomarkers that can differentiate between diagnostic subgroups, predict worsening symptoms, or suggest novel therapeutic targets would be extremely valuable for patients, researchers, and clinicians.MethodsMEDLINE was searched for reports published between 2016 and 2021 using search terms (suicid*) AND (biomarker*) OR (indicat*). Reports that compared biomarkers between suicidal ideation, suicide attempt, death from suicide, or any suicide subgroup against other neuropsychiatric disorders were included. Studies exclusively comparing suicidal behavior or death from suicide with healthy controls were not included to ensure that biomarkers were specific to suicide and not other psychopathology.ResultsThis review summarizes the last 5 years of research into suicide-associated biomarkers and provides a comprehensive guide for promising and novel biomarkers that encompass varying presentations of suicidal ideation, suicide attempt, and death by suicide. The serotonergic system, inflammation, hypothalamic-pituitary-adrenal axis, lipids, and endocannabinoids emerged as the most promising diagnostic, predictive, and therapeutic indicators.ConclusionsThe utility of diagnostic and predictive biomarkers is evident, particularly for suicide prevention. While larger-scale studies and further in-depth research are required, the last 5 years of research has uncovered essential biomarkers that could ultimately improve predictive strategies, aid diagnostics, and help develop future therapeutic targets.     

Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.     

Somatic Alterations Contributing to Metastasis of a Castration‐Resistant Prostate Cancer

Metastatic castration‐resistant prostate cancer (mCRPC) is a lethal disease, and molecular markers that differentiate indolent from aggressive subtypes are needed. We sequenced the exomes of five metastatic tumors and healthy kidney tissue from an index case with mCRPC to identify lesions associated with disease progression and metastasis. An Ashkenazi Jewish (AJ) germline founder mutation, del185AG in BRCA1, was observed and AJ ancestry was confirmed. Sixty‐two somatic variants altered proteins in tumors, including cancer‐associated genes, TMPRSS2‐ERG, PBRM1, and TET2. The majority (n = 53) of somatic variants were present in all metastases and only a subset (n = 31) was observed in the primary tumor. Integrating tumor next‐generation sequencing and DNA copy number showed somatic loss of BRCA1 and TMPRSS2‐ERG. We sequenced 19 genes with deleterious mutations in the index case in additional mCRPC samples and detected a frameshift, two somatic missense alterations, tumor loss of heterozygosity, and combinations of germline missense SNPs in TET2. In summary, genetic analysis of metastases from an index case permitted us to infer a chronology for the clonal spread of disease based on sequential accrual of somatic lesions. The role of TET2 in mCRPC deserves additional analysis and may define a subset of metastatic disease.