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Cancer remains one of the most complex and challenging diseases in mankind. To address the need for a personalized treatment approach for particularly complex tumor cases, molecular tumor boards (MTBs) have been initiated. MTBs are interdisciplinary teams that perform in-depth molecular diagnostics to cooperatively and interdisciplinarily advise on the best therapeutic strategy. Current molecular diagnostics are routinely performed on the transcriptomic and genomic levels, aiming to identify tumor-driving mutations. However, these approaches can only partially capture the actual phenotype and the molecular key players of tumor growth and progression. Thus, direct investigation of the expressed proteins and activated signaling pathways provide valuable complementary information on the tumor-driving molecular characteristics of the tissue. Technological advancements in mass spectrometry-based proteomics enable the robust, rapid, and sensitive detection of thousands of proteins in minimal sample amounts, paving the way for clinical proteomics and the probing of oncogenic signaling activity. Therefore, proteomics is currently being integrated into molecular diagnostics within MTBs and holds promising potential in aiding tumor classification and identifying personalized treatment strategies. This review introduces MTBs and describes current clinical proteomics, its potential in precision oncology, and highlights the benefits of multi-omic data integration., (© 2023 The Authors. PROTEOMICS published by Wiley‐VCH GmbH.)

Interaction of yeast phenylalanine tRNA with oligonucleotides complementary to its 3′-terminal nucleotide sequence was thoroughly studied. Using the gel retardation technique, thermodynamic and kinetic parameters of the tRNA complexation in physiological conditions were determined. Analysis of dependences of the complex formation on the oligonucleotide concentration and incubation time showed that this process proceeds in two stages. At the first stage, a metastable complex of the oligonucleotide with the open, single-stranded sequence ACCA at the 3′ end of tRNA rapidly forms. The second stage involves a slow intramolecular rearrangement of the resulting metastable complex into a full-sized heteroduplex accompanied by the tRNAPhe unfolding. The data gained suggest that the RNA unfolding stage is limiting in the interaction of oligonucleotides with natural RNAs. Principles of selection of optimal hybridization probes and antisense oligonucleotides are discussed. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, affecting a significant proportion of the elderly population. AD is characterized by cognitive decline and functional impairments due to pathological hallmarks like amyloid β-peptide (Aβ) plaques and neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau. Microglial activation, chronic neuroinflammation, and disruptions in neuronal communication further exacerbate the disease. Emerging research suggests that immune modulation could play a key role in AD treatment given the significant involvement of neuroinflammatory processes. This review focuses on recent advancements in immunotherapy strategies aimed at modulating immune responses in AD, with a specific emphasis on microglial behavior, amyloid clearance, and tau pathology. By exploring these immunotherapeutic approaches, we aim to provide insights into their potential to alter disease progression and improve patient outcomes, contributing to the evolving landscape of AD treatment. [ABSTRACT FROM AUTHOR]

Tick bites and tick-related diseases are on the rise. Diagnostic tests that identify well-characterised tick-borne pathogens (TBPs) possess limited capacity to address the causation of symptoms associated with poorly characterised tick-related illnesses, such as debilitating symptom complexes attributed to ticks (DSCATT) in Australia. Identification of local signals in tick-bitten skin that can be detected systemically in blood would have both clinical (diagnostic or prognostic) and research (mechanistic insight) utility, as a blood sample is more readily obtainable than tissue biopsies. We hypothesised that blood samples may reveal signals which reflect relevant local (tissue) events and that the time course of these signals may align with local pathophysiology. As a first step towards testing this hypothesis, we compared molecular signatures in skin biopsies taken from the tick-bite location of human participants, as published in our previous study, together with peripheral blood signatures obtained concurrently. This approach captures differentially expressed molecules across multiple omics datasets derived from peripheral blood (including cellular and cell-free transcriptomics, proteomics, metabolomics, and DNA methylation), and skin biopsies (spatial transcriptomics). Our original data revealed that extracellular matrix organisation and platelet degranulation pathways were upregulated in the skin within 72 h of a tick bite. The same signals appeared in blood, where they then remained elevated for three months, displaying longitudinally consistent alterations of biological functions. Despite the limited sample size, these data represent proof-of-concept that molecular events in the skin following a tick bite can be detectable systemically. This underscores the potential value of blood samples, akin to a liquid biopsy, to capture biomarkers reflecting local tissue processes. [ABSTRACT FROM AUTHOR]

Background: GC16 is a novel pesticide with acaricidal properties against the spider mite Tetranychus pueraricola (Ehara & Gotoh). Its physiological mechanisms have been described previously, but its molecular mechanisms of action remain unclear. Thus, we aimed to explore the acaricidal mechanisms of GC16 through transcriptomic and proteomic analyses. The results were verified using transmission electron microscopy (TEM), immunofluorescence assay, and western blotting. Results: Transcriptomic and proteomic analyses revealed 2717 differentially expressed genes (DEGs) and 374 differentially expressed proteins (DEPs) between the GC16-treated and control mites. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the DEGs and DEPs were enriched in the autophagy pathway. TEM showed that the number of autophagosomes and autolysosomes was higher in the GC16-treated mites than in the control mites. Immunofluorescence assay and western blot results consistently indicated that GC16 treatment significantly enhanced the relative expression of the autophagy protein LC3 in insect Sf9 cells. The intracellular calcium concentration in the GC16-treated Sf9 cells was 2.30 times higher than that in the control cells, suggesting that GC16 disrupted calcium homeostasis and potentially acted as a calcium-driven nerve agent. Conclusions: Autophagy is involved in the toxicity of GC16 against T. pueraricola and may be activated by elevated Ca2+ levels. This study reveals the molecular insecticidal mechanisms of GC16 and provides rationale for the field application of GC16 to control pest mites. [ABSTRACT FROM AUTHOR]

Background: Dementia patients commonly present multiple neuropathologies, worsening cognitive function, yet structural neuroimaging signatures of dementia have not been positioned in the context of combined pathology. In this study, we implemented an MRI voxel-based approach to explore combined and independent effects of dementia pathologies on grey and white matter structural changes. Methods: In 91 amnestic dementia patients with post-mortem brain donation, grey matter density and white matter hyperintensity (WMH) burdens were obtained from pre-mortem MRI and analyzed in relation to Alzheimer's, vascular, Lewy body, TDP-43, and hippocampal sclerosis (HS) pathologies. After exploring co-occurrence profiles of these pathologies, voxel-based morphometry was implemented to determine their joint and independent effects on grey matter loss. The impact of these pathologies on WMH burden was then evaluated both in spatial and quantitative combined analyses, using voxel-based and generalized linear models respectively. Results: 86.8% of patients in this cohort presented more than one pathology. The combined structural effect of these pathologies was a focal impact on hippocampal grey matter atrophy, primarily driven by HS and Alzheimer's pathology (family-wise error corrected, p < 0.05), which also exhibited the strongest individual effects (uncorrected, p < 0.001). WMHs, predominant in middle and anterior cerebral portions, were most strongly associated with vascular (T = 2.47, p = 0.017) and tau pathologies (T = 2.09, p = 0.041). Conclusions: The mixed associations of these dementia neuroimaging hallmarks are relevant for the fine-tuning of diagnostic protocols and underscore the need for comprehensive pathology evaluations in the study of dementia phenotypes. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC) is the main histological subtype of lung cancer. For locally advanced and advanced NSCLC, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI)-targeted therapy has been the first choice for NSCLC patients with EGFR mutations. TKIs, as targeted drugs, inhibit kinase activity and autophosphorylation by competitively binding to the ATP binding site of the EGFR tyrosine kinase domain, which blocks the signal transduction mediated by EGFR and thus inhibits the proliferation of tumor cells. However, drug resistance to TKIs is inevitable. EGFR is also a highly glycosylated receptor tyrosine kinase, and a wide range of crosstalk occurs between phosphorylation and glycosylation. Therefore, can the phosphorylation state be altered by glycosylation to improve drug resistance? In this review, we summarize phosphorylation, glycosylation and the crosstalk between these processes as well as the current research status and methods. We also summarize the autophosphorylation and glycosylation sites of the EGFR protein and their crosstalk. By exploring the relationship between EGFR glycosylation and autophosphorylation in targeted TKI therapy, we find that research on EGFR glycosylation is crucial for targeted NSCLC treatment and will become a research direction for identifying potential targets related to regulating TKI drug sensitivity. [ABSTRACT FROM AUTHOR]

Background: This study aims to analyze the exploration degree of popular model organisms by utilizing annotations from the UniProtKB (Swiss-Prot) knowledge base. The research focuses on understanding the genomic and post-genomic data of various organisms, particularly in relation to aging as an integral model for studying the molecular mechanisms underlying pathological processes and physiological states. Methods: Having characterized the organisms by selected parameters (numbers of gene splice variants, post-translational modifications, etc.) using previously developed information models, we calculated proteome sizes: the number of possible proteoforms for each species. Our analysis also involved searching for orthologs of human aging genes within these model species. Results: Our findings indicate that genomic and post-genomic data for more primitive species, such as bacteria and fungi, are more comprehensively characterized compared to other organisms. This is attributed to their experimental accessibility and simplicity. Additionally, we discovered that the genomes of the most studied model organisms allow for a detailed analysis of the aging process, revealing a greater number of orthologous genes related to aging. Conclusions: The results highlight the importance of annotating the genomes of less-studied species to identify orthologs of marker genes associated with complex physiological processes, including aging. Species that potentially possess unique traits associated with longevity and resilience to age-related changes require comprehensive genomic studies. [ABSTRACT FROM AUTHOR]

Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate., (© 2023 The Authors. Proteomics published by Wiley-VCH GmbH.)

Background: The CD2-associated protein (CD2AP) was initially identified in peripheral immune cells and regulates cytoskeleton and protein trafficking. Single nucleotide polymorphisms (SNPs) in the CD2AP gene have been associated with Alzheimer's disease (AD). However, the functional role of CD2AP, especially its role in microglia during AD onset, remains elusive. Methods: CD2AP protein levels in cultured primary cells and in 5xFAD mice was studied. Microglial CD2AP-deficient mice were crossed with 5xFAD mice and the offspring were subjected to neuropathological assessment, behavioral tests, electrophysiology, RNA-seq, Golgi staining, and biochemistry analysis. Primary microglia were also isolated for assessing their uptake and morphology changes. Results: We find that CD2AP is abundantly expressed in microglia and its levels are elevated in the brain of AD patients and the 5xFAD model mice at pathological stages. We demonstrate that CD2AP haploinsufficiency in microglia significantly attenuates cognitive and synaptic deficits, weakens the response of microglia to Aβ and the formation of disease-associated microglia (DAM), and alleviates synapse loss in 5xFAD mice. We show that CD2AP-deficient microglia exhibit compromised uptake ability. In addition, we find that CD2AP expression is positively correlated with the expression of the complement C1q that is important for synapse phagocytosis and the formation of DAM in response to Aβ deposition. Moreover, we reveal that CD2AP interacts with colony stimulating factor 1 receptor (CSF1R) and regulates CSF1R cell surface levels, which may further affect C1q expression. Conclusions: Our results demonstrate that CD2AP regulates microgliosis and identify a protective function of microglial CD2AP deficiency against Aβ deposition, suggesting the importance of detailed investigation of AD-associated genes in different brain cells for thoroughly understanding their exact contribution to AD. [ABSTRACT FROM AUTHOR]

Microglia are dynamic central nervous system cells crucial for maintaining homeostasis and responding to neuroinflammation, as evidenced by their varied morphologies. Existing morphology analysis often fails to detect subtle variations within the full spectrum of microglial morphologies due to their reliance on predefined categories. Here, we present MorphoGlia, an interactive, user-friendly pipeline that objectively characterizes microglial morphologies. MorphoGlia employs a machine learning ensemble to select relevant morphological features of microglia cells, perform dimensionality reduction, cluster these features, and subsequently map the clustered cells back onto the tissue, providing a spatial context for the identified microglial morphologies. We applied this pipeline to compare the responses between saline solution (SS) and scopolamine (SCOP) groups in a SCOP-induced mouse model of Alzheimer's disease, with a specific focus on the hippocampal subregions CA1 and Hilus. Next, we assessed microglial morphologies across four groups: SS-CA1, SCOP-CA1, SS-Hilus, and SCOP-Hilus. The results demonstrated that MorphoGlia effectively differentiated between SS and SCOP-treated groups, identifying distinct clusters of microglial morphologies commonly associated with pro-inflammatory states in the SCOP groups. Additionally, MorphoGlia enabled spatial mapping of these clusters, identifying the most affected hippocampal layers. This study highlights MorphoGlia's capability to provide unbiased analysis and clustering of microglial morphological states, making it a valuable tool for exploring microglial heterogeneity and its implications for central nervous system pathologies. [ABSTRACT FROM AUTHOR]

An increasing number of ecotoxicological studies have used omics-data to understand the dose-response patterns of environmental stressors. However, very few have investigated complex non-monotonic dose-response patterns with multi-omics data. In the present study, we developed a novel semi-supervised network analysis workflow as an alternative to benchmark dose (BMD) modelling. We utilised a previously published multi-omics dataset generated from Daphnia magna after chronic gamma radiation exposure to obtain novel knowledge on the dose-dependent effects of radiation. Our approach combines 1) unsupervised co-expression network analysis to group genes with similar dose responses into modules; 2) supervised classification of these modules by relevant response patterns; 3) reconstruction of regulatory networks based on transcription factor binding motifs to reveal the mechanistic underpinning of the modules; 4) differential co-expression network analysis to compare the discovered modules across two datasets with different exposure periods; and 5) pathway enrichment analysis to integrate transcriptomics and metabolomics data. Our method unveiled both known and novel effects of gamma radiation, provide insight into shifts in responses from low to high dose rates, and can be used as an alternative approach for multi-omics dose-response analysis in future. The workflow SOLA (Semi-supervised Omics Landscape Analysis) is available at https://gitlab.com/wanxin.lai/SOLA.git. [ABSTRACT FROM AUTHOR]

Recombinases have several potential advantages as genome editing tools compared to nucleases and other editing enzymes, but the process of engineering them to efficiently recombine predetermined DNA targets demands considerable investment of time and labor. Here we sought to harness zinc-finger DNA-binding domains (ZFDs) to program recombinase binding by developing fusions, in which ZFDs are inserted into recombinase coding sequences. By screening libraries of hybrid proteins, we optimized the insertion site, linker length, spacing and ZFD orientation and generated Cre-type recombinases that remain dormant unless the insertionally fused ZFD binds its target site placed in the vicinity of the recombinase binding site. The developed fusion improved targeted editing efficiencies of recombinases by four-fold and abolished measurable off-target activity in mammalian cells. The ZFD-dependent activity is transferable to a recombinase with relaxed specificity, providing the means for developing fully programmable recombinases. Our engineered recombinases provide improved genome editing tools with increased precision and efficiency. Recombinases fused with zinc-finger domains are active only when bound to their DNA targets. [ABSTRACT FROM AUTHOR]

This article provides a systematic review of research conducted on the proteomic composition of blood as part of a complex biological age estimation. We performed a comprehensive analysis of 17 publicly available datasets and compiled an integral list of proteins. These proteins were sorted based on their detection probability using mass spectrometry in human plasma. We propose this list as a basis for creating a panel of peptides and quantifying the content of selected proteins in the format of a proteomic aging clock. The selected proteins are especially notable for their roles in inflammatory processes and lipid metabolism. Our findings suggest, for the first time, that proteins associated with systemic disorders, including those approved by the FDA for clinical use, could serve as potential markers of aging. [ABSTRACT FROM AUTHOR]

Neuroplasticity is the brain's ability to reorganize and modify its neuronal connections in response to environmental stimuli, experiences, learning, and disease processes. This encompasses a variety of mechanisms, including changes in synaptic strength and connectivity, the formation of new synapses, alterations in neuronal structure and function, and the generation of new neurons. Proper functioning of synapses, which facilitate neuron-to-neuron communication, is crucial for brain activity. Neuronal synapse homeostasis, which involves regulating and maintaining synaptic strength and function in the central nervous system (CNS), is vital for this process. Disruptions in synaptic balance, due to factors like inflammation, aging, or infection, can lead to impaired brain function. This review highlights the main aspects and mechanisms underlying synaptic homeostasis, particularly in the context of aging, infection, and inflammation. [ABSTRACT FROM AUTHOR]

Background: The Blood-Brain Barrier (BBB) is a complex and dynamic interface that regulates the exchange of molecules and cells between the blood and the central nervous system. It undergoes structural and functional throughout oxidative stress and inflammation, which may compromise its integrity and contribute to the pathogenesis of neurodegenerative diseases. Main body: Maintaining BBB integrity is of utmost importance in preventing a wide range of neurological disorders. NRF2 is the main transcription factor that regulates cellular redox balance and inflammation-related gene expression. It has also demonstrated a potential role in regulating tight junction integrity and contributing to the inhibition of ECM remodeling, by reducing the expression of several metalloprotease family members involved in maintaining BBB function. Overall, we review current insights on the role of NRF2 in addressing protection against the effects of BBB dysfunction, discuss its involvement in BBB maintenance in different neuropathological diseases, as well as, some of its potential activators that have been used in vitro and in vivo animal models for preventing barrier dysfunction. Conclusions: Thus, emerging evidence suggests that upregulation of NRF2 and its target genes could suppress oxidative stress, and neuroinflammation, restore BBB integrity, and increase its protection. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a kind of neurodegenerative diseases characterized by beta-amyloid deposition and neurofibrillary tangles and is also the main cause of dementia. According to statistics, the incidence of AD is constantly increasing, bringing a great burden to individuals and society. Nonetheless, there is no cure for AD, and the available drugs are very limited apart from cholinesterase inhibitors and N-Methyl-D-aspartic acid (NMDA) antagonists, which merely alleviate symptoms without delaying the progression of the disease. Therefore, there is an urgent need to develop a medicine that can delay the progression of AD or cure it. In recent years, increasing evidence suggests that metal complexes have the enormous potential to treat AD through inhibiting the aggregation and cytotoxicity of A β , interfering with the congregation and hyperphosphorylation of tau, regulating dysfunctional synaptic and unbalanced neurotransmitters, etc. In this review, we summarize the current metal complexes and their mechanisms of action for treating AD, including ruthenium, platinum, zinc, vanadium, copper, magnesium, and other complexes. [ABSTRACT FROM AUTHOR]

Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-series Study (BATS) in the North Atlantic Ocean collected by in situ pumps and the autonomous underwater vehicle (AUV) Clio were distributed with a paired metagenome, and one-dimensional (1D) liquid chromatographic data-dependent acquisition mass spectrometry analysis was stipulated. Analysis of mass spectra from seven laboratories through a common bioinformatic pipeline identified a shared set of 1056 proteins from 1395 shared peptide constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R2 values averaged 0.62±0.11 , and a Sørensen similarity analysis of the top 1000 proteins revealed 70 %–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. A bioinformatic intercomparison study, involving 10 laboratories using eight software packages, successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Lessons learned and potential improvements in methods were described. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research, including integration into global-scale ocean surveys and ocean biogeochemical models. [ABSTRACT FROM AUTHOR]

Recent technological advancements in mass spectrometry (MS)‐based proteomics technologies have accelerated its application to study greater and greater numbers of human tumor specimens. Over the last several years, the Clinical Proteomic Tumor Analysis Consortium, the International Cancer Proteogenome Consortium, and others have generated MS‐based proteomic profiling data combined with corresponding multiomics data on thousands of human tumors to date. Proteomic data sets in the public domain can be re‐examined by other researchers with different questions in mind from what the original studies explored. In this review, we examine the increasing role of proteomics in studying cancer, along with the potential for previous studies and their associated data sets to contribute to improving the diagnosis and treatment of cancer in the clinical setting. We also explore publicly available proteomics and multi‐omics data from cancer cell line models to show how such data may aid in identifying therapeutic strategies for cancer subsets. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) affects various brain cell types, including astrocytes, which are the most abundant cell types in the central nervous system (CNS). Astrocytes not only provide homeostatic support to neurons but also actively regulate synaptic signaling and functions and become reactive in response to CNS insults through diverse signaling pathways including the JAK/STAT, NF‐κB, and GPCR‐elicited pathways. The advent of new technology for transcriptomic profiling at the single‐cell level has led to increasing recognition of the highly versatile nature of reactive astrocytes and the context‐dependent specificity of astrocyte reactivity. In AD, reactive astrocytes have long been observed in senile plaques and have recently been suggested to play a role in AD pathogenesis and progression. However, the precise contributions of reactive astrocytes to AD remain elusive, and targeting this complex cell population for AD treatment poses significant challenges. In this review, we summarize the current understanding of astrocyte reactivity and its role in AD, with a particular focus on the signaling pathways that promote astrocyte reactivity and the heterogeneity of reactive astrocytes. Furthermore, we explore potential implications for the development of therapeutics for AD. Our objective is to shed light on the complex involvement of astrocytes in AD and offer insights into potential therapeutic targets and strategies for treating and managing this devastating neurodegenerative disorder. [ABSTRACT FROM AUTHOR]

Microglia are critical responders to amyloid beta (Aβ) plaques in Alzheimer's disease (AD). Therefore, the therapeutic targeting of microglia in AD is of high clinical interest. While previous investigation has focused on the innate immune receptors governing microglial functions in response to Aβ plaques, how microglial innate immune responses are regulated is not well understood. Interestingly, many of these microglial innate immune receptors contain unique cytoplasmic motifs, termed immunoreceptor tyrosine‐based activating and inhibitory motifs (ITAM/ITIM), that are commonly known to regulate immune activation and inhibition in the periphery. In this review, we summarize the diverse functions employed by microglia in response to Aβ plaques and also discuss the innate immune receptors and intracellular signaling players that guide these functions. Specifically, we focus on the role of ITAM and ITIM signaling cascades in regulating microglia innate immune responses. A better understanding of how microglial innate immune responses are regulated in AD may provide novel therapeutic avenues to tune the microglial innate immune response in AD pathology. [ABSTRACT FROM AUTHOR]

Antibiotic resistance has become one of the most significant clinical crises of the modern day. With pathogens developing immunities against existing antibiotic medications, it has become essential to find alternative compounds that can inhibit the growth of these harmful bacteria. Microorganisms residing in marine environments are promising options for this purpose. This hypothesis is backed by previous experiments with the natural products of marine microbes, studies on their ecological roles and patterns of evolution, and advances in technologies for studying marine microbes. Diving deeper into this information, this paper highlights how breakthroughs in the field of marine-derived antibiotics--including in situ cultivation, CRISPR-Cas9 genetic engineering techniques, and numerous ML models such as Evodictor--have allowed researchers to access and study marine microbes' metabolites for antimicrobial properties with considerable success. We aim to establish that future drug discovery efforts should be shifted to our oceans, the 70 percent of our world that has been left largely unexplored. [ABSTRACT FROM AUTHOR]

Osteoporosis (OP) is a prevalent skeletal disorder characterized by decreased bone mineral density (BMD) and increased fracture risk. The advancements in omics technologies—genomics, transcriptomics, proteomics, and metabolomics—have provided significant insights into the molecular mechanisms driving OP. These technologies offer critical perspectives on genetic predispositions, gene expression regulation, protein signatures, and metabolic alterations, enabling the identification of novel biomarkers for diagnosis and therapeutic targets. This review underscores the potential of these multi-omics approaches to bridge the gap between basic research and clinical applications, paving the way for precision medicine in OP management. By integrating these technologies, researchers can contribute to improved diagnostics, preventative strategies, and treatments for patients suffering from OP and related conditions. [ABSTRACT FROM AUTHOR]

Worldwide, around 50 million people live with dementia, and this number is projected to triple by 2050. It has been estimated that 20% of all dementia cases have a predominant cerebrovascular pathology, while perhaps another 20% of vascular diseases contribute to a mixed dementia picture. Therefore, the vascular contribution to dementia affects 20 million people currently and will increase markedly in the next few decades, particularly in lower- and middle-income countries. In this review, we discuss the mechanisms of vascular cognitive impairment (VCI) and review management. VCI refers to the spectrum of cerebrovascular pathologies that contribute to any degree of cognitive impairment, ranging from subjective cognitive decline, to mild cognitive impairment, to dementia. While acute cognitive decline occurring soon after a stroke is the most recognized form of VCI, chronic cerebrovascular disease, in particular cerebral small-vessel disease, can cause insidious cognitive decline in the absence of stroke. Moreover, cerebrovascular disease not only commonly co-occurs with Alzheimer's disease (AD) and increases the probability that AD pathology will result in clinical dementia, but may also contribute etiologically to the development of AD pathologies. Despite its enormous health and economic impact, VCI has been a neglected research area, with few adequately powered trials of therapies, resulting in few proven treatments. Current management of VCI emphasizes prevention and treatment of stroke and vascular risk factors, with most evidence for intensive hypertension control. Reperfusion therapies in acute stroke may attenuate the risk of VCI. Associated behavioral symptoms such as apathy and poststroke emotionalism are common. We also highlight novel treatment strategies that will hopefully lead to new disease course-modifying therapies. Finally, we highlight the importance of including cognitive endpoints in large cardiovascular prevention trials and the need for an increased research focus and funding for this important area. [ABSTRACT FROM AUTHOR]

There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases., (© 2022 The Authors. Proteomics published by Wiley-VCH GmbH.)

The Religious Order Study and Memory and Aging Project (ROSMAP) is an initiative that integrates two longitudinal cohort studies, which have been collecting clinicopathological and molecular data since the early 1990s. This extensive dataset includes a wide array of omic data, revealing the complex interactions between molecular levels in neurodegenerative diseases (ND) and aging. Neurodegenerative diseases (ND) are frequently associated with morbidity and cognitive decline in older adults. Omics research, in conjunction with clinical variables, is crucial for advancing our understanding of the diagnosis and treatment of neurodegenerative diseases. This summary reviews the extensive omics research--encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and multiomics--conducted through the ROSMAP study. It highlights the significant advancements in understanding the mechanisms underlying neurodegenerative diseases, with a particular focus on Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Background: Protein biomarkers may contribute to the identification of vulnerable subgroups for premature mortality. This study aimed to investigate the association of plasma proteins with all-cause and cause-specific mortality among individuals with and without baseline type 2 diabetes (T2D) and evaluate their impact on the prediction of all-cause mortality in two prospective Cooperative Health Research in the Region of Augsburg (KORA) studies. Methods: The discovery cohort comprised 1545 participants (median follow-up 15.6 years; 244 with T2D: 116 total, 62 cardiovascular, 31 cancer-related and 23 other-cause deaths; 1301 without T2D: 321 total, 114 cardiovascular, 120 cancer-related and 87 other-cause deaths). The validation cohort comprised 1031 participants (median follow-up 6.9 years; 203 with T2D: 76 total, 45 cardiovascular, 19 cancer-related and 12 other-cause deaths; 828 without T2D: 169 total, 74 cardiovascular, 39 cancer-related and 56 other-cause deaths). We used Cox regression to examine associations of 233 plasma proteins with all-cause and cause-specific mortality and Lasso regression to construct prediction models for all-cause mortality stratifying by baseline T2D. C-index, category-free net reclassification index (cfNRI), and integrated discrimination improvement (IDI) were conducted to evaluate the predictive performance of built prediction models. Results: Thirty-five and 62 proteins, with 29 overlapping, were positively associated with all-cause mortality in the group with and without T2D, respectively. Out of these, in the group with T2D, 35, eight, and 26 were positively associated with cardiovascular, cancer-related, and other-cause mortality, while in the group without T2D, 55, 41, and 47 were positively associated with respective cause-specific outcomes in the pooled analysis of both cohorts. Regulation of insulin-like growth factor (IGF) transport and uptake by IGF-binding proteins emerged as a unique pathway enriched for all-cause and cardiovascular mortality in individuals with T2D. The combined model containing the selected proteins (five and 12 proteins, with four overlapping, in the group with and without T2D, respectively) and clinical risk factors improved the prediction of all-cause mortality by C-index, cfNRI, and IDI. Conclusions: This study uncovered shared and unique mortality-related proteins in persons with and without T2D and emphasized the role of proteins in improving the prediction of mortality in different T2D subgroups. [ABSTRACT FROM AUTHOR]

Dysregulated proteome is an essential contributor in carcinogenesis. Protein fluctuations fuel the progression of malignant transformation, such as uncontrolled proliferation, metastasis, and chemo/radiotherapy resistance, which severely impair therapeutic effectiveness and cause disease recurrence and eventually mortality among cancer patients. Cellular heterogeneity is widely observed in cancer and numerous cell subtypes have been characterized that greatly influence cancer progression. Population‐averaged research may not fully reveal the heterogeneity, leading to inaccurate conclusions. Thus, deep mining of the multiplex proteome at the single‐cell resolution will provide new insights into cancer biology, to develop prognostic biomarkers and treatments. Considering the recent advances in single‐cell proteomics, herein we review several novel technologies with particular focus on single‐cell mass spectrometry analysis, and summarize their advantages and practical applications in the diagnosis and treatment for cancer. Technological development in single‐cell proteomics will bring a paradigm shift in cancer detection, intervention, and therapy. [ABSTRACT FROM AUTHOR]

Background. Clear cell renal cell carcinoma (ccRCC) is a renal cortical malignancy with a complex pathogenesis. Identifying ideal biomarkers to establish more accurate promising prognostic models is crucial for the survival of kidney cancer patients. Methods. Seurat R package was used for single‐cell RNA‐sequencing (scRNA‐seq) data filtering, dimensionality reduction, clustering, and differentially expressed genes analysis. Gene coexpression network analysis (WGCNA) was performed to identify the cytotoxicity‐related module. The independent cytotoxicity‐related risk model was established by the survival R package, and Kaplan–Meier (KM) survival analysis and timeROC with area under the curve (AUC) were employed to confirm the prognosis and effectiveness of the risk model. The risk and prognosis in patients suffering from ccRCC were predicted by establishing a nomogram. A comparison of the level of immune infiltration in different risk groups and subtypes using the CIBERSORT, MCP‐counter, and TIMER methods, as well as assessment of drug sensitivity to conventional chemotherapeutic agents in risk groups using the pRRophetic package, was made. Results. Eleven ccRCC subpopulations were identified by single‐cell sequencing data from the GSE224630 dataset. The identified cytotoxicity‐related T‐cell cluster and module genes defined three cytotoxicity‐related molecular subtypes. Six key genes (SOWAHB, SLC16A12, IL20RB, SLC12A8, PLG, and HHLA2) affecting prognosis risk genes were selected for developing a risk model. A nomogram containing the RiskScore and stage revealed that the RiskScore contributed the most and exhibited excellent predicted performance for prognosis in the calibration plots and decision curve analysis (DCA). Notably, high‐risk patients with ccRCC demonstrate a poorer prognosis with higher immune infiltration characteristics and TIDE scores, whereas low‐risk patients are more likely to benefit from immunotherapy. Conclusions. A ccRCC survival prognostic model was produced based on the cytotoxicity‐related signature, which had important clinical significance and may provide guidance for ccRCC treatment. [ABSTRACT FROM AUTHOR]

Introduction: Emerging evidence suggests a connection between vulnerability to infections and Alzheimer's disease (AD). The nectin cell adhesion molecule 2 (NECTIN2) gene coding for a membrane component of adherens junctions is involved in response to infections, and its single nucleotide polymorphism (SNP) rs6859 was significantly associated with AD risk in several human cohorts. It is unclear, however, how exactly rs6859 influences the development of AD pathology. The aggregation of hyperphosphorylated tau protein (pTau) is a key pathological feature of neurodegeneration in AD, which may be induced by infections, among other factors, and potentially influenced by genes involved in both AD and vulnerability to infections, such as NECTIN2. Materials and methods: We conducted a causal mediation analysis (CMA) on a sample of 708 participants in the Alzheimer's disease Neuroimaging Initiative (ADNI). The relationship between rs6859 and Alzheimer's disease (AD), with AD (yes/no) as the outcome and pTau-181 levels in the cerebrospinal fluid (CSF) acting as a mediator in this association, was assessed. Adjusted estimates from the probit and linear regression models were used in the CMA model, where an additive model considered an increase in dosage of the rs6859 A allele (AD risk factor). Results: The increase in dose of allele A of the SNP rs6859 resulted in about 0.144 increase per standard deviation (SD) of pTau-181 (95% CI: 0.041, 0.248, p < 0.01). When included together in the probit model, the change in A allele dose and each standard deviation change in pTau-181 predicted 6.84% and 9.79% higher probabilities for AD, respectively. In the CMA, the proportion of the average mediated effect was 17.05% and was higher for the risk allele homozygotes (AA), at 19.40% (95% CI: 6.20%, 43.00%, p < 0.01). The sensitivity analysis confirmed the evidence of a robust mediation effect. Conclusion: This study reported a new potential causal relationship between pTau-181 and AD. We found that the association between rs6859 in the NECTIN2 gene and AD is partly mediated by pTau-181 levels in CSF. The rest of this association may be mediated by other factors. Our finding sheds light on the complex interplay between genetic susceptibility, protein aggregation, and neurodegeneration in AD. Further research, using other biomarkers, is needed to uncover the remaining mechanisms of the association between the NECTIN2 gene and AD. [ABSTRACT FROM AUTHOR]

Drug delivery systems (DDSs) enable the controlled release of drugs in the body. DDSs have attracted increasing attention for the treatment of various disorders, including cancer, inflammatory diseases, and age-related diseases. With recent advancements in our understanding of the molecular mechanisms of aging, new target molecules and drug delivery carriers for age-related diseases have been reported. In this review, we will summarize the recent research on DDSs for age-related diseases and identify DDS strategies in the treatment of age-related diseases. [ABSTRACT FROM AUTHOR]

Vascular pathologies are among the most common contributors to neurodegenerative changes across the spectrum of normal aging to dementia. Cerebral small vessel disease (SVD) encompasses a wide range of conditions affecting capillaries, small arteries, and arterioles, as well as perivascular spaces and fluid dynamics in the brain, playing a significant role in vascular contributions to cognitive impairment and dementia (VCID). These factors can accelerate the progression of SVD and neuronal degeneration. Since aging is the primary risk factor for Alzheimer’s disease (AD) and AD-related dementias (ADRD), this Research Topic aims to gather recent research to better understand vascular contributions to healthy aging and age-related cognitive impairment. Other risk factors include diabetes, lifestyle factors, high cholesterol, vascular inflammation, and immune remodeling, all of which can accelerate cognitive dysfunction progression. This special issue includes a total of 21 articles comprising Reviews, Perspectives, and Original Research articles. The articles cover various technical and biological aspects related to recent progress in aging and dementia research. We aim to promote research exchange across different fields, including imaging, VCID, molecular biology, neuroinflammation, and immunology. Most papers in this special issue focus on understanding the disease mechanisms of AD/ADRD and developing new therapeutic strategies. [ABSTRACT FROM AUTHOR]

Hereditary neurodegenerative diseases (hNDDs) such as Alzheimer's, Parkinson's, Huntington's disease, and others are primarily characterized by their progressive nature, severely compromising both the cognitive and motor abilities of patients. The underlying genetic component in hNDDs contributes to disease risk, creating a complex genetic landscape. Considering the fact that growth factors play crucial roles in regulating cellular processes, such as proliferation, differentiation, and survival, they could have therapeutic potential for hNDDs, provided appropriate dosing and safe delivery approaches are ensured. This article presents a detailed overview of growth factors, and explores their therapeutic potential in treating hNDDs, emphasizing their roles in neuronal survival, growth, and synaptic plasticity. However, challenges such as proper dosing, delivery methods, and patient variability can hinder their clinical application. [ABSTRACT FROM AUTHOR]

Peripheral insulin resistance (IR) is a well-documented, independent risk factor for the development of type 2 diabetes, cardiovascular disease, cancer and cellular senescence. Recently, the brain has also been identified as an insulin-responsive region, where insulin acts as regulator of the brain metabolism. Despite the clear link between IR and the brain, the exact mechanisms underlying this relationship remain unclear. Therapeutic intervention in patients showing symptoms of neurodegenerative diseases has produced little or no results. It has been demonstrated that insulin resistance plays a significant role in the pathogenesis of neurodegenerative diseases, particularly cognitive decline. Peripheral and brain IR may represent a modifiable state that could be used to prevent major brain disorders. In this review, we will analyse the scientific literature supporting IR as a risk factor for Alzheimer's disease and suggest some therapeutic strategies to provide a new proposal for the prevention of brain IR and its consequences. [ABSTRACT FROM AUTHOR]