Key Signature Research Articles

Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators’ brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.

Oxidative stress drives vascular smooth muscle cell damage in acute Stanford type A aortic dissection through HIF-1α/HO-1 mediated ferroptosis

BackgroundAcute Stanford type A aortic dissection (ATAAD) is characterized by intimal tearing and false lumen formation containing large amounts of erythrocytes with heme. Heme oxygenase 1 (HO-1) is the key enzyme to degrade heme for iron accumulation and further ferroptosis. The current study aimed at investigating the role of HO-1 in the dissection progression of ATAAD. MethodsBioinformatic analyses and experimental validation were performed to reveal ferroptosis and HO-1 expression in ATAAD. Human aortic vascular smooth muscle cell (HA-VSMC) was used to explore underlying molecular mechanisms and the role of HO-1 overexpression in ATAAD. ResultsFerroptosis was identified as a critical manner of regulated cell death in ATAAD. HO-1 was screened as a key signature of ferroptosis in ATAAD, which was closely associated with oxidative stress. Single cell/nucleus transcriptomic analysis and histological staining revealed that HO-1 and HIF-1α were upregulated in vascular smooth muscle cell (VSMC) of ATAAD. Further in vitro experiments showed that H2O2-induced oxidative stress increased VSMC ferroptosis with the overexpression of HO-1, which could be suppressed by HIF-1α inhibitor PX-478. HIF-1α could transcriptionally regulate the expression of HO-1 through binding to its promoter region. Pharmacological inhibition of HO-1 by zinc protoporphyrin (ZnPP) did not reduce H2O2-induced HA-VSMC damage without heme co-incubation. However, H2O2-induced HA-VSMC damage was worsened when heme was added into the medium, and ZnPP could reduce HA-VSMC damage in this condition. ConclusionHO-1 is a key signature of VSMC ferroptosis in ATAAD. HIF-1α/HO-1 mediated ferroptosis might participate in oxidative stress induced VSMC damage.

Metaproteogenomic analysis of saliva samples from Parkinson’s disease patients with cognitive impairment

Cognitive impairment (CI) is very common in patients with Parkinson’s Disease (PD) and progressively develops on a spectrum from mild cognitive impairment (PD-MCI) to full dementia (PDD). Identification of PD patients at risk of developing cognitive decline, therefore, is unmet need in the clinic to manage the disease. Previous studies reported that oral microbiota of PD patients was altered even at early stages and poor oral hygiene is associated with dementia. However, data from single modalities are often unable to explain complex chronic diseases in the brain and cannot reliably predict the risk of disease progression. Here, we performed integrative metaproteogenomic characterization of salivary microbiota and tested the hypothesis that biological molecules of saliva and saliva microbiota dynamically shift in association with the progression of cognitive decline and harbor discriminatory key signatures across the spectrum of CI in PD. We recruited a cohort of 115 participants in a multi-center study and employed multi-omics factor analysis (MOFA) to integrate amplicon sequencing and metaproteomic analysis to identify signature taxa and proteins in saliva. Our baseline analyses revealed contrasting interplay between the genus Neisseria and Lactobacillus and Ligilactobacillus genera across the spectrum of CI. The group specific signature profiles enabled us to identify bacterial genera and protein groups associated with CI stages in PD. Our study describes compositional dynamics of saliva across the spectrum of CI in PD and paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD.

Self-emulsifying drug delivery systems (SEDDS) disrupt the gut microbiota and trigger an intestinal inflammatory response in rats

Self-emulsifying drug delivery systems (i.e. SEDDS, SMEDDS and SNEDDS) are widely employed as solubility and bioavailability enhancing formulation strategies for poorly water-soluble drugs. Despite the capacity for SEDDS to effectively facilitate oral drug absorption, tolerability concerns exist due to the capacity for high concentrations of surfactants (typically present within SEDDS) to induce gastrointestinal toxicity and mucosal irritation. With new knowledge surrounding the role of the gut microbiota in modulating intestinal inflammation and mucosal injury, there is a clear need to determine the impact of SEDDS on the gut microbiota. The current study is the first of its kind to demonstrate the detrimental impact of SEDDS on the gut microbiota of Sprague-Dawley rats, following daily oral administration (100 mg/kg) for 21 days. SEDDS comprising a lipid phase (i.e. Type I, II and III formulations according to the Lipid Formulation Classification Scheme) induced significant changes to the composition and diversity of the gut microbiota, evidenced through a reduction in operational taxonomic units (OTUs) and alpha diversity (Shannon’s index), along with statistically significant shifts in beta diversity (according to PERMANOVA of multi-dimensional Bray-Curtis plots). Key signatures of gut microbiota dysbiosis correlated with the increased expression of pro-inflammatory cytokines within the jejunum, while mucosal injury was characterised by significant reductions in plasma citrulline levels, a validated biomarker of enterocyte mass and mucosal barrier integrity. These findings have potential clinical ramifications for chronically administered drugs that are formulated with SEDDS and stresses the need for further studies that investigate dose-dependent effects of SEDDS on the gastrointestinal microenvironment in a clinical setting.

Dissecting molecular evolution of class 1 integron gene cassettes and identifying their bacterial hosts in suburban creeks via epicPCR.

Our study aimed to sequence class 1 integrons in uncultured environmental bacterial cells in freshwater from suburban creeks and uncover the taxonomy of their bacterial hosts. We also aimed to characterize integron gene cassettes with altered DNA sequences relative to those from databases or literature and identify key signatures of their molecular evolution. We applied a single-cell fusion PCR-based technique-emulsion, paired isolation and concatenation PCR (epicPCR)-to link class 1 integron gene cassette arrays to the phylogenetic markers of their bacterial hosts. The levels of streptomycin resistance conferred by the WT and altered aadA5 and aadA11 gene cassettes that encode aminoglycoside (3″) adenylyltransferases were experimentally quantified in an Escherichia coli host. Class 1 integron gene cassette arrays were detected in Alphaproteobacteria and Gammaproteobacteria hosts. A subset of three gene cassettes displayed signatures of molecular evolution, namely the gain of a regulatory 5'-untranslated region (5'-UTR), the loss of attC recombination sites between adjacent gene cassettes, and the invasion of a 5'-UTR by an IS element. Notably, our experimental testing of a novel variant of the aadA11 gene cassette demonstrated that gaining the observed 5'-UTR contributed to a 3-fold increase in the MIC of streptomycin relative to the ancestral reference gene cassette in E. coli. Dissecting the observed signatures of molecular evolution of class 1 integrons allowed us to explain their effects on antibiotic resistance phenotypes, while identifying their bacterial hosts enabled us to make better inferences on the likely origins of novel gene cassettes and IS that invade known gene cassettes.

Krylov complexity in the IP matrix model

The IP matrix model is a simple large N quantum mechanical model made up of an adjoint harmonic oscillator plus a fundamental harmonic oscillator. It is a model introduced previously as a toy model of the gauge theory dual of an AdS black hole. In the large N limit, one can solve the Schwinger-Dyson equation for the fundamental correlator, and at sufficiently high temperature, this model shows key signatures of thermalization and information loss; the correlator decay exponentially in time, and the spectral density becomes continuous and gapless. We study the Lanczos coefficients bn in this model and at sufficiently high temperature, it grows linearly in n with logarithmic corrections, which is one of the fastest growth under certain conditions. As a result, the Krylov complexity grows exponentially in time as ∼expOt\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sim \\exp \\left(\\mathcal{O}\\left(\\sqrt{t}\\right)\\right) $$\\end{document}. These results indicate that the IP model at sufficiently high temperature is chaotic.

Exercise gas exchange and echo-derived analysis in HFpEF based on patterns of oxygen peripheral utilization

Abstract Background Exercise limitation is a key signature of heart failure with preserved ejection fraction (HFpEF) syndrome evolution with studies highlighting a significant cardiac reserve limitation and others identifying a predominant limit in the peripheral VO2 kinetics and utilization. Aims To clarify the cardiopulmonary and hemodynamic response in HFpEF according to the high or low peripheral O2 utilization patterns during maximal exercise. Materials and Method 38 patients with a HFpEF diagnosis based on the ESC HFpEFF criteria underwent cardiopulmonary exercise test (CPET) combined with stress echocardiography. Patients were divided in two groups according to the median peak c(A-V) O2 difference (Group 1: &amp;lt; 11 mL/dL and Group 2: &amp;gt; 11 mL/dL). Cardiac output (CO) was calculated by echocardiography according to the formula LVOT velocity integral x LVOT area. Data were obtained after a familiarization CPET session. Results Group 1 and 2 presented similar rest demographic, left and right hemodynamic data (table). The relationship between CO and c (A-V) O2 in terms of VO2 isopleths at peak exercise were not related to any difference in CO (figure) Conclusions In HFpEF, an impairment in O2 utilization during exercise appears independent of the cardiac reserve response (similar peak CO increase) but rather peripheral mechanisms implicated in O2 diffusion/release seem to play a dominant role, emerging as selective therapeutic targets for improving functional capacity and symptoms.

A Lightweight Security Model using Delta Probabilistic Hashing Technique for Secured Data Transmission in IoT Systems

Secure data transmission is one of the most pressing concerns for resource constrained IoT devices. There is a need for an efficient and lightweight solution for data security in IoT applications. The proposed study is primarily concerned with the creation of a lightweight data security model for an IoT data transmission-based application for data transmission and storage in smart cities. The fundamental contribution of the proposed security model is the creation of a distinct hashing algorithm based on the specific pattern of the previous sequential change in value. The Delta Probabilistic Hashing (DPH) based architecture of key extraction technique for data security will perform this. Based on the hash key signature approach, this kind of safe data handling procedure provides a random key for data encryption, which will simplify the model and speed up the algorithm's operation. Our approach's main features are enhanced efficiency and throughput, lightweight data security, and adaptive key generation.

Phosphatase specificity principles uncovered by MRBLE:Dephos and global substrate identification.

Phosphoprotein phosphatases (PPPs) regulate major signaling pathways, but the determinants of phosphatase specificity are poorly understood. This is because methods to investigate this at scale are lacking. Here, we develop a novel in vitro assay, MRBLE:Dephos, that allows multiplexing of dephosphorylation reactions to determine phosphatase preferences. Using MRBLE:Dephos, we establish amino acid preferences of the residues surrounding the dephosphorylation site for PP1 and PP2A-B55, which reveals common and unique preferences. To compare the MRBLE:Dephos results to cellular substrates, we focused on mitotic exit that requires extensive dephosphorylation by PP1 and PP2A-B55. We use specific inhibition of PP1 and PP2A-B55 in mitotic exit lysates coupled with phosphoproteomics to identify more than 2,000 regulated sites. Importantly, the sites dephosphorylated during mitotic exit reveal key signatures that are consistent with MRBLE:Dephos. Furthermore, integration of our phosphoproteomic data with mitotic interactomes of PP1 and PP2A-B55 provides insight into how binding of phosphatases to substrates shapes dephosphorylation. Collectively, we develop novel approaches to investigate protein phosphatases that provide insight into mitotic exit regulation.

Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3

The ATLAS experiment relies on real-time hadronic jet reconstruction and b-tagging to record fully hadronic events containing b-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm the high-level-trigger farm, even at the reduced event rate that passes the ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAS has mitigated these computational demands by introducing a fast neural-network-based b-tagger, which acts as a low-precision filter using input from hadronic jets and tracks. It runs after a hardware trigger and before the remaining high-level-trigger reconstruction. This design relies on the negligible cost of neural-network inference as compared to track reconstruction, and the cost reduction from limiting tracking to specific regions of the detector. In the case of Standard Model HH → bb̅bb̅, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaining high-level trigger by a factor of five at the small cost of reducing the overall signal efficiency by roughly 2%.

Spatial and temporal control of the volcanic activities over the distribution of sediments in the Magadi basin, Kenya Rift

High-velocity layers in basins with significant sub-basalt coverage, such as the Magadi basin, can impede geophysical imaging of potential subsurface hydrocarbon deposits. Using magnetic and gravity methods, this study examines the influence of volcano-tectonic processes and the basement on the evolution of the Magadi basin. Regional-residual separation analyses identified key structures and signatures. Lineaments and depths of the causative sources were determined using Euler deconvolution. Butterworth low-pass filters on aeromagnetic data isolated depth-varying magnetic layer responses. The study demonstrates a westward displacement of volcanic flows in the Magadi basin, originating from nearly all volcanic plugs. Depocenters near the western boundary fault are more affected by westerly movements of the volcano-tectonic flows than depocenters near the eastern boundary fault. The Rift underwent internal compartmentalization, resulting in depocenters with unique and intermittent tectonic and sedimentary occurrences. Rift segmentation led to modifications in catchment areas, which caused sudden variations in sediment flux, ultimately leading to the isolation of the depocenters. This study identifies the initial compartmentalized depocenters of Nguruman, Koora, and Forty-six. The initial Nguruman depocenter is oriented SW-NE and spans approximately 2512 sq. km with a sediment thickness range of 2000–4000 m. The presence of horsts in the southern and northern parts precludes volcaniclastics from the depocenter. Active tectonics and inversion caused the initial Nguruman depocenter to split into two halves: the northern Musenke depocenter and the southern Pakase. Euler depth analysis indicates sedimentary formations are thicker in compartmentalized depocenters in Magadi's western and southern regions than near the eastern boundary fault. The sediment thickness range in the Koora basin is approximately 1000–3000 m, while Pakase on the western flank has a sediment thickness range of 2000–3800 m.

Candida auris-macrophage cellular interactions and transcriptional response.

The pathogenic yeast Candida auris represents a global threat of the utmost clinical relevance. This emerging fungal species is remarkable in its resistance to commonly used antifungal agents and its persistence in the nosocomial settings. The innate immune system is one the first lines of defense preventing the dissemination of pathogens in the host. C. auris is susceptible to circulating phagocytes, and understanding the molecular details of these interactions may suggest routes to improved therapies. In this work, we examined the interactions of this yeast with macrophages. We found that macrophages avidly phagocytose C. auris; however, intracellular replication is not inhibited, indicating that C. auris resists the killing mechanisms imposed by the phagocyte. Unlike Candida albicans, phagocytosis of C. auris does not induce macrophage lysis. The transcriptional response of C. auris to macrophage phagocytosis is very similar to other members of the CUG clade (C. albicans, C. tropicalis, C. parapsilosis, C. lusitaniae), i.e., downregulation of transcription/translation and upregulation of alternative carbon metabolism pathways, transporters, and induction of oxidative stress response and proteolysis. Gene family expansions are common in this yeast, and we found that many of these genes are induced in response to macrophage co-incubation. Among these, amino acid and oligopeptide transporters, as well as lipases and proteases, are upregulated. Thus, C. auris shares key transcriptional signatures shared with other fungal pathogens and capitalizes on the expansion of gene families coding for potential virulence attributes that allow its survival, persistence, and evasion of the innate immune system.

Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability.

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy-so-called interictal epileptiform activity-with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

Integrated transcriptomic and proteomic profiling reveals the key molecular signatures of brain endothelial reperfusion injury.

Reperfusion therapy after ischemic stroke often causes brain microvascular injury. However, the underlying mechanisms are unclear. Transcriptomic and proteomic analyses were performed on human cerebral microvascular endothelial cells following oxygen-glucose deprivation (OGD) or OGD plus recovery (OGD/R) to identify molecules and signaling pathways dysregulated by reperfusion. Major findings were further validated in a mouse model of cerebral ischemia and reperfusion. Transcriptomic analysis identified 390 differentially expressed genes (DEGs) between the OGD/R and OGD group. Pathway analysis indicated that these genes were mostly associated with inflammation, including the TNF signaling pathway, TGF-β signaling pathway, cytokine-cytokine receptor interaction, NOD-like receptor signaling pathway, and NF-κB signaling pathway. Proteomic analysis identified 201 differentially expressed proteins (DEPs), which were primarily associated with extracellular matrix destruction and remodeling, impairment of endothelial transport function, and inflammatory responses. Six genes (DUSP1, JUNB, NFKBIA, NR4A1, SERPINE1, and THBS1) were upregulated by OGD/R at both the mRNA and protein levels. In mice with cerebral ischemia and reperfusion, brain TNF signaling pathway was activated by reperfusion, and inhibiting TNF-α with adalimumab significantly attenuated reperfusion-induced brain endothelial inflammation. In addition, the protein level of THBS1 was substantially upregulated upon reperfusion in brain endothelial cells and the peri-endothelial area in mice receiving cerebral ischemia. Our study reveals the key molecular signatures of brain endothelial reperfusion injury and provides potential therapeutic targets for the treatment of brain microvascular injury after reperfusion therapy in ischemic stroke.

The High-redshift Clusters Occupied by Bent Radio AGN (COBRA) Survey: Investigating the Role of Environment on Bent Radio AGNs Using LOFAR

Bent radio active galactic nucleus (AGN) morphology depends on the density of the surrounding gas. However, bent sources are found inside and outside clusters, raising the question of how environment impacts bent AGN morphology. We analyze new LOw-Frequency Array the LOFAR Two-metre Sky Survey (LoTSS) Data Release II observations of 20 bent AGNs in clusters and 15 not in clusters from the high-z Clusters Occupied by Bent Radio AGN (COBRA) survey (0.35 < z < 2.35). We measure the impact of environment on size, lobe symmetry, and radio luminosity. We find that the most asymmetric radio lobes lie outside of clusters, and we uncover a tentative anticorrelation between the total projected physical area and cluster overdensity. Additionally, we, for the first time, present spectral index measurements of a large sample of high-z bent sources using LoTSS and Very Large Array Faint Images of the Radio Sky at Twenty-centimeters (VLA FIRST) observations. We find that the median spectral index for the cluster sample is −0.76 ± 0.01, while the median spectral index for the noncluster sample is −0.81 ± 0.02. Furthermore, 13 of 20 cluster bent AGNs have flat cores (α ≥ −0.6) compared to 4 of 15 of noncluster bent AGNs, indicating a key environmental signature. Beyond core spectral index, bent AGNs inside and outside clusters are remarkably similar. We conclude that the noncluster sample may be more representative of bent AGNs at large offsets from the cluster center (> 1.2 Mpc) or bent AGNs in weaker groups rather than the field.

Single-cell transcriptome and metagenome profiling reveals the genetic basis of rumen functions and convergent developmental patterns in ruminants.

The rumen undergoes developmental changes during maturation. To characterize this understudied dynamic process, we profiled single-cell transcriptomes of about 308,000 cells from the rumen tissues of sheep and goats at 17 time points. We built comprehensive transcriptome and metagenome atlases from early embryonic to rumination stages, and recapitulated histomorphometric and transcriptional features of the rumen, revealing key transitional signatures associated with the development of ruminal cells, microbiota, and core transcriptional regulatory networks. In addition, we identified and validated potential cross-talk between host cells and microbiomes and revealed their roles in modulating the spatiotemporal expression of key genes in ruminal cells. Cross-species analyses revealed convergent developmental patterns of cellular heterogeneity, gene expression, and cell-cell and microbiome-cell interactions. Finally, we uncovered how the interactions can act upon the symbiotic rumen system to modify the processes of fermentation, fiber digestion, and immune defense. These results significantly enhance understanding of the genetic basis of the unique roles of rumen.

RGS5 as a Biomarker of Pericytes, Involvement in Vascular Remodeling and Pulmonary Arterial Hypertension.

Pulmonary arterial hypertension (PAH) is a life-threatening disease characterized by a sustained rise in mean pulmonary artery pressure. Pulmonary vascular remodeling serves an important role in PAH. Identifying a key driver gene to regulate vascular remodeling of the pulmonary microvasculature is critical for PAH management. Differentially expressed genes were identified using the Gene Expression Omnibus (GEO) GSE117261, GSE48149, GSE113439, GSE53408 and GSE16947 datasets. A co-expression network was constructed using weighted gene co-expression network analysis. Novel and key signatures of PAH were screened using four algorithms, including weighted gene co-expression network analysis, GEO2R analysis, support vector machines recursive feature elimination and robust rank aggregation rank analysis. Regulator of G-protein signaling 5 (RGS5), a pro-apoptotic/anti-proliferative protein, which regulate arterial tone and blood pressure in vascular smooth muscle cells. The expression of RGS5 was determined using reverse transcription-quantitative PCR (RT-qPCR) in PAH and normal mice. The location of RGS5 and pericytes was detected using immunofluorescence. Compared with that in the normal group, RGS5 expression was upregulated in the PAH group based on GEO and RT-qPCR analyses. RGS5 expression in single cells was enriched in pericytes in single-cell RNA sequencing analysis. RGS5 co-localization with pericytes was detected in the pulmonary microvasculature of PAH. RGS5 regulates vascular remodeling of the pulmonary microvasculature and the occurrence of PAH through pericytes, which has provided novel ideas and strategies regarding the occurrence and innovative treatment of PAH.

Longitudinal Profiling of Tumor RNA Expression Signatures Reveal Key Biological Features Associated with Response to Neoadjuvant Stereotactic Body Radiation Therapy in High-Risk Prostate Cancer

Stereotactic body radiation therapy (SBRT) is a safe and effective treatment for localized prostate cancer (PCa). PREPARE-SBRT is a clinical trial testing the safety of neoadjuvant MRI-guided SBRT for men with high-risk localized PCa. We leveraged paired samples from pre-treatment biopsy and irradiated prostatectomy (RP) specimens to evaluate transcriptomic changes in irradiated tumors at acute time points following neoadjuvant SBRT. Tumor RNA expression profiles were generated using Decipher GRID by Veracyte on 12 subjects with paired pre- and post-SBRT tissues (n = 24). Descriptive statistics using gene expression profiles describing key biological features [DNA damage & repair (DDR), tumor proliferation, suppressed immune, activated immune, tumor microenvironment (TME)] and an exploratory analysis of RT sensitivity score with binary classification as sensitive or resistant were reported. A control cohort of transcriptomic profiles of 803 matched untreated biopsy and matching RP samples from the same subjects were used to control for signature differences attributable to sample type. Key tumor biology signatures most frequently observed were DDR (15/24), TME (11/24) and tumor proliferation (11/24). Signatures associated with tumor proliferation were disproportionately represented in pre-treatment samples (10/11) whereas TME-associated signatures were enriched predominantly in irradiated RP samples (8/11). Collectively, immune-related immune signatures skewed towards immune activation. All 3 samples annotated with suppressed immune signatures were from pre-treatment specimens whereas 75% (6/8) of samples annotated with activated immune status were from irradiated specimens. Additionally, conversion from suppressed to activated immune status was observed in 2 of 3 subjects (66%). In total, 42% of specimens (10/24) were designated as radio-resistant by RT sensitivity score. Among 8 baseline specimens annotated with RT resistant status, 75% of subjects (6/8) converted to RT sensitive status after neoadjuvant SBRT. Interestingly, in the two subjects with persistent radio-resistant status in pre- and post-samples there was associated with upregulation of TGF-β or PI3K-AKT pathway activation signatures. Pre- and post-SBRT transcriptomic signatures were heterogeneous and dynamic in a cohort of 12 patients with high-risk localized PCa highlighting the importance of studying longitudinal changes in individual patients. These data highlight an opportunity to leverage tumor RNA expression profiles to personalize patient and treatment selection and augment radiation response assessment. gov ID (NCT03663218).

Ride, Ride, Ride, Let It Ride: Pathological Lesions in Horse Skeletons Related to Riding.

The last 30 years have seen researchers working towards determining the earliest date of domestication for the horse (E. caballus), using osteological and pathological changes to a horse’s skeleton to infer evidence for riding—a key signature of domestication. This article provides an investigation and evaluation of the methods used, testing them on the skeletal remains of 12 horses of unknown provenience and history from Alberta, Canada. These methods include studies on the skull (cranium and mandible), the dentition (teeth), the spine, and the metapodials (lower leg bones). Overall, three of the horses exhibit osteological changes consistent with riding, three have ambiguous results, and the remaining six do not show sufficient changes. The limitations of the methods, the collections, and those of the researcher, are discussed in relation to the findings.

The Evolution of the Cold Gas Fraction in Nearby Clusters’ Ram-pressure-stripped Galaxies

Cluster galaxies are affected by the surrounding environment, which influences, in particular, their gas, stellar content, and morphology. In particular, the ram pressure exerted by the intracluster medium promotes the formation of multiphase tails of stripped gas detectable both at optical wavelengths and in the submillimeter and radio regimes, tracing the cold molecular and atomic gas components, respectively. In this work we analyze a sample of 16 galaxies belonging to clusters at redshift ∼0.05 showing evidence of an asymmetric H i morphology (based on MeerKAT observations) with and without a star-forming tail. To this sample we add three galaxies with evidence of a star-forming tail and no H i detection. Here we present the galaxies’ H2 gas content from APEX observations of the CO (2–1) emission. We find that in most galaxies with a star-forming tail the H2 global content is enhanced with respect to undisturbed field galaxies with similar stellar masses, suggesting an evolutionary path driven by the ram pressure stripping. As galaxies enter into the clusters, their H i is displaced but also partially converted into H2, so that they are H2 enriched when they pass close to the pericenter, that is, when they also develop the star-forming tails that are well visible in UV or B broad bands and in Hα emission. An inspection of the phase-space diagram for our sample suggests an anticorrelation between the H i and H2 gas phases as galaxies fall into the cluster potential. This peculiar behavior is a key signature of the ram pressure stripping in action.