Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases.

Disease risk prediction based on genomic sequence and transcriptional profile can improve disease screening and prevention. Despite identifying many disease-associated DNA variants, distinguishing deleterious non-coding DNA variations remains poor for most common diseases. In this study, we designed in vitro experiments to uncover the significance of occupancy and competitive binding between P53 and cMYC on common target genes. Analyzing publicly available ChIP-seq data for P53 and cMYC in embryonic stem cells showed that ~344-366 regions are co-occupied, and on average, two cis-overlapping motifs (CisOMs) per region were identified, suggesting that co-occupancy is evolutionarily conserved. Using U2OS and Raji cells untreated and treated with doxorubicin to increase P53 protein level while potentially reducing cMYC level, ChIP-seq analysis illustrated that around 16 to 922 genomic regions were co-occupied by P53 and cMYC, and substitutions of cMYC signals by P53 were detected post doxorubicin treatment. Around 187 expressed genes near co-occupied regions were altered at mRNA level according to RNA-seq data analysis. We utilized a computational motif-matching approach to illustrate that changes in predicted P53 binding affinity in CisOMs of co-occupied elements significantly correlate with alterations in reporter gene expression. We performed a similar analysis using SNPs mapped in CisOMs for P53 and cMYC from ChIP-seq data, and expression of target genes from GTEx portal. We found significant correlation between change in cMYC-motif binding affinity in CisOMs and altered expression. Our study brings us closer to developing a generally applicable approach to filter etiological non-coding variations associated with common diseases.

Quantitative estimates of the regulatory influence of long non-coding RNAs on global gene expression variation using TCGA breast cancer transcriptomic data.

Long non-coding RNAs (lncRNAs) have received attention in recent years for their regulatory roles in diverse biological contexts including cancer, yet large gaps remain in our understanding of their mechanisms and global maps of their targets. In this work, we investigated a basic unanswered question of lncRNA systems biology: to what extent can gene expression variation across individuals be attributed to lncRNA-driven regulation? To answer this, we analyzed RNA-seq data from a cohort of breast cancer patients, explaining each gene's expression variation using a small set of automatically selected lncRNA regulators. A key aspect of this analysis is that it accounts for confounding effects of transcription factors (TFs) as common regulators of a lncRNA-mRNA pair, to enrich the explained gene expression for lncRNA-mediated regulation. We found that for 16% of analyzed genes, lncRNAs can explain more than 20% of expression variation. We observed 25-50% of the putative regulator lncRNAs to be in 'cis' to, i.e., overlapping or located proximally to the target gene. This led us to quantify the global regulatory impact of such cis-located lncRNAs, which was found to be substantially greater than that of trans-located lncRNAs. Additionally, by including statistical interaction terms involving lncRNA-protein pairs as predictors in our regression models, we identified cases where a lncRNA's regulatory effect depends on the presence of a TF or RNA-binding protein. Finally, we created a high-confidence lncRNA-gene regulatory network whose edges are supported by co-expression as well as a plausible mechanism such as cis-action, protein scaffolding or competing endogenous RNAs. Our work is a first attempt to quantify the extent of gene expression control exerted globally by lncRNAs, especially those located proximally to their regulatory targets, in a specific biological (breast cancer) context. It also marks a first step towards systematic reconstruction of lncRNA regulatory networks, going beyond the current paradigm of co-expression networks, and motivates future analyses assessing the generalizability of our findings to additional biological contexts.

Real time changes in the expression of eicosanoid synthesizing enzymes during inflammation.

Immune responses during inflammation involve complex, well-coordinated lipid signaling pathways. Eicosanoids are a class of lipid signaling molecules derived from polyunsaturated fatty acids such as arachidonic acid and constitute a major network that controls inflammation and its subsequent resolution. Arachidonic acid is metabolized by enzymes in three different pathways to form a variety of lipid metabolites that can be either pro- or anti-inflammatory. Therefore, an understanding of the time-dependent gene expression, lipid metabolite profiles and cytokine profiles during the initial inflammatory response is necessary, as it will allow for the design of time-dependent therapeutics. Herein, we investigate the multi-level regulation of this process. After stimulating RAW 264.7 cells, a mouse-derived macrophage cell line commonly used to examine inflammatory responses, we examine the gene expression of 44 relevant lipid metabolizing enzymes from the different eicosanoid synthesizing classes. We also measure the formation of lipid metabolites and production of cytokines at selected time points. Results reveal a dynamic relationship between the time-course of inflammation dependent gene expression of the three eicosanoid synthesizing enzymes.

Alcohol for seizure induction in the epilepsy monitoring unit.

RATIONALE: Seizure induction techniques are used in the epilepsy monitoring unit (EMU) to increase diagnostic yield and reduce length of stay. There are insufficient data on the efficacy of alcohol as an induction technique. METHODS: We performed a retrospective cohort study using six years of EMU data at our institution. We compared cases who received alcohol for seizure induction to matched controls who did not. The groups were matched on the following variables: age, reason for admission, length of stay, number of antiseizure medications (ASM) at admission, whether ASMs were tapered during admission, and presence of interictal epileptiform discharges. We used both propensity score and exact matching strategies. We compared the likelihood of epileptic seizures and nonepileptic events in cases versus controls using Kaplan-Meier time-to-event analysis, as well as odds ratios for these outcomes occurring at any time during the admission. RESULTS: We analyzed 256 cases who received alcohol (median dose 2.5 standard drinks) and 256 propensity score-matched controls. Cases who received alcohol were no more likely than controls to have an epileptic seizure (X2(1) = 0.01, p = 0.93) or nonepileptic event (X2(1) = 2.1, p = 0.14) in the first 48 h after alcohol administration. For the admission overall, cases were no more likely to have an epileptic seizure (OR 0.89, 95 % CI 0.61-1.28, p = 0.58), nonepileptic event (OR 0.97, CI 0.62-1.53, p = 1.00), nor require rescue benzodiazepine (OR 0.63, CI 0.35-1.12, p = 0.15). Stratified analyses revealed no increased risk of epileptic seizure in any subgroups. Sensitivity analysis using exact matching showed that results were robust to matching strategy. CONCLUSIONS: Alcohol was not an effective induction technique in the EMU. This finding has implications for counseling patients with epilepsy about the risks of drinking alcohol in moderation in their daily lives.

Clinical characteristics and surgical outcomes of epilepsy associated with temporal encephalocele: A systematic review.

Temporal encephaloceles (TE) are an under-identified, potentially intervenable cause of epilepsy. This systematic review consolidates the current data to identify the major clinical, neuroimaging, and EEG features and surgical outcomes of epilepsy associated with TE. Literature searches were carried out using MEDLINE, Embase, PsycINFO, Scopus, and Cochrane Library databases from inception to December 7, 2023. Studies were included if they described clinical, neuroimaging, EEG, or surgical data in ≥5 patients with TE and epilepsy. Of 562 studies identified in the search, 24 met the eligibility criteria, reporting 423 unique patients with both epilepsy and TE. Compared to epilepsy patients without TE, those with TE had a higher mean age of seizure onset and were less likely to have a history of febrile seizures. Seizure semiologies were variable, but primarily mirrored temporal lobe onset patterns. Epilepsy patients with TE had a higher likelihood of having clinical or radiographic features of idiopathic intracranial hypertension (IIH) than those without. Brain MRI may show ipsilateral mesial temporal sclerosis (16 %). CT scans of the skull base usually revealed bony defects near the TE (90 %). Brain PET scans primarily showed ipsilateral temporal lobe hypometabolism (80 %), mostly in the anterior temporal lobe (67 %). Scalp EEG mostly lateralized ipsilateral to the implicated TE (92 % seizure onset) and localized to the temporal lobe (96 %). Intracranial EEG revealed seizure onset near the TE (11 of 12 cases including TE-adjacent electrodes) with variable timing of spread to the ipsilateral hippocampus. After surgical treatment of the TE, the rate of Engel I or ILAE 1 outcomes at one year was 75 % for lesionectomy, 85 % for anterior temporal lobectomy (ATL), and 80 % for ATL with amygdalohippocampectomy. Further studies are needed to better elucidate the relationship between IIH, TE, and epilepsy, improve the identification of TE, and optimize surgical interventions.

Can ChatGPT outperform a neurosurgical trainee? A prospective comparative study.

PURPOSE: This study aimed to compare the performance of ChatGPT, a large language model (LLM), with human neurosurgical applicants in a neurosurgical national selection interview, to assess the potential of artificial intelligence (AI) and LLMs in healthcare and provide insights into their integration into the field. METHODS: In a prospective comparative study, a set of neurosurgical national selection-style interview questions were asked to eight human participants and ChatGPT in an online interview. All participants were doctors currently practicing in the UK who had applied for a neurosurgical National Training Number. Interviews were recorded, anonymised, and scored by three neurosurgical consultants with experience as interviewers for national selection. Answers provided by ChatGPT were used as a template for a virtual interview. Interview transcripts were subsequently scored by neurosurgical consultants using criteria utilised in real national selection interviews. Overall interview score and subdomain scores were compared between human participants and ChatGPT. RESULTS: For overall score, ChatGPT fell behind six human competitors and did not achieve a mean score higher than any individuals who achieved training positions. Several factors, including factual inaccuracies and deviations from expected structure and style may have contributed to ChatGPT's underperformance. CONCLUSIONS: LLMs such as ChatGPT have huge potential for integration in healthcare. However, this study emphasises the need for further development to address limitations and challenges. While LLMs have not surpassed human performance yet, collaboration between humans and AI systems holds promise for the future of healthcare.

Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention.

BACKGROUND: Many long non-coding RNAs, known to be involved in transcriptional regulation, are enriched in the nucleus and interact with chromatin. However, their mechanisms of chromatin interaction and the served cellular functions are poorly understood. We sought to characterize the mechanisms of lncRNA nuclear retention by systematically mapping the sequence and chromatin features that distinguish lncRNA-interacting genomic segments. RESULTS: We found DNA 5-mer frequencies to be predictive of chromatin interactions for all lncRNAs, suggesting sequence-specificity as a global theme in the interactome. Sequence features representing protein-DNA and protein-RNA binding motifs revealed potential mechanisms for specific lncRNAs. Complementary to these global themes, transcription-related features and DNA-RNA triplex formation potential were noted to be highly predictive for two mutually exclusive sets of lncRNAs. DNA methylation was also noted to be a significant predictor, but only when combined with other epigenomic features. CONCLUSIONS: Taken together, our statistical findings suggest that a group of lncRNAs interacts with transcriptionally inactive chromatin through triplex formation, whereas another group interacts with transcriptionally active regions and is involved in DNA Damage Response (DDR) through formation of R-loops. Curiously, we observed a strong pattern of enrichment of 5-mers in four potentially interacting entities: lncRNA-bound DNA tiles, lncRNAs, miRNA seed sequences, and repeat elements. This finding points to a broad sequence-based network of interactions that may underlie regulation of fundamental cellular functions. Overall, this study reveals diverse sequence and chromatin features related to lncRNA-chromatin interactions, suggesting potential mechanisms of nuclear retention and regulatory function.

Influenza A virus infection disrupts oligodendrocyte homeostasis and alters the myelin lipidome in the adult mouse.

BACKGROUND: Recent data suggest that myelin may be altered by physiological events occurring outside of the central nervous system, which may cause changes to cognition and behavior. Similarly, peripheral infection by non-neurotropic viruses is also known to evoke changes to cognition and behavior. METHODS: Mice were inoculated with saline or influenza A virus. Bulk RNA-seq, lipidomics, RT-qPCR, flow cytometry, immunostaining, and western blots were used to determine the effect of infection on OL viability, protein expression and changes to the lipidome. To determine if microglia mediated infection-induced changes to OL homeostasis, mice were treated with GW2580, an inhibitor of microglia activation. Additionally, conditioned medium experiments using primary glial cell cultures were also used to test whether secreted factors from microglia could suppress OL gene expression. RESULTS: Transcriptomic and RT-qPCR analyses revealed temporal downregulation of OL-specific transcripts with concurrent upregulation of markers characteristic of cellular stress. OLs isolated from infected mice had reduced cellular expression of myelin proteins compared with those from saline-inoculated controls. In contrast, the expression of these proteins within myelin was not different between groups. Similarly, histological and immunoblotting analysis performed on various brain regions indicated that infection did not alter OL viability, but increased expression of a cellular stress marker. Shot-gun lipidomic analysis revealed that infection altered the lipid profile within the prefrontal cortex as well as in purified brain myelin and that these changes persisted after recovery from infection. Treatment with GW2580 during infection suppressed the expression of genes associated with glial activation and partially restored OL-specific transcripts to baseline levels. Finally, conditioned medium from activated microglia reduced OL-gene expression in primary OLs without altering their viability. CONCLUSIONS: These findings show that peripheral respiratory viral infection with IAV is capable of altering OL homeostasis and indicate that microglia activation is likely involved in the process.

Flexible, high-resolution cortical arrays with large coverage capture microscale high-frequency oscillations in patients with epilepsy.

OBJECTIVE: Effective surgical treatment of drug-resistant epilepsy depends on accurate localization of the epileptogenic zone (EZ). High-frequency oscillations (HFOs) are potential biomarkers of the EZ. Previous research has shown that HFOs often occur within submillimeter areas of brain tissue and that the coarse spatial sampling of clinical intracranial electrode arrays may limit the accurate capture of HFO activity. In this study, we sought to characterize microscale HFO activity captured on thin, flexible microelectrocorticographic (µECoG) arrays, which provide high spatial resolution over large cortical surface areas. METHODS: We used novel liquid crystal polymer thin-film µECoG arrays (.76-1.72-mm intercontact spacing) to capture HFOs in eight intraoperative recordings from seven patients with epilepsy. We identified ripple (80-250 Hz) and fast ripple (250-600 Hz) HFOs using a common energy thresholding detection algorithm along with two stages of artifact rejection. We visualized microscale subregions of HFO activity using spatial maps of HFO rate, signal-to-noise ratio, and mean peak frequency. We quantified the spatial extent of HFO events by measuring covariance between detected HFOs and surrounding activity. We also compared HFO detection rates on microcontacts to simulated macrocontacts by spatially averaging data. RESULTS: We found visually delineable subregions of elevated HFO activity within each µECoG recording. Forty-seven percent of HFOs occurred on single 200-µm-diameter recording contacts, with minimal high-frequency activity on surrounding contacts. Other HFO events occurred across multiple contacts simultaneously, with covarying activity most often limited to a .95-mm radius. Through spatial averaging, we estimated that macrocontacts with 2-3-mm diameter would only capture 44% of the HFOs detected in our µECoG recordings. SIGNIFICANCE: These results demonstrate that thin-film microcontact surface arrays with both highresolution and large coverage accurately capture microscale HFO activity and may improve the utility of HFOs to localize the EZ for treatment of drug-resistant epilepsy.

Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform.

We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis, and expression signature analysis. The system specializes in "knowledge-guided" data mining and machine learning algorithms, in which user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge bases and encoded in a massive "Knowledge Network." KnowEnG adheres to "FAIR" principles (findable, accessible, interoperable, and reuseable): its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution, and are interoperable with other computing platforms. The analysis tools are made available through multiple access modes, including a web portal with specialized visualization modules. We demonstrate the KnowEnG system's potential value in democratization of advanced tools for the modern genomics era through several case studies that use its tools to recreate and expand upon the published analysis of cancer data sets.

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks.

Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer 'grammar' in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.

VarSAn: associating pathways with a set of genomic variants using network analysis.

There is a pressing need today to mechanistically interpret sets of genomic variants associated with diseases. Here we present a tool called 'VarSAn' that uses a network analysis algorithm to identify pathways relevant to a given set of variants. VarSAn analyzes a configurable network whose nodes represent variants, genes and pathways, using a Random Walk with Restarts algorithm to rank pathways for relevance to the given variants, and reports P-values for pathway relevance. It treats non-coding and coding variants differently, properly accounts for the number of pathways impacted by each variant and identifies relevant pathways even if many variants do not directly impact genes of the pathway. We use VarSAn to identify pathways relevant to variants related to cancer and several other diseases, as well as drug response variation. We find VarSAn's pathway ranking to be complementary to the standard approach of enrichment tests on genes related to the query set. We adopt a novel benchmarking strategy to quantify its advantage over this baseline approach. Finally, we use VarSAn to discover key pathways, including the VEGFA-VEGFR2 pathway, related to de novo variants in patients of Hypoplastic Left Heart Syndrome, a rare and severe congenital heart defect.

Global shape of Toll activation is determined by wntD enhancer properties.

Buffering variability in morphogen distribution is essential for reproducible patterning. A theoretically proposed class of mechanisms, termed "distal pinning," achieves robustness by combining local sensing of morphogen levels with global modulation of gradient spread. Here, we demonstrate a critical role for morphogen sensing by a gene enhancer, which ultimately determines the final global distribution of the morphogen and enables reproducible patterning. Specifically, we show that, while the pattern of Toll activation in the early Drosophila embryo is robust to gene dosage of its locally produced regulator, WntD, it is sensitive to a single-nucleotide change in the wntD enhancer. Thus, enhancer properties of locally produced WntD directly impinge on the global morphogen profile.

Behavior-related gene regulatory networks: A new level of organization in the brain.

Neuronal networks are the standard heuristic model today for describing brain activity associated with animal behavior. Recent studies have revealed an extensive role for a completely distinct layer of networked activities in the brain-the gene regulatory network (GRN)-that orchestrates expression levels of hundreds to thousands of genes in a behavior-related manner. We examine emerging insights into the relationships between these two types of networks and discuss their interplay in spatial as well as temporal dimensions, across multiple scales of organization. We discuss properties expected of behavior-related GRNs by drawing inspiration from the rich literature on GRNs related to animal development, comparing and contrasting these two broad classes of GRNs as they relate to their respective phenotypic manifestations. Developmental GRNs also represent a third layer of network biology, playing out over a third timescale, which is believed to play a crucial mediatory role between neuronal networks and behavioral GRNs. We end with a special emphasis on social behavior, discuss whether unique GRN organization and cis-regulatory architecture underlies this special class of behavior, and review literature that suggests an affirmative answer.

Patient preferences pertaining to treatment options for drug-resistant focal epilepsy.

OBJECTIVE: To determine patient acceptability of benefit-risk trade-offs in selecting treatment options for drug-resistant mesial temporal lobe epilepsy, including open brain surgery, laser ablation (laser interstitial thermal therapy [LITT]), and continued medications. METHODS: A discrete-choice experiment survey was developed, consisting of 20 versions that were randomly assigned to respondents. Each version had 8 sets of constructed treatment alternatives, representing open brain surgery, LITT, or continued medical management. For each set, respondents indicated the treatment alternative they would choose first. Treatment alternatives were characterized by varying levels of chance of seizure freedom for at least 2 years (20-70%), risk of 30-day mortality (0-10%), and risk of neurological deficits (0-40%). Respondents' choices were analyzed using random-parameters logit models to quantify acceptable benefit-risk trade-offs. Preference heterogeneity was evaluated using latent-class analysis. RESULTS: The survey was administered to 2 cohorts of adult patients with drug-resistant epilepsy: a Duke cohort identified using diagnostic codes (n = 106) and a web-recruited panel with a self-reported physician diagnosis of drug-resistant epilepsy (n = 300). Based on mean preference weights, respondents who indicated a willingness to consider surgical intervention would accept a reduction in chance of seizure freedom from 70% to a minimum-acceptable benefit (MAB) of 23% if they could undergo LITT rather than open brain surgery. For a reduction in 30-day mortality from 1% to 0%, MAB was 52%. For a reduction in risk of long-term deficits from 10% to 0%, MAB was 39%. Latent-class analysis revealed additional choice patterns identifying respondent groups that more strongly favored continuing medications or undergoing surgery. CONCLUSION: Patients who are receptive to surgery would accept significantly lower treatment effectiveness to undergo a minimally invasive procedure relative to open brain surgery. They also were willing to accept lower treatment benefit to reduce risks of mortality or neurological deficits.

Punicalagin and ellagic acid containing Punica granatum L. fruit rind extract prevents vincristine-induced neuropathic pain in rats: an in silico and in vivo evidence of GABAergic action and cytokine inhibition.

Objectives: We aimed to investigate the protective potential of Punica granatum L. fruit rind extract (PFE) containing punicalagin (10.3% W/W), ellagic acid (EA) (2.7%W/W) in vincristine (75 µg/kg i.p.)- induced neuropathic pain in Wistar rats.Methods: Docking simulation studies were done on the three-dimensional (3D) structure of the GABAA and PPAR γ receptor for the binding of EA as well as punicalagin docking studies on TNF-α, and IL-6. The Present Study conceptualized a test battery to evaluate the behavioral, biochemical and histological changes.Results: Vincristine -induced significant cold allodynia, mechanical hyperalgesia, and functional deficit on 12th and 21st days. It also increased in the levels of TNF-α (Tumor necrosis factor-α), IL-6 (Interleukin-6), and MPO (Myeloperoxidase). Administration of PFE (100 and 300 mg/kg, p.o.), EA (50 mg/kg), and gabapentin (100 mg/kg) attenuated Vincristine-induced behavioral and biochemical changes significantly (P < .05). PFE showed better antinociceptive activity to EA. The histopathological evaluation also revealed the protective effects of PFE. Pretreatment of bicuculline (selective antagonist of GABAA receptors) reversed antinociceptive action of PFE, but administration of γ aminobutyric acid potentiated the action of PFE. PPAR-γ antagonist BADGE did not modify the effect of PFE. Docking results revealed that EA properly positioned into GABA and PPARγ binding site and acts as a partial agonist. Docking score of Punicalagin found to be - 9.02 kcal/mol and - 8.32 kcal/mol on IL-6 and TNFα respectively.Discussion: Conclusively, the attenuating effect of PFE may be attributed to the GABAergic system, cytokine inhibition, and anti-inflammatory activities.

Hemicraniectomy and externalized ventricular drain placement in a pediatric patient with myelin oligodendrocyte glycoprotein-associated tumefactive demyelinating disease.

BACKGROUND: Acquired demyelination of the central nervous system in children can manifest as multiple sclerosis, neuromyelitis optica, myelin oligodendrocyte glycoprotein (MOG)-associated demyelination, or as an acute monophasic illness without serum antibodies. Rarely do patients with demyelinating disease need surgical intervention for fulminant crises. CASE: We report a case of anti-MOG antibody-related tumefactive demyelination in a 10-year-old female who required urgent hemicraniectomy and external ventricular drain placement for progressive white matter edema with obstructive hydrocephalus, subfalcine, and transtentorial herniation.

Label-free visualization and characterization of extracellular vesicles in breast cancer.

Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples. With a pixel-level segmentation mask provided by the deep neural network, individual EVs can be analyzed in terms of their optical signature in the context of their spatial distribution. Quantitative analysis of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. Furthermore, the percentage of NAD(P)H-rich EVs is highly correlated with human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as its potential for clinical applications. In addition to the characterization of EV properties, we also demonstrate label-free monitoring of EV dynamics (uptake, release, and movement) in live cells and animals. The in situ metabolic profiling capacity of the proposed method together with the finding of increasing NAD(P)H-rich EV subpopulations in breast cancer have the potential for empowering applications in basic science and enhancing our understanding of the active metabolic roles that EVs play in cancer progression.

"Can differences in hospitalised mild traumatic brain injury (mTBI) outcomes at 12 months be predicted?"

OBJECTIVES: To identify risk factors for poor outcome one year post-mild traumatic brain injury (mTBI). DESIGN: This study was a prospective observational study using consecutive adult hospital admissions with mTBI. SUBJECTS: A total of 869 consecutive mTBI patients were enrolled in this study. METHODS: All patients were reviewed by the specialist TBI rehabilitation team at six weeks and one year following mTBI. Demographic and injury data collected included: age, gender, TBI severity and Glasgow Coma Scale (GCS). At twelve months, global outcome was assessed by the Extended Glasgow Outcome Score (GOSE) and participation restriction by the Rivermead Head Injury Follow-up Questionnaire (RHFUQ) via semi-structured interview. An ordinal regression (OR) was used to identify associated factors for poor GOSE outcome and a linear regression for a poor RHFUQ outcome. RESULTS: In the GOSE analysis, lower GCS (p < 0.001), medical comorbidity (p = 0.027), depression (p < 0.001) and male gender (p = 0.008) were identified as risk factors for poor outcome. The RHFUQ analysis identified: lower GCS (p = 0.002), female gender (p = 0.001) and injuries from assault (p = 0.003) were variables associated with worse social functioning at one year. CONCLUSION: mTBI is associated with a significant impact upon the physical health and psychosocial function of affected individuals. The results of this study demonstrate that differences in mTBI outcome can be identified at twelve months post-mTBI and that certain features, particularly GCS, are associated with poorer outcomes.

Long-term oncological outcomes after haemorrhagic apoplexy in pituitary adenoma managed operatively and non-operatively.

INTRODUCTION: Depending on severity of presentation, pituitary apoplexy can be managed with acute surgery or non-operatively. We aim to assess long-term tumour control, visual and endocrinological outcomes following pituitary apoplexy with special emphasis on patients treated non-operatively. METHODS: Multicentre retrospective cohort study. All patients with symptomatic pituitary apoplexy were included. Patients were divided into 3 groups: group 1: surgery within 7 days; group 2: surgery 7 days-3 months; group 3: non-operative. Further intervention for oncological reasons during follow-up was the primary outcome. Secondary outcome measures included visual and endocrinological function at last follow-up. RESULTS: One hundred sixty patients were identified with mean follow-up of 48 months (n = 61 group 1; n = 34 group 2; n = 64 group 3). Factors influencing decision for surgical treatment included visual acuity loss (OR: 2.50; 95% CI: 1.02-6.10), oculomotor nerve palsy (OR: 2.80; 95% CI: 1.08-7.25) and compression of chiasm on imaging (OR: 9.50; 95% CI: 2.06-43.73). Treatment for tumour progression/recurrence was required in 17%, 37% and 24% in groups 1, 2 and 3, respectively (p = 0.07). Urgent surgery (OR: 0.16; 95% CI: 0.04-0.59) and tumour regression on follow-up (OR: 0.04; 95% CI: 0.04-0.36) were independently associated with long-term tumour control. Visual and endocrinological outcomes were comparable between groups. CONCLUSION: Urgent surgery is an independent predictor of long-term tumour control following pituitary apoplexy. However, 76% of patients who successfully complete 3 months of non-operative treatment may not require any intervention in the long term.