Search

Abstract Recent failures translating preclinical behavioral treatment effects to positive clinical trial results in humans with Fragile X Syndrome (FXS) support refocusing attention on biological pathways and associated measures, such as electroencephalography (EEG), with strong translational potential and small molecule target engagement. This study utilized guided machine learning to test promising translational EEG measures (resting power and auditory chirp oscillatory variables) in a large heterogeneous sample of individuals with FXS to identify best performing EEG variables for reliably separating individuals with FXS, and genetically-mediated subgroups within FXS, from typically developing controls. Best performing variables included resting relative frontal theta power, all combined posterior-head resting power bands, posterior peak alpha frequency (PAF), combined PAF across all measured regions, combined theta, alpha, and gamma power during the chirp, and all combined chirp oscillatory variables. Sub-group analyses for resting EEG best discriminated non-mosaic FXS males via frontal theta resting relative power (AUC = 0.8759), even with data reduced to a 20-channel clinical montage (AUC = 0.9062). In the chirp task, FXS females and non-mosaic males were nearly perfectly discriminated by combined theta, alpha, and gamma power (AUC = 0.9444) and a combination of all variables (AUC = 0.9610), respectively. Results support use of resting and auditory oscillatory tasks to reliably identify neural deficit in FXS, and to identify specific translational targets for genetically-mediated sub-groups, supporting potential points for stratification.

Abstract Functional electrical stimulation (FES) can support functional restoration of a paretic limb post-stroke. Hebbian plasticity depends on temporally coinciding pre- and post-synaptic activity. A tight temporal relationship between motor cortical (MC) activity associated with attempted movement and FES-generated visuo-proprioceptive feedback is hypothesized to enhance motor recovery. Using a brain–computer interface (BCI) to classify MC spectral power in electroencephalographic (EEG) signals to trigger FES-delivery with detection of movement attempts improved motor outcomes in chronic stroke patients. We hypothesized that heightened neural plasticity earlier post-stroke would further enhance corticomuscular functional connectivity and motor recovery. We compared subcortical non-dominant hemisphere stroke patients in BCI-FES and Random-FES (FES temporally independent of MC movement attempt detection) groups. The primary outcome measure was the Fugl-Meyer Assessment, Upper Extremity (FMA-UE). We recorded high-density EEG and transcranial magnetic stimulation-induced motor evoked potentials before and after treatment. The BCI group showed greater: FMA-UE improvement; motor evoked potential amplitude; beta oscillatory power and long-range temporal correlation reduction over contralateral MC; and corticomuscular coherence with contralateral MC. These changes are consistent with enhanced post-stroke motor improvement when movement is synchronized with MC activity reflecting attempted movement.

Abstract Hepatitis C virus (HCV) is a plus-stranded RNA virus that often chronically infects liver hepatocytes and causes liver cirrhosis and cancer. These viruses replicate their genomes employing error-prone replicases. Thereby, they routinely generate a large ‘cloud’ of RNA genomes (quasispecies) which—by trial and error—comprehensively explore the sequence space available for functional RNA genomes that maintain the ability for efficient replication and immune escape. In this context, it is important to identify which RNA secondary structures in the sequence space of the HCV genome are conserved, likely due to functional requirements. Here, we provide the first genome-wide multiple sequence alignment (MSA) with the prediction of RNA secondary structures throughout all representative full-length HCV genomes. We selected 57 representative genomes by clustering all complete HCV genomes from the BV-BRC database based on k-mer distributions and dimension reduction and adding RefSeq sequences. We include annotations of previously recognized features for easy comparison to other studies. Our results indicate that mainly the core coding region, the C-terminal NS5A region, and the NS5B region contain secondary structure elements that are conserved beyond coding sequence requirements, indicating functionality on the RNA level. In contrast, the genome regions in between contain less highly conserved structures. The results provide a complete description of all conserved RNA secondary structures and make clear that functionally important RNA secondary structures are present in certain HCV genome regions but are largely absent from other regions. Full-genome alignments of all branches of Hepacivirus C are provided in the supplement.

Abstract Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis.

Abstract Vestibular schwannomas (VS) are the most common tumor of the skull base with available treatment options that carry a risk of iatrogenic injury to the facial nerve, which can significantly impact patients’ quality of life. As facial nerve outcomes remain challenging to prognosticate, we endeavored to utilize machine learning to decipher predictive factors relevant to facial nerve outcomes following microsurgical resection of VS. A database of patient-, tumor- and surgery-specific features was constructed via retrospective chart review of 242 consecutive patients who underwent microsurgical resection of VS over a 7-year study period. This database was then used to train non-linear supervised machine learning classifiers to predict facial nerve preservation, defined as House-Brackmann (HB) I vs. facial nerve injury, defined as HB II–VI, as determined at 6-month outpatient follow-up. A random forest algorithm demonstrated 90.5% accuracy, 90% sensitivity and 90% specificity in facial nerve injury prognostication. A random variable (rv) was generated by randomly sampling a Gaussian distribution and used as a benchmark to compare the predictiveness of other features. This analysis revealed age, body mass index (BMI), case length and the tumor dimension representing tumor growth towards the brainstem as prognosticators of facial nerve injury. When validated via prospective assessment of facial nerve injury risk, this model demonstrated 84% accuracy. Here, we describe the development of a machine learning algorithm to predict the likelihood of facial nerve injury following microsurgical resection of VS. In addition to serving as a clinically applicable tool, this highlights the potential of machine learning to reveal non-linear relationships between variables which may have clinical value in prognostication of outcomes for high-risk surgical procedures.

Abstract Recent demonstrations of room-temperature lasing in optically pumped GeSn show promise for future CMOS compatible lasers for Si-photonics applications. However, challenges remain for electrically pumped devices. Investigation of the processes that limit device performance is therefore vital in aiding the production of future commercial devices. In this work, a combined experimental and modelling approach is utilised to explore the dominant loss processes in current devices. By manipulating the band structure of functioning devices using high hydrostatic pressure techniques at low temperature, the dominant carrier recombination pathways are identified. This reveals that 93 $$~\pm ~$$ ± 5% of the threshold current is attributable to defect-related recombination at a temperature, T = 85 K. Furthermore, carrier occupation of L-valley states (carrier leakage) is responsible for 1.1 $$~\pm ~$$ ± 0.3% of the threshold current, but this sharply increases to 50% with a decrease of just 30 meV in the L- $$\Gamma$$ Γ separation energy. This indicates that thermal broadening of a similar order may reproduce these adverse effects, limiting device performance at higher temperatures. Temperature dependent calculations show that carrier occupation of indirect valley L-states strongly affects the transparency carrier density and is therefore very sensitive to the Sn composition, leading to an effective operational temperature range for given Sn compositions and strain values. Recommendations for future device designs are proposed based on band structure and growth optimisations.

Abstract Suppression of threading dislocations (TDs) in thin germanium (Ge) layers grown on silicon (Si) substrates has been critical for realizing high-performance Si-based optoelectronic and electronic devices. An advanced growth strategy is desired to minimize the TD density within a thin Ge buffer layer in Ge-on-Si systems. In this work, we investigate the impact of P dopants in 500-nm thin Ge layers, with doping concentrations from 1 to 50 × 1018 cm−3. The introduction of P dopants has efficiently promoted TD reduction, whose potential mechanism has been explored by comparing it to the well-established Sb-doped Ge-on-Si system. P and Sb dopants reveal different defect-suppression mechanisms in Ge-on-Si samples, inspiring a novel co-doping technique by exploiting the advantages of both dopants. The surface TDD of the Ge buffer has been further reduced by the co-doping technique to the order of 107 cm−2 with a thin Ge layer (of only 500 nm), which could provide a high-quality platform for high-performance Si-based semiconductor devices.

Abstract Here, we establish a CT-radiomics based method for application in invasive, orthotopic rodent brain tumour models. Twenty four NOD/SCID mice were implanted with U87R-Luc2 GBM cells and longitudinally imaged via contrast enhanced (CE-CT) imaging. Pyradiomics was employed to extract CT-radiomic features from the tumour-implanted hemisphere and non-tumour-implanted hemisphere of acquired CT-scans. Inter-correlated features were removed (Spearman correlation > 0.85) and remaining features underwent predictive analysis (recursive feature elimination or Boruta algorithm). An area under the curve of the receiver operating characteristic curve was implemented to evaluate radiomic features for their capacity to predict defined outcomes. Firstly, we identified a subset of radiomic features which distinguish the tumour-implanted hemisphere and non- tumour-implanted hemisphere (i.e, tumour presence from normal tissue). Secondly, we successfully translate preclinical CT-radiomic pipelines to GBM patient CT scans (n = 10), identifying similar trends in tumour-specific feature intensities (E.g. ‘glszm Zone Entropy’), thereby suggesting a mouse-to-human species conservation (a conservation of radiomic features across species). Thirdly, comparison of features across timepoints identify features which support preclinical tumour detection earlier than is possible by visual assessment of CT scans. This work establishes robust, preclinical CT-radiomic pipelines and describes the application of CE-CT for in-depth orthotopic brain tumour monitoring. Overall we provide evidence for the role of pre-clinical ‘discovery’ radiomics in the neuro-oncology space.

Abstract Functional MRI (fMRI) of the spinal cord is an expanding area of research with potential to investigate neuronal activity in the central nervous system. We aimed to characterize the functional connectivity features of the human lumbar spinal cord using resting-state fMRI (rs-fMRI) at 3T, using region-based and data-driven analysis approaches. A 3D multi-shot gradient echo resting-state blood oxygenation level dependent-sensitive rs-fMRI protocol was implemented in 26 healthy participants. Average temporal signal-to-noise ratio in the gray matter was 16.35 ± 4.79 after denoising. Evidence of synchronous signal fluctuations in the ventral and dorsal horns with their contralateral counterparts was observed in representative participants using interactive, exploratory seed-based correlations. Group-wise average in-slice Pearson’s correlations were 0.43 ± 0.17 between ventral horns, and 0.48 ± 0.16 between dorsal horns. Group spatial independent component analysis (ICA) was used to identify areas of coherent activity¸ and revealed components within the gray matter corresponding to anatomical regions. Lower-dimensionality ICA revealed bilateral components corresponding to ventral and dorsal networks. Additional separate ICAs were run on two subsets of the participant group, yielding two sets of components that showed visual consistency and moderate spatial overlap. This work shows feasibility of rs-fMRI to probe the functional features and organization of the lumbar spinal cord.

Abstract Traditional diagnostic formulations of psychotic disorders have low correspondence with underlying disease neurobiology. This has led to a growing interest in using brain-based biomarkers to capture biologically-informed psychosis constructs. Building upon our prior work on the B-SNIP Psychosis Biotypes, we aimed to examine whether structural MRI (an independent biomarker not used in the Biotype development) can effectively classify the Biotypes. Whole brain voxel-wise grey matter density (GMD) maps from T1-weighted images were used to train and test (using repeated randomized train/test splits) binary L2-penalized logistic regression models to discriminate psychosis cases (n = 557) from healthy controls (CON, n = 251). A total of six models were evaluated across two psychosis categorization schemes: (i) three Biotypes (B1, B2, B3) and (ii) three DSM diagnoses (schizophrenia (SZ), schizoaffective (SAD) and bipolar (BD) disorders). Above-chance classification accuracies were observed in all Biotype (B1 = 0.70, B2 = 0.65, and B3 = 0.56) and diagnosis (SZ = 0.64, SAD = 0.64, and BD = 0.59) models. However, the only model that showed evidence of specificity was B1, i.e., the model was able to discriminate B1 vs. CON and did not misclassify other psychosis cases (B2 or B3) as B1 at rates above nominal chance. The GMD-based classifier evidence for B1 showed a negative association with an estimate of premorbid general intellectual ability, regardless of group membership, i.e. psychosis or CON. Our findings indicate that, complimentary to clinical diagnoses, the B-SNIP Psychosis Biotypes may offer a promising approach to capture specific aspects of psychosis neurobiology.

Abstract Feline mammary adenocarcinomas (FMA) are aggressive tumours with metastatic capability and limited treatment options. This study aims to investigate whether miRNAs associated with FMA tumours are secreted in extracellular vesicles (EVs) and whether they can potentially be used as a cancer biomarker in EVs from feline plasma. Tumours and matched tumour free margins from 10 felines with FMA were selected. Following a detailed literature search, RT-qPCR analyses of 90 miRNAs identified 8 miRNAs of interest for further investigation. Tumour tissue, margins and plasma were subsequently collected from a further 10 felines with FMA. EVs were isolated from the plasma. RT-qPCR expression analyses of the 8 miRNAs of interest were carried out in tumour tissue, margins, FMA EVs and control EVs. Additionally, proteomic analysis of both control and FMA plasma derived EVs was undertaken. RT-qPCR revealed significantly increased miR-20a and miR-15b in tumours compared to margins. A significant decrease in miR-15b and miR-20a was detected in EVs from FMAs compared to healthy feline EVs. The proteomic content of EVs distinguished FMAs from controls, with the protein targets of miR-20a and miR-15b also displaying lower levels in the EVs from patients with FMA. This study has demonstrated that miRNAs are readily detectable in both the tissue and plasma derived EVs from patients with FMA. These miRNAs and their protein targets are a detectable panel of markers in circulating plasma EVs that may inform future diagnostic tests for FMA in a non-invasive manner. Moreover, the clinical relevance of miR-20a and miR-15b warrants further investigation.

Abstract Malignant gliomas are a type of primary brain tumour that originates in glial cells. Among them, glioblastoma multiforme (GBM) is the most common and the most aggressive brain tumour in adults, classified as grade IV by the World Health Organization. The standard care for GBM, known as the Stupp protocol includes surgical resection followed by oral chemotherapy with temozolomide (TMZ). This treatment option provides a median survival prognosis of only 16–18 months to patients mainly due to tumour recurrence. Therefore, enhanced treatment options are urgently needed for this disease. Here we show the development, characterization, and in vitro and in vivo evaluation of a new composite material for local therapy of GBM post-surgery. We developed responsive nanoparticles that were loaded with paclitaxel (PTX), and that showed penetration in 3D spheroids and cell internalization. These nanoparticles were found to be cytotoxic in 2D (U-87 cells) and 3D (U-87 spheroids) models of GBM. The incorporation of these nanoparticles into a hydrogel facilitates their sustained release in time. Moreover, the formulation of this hydrogel containing PTX-loaded responsive nanoparticles and free TMZ was able to delay tumour recurrence in vivo after resection surgery. Therefore, our formulation represents a promising approach to develop combined local therapies against GBM using injectable hydrogels containing nanoparticles.

Abstract To successfully establish itself in a novel environment, an animal must make an inherent trade-off between knowledge accumulation and exploitation of knowledge gained (i.e., the exploration–exploitation dilemma). To evaluate how habitat quality affects the spatio-temporal scale of switching between exploration and exploitation during home range establishment, we conducted experimental trials comparing resource selection and space-use of translocated animals to those of reference individuals using reciprocal translocations between habitat types of differing quality. We selected wild pigs (Sus scrofa) as a model species to investigate hypotheses related to the movement behavior of translocated individuals because they are globally distributed large mammals that are often translocated within their introduced range to facilitate recreational hunting. Individuals translocated to higher quality habitat (i.e. higher proportions of bottomland hardwood habitats) exhibited smaller exploratory movements and began exploiting resources more quickly than those introduced to lower quality areas, although those in lower-quality areas demonstrated an increased rate of selection for preferred habitat as they gained knowledge of the landscape. Our data demonstrate that habitat quality mediates the spatial and temporal scale at which animals respond behaviorally to novel environments, and how these processes may determine the success of population establishment.

Abstract Patients with non-small cell lung cancer (NSCLC) who have distant metastases have a poor prognosis. To determine which genomic factors of the primary tumor are associated with metastasis, we analyzed data from 759 patients originally diagnosed with stage I–III NSCLC as part of the AACR Project GENIE Biopharma Collaborative consortium. We found that TP53 mutations were significantly associated with the development of new distant metastases. TP53 mutations were also more prevalent in patients with a history of smoking, suggesting that these patients may be at increased risk for distant metastasis. Our results suggest that additional investigation of the optimal management of patients with early-stage NSCLC harboring TP53 mutations at diagnosis is warranted in light of their higher likelihood of developing new distant metastases.

Abstract Improving maternal nutrition during pregnancy/lactation is a promising strategy to maximise the intestinal health of piglets undergoing abrupt weaning under commercial production conditions. This experiment investigated the effects of maternal supplementation of a casein hydrolysate and yeast β-glucan (CH-YBG) from day 83 of gestation until weaning (day 28) on sow faecal microbial populations and measures of piglet gastrointestinal health parameters at weaning. Sows (n = 10 sows/group) were assigned to: (1) control diet, and (2) control diet + CH-YBG. Maternal supplementation increased the abundance of the phylum Firmicutes, including members Lactobacillus in the sows faeces, with a concomitant increase in the caecal abundance of Lactobacillus in the weaned piglets compared to the controls. Piglets weaned from the supplemented sows had increased villus height in the duodenum (P

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Abstract Intestinal functions demonstrate circadian rhythms thought to be entrained, in part, by an organisms’ intrinsic feeding and fasting periods as well as by the intestinal microbiome. Circadian disruption as a result of ill-timed nutrient exposure and obesogenic feeding poses an increased risk to disease. As such, the aim of this study was to assess the relationships between dietary timing, composition, and the microbiome with regard to rhythmic small intestinal structure and mucosal immunity. Rodent chow (RC)-mice exhibited time-dependent increases in small intestinal weight, villus height, and crypt depth as well as an increased proportion of CD8αα+ cells and concomitant decrease in CD8αβ+ cells at the onset of the feeding period (p

Bone marrow mononuclear cell (BM-MNC) therapy in ST-elevation acute myocardial infarction (STEMI) has no biological inclusion criteria. Here, we analyzed 63 biomarkers and cytokines in baseline plasma samples from 77 STEMI patients treated with BM-MNCs in the TIME and Late-TIME trials as well as 61 STEMI patients treated with placebo. Response to cell therapy was defined by changes in left ventricular ejection fraction, systolic/diastolic volumes, and wall motion indexes. We investigated the clinical value of circulating proteins in outcome prediction using significance testing, partial least squares discriminant analysis, and receiver operating characteristic (ROC) analysis. Responders had higher biomarker levels (76-94% elevated) than non-responders. Several biomarkers had values that differed significantly (P 0.70 including interleukin 15. These biomarkers were not involved in the placebo-treated subjects suggesting that they may have predictive power. We conclude that plasma profiling after STEMI may help identify patients with a greater likelihood of response to cell-based treatment. Prospective trials are needed to assess the predictive value of the circulating biomarkers.