Contributions of bile acids to gastrointestinal physiology as receptor agonists and modifiers of ion channels

Bile acids (BAs) are known to be important regulators of intestinal motility and epithelial fluid and electrolyte transport. Over the past two decades, significant advances in identifying and characterizing the receptors, transporters, and ion channels targeted by BAs have led to exciting new insights into the molecular mechanisms involved in these processes. Our appreciation of BAs, their receptors, and BA-modulated ion channels as potential targets for the development of new approaches to treat intestinal motility and transport disorders is increasing. In the current review, we aim to summarize recent advances in our knowledge of the different BA receptors and BA-modulated ion channels present in the gastrointestinal system. We discuss how they regulate motility and epithelial transport, their roles in pathogenesis, and their therapeutic potential in a range of gastrointestinal diseases.

Attention Differentially Affects Acoustic and Phonetic Feature Encoding in a Multispeaker Environment

Humans have the remarkable ability to selectively focus on a single talker in the midst of other competing talkers. The neural mechanisms that underlie this phenomenon remain incompletely understood. In particular, there has been longstanding debate over whether attention operates at an early or late stage in the speech processing hierarchy. One way to better understand this is to examine how attention might differentially affect neurophysiological indices of hierarchical acoustic and linguistic speech representations. In this study, we do this by using encoding models to identify neural correlates of speech processing at various levels of representation. Specifically, we recorded EEG from fourteen human subjects (nine female and five male) during a "cocktail party" attention experiment. Model comparisons based on these data revealed phonetic feature processing for attended, but not unattended speech. Furthermore, we show that attention specifically enhances isolated indices of phonetic feature processing, but that such attention effects are not apparent for isolated measures of acoustic processing. These results provide new insights into the effects of attention on different prelexical representations of speech, insights that complement recent anatomic accounts of the hierarchical encoding of attended speech. Furthermore, our findings support the notion that, for attended speech, phonetic features are processed as a distinct stage, separate from the processing of the speech acoustics.SIGNIFICANCE STATEMENT Humans are very good at paying attention to one speaker in an environment with multiple speakers. However, the details of how attended and unattended speech are processed differently by the brain is not completely clear. Here, we explore how attention affects the processing of the acoustic sounds of speech as well as the mapping of those sounds onto categorical phonetic features. We find evidence of categorical phonetic feature processing for attended, but not unattended speech. Furthermore, we find evidence that categorical phonetic feature processing is enhanced by attention, but acoustic processing is not. These findings add an important new layer in our understanding of how the human brain solves the cocktail party problem.

Defining Swelling Kinetics in Block Copolymer Thin Films: The Critical Role of Temperature and Vapour Pressure Ramp

We studied the kinetics of swelling in high-χ lamellar-forming poly(styrene)-block- poly(lactic acid) (PS-b-PLA) block copolymer (BCP) by varying the heating rate and monitoring the solvent vapour pressure and the substrate temperature in situ during solvo-thermal vapour annealing (STVA) in an oven, and analysing the resulting morphology. Our results demonstrate that there is not only a solvent vapour pressure threshold (120 kPa), but also that the rate of reaching this pressure threshold has a significant effect on the microphase separation and the resulting morphologies. To study the heating rate effect, identical films were annealed in a tetrahydrofuran (THF) vapour environment under three different ramp regimes, low (rT<1 °C/min), medium (24 °C/min), for 60, 90 and 120 min, respectively, while the solvent vapour pressure and the substrate temperature were measured in real time. The translational order improved significantly with increasing the heating rate. The solvent mass uptake calculated for the different ramp regimes during annealing is linearly proportional to time, indicating that the swelling kinetics followed Case II diffusion. Two stages of the swelling behaviour were observed: (i) diffusion at the initial stages of swelling and (ii) stress relaxation, controlled at later stages. Films with a faster rate of increase in vapour pressure (rP>2 kPa/min) reached the pressure threshold value at an early stage of the swelling and attained a good phase separation. According to our results, highly ordered patterns are only obtained when the volume fraction of the solvent exceeds the polymer volume fraction, i.e., (φs≥φp), during the swelling process, and below this threshold value (φs=0.5), the films did not obtain a good structural order, even at longer annealing times.

Whole genome sequencing and in vitro splice assays reveal genetic causes for inherited retinal diseases

Inherited retinal diseases (IRDs) are a major cause of visual impairment. These clinically heterogeneous disorders are caused by pathogenic variants in more than 270 genes. As 30-40% of cases remain genetically unexplained following conventional genetic testing, we aimed to obtain a genetic diagnosis in an IRD cohort in which the genetic cause was not found using whole-exome sequencing or targeted capture sequencing. We performed whole-genome sequencing (WGS) to identify causative variants in 100 unresolved cases. After initial prioritization, we performed an in-depth interrogation of all noncoding and structural variants in genes when one candidate variant was detected. In addition, functional analysis of putative splice-altering variants was performed using in vitro splice assays. We identified the genetic cause of the disease in 24 patients. Causative coding variants were observed in genes such as ATXN7, CEP78, EYS, FAM161A, and HGSNAT. Gene disrupting structural variants were also detected in ATXN7, PRPF31, and RPGRIP1. In 14 monoallelic cases, we prioritized candidate noncanonical splice sites or deep-intronic variants that were predicted to disrupt the splicing process based on in silico analyses. Of these, seven cases were resolved as they carried pathogenic splice defects. WGS is a powerful tool to identify causative variants residing outside coding regions or heterozygous structural variants. This approach was most efficient in cases with a distinct clinical diagnosis. In addition, in vitro splice assays provide important evidence of the pathogenicity of rare variants.

ISGylation drives basal breast tumour progression by promoting EGFR recycling and Akt signalling

ISG15 is an ubiquitin-like modifier that is associated with reduced survival rates in breast cancer patients. The mechanism by which ISG15 achieves this however remains elusive. We demonstrate that modification of Rab GDP-Dissociation Inhibitor Beta (GDI2) by ISG15 (ISGylation) alters endocytic recycling of the EGF receptor (EGFR) in non-interferon stimulated cells using CRISPR-knock out models for ISGylation. By regulating EGFR trafficking, ISGylation enhances EGFR recycling and sustains Akt-signalling. We further show that Akt signalling positively correlates with levels of ISG15 and its E2-ligase in basal breast cancer cohorts, confirming the link between ISGylation and Akt signalling in human tumours. Persistent and enhanced Akt activation explains the more aggressive tumour behaviour observed in human breast cancers. We show that ISGylation can act as a driver of tumour progression rather than merely being a bystander.

SARS-CoV-2 Antibody Testing in Health Care Workers: A Comparison of the Clinical Performance of Three Commercially Available Antibody Assays

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies are an excellent indicator of past COVID-19 infection. As the COVID-19 pandemic progresses, retained sensitivity over time is an important quality in an antibody assay that is to be used for the purpose of population seroprevalence studies. We compared 5,788 health care worker (HCW) serum samples by using two serological assays (Abbott SARS-CoV-2 anti-nucleocapsid immunoglobulin G (IgG) and Roche anti-SARS-CoV-2 anti-nucleocapsid total antibody) and a subset of samples (all Abbott assay positive or grayzone, n = 485) on Wantai SARS-CoV-2 anti-spike antibody enzyme-linked immunosorbent assay (ELISA). For 367 samples from HCW with a previous PCR-confirmed SARS-CoV-2 infection, we correlated the timing of infection with assay results. Overall, seroprevalence was 4.2% on Abbott and 9.5% on Roche. Of those with previously confirmed infection, 41% (150/367) and 95% (348/367) tested positive on Abbott and Roche, respectively. At 21 weeks (150 days) after confirmed infection, positivity on Abbott started to decline. Roche positivity was retained for the entire study period (33 weeks). Factors associated (P ≤ 0.050) with Abbott seronegativity in those with previous PCR-confirmed infection included sex (odds ratio [OR], 0.30 male ; 95% confidence interval [CI], 0.15 to 0.60), symptom severity (OR 0.19 severe symptoms; 95% CI, 0.05 to 0.61), ethnicity (OR, 0.28 Asian ethnicity; 95% CI, 0.12 to 0.60), and time since PCR diagnosis (OR, 2.06 for infection 6 months previously; 95% CI, 1.01 to 4.30). Wantai detected all previously confirmed infections. In our population, Roche detected antibodies up to at least 7 months after natural infection with SARS-CoV-2. This finding indicates that the Roche total antibody assay is better suited than Abbott IgG assay to population-based studies. Wantai demonstrated high sensitivity, but sample selection was biased. The relationship between serological response and functional immunity to SARS-CoV-2 infection needs to be delineated. IMPORTANCE As the COVID-19 pandemic progresses, retained sensitivity over time is an important quality in an antibody assay that is to be used for the purpose of population seroprevalence studies. There is a relative paucity of published literature in this field to help guide public health specialists when planning seroprevalence studies. In this study, we compared results of 5,788 health care worker blood samples tested by using two assays (Roche and Elecsys, anti-nucleocapsid antibody) and by testing a subset on a third assay (Wantai enzyme-linked immunosorbent assay [ELISA] anti-spike antibody). We found significant differences in the performance of these assays, especially with distance in time from PCR-confirmed COVID-19 infection, and we feel these results may significantly impact the choice of assay for others conducting similar studies.

Scattering interference signature of a pair density wave state in the cuprate pseudogap phase

An unidentified quantum fluid designated the pseudogap (PG) phase is produced by electron-density depletion in the CuO2 antiferromagnetic insulator. Current theories suggest that the PG phase may be a pair density wave (PDW) state characterized by a spatially modulating density of electron pairs. Such a state should exhibit a periodically modulating energy gap [Formula: see text] in real-space, and a characteristic quasiparticle scattering interference (QPI) signature [Formula: see text] in wavevector space. By studying strongly underdoped Bi2Sr2CaDyCu2O8 at hole-density ~0.08 in the superconductive phase, we detect the 8a0-periodic [Formula: see text] modulations signifying a PDW coexisting with superconductivity. Then, by visualizing the temperature dependence of this electronic structure from the superconducting into the pseudogap phase, we find the evolution of the scattering interference signature [Formula: see text] that is predicted specifically for the temperature dependence of an 8a0-periodic PDW. These observations are consistent with theory for the transition from a PDW state coexisting with d-wave superconductivity to a pure PDW state in the Bi2Sr2CaDyCu2O8 pseudogap phase.

High resolution global spatiotemporal assessment of rooftop solar photovoltaics potential for renewable electricity generation

Rooftop solar photovoltaics currently account for 40% of the global solar photovoltaics installed capacity and one-fourth of the total renewable capacity additions in 2018. Yet, only limited information is available on its global potential and associated costs at a high spatiotemporal resolution. Here, we present a high-resolution global assessment of rooftop solar photovoltaics potential using big data, machine learning and geospatial analysis. We analyse 130 million km2 of global land surface area to demarcate 0.2 million km2 of rooftop area, which together represent 27 PWh yr-1 of electricity generation potential for costs between 40-280 $ MWh-1. Out of this, 10 PWh yr-1 can be realised below 100 $ MWh-1. The global potential is predominantly spread between Asia (47%), North America (20%) and Europe (13%). The cost of attaining the potential is lowest in India (66 $ MWh-1) and China (68 $ MWh-1), with USA (238 $ MWh-1) and UK (251 $ MWh-1) representing some of the costliest countries.

Lake Ohrid's tephrochronological dataset reveals 1.36 Ma of Mediterranean explosive volcanic activity

Tephrochronology relies on the availability of the stratigraphical, geochemical and geochronological datasets of volcanic deposits, three preconditions which are both often only fragmentary accessible. This study presents the tephrochronological dataset from the Lake Ohrid (Balkans) sediment succession continuously reaching back to 1.36 Ma. 57 tephra layers were investigated for their morphological appearance, geochemical fingerprint, and (chrono-)stratigraphic position. Glass fragments of tephra layers were analyzed for their major element composition using Energy-Dispersive-Spectroscopy and Wavelength-Dispersive Spectroscopy and for their trace element composition by Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry. Radiometric dated equivalents of 16 tephra layers and orbital tuning of geochemical proxy data provided the basis for the age-depth model of the Lake Ohrid sediment succession. The age-depth model, in turn, provides ages for unknown or undated tephra layers. This dataset forms the basis for a regional stratigraphic framework and provides insights into the central Mediterranean explosive volcanic activity during the last 1.36 Ma.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Chromatin remodeling due to degradation of citrate carrier impairs osteogenesis of aged mesenchymal stem cells

Aging is accompanied by a general decline in the function of many cellular pathways. However, whether these are causally or functionally interconnected remains elusive. Here, we study the effect of mitochondrial-nuclear communication on stem cell aging. We show that aged mesenchymal stem cells exhibit reduced chromatin accessibility and lower histone acetylation, particularly on promoters and enhancers of osteogenic genes. The reduced histone acetylation is due to impaired export of mitochondrial acetyl-CoA, owing to the lower levels of citrate carrier (CiC). We demonstrate that aged cells showed enhanced lysosomal degradation of CiC, which is mediated via mitochondrial-derived vesicles. Strikingly, restoring cytosolic acetyl-CoA levels either by exogenous CiC expression or via acetate supplementation, remodels the chromatin landscape and rescues the osteogenesis defects of aged mesenchymal stem cells. Collectively, our results establish a tight, age-dependent connection between mitochondrial quality control, chromatin and stem cell fate, which are linked together by CiC.

Transcriptional CDK inhibitors, CYC065 and THZ1 promote Bim-dependent apoptosis in primary and recurrent GBM through cell cycle arrest and Mcl-1 downregulation

Activation of cyclin-dependent kinases (CDKs) contributes to the uncontrolled proliferation of tumour cells. Genomic alterations that lead to the constitutive activation or overexpression of CDKs can support tumourigenesis including glioblastoma (GBM), the most common and aggressive primary brain tumour in adults. The incurability of GBM highlights the need to discover novel and more effective treatment options. Since CDKs 2, 7 and 9 were found to be overexpressed in GBM, we tested the therapeutic efficacy of two CDK inhibitors (CKIs) (CYC065 and THZ1) in a heterogeneous panel of GBM patient-derived cell lines (PDCLs) cultured as gliomaspheres, as preclinically relevant models. CYC065 and THZ1 treatments suppressed invasion and induced viability loss in the majority of gliomaspheres, irrespective of the mutational background of the GBM cases, but spared primary cortical neurons. Viability loss arose from G2/M cell cycle arrest following treatment and subsequent induction of apoptotic cell death. Treatment efficacies and treatment durations required to induce cell death were associated with proliferation velocities, and apoptosis induction correlated with complete abolishment of Mcl-1 expression, a cell cycle-regulated antiapoptotic Bcl-2 family member. GBM models generally appeared highly dependent on Mcl-1 expression for cell survival, as demonstrated by pharmacological Mcl-1 inhibition or depletion of Mcl-1 expression. Further analyses identified CKI-induced Mcl-1 loss as a prerequisite to establish conditions at which the BH3-only protein Bim can efficiently induce apoptosis, with cellular Bim amounts strongly correlating with treatment efficacy. CKIs reduced proliferation and promoted apoptosis also in chick embryo xenograft models of primary and recurrent GBM. Collectively, these studies highlight the potential of these novel CKIs to suppress growth and induce cell death of patient-derived GBM cultures in vitro and in vivo, warranting further clinical investigation.

Microbiota from young mice counteracts selective age-associated behavioral deficits

The gut microbiota is increasingly recognized as an important regulator of host immunity and brain health. The aging process yields dramatic alterations in the microbiota, which is linked to poorer health and frailty in elderly populations. However, there is limited evidence for a mechanistic role of the gut microbiota in brain health and neuroimmunity during aging processes. Therefore, we conducted fecal microbiota transplantation from either young (3-4 months) or old (19-20 months) donor mice into aged recipient mice (19-20 months). Transplant of a microbiota from young donors reversed aging-associated differences in peripheral and brain immunity, as well as the hippocampal metabolome and transcriptome of aging recipient mice. Finally, the young donor-derived microbiota attenuated selective age-associated impairments in cognitive behavior when transplanted into an aged host. Our results reveal that the microbiome may be a suitable therapeutic target to promote healthy aging.

Squaramide-Based Self-Associating Amphiphiles for Anion Recognition

The synthesis and characterisation of two novel self-assembled amphiphiles (SSAs) SQS-1 and SQS-2 are reported. Both compounds, based on the squaramide motif, were fully soluble in a range of solvents and were shown to undergo self-assembly through a range of physical techniques. Self-assembly was shown to favour the formation of crystalline domains on the nanoscale but also fibrillar film formation, as suggested by SEM analysis. Moreover, both SQS-1 and SQS-2 were capable of anion recognition in DMSO solution as demonstrated using 1 H NMR and UV/Vis absorption spectroscopy, but displayed lower binding affinities for various anions when compared against other squaramide based receptors. In more competitive solvent mixtures SQS-1 gave rise to a colourimetric response in the presence of HPO42- that was clearly visible to the naked eye. We anticipate that the observed response is due to the basic nature of the HPO42- anion when compared against other biologically relevant anions.

Structural basis of the membrane intramolecular transacylase reaction responsible for lyso-form lipoprotein synthesis

Lipoproteins serve diverse functions in the bacterial cell and some are essential for survival. Some lipoproteins are adjuvants eliciting responses from the innate immune system of the host. The growing list of membrane enzymes responsible for lipoprotein synthesis includes the recently discovered lipoprotein intramolecular transacylase, Lit. Lit creates a lipoprotein that is less immunogenic, possibly enabling the bacteria to gain a foothold in the host by stealth. Here, we report the crystal structure of the Lit enzyme from Bacillus cereus and describe its mechanism of action. Lit consists of four transmembrane helices with an extracellular cap. Conserved residues map to the cap-membrane interface. They include two catalytic histidines that function to effect unimolecular transacylation. The reaction involves acyl transfer from the sn-2 position of the glyceryl moiety to the amino group on the N-terminal cysteine of the substrate via an 8-membered ring intermediate. Transacylation takes place in a confined aromatic residue-rich environment that likely evolved to bring distant moieties on the substrate into proximity and proper orientation for catalysis.

METAnnotatorX2: a Comprehensive Tool for Deep and Shallow Metagenomic Data Set Analyses

The use of bioinformatic tools for read-based taxonomic and functional analyses of metagenomic data sets, including their assembly and management, is rather fragmentary due to the absence of an accepted gold standard. Moreover, most currently available software tools need input of millions of reads and rely on approximations in data analysis in order to reduce computing times. These issues result in suboptimal results in terms of accuracy, sensitivity, and specificity when used either for the reconstruction of taxonomic or functional profiles through read analysis or analysis of genomes reconstructed by metagenomic assembly. Moreover, the recent introduction of novel DNA sequencing technologies that generate long reads, such as Nanopore and PacBio, represent a valuable data resource that still suffers from a lack of dedicated tools to perform integrated hybrid analysis alongside short read data. In order to overcome these limitations, here we describe a comprehensive bioinformatic platform, METAnnotatorX2, aimed at providing an optimized user-friendly resource which maximizes output quality, while also allowing user-specific adaptation of the pipeline and straightforward integrated analysis of both short and long read data. To further improve performance quality and accuracy of taxonomic assignment of reads and contigs, custom preprocessed and taxonomically revised genomic databases for viruses, prokaryotes, and various eukaryotes were developed. The performance of METAnnotatorX2 was tested by analysis of artificial data sets encompassing viral, archaeal, bacterial, and eukaryotic (fungal) sequence reads that simulate different biological matrices. Moreover, real biological samples were employed to validate in silico results. IMPORTANCE We developed a novel tool, i.e., METAnnotatorX2, that includes a number of new advanced features for analysis of deep and shallow metagenomic data sets and is accompanied by (regularly updated) customized databases for archaea, bacteria, fungi, protists, and viruses. Both software and databases were developed so as to maximize sensitivity and specificity while including support for shallow metagenomic data sets. Through extensive tests performed on Illumina and Nanopore artificial data sets, we demonstrated the high performance of the software to not only extract taxonomic and functional information from sequence reads but also to assemble and process genomes from metagenomic data. The robustness of these functionalities was validated using "real-life" data sets obtained from Illumina and Nanopore sequencing of biological samples. Furthermore, the performance of METAnnotatorX2 was compared to other available software tools for analysis of shotgun metagenomics data.

Methods for latent image simulations in photolithography with a polychromatic light attenuation equation for fabricating VIAs in 2.5D and 3D advanced packaging architectures

As demand accelerates for multifunctional devices with a small footprint and minimal power consumption, 2.5D and 3D advanced packaging architectures have emerged as an essential solution that use through-substrate vias (TSVs) as vertical interconnects. Vertical stacking enables chip packages with increased functionality, enhanced design versatility, minimal power loss, reduced footprint and high bandwidth. Unlocking the potential of photolithography for vertical interconnect access (VIA) fabrication requires fast and accurate predictive modeling of diffraction effects and resist film photochemistry. This procedure is especially challenging for broad-spectrum exposure systems that use, for example, Hg bulbs with g-, h-, and i-line UV radiation. In this paper, we present new methods and equations for VIA latent image determination in photolithography that are suitable for broad-spectrum exposure and negate the need for complex and time-consuming in situ metrology. Our technique is accurate, converges quickly on the average modern PC and could be readily integrated into photolithography simulation software. We derive a polychromatic light attenuation equation from the Beer-Lambert law, which can be used in a critical exposure dose model to determine the photochemical reaction state. We integrate this equation with an exact scalar diffraction formula to produce a succinct equation comprising a complete coupling between light propagation phenomena and photochemical behavior. We then perform a comparative study between 2D/3D photoresist latent image simulation geometries and directly corresponding experimental data, which demonstrates a highly positive correlation. We anticipate that this technique will be a valuable asset to photolithography, micro- and nano-optical systems and advanced packaging/system integration with applications in technology domains ranging from space to automotive to the Internet of Things (IoT).

Transcriptional CDK Inhibitors CYC065 and THZ1 Induce Apoptosis in Glioma Stem Cells Derived from Recurrent GBM

Glioma stem cells (GSCs) are tumour initiating cells which contribute to treatment resistance, temozolomide (TMZ) chemotherapy and radiotherapy, in glioblastoma (GBM), the most aggressive adult brain tumour. A major contributor to the uncontrolled tumour cell proliferation in GBM is the hyper activation of cyclin-dependent kinases (CDKs). Due to resistance to standard of care, GBMs relapse in almost all patients. Targeting GSCs using transcriptional CDK inhibitors, CYC065 and THZ1 is a potential novel treatment to prevent relapse of the tumour. TCGA-GBM data analysis has shown that the GSC markers, CD133 and CD44 were significantly upregulated in GBM patient tumours compared to non-tumour tissue. CD133 and CD44 stem cell markers were also expressed in gliomaspheres derived from recurrent GBM tumours. Light Sheet Florescence Microscopy (LSFM) further revealed heterogeneous expression of these GSC markers in gliomaspheres. Gliomaspheres from recurrent tumours were highly sensitive to transcriptional CDK inhibitors, CYC065 and THZ1 and underwent apoptosis while being resistant to TMZ. Apoptotic cell death in GSC subpopulations and non-stem tumour cells resulted in sphere disruption. Collectively, our study highlights the potential of these novel CKIs to induce cell death in GSCs from recurrent tumours, warranting further clinical investigation.

A postbiotic consisting of heat-treated lactobacilli has a bifidogenic effect in pure culture and in human fermented faecal communities

The gut microbiota has a significant impact on host health. Dietary interventions using probiotics, prebiotics and postbiotics have the potential to alter microbiota composition and function. Other therapeutic interventions such as antibiotics and faecal microbiota transplantation have also been shown to significantly alter the microbiota and its metabolites. Supplementation of a faecal fermentation model of the human gut with a postbiotic product Lactobacillus LB led to changes in microbiome composition (i.e. increase in beneficial bifidobacteria) and associated metabolic changes (i.e. increased acid production). Lactobacillus LB is a heat-treated preparation of cellular biomass and a fermentate generated by Limosilactobacillus fermentum CNCM MA65/4E-1b (formerly known as Lactobacillus fermentum CNCM MA65/4E-1b) and Lactobacillus delbrueckii ssp. delbrueckii CNCM MA65/4E-2z, medically relevant strains used to produce antidiarrheal preparations. In pure culture, Lactobacillus LB also stimulates the growth of a range of bifidobacterial species and strains. Lactobacillus LB-like preparations generated using other Lactobacillaceae, including commercially available probiotic bacteria, did not have the same impact on a model strain (Bifidobacterium longum subsp. infantis ATCC 15697). This bifidogenic activity is heat- and enzyme-stable and cannot be attributed to lactose, which is a major constituent of Lactobacillus LB. L fermentum CNCM MA65/4E-1b is largely responsible for the observed activity and there is a clear role for compounds smaller than 1 kDa.Importance In general, disruptions to the gut microbiota are associated with multiple disorders in humans. The presence of high levels of Bifidobacterium spp. in the human gut is commonly considered to be beneficial. Bifidobacteria can be supplemented in the diet (as probiotics) or those bifidobacteria already present in the gut can be stimulated by the consumption of prebiotics such as inulin. We demonstrate that Lactobacillus LB (a product consisting of two heat-killed lactic acid bacteria and their metabolites) can stimulate the growth of bifidobacteria in human fermented faecal communities and in pure culture. Given the heat-treatment applied during the production process, there is no risk of the lactic acid bacteria colonising (or causing bacteraemia) in vulnerable consumers (infants, immunocompromised, etc). Lactobacillus LB has the potential to affect human health by selectively promoting the growth of beneficial bacteria.

Bioactive potential of natural biomaterials: identification, retention and assessment of biological properties

Biomaterials have had an increasingly important role in recent decades, in biomedical device design and the development of tissue engineering solutions for cell delivery, drug delivery, device integration, tissue replacement, and more. There is an increasing trend in tissue engineering to use natural substrates, such as macromolecules native to plants and animals to improve the biocompatibility and biodegradability of delivered materials. At the same time, these materials have favourable mechanical properties and often considered to be biologically inert. More importantly, these macromolecules possess innate functions and properties due to their unique chemical composition and structure, which increase their bioactivity and therapeutic potential in a wide range of applications. While much focus has been on integrating these materials into these devices via a spectrum of cross-linking mechanisms, little attention is drawn to residual bioactivity that is often hampered during isolation, purification, and production processes. Herein, we discuss methods of initial material characterisation to determine innate bioactivity, means of material processing including cross-linking, decellularisation, and purification techniques and finally, a biological assessment of retained bioactivity of a final product. This review aims to address considerations for biomaterials design from natural polymers, through the optimisation and preservation of bioactive components that maximise the inherent bioactive potency of the substrate to promote tissue regeneration.

Investigating response time and accuracy in online classifier learning for multimedia publish-subscribe systems

The enormous growth of multimedia content in the field of the Internet of Things (IoT) leads to the challenge of processing multimedia streams in real-time. Event-based systems are constructed to process event streams. They cannot natively consume multimedia event types produced by the Internet of Multimedia Things (IoMT) generated data to answer multimedia-based user subscriptions. Machine learning-based techniques have enabled rapid progress in solving real-world problems and need to be optimised for the low response time of the multimedia event processing paradigm. In this paper, we describe a classifier construction approach for the training of online classifiers, that can handle dynamic subscriptions with low response time and provide reasonable accuracy for the multimedia event processing. We find that the current object detection methods can be configured dynamically for the construction of classifiers in real-time, by tuning hyperparameters even when training from scratch. Our experiments demonstrate that deep neural network-based object detection models, with hyperparameter tuning, can improve the performance within less training time for the answering of previously unknown user subscriptions. The results from this study show that the proposed online classifier training based model can achieve accuracy of 79.00% with 15-min of training and 84.28% with 1-hour training from scratch on a single GPU for the processing of multimedia events.

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Associations between Neurocardiovascular Signal Entropy and Physical Frailty

In this cross-sectional study, the relationship between noninvasively measured neurocardiovascular signal entropy and physical frailty was explored in a sample of community-dwelling older adults from The Irish Longitudinal Study on Ageing (TILDA). The hypothesis under investigation was that dysfunction in the neurovascular and cardiovascular systems, as quantified by short-length signal complexity during a lying-to-stand test (active stand), could provide a marker for frailty. Frailty status (i.e., "non-frail", "pre-frail", and "frail") was based on Fried's criteria (i.e., exhaustion, unexplained weight loss, weakness, slowness, and low physical activity). Approximate entropy (ApEn) and sample entropy (SampEn) were calculated during resting (lying down), active standing, and recovery phases. There was continuously measured blood pressure/heart rate data from 2645 individuals (53.0% female) and frontal lobe tissue oxygenation data from 2225 participants (52.3% female); both samples had a mean (SD) age of 64.3 (7.7) years. Results revealed statistically significant associations between neurocardiovascular signal entropy and frailty status. Entropy differences between non-frail and pre-frail/frail were greater during resting state compared with standing and recovery phases. Compared with ApEn, SampEn seemed to have better discriminating power between non-frail and pre-frail/frail individuals. The quantification of entropy in short length neurocardiovascular signals could provide a clinically useful marker of the multiple physiological dysregulations that underlie physical frailty.

Investigating the Role of Diet and Exercise in Gut Microbe-Host Cometabolism

We investigated the individual and combined effects of diet and physical exercise on metabolism and the gut microbiome to establish how these lifestyle factors influence host-microbiome cometabolism. Urinary and fecal samples were collected from athletes and less active controls. Individuals were further classified according to an objective dietary assessment score of adherence to healthy dietary habits according to WHO guidelines, calculated from their proton nuclear magnetic resonance (1H-NMR) urinary profiles. Subsequent models were generated comparing extremes of dietary habits, exercise, and the combined effect of both. Differences in metabolic phenotypes and gut microbiome profiles between the two groups were assessed. Each of the models pertaining to diet healthiness, physical exercise, or a combination of both displayed a metabolic and functional microbial signature, with a significant proportion of the metabolites identified as discriminating between the various pairwise comparisons resulting from gut microbe-host cometabolism. Microbial diversity was associated with a combination of high adherence to healthy dietary habits and exercise and was correlated with a distinct array of microbially derived metabolites, including markers of proteolytic activity. Improved control of dietary confounders, through the use of an objective dietary assessment score, has uncovered further insights into the complex, multifactorial relationship between diet, exercise, the gut microbiome, and metabolism. Furthermore, the observation of higher proteolytic activity associated with higher microbial diversity indicates that increased microbial diversity may confer deleterious as well as beneficial effects on the host.IMPORTANCE Improved control of dietary confounders, through the use of an objective dietary assessment score, has uncovered further insights into the complex, multifactorial relationship between diet, exercise, the gut microbiome, and metabolism. Each of the models pertaining to diet healthiness, physical exercise, or a combination of both, displayed a distinct metabolic and functional microbial signature. A significant proportion of the metabolites identified as discriminating between the various pairwise comparisons result from gut microbe-host cometabolism, and the identified interactions have expanded current knowledge in this area. Furthermore, although increased microbial diversity has previously been linked with health, our observation of higher microbial diversity being associated with increased proteolytic activity indicates that it may confer deleterious as well as beneficial effects on the host.

Fermented-Food Metagenomics Reveals Substrate-Associated Differences in Taxonomy and Health-Associated and Antibiotic Resistance Determinants

Fermented foods have been the focus of ever greater interest as a consequence of purported health benefits. Indeed, it has been suggested that consumption of these foods helps to address the negative consequences of "industrialization" of the human gut microbiota in Western society. However, as the mechanisms via which the microbes in fermented foods improve health are not understood, it is necessary to develop an understanding of the composition and functionality of the fermented-food microbiota to better harness desirable traits. Here, we considerably expand the understanding of fermented-food microbiomes by employing shotgun metagenomic sequencing to provide a comprehensive insight into the microbial composition, diversity, and functional potential (including antimicrobial resistance and carbohydrate-degrading and health-associated gene content) of a diverse range of 58 fermented foods from artisanal producers from a number of countries. Food type, i.e., dairy-, sugar-, or brine-type fermented foods, was the primary driver of microbial composition, with dairy foods found to have the lowest microbial diversity. From the combined data set, 127 high-quality metagenome-assembled genomes (MAGs), including 10 MAGs representing putatively novel species of Acetobacter, Acidisphaera, Gluconobacter, Companilactobacillus, Leuconostoc, and Rouxiella, were generated. Potential health promoting attributes were more common in fermented foods than nonfermented equivalents, with water kefirs, sauerkrauts, and kvasses containing the greatest numbers of potentially health-associated gene clusters. Ultimately, this study provides the most comprehensive insight into the microbiomes of fermented foods to date and yields novel information regarding their relative health-promoting potential.IMPORTANCE Fermented foods are regaining popularity worldwide due in part to a greater appreciation of the health benefits of these foods and the associated microorganisms. Here, we use state-of-the-art approaches to explore the microbiomes of 58 of these foods, identifying the factors that drive the microbial composition of these foods and potential functional benefits associated with these populations. Food type, i.e., dairy-, sugar-, or brine-type fermented foods, was the primary driver of microbial composition, with dairy foods found to have the lowest microbial diversity and, notably, potential health promoting attributes were more common in fermented foods than nonfermented equivalents. The information provided here will provide significant opportunities for the further optimization of fermented-food production and the harnessing of their health-promoting potential.