U1 snRNP regulates cancer cell migration and invasion in vitro

Housekeeping U1 snRNA facilitates antiviral innate immunity by promoting TRIM25-mediated RIG-I activation

U1 small nuclear RNA (snRNA) is an abundant and evolutionarily conserved 164-nucleotide RNA species that functions in pre-mRNA splicing, and it is considered to be a housekeeping non-coding RNA. However, the role of U1 snRNA in regulating host antiviral immunity remains largely unexplored. Here, we find that RNVU1-18, a U1 pseudogene, is significantly upregulated in the host infected with RNA viruses, including influenza and respiratory syncytial virus. Overexpression of U1 snRNA protects cells against RNA viruses, while knockdown of U1 snRNA leads to more viral burden in vitro and in vivo. Knockout of RNVU1-18 is sufficient to impair the type I interferon-dependent antiviral innate immunity. U1 snRNA is required to fully activate the retinoic acid-inducible gene I (RIG-I)-dependent antiviral signaling, since it interacts with tripartite motif 25 (TRIM25) and enhances the RIG-I-TRIM25 interaction to trigger K63-linked ubiquitination of RIG-I. Our study reveals the important role of housekeeping U1 snRNA in regulating host antiviral innate immunity and restricting RNA virus infection.

Finely tuned water structure and transport in functionalized carbon nanotube membranes during desalination

Molecular dynamics simulations were performed to tune the transport of water molecules in nanostructured membrane in a desalination process. Four armchair-type (7,7), (8,8), (9,9) and (10,10) carbon nanotubes (CNTs) with pore diameters around 1 nm were chosen, their interior surfaces were modified with -OH, -CH3 and -F groups. Simulation results show that water transport in nanochannel depends on confined water structures which could be regulated by precisely controlled channel diameter and chemical functionalization. Increasing CNT diameter changes water structures from single-file-like to be square and hexagonal-like, then into a disordered pattern, resulting in a concave-shaped trend of water permeance. The -OH functional groups promote structural ordering of water molecules in (7,7) CNT, but disrupt water structures in (8,8) and (9,9) CNTs, and reduce the order degree of water molecules in (10,10) CNT, moreover, exert an attraction to enhance surface friction inside channel. The -CH3 groups induce more strictly single-file movement of water molecules in (7,7) CNT, turning water structures in (8,8) and (9,9) CNTs into two and triangular column arrangements, improving water transport, however, causing again square-like water structure in (10,10) CNT. Fluorinations of CNT make water structure more disordered in (7,7), (9,9) and (10,10) CNTs, while enhance the square water structure in (8,8) CNT with a lower water permeance. Through changing channel diameter and functionalization, the low tetrahedral order corresponds to a more single-file-like water structure, associated with rapid water diffusion and high permeability; an increase in tetrahedrality results in more ice-like water structures, lower water diffusion coefficients, and permeability. The results of this study demonstrate that water transport could be finely regulated via a functionalized CNT membrane.

Transcriptionally active chromatin loops contain both 'active' and 'inactive' histone modifications that exhibit exclusivity at the level of nucleosome clusters

Chromatin state is thought to impart regulatory function to the underlying DNA sequence. This can be established through histone modifications and chromatin organisation, but exactly how these factors relate to one another to regulate gene expression is unclear. In this study, we have used super-resolution microscopy to image the Y loops of Drosophila melanogaster primary spermatocytes, which are enormous transcriptionally active chromatin fibres, each representing single transcription units that are individually resolvable in the nuclear interior. We previously found that the Y loops consist of regular clusters of nucleosomes, with an estimated median of 54 nucleosomes per cluster with wide variation.In this study, we report that the histone modifications H3K4me3, H3K27me3, and H3K36me3 are also clustered along the Y loops, with H3K4me3 more associated with diffuse chromatin compared to H3K27me3. These histone modifications form domains that can be stretches of Y loop chromatin micrometres long, or can be in short alternating domains. The different histone modifications are associated with different sizes of chromatin clusters and unique morphologies. Strikingly, a single chromatin cluster almost always only contains only one type of the histone modifications that were labelled, suggesting exclusivity, and therefore regulation at the level of individual chromatin clusters. The active mark H3K36me3 is more associated with actively elongating RNA polymerase II than H3K27me3, with polymerase often appearing on what are assumed to be looping regions on the periphery of chromatin clusters.These results provide a foundation for understanding the relationship between chromatin state, chromatin organisation, and transcription regulation - with potential implications for pause-release dynamics, splicing complex organisation and chromatin dynamics during polymerase progression along a gene.

Multi-omic integration of microbiome data for identifying disease-associated modules

Multi-omic studies of the human gut microbiome are crucial for understanding its role in disease across multiple functional layers. Nevertheless, integrating and analyzing such complex datasets poses significant challenges. Most notably, current analysis methods often yield extensive lists of disease-associated features (e.g., species, pathways, or metabolites), without capturing the multi-layered structure of the data. Here, we address this challenge by introducing "MintTea", an intermediate integration-based approach combining canonical correlation analysis extensions, consensus analysis, and an evaluation protocol. MintTea identifies "disease-associated multi-omic modules", comprising features from multiple omics that shift in concord and that collectively associate with the disease. Applied to diverse cohorts, MintTea captures modules with high predictive power, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome study, MintTea identifies a module with serum glutamate- and TCA cycle-related metabolites, along with bacterial species linked to insulin resistance. In another dataset, MintTea identifies a module associated with late-stage colorectal cancer, including Peptostreptococcus and Gemella species and fecal amino acids, in line with these species' metabolic activity and their coordinated gradual increase with cancer development. This work demonstrates the potential of advanced integration methods in generating systems-level, multifaceted hypotheses underlying microbiome-disease interactions.

Multifunctional Block Copolymers, Acting as Recycling Aids, by Atom Transfer Radical Polymerization

Block copolymers utilizing oligomeric poly(pentylene-co-hexylene carbonate)diol modified with 2,4-diisocyanatotoluene and further with 2-bromo-N-(3-hydroxypropyl)-2-methylpropanamide were synthesized and utilized as Activators ReGenerated by Electron Transfer Atom Transfer Radical Polymerization macroinitiators to obtain a first generation of multifunctional recycling additives with poly(glycidyl methacrylate-co-butyl methacrylate-co-methyl methacrylate) side chains, which could act as chain extenders. Then, chosen additive was reacted with a radical scavenger, 3,5-ditertbutyl-4-hydroxybenzoic acid (DHBA), to obtain a second generation of reactive additives. Those copolymers had different numbers of epoxy groups per polymer chain, and different number of epoxides opened with DHBA, hence showed a range of properties, and were utilized as reactive modifiers for polylactide (PLA) extrusion melting. The first-generation modifiers caused an increase in PLA's blends relative melt viscosity, stabilized material properties, and enhanced impact strength, while the second-generation modifiers with more than 8 % of epoxide ring opened showed worse properties. However, they managed to suppress the UV degradation of PLA blend plates.

Variational Tensor Wave Functions for the Interacting Quantum Spin Hall Phase

The quantum spin hall (QSH) phase, also known as the 2D topological insulator, is characterized by protected helical edge modes arising from time reversal symmetry. While initially proposed as band insulators, this phase can also manifest in strongly correlated systems where conventional band theory fails. To overcome the challenge of simulating this phase in realistic correlated models, we propose a novel framework utilizing fermionic tensor network states. Our approach involves constructing a tensor representation of the fixed-point wave function based on an exact solvable model, enabling us to derive a set of tensor equations governing the transformation rules of local tensors under symmetry operations. These tensor equations lead to the anomalous edge theory, which provides a comprehensive description of the QSH phase. By solving these tensor equations, we obtain variational ansatz for the QSH phase, which we subsequently verify its topological properties through numerical calculations. This method serves as an initial step toward employing tensor algorithms to simulate the QSH phase in strongly correlated systems, opening new avenues for investigating and understanding topological phenomena in complex materials.

Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks

Computational neuroscience studies have shown that the structure of neural variability to an unchanged stimulus affects the amount of information encoded. Some artificial deep neural networks, such as those with Monte Carlo dropout layers, also have variable responses when the input is fixed. However, the structure of the trial-by-trial neural covariance in neural networks with dropout has not been studied, and its role in decoding accuracy is unknown. We studied the above questions in a convolutional neural network model with dropout in both the training and testing phases. We found that trial-by-trial correlation between neurons (i.e., noise correlation) is positive and low dimensional. Neurons that are close in a feature map have larger noise correlation. These properties are surprisingly similar to the findings in the visual cortex. We further analyzed the alignment of the main axes of the covariance matrix. We found that different images share a common trial-by-trial noise covariance subspace, and they are aligned with the global signal covariance. This evidence that the noise covariance is aligned with signal covariance suggests that noise covariance in dropout neural networks reduces network accuracy, which we further verified directly with a trial-shuffling procedure commonly used in neuroscience. These findings highlight a previously overlooked aspect of dropout layers that can affect network performance. Such dropout networks could also potentially be a computational model of neural variability.

Tumor-infiltrating CD8+ sub-populations in primary and recurrent glioblastoma: An in-silico study

Background

Glioblastoma multiforme (GBM) remains an incurable primary brain tumor. CD8+ tumor-infiltrating lymphocytes (TILs) can target malignant cells; however, their anti-tumoral immune responses mostly do not lead to GBM rejection in GBM patients. We profiled the sub-populations of tumor-infiltrating CD8+ T-cells, i.e., naïve, cytotoxic, and exhausted cells, in primary and recurrent GBM tissues and provided a blueprint for future precision-based GBM immunotherapy.

Method

We re-analyzed the raw data of single-cell RNA sequencing on the cells residing in the GBM microenvironment and leveraged tumor bulk RNA analyses to study the significance of CD8+ TILs sub-populations in primary and recurrent GBM. We investigated cell-cell interaction between exhausted CD8+ TILs and other immune cells residing in the primary and recurrent GBM microenvironments and profiled the expression changes following CD8+ TILs' transition from primary GBM to recurrent GBM.

Results

Exhausted CD8+ TILs are the majority of CD8+ TILs sub-populations in primary and recurrent GBM, and cytotoxic CD8+ TILs display decreased expression of inhibitory immune checkpoint (IC) molecules in the primary and recurrent GBM. In the primary and recurrent GBM microenvironment, exhausted CD8+ TILs interact most with tumor-infiltrating dendritic cells.

Conclusion

This study demonstrates the profiles of CD8+ TILs sub-populations in primary and recurrent GBM and provides a proof-of-concept for future precision-based GBM immunotherapy.

eSVD-DE: cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings

BACKGROUND

Single-cell RNA-sequencing (scRNA) datasets are becoming increasingly popular in clinical and cohort studies, but there is a lack of methods to investigate differentially expressed (DE) genes among such datasets with numerous individuals. While numerous methods exist to find DE genes for scRNA data from limited individuals, differential-expression testing for large cohorts of case and control individuals using scRNA data poses unique challenges due to substantial effects of human variation, i.e., individual-level confounding covariates that are difficult to account for in the presence of sparsely-observed genes.

RESULTS

We develop the eSVD-DE, a matrix factorization that pools information across genes and removes confounding covariate effects, followed by a novel two-sample test in mean expression between case and control individuals. In general, differential testing after dimension reduction yields an inflation of Type-1 errors. However, we overcome this by testing for differences between the case and control individuals' posterior mean distributions via a hierarchical model. In previously published datasets of various biological systems, eSVD-DE has more accuracy and power compared to other DE methods typically repurposed for analyzing cohort-wide differential expression.

CONCLUSIONS

eSVD-DE proposes a novel and powerful way to test for DE genes among cohorts after performing a dimension reduction. Accurate identification of differential expression on the individual level, instead of the cell level, is important for linking scRNA-seq studies to our understanding of the human population.

The phenomenology of pareidolia in healthy subjects and patients with left- or right-hemispheric stroke

Pareidolia are perceptions of recognizable images or meaningful patterns where none exist. In recent years, this phenomenon has been increasingly studied in healthy subjects and patients with neurological or psychiatric diseases. The current study examined pareidolia production in a group of 53 stroke patients and 82 neurologically healthy controls who performed a natural images task. We found a significant reduction of absolute pareidolia production in left- and right-hemispheric stroke patients, with right-hemispheric patients producing overall fewest pareidolic output. Responses were categorized into 28 distinct categories, with 'Animal', 'Human', 'Face', and 'Body parts' being the most common, accounting for 72% of all pareidolia. Regarding the percentages of the different categories of pareidolia, we found a significant reduction for the percentage of "Body parts" pareidolia in the left-hemispheric patient group as compared to the control group, while the percentage of this pareidolia type was not significantly reduced in right-hemispheric patients compared to healthy controls. These results support the hypothesis that pareidolia production may be influenced by local-global visual processing with the left hemisphere being involved in local and detailed analytical visual processing to a greater extent. As such, a lesion to the right hemisphere, that is believed to be critical for global visual processing, might explain the overall fewest pareidolic output produced by the right-hemispheric patients.

Toll/interleukin-1 receptor (TIR) domain-containing proteins have NAD-RNA decapping activity

The occurrence of NAD+ as a non-canonical RNA cap has been demonstrated in diverse organisms. TIR domain-containing proteins present in all kingdoms of life act in defense responses and can have NADase activity that hydrolyzes NAD+. Here, we show that TIR domain-containing proteins from several bacterial and one archaeal species can remove the NAM moiety from NAD-capped RNAs (NAD-RNAs). We demonstrate that the deNAMing activity of AbTir (from Acinetobacter baumannii) on NAD-RNA specifically produces a cyclic ADPR-RNA, which can be further decapped in vitro by known decapping enzymes. Heterologous expression of the wild-type but not a catalytic mutant AbTir in E. coli suppressed cell propagation and reduced the levels of NAD-RNAs from a subset of genes before cellular NAD+ levels are impacted. Collectively, the in vitro and in vivo analyses demonstrate that TIR domain-containing proteins can function as a deNAMing enzyme of NAD-RNAs, raising the possibility of TIR domain proteins acting in gene expression regulation.

KIO3-catalyzed selective oxidation of thiols to disulfides in water under ambient conditions

Herein, we report a KIO3-catalyzed oxidative coupling of thiols to their corresponding disulfides in water, in a short time and at ambient temperature. The reaction has a broad scope and exhibits good functional group tolerance, resulting in the desired products in excellent yields. This approach allows the reuse of the reaction system in multiple cycles and scale-up. Furthermore, the current protocol demonstrates compatibility for in situ generation of disulfides and post application in C(sp2)-H bond sulfenylation.

Nanobubble-actuated ultrasound neuromodulation for selectively shaping behavior in mice

Ultrasound is an acoustic wave which can noninvasively penetrate the skull to deep brain regions, enabling neuromodulation. However, conventional ultrasound's spatial resolution is diffraction-limited and low-precision. Here, we report acoustic nanobubble-mediated ultrasound stimulation capable of localizing ultrasound's effects to only the desired brain region in male mice. By varying the delivery site of nanobubbles, ultrasound could activate specific regions of the mouse motor cortex, evoking EMG signaling and limb movement, and could also, separately, activate one of two nearby deep brain regions to elicit distinct behaviors (freezing or rotation). Sonicated neurons displayed reversible, low-latency calcium responses and increased c-Fos expression in the sub-millimeter-scale region with nanobubbles present. Ultrasound stimulation of the relevant region also modified depression-like behavior in a mouse model. We also provide evidence of a role for mechanosensitive ion channels. Altogether, our treatment scheme allows spatially-targetable, repeatable and temporally-precise activation of deep brain circuits for neuromodulation without needing genetic modification.

Cortical Zinc Signaling Is Necessary for Changes in Mouse Pupil Diameter That Are Evoked by Background Sounds with Different Contrasts

Luminance-independent changes in pupil diameter (PD) during wakefulness influence and are influenced by neuromodulatory, neuronal, and behavioral responses. However, it is unclear whether changes in neuromodulatory activity in a specific brain area are necessary for the associated changes in PD or whether some different mechanisms cause parallel fluctuations in both PD and neuromodulation. To answer this question, we simultaneously recorded PD and cortical neuronal activity in male and female mice. Namely, we measured PD and neuronal activity during adaptation to sound contrast, which is a well-described adaptation conserved in many species and brain areas. In the primary auditory cortex (A1), increases in the variability of sound level (contrast) induce a decrease in the slope of the neuronal input-output relationship, neuronal gain, which depends on cortical neuromodulatory zinc signaling. We found a previously unknown modulation of PD by changes in background sensory context: high stimulus contrast sounds evoke larger increases in evoked PD compared with low-contrast sounds. To explore whether these changes in evoked PD are controlled by cortical neuromodulatory zinc signaling, we imaged single-cell neural activity in A1, manipulated zinc signaling in the cortex, and assessed PD in the same awake mouse. We found that cortical synaptic zinc signaling is necessary for increases in PD during high-contrast background sounds compared with low-contrast sounds. This finding advances our knowledge about how cortical neuromodulatory activity affects PD changes and thus advances our understanding of the brain states, circuits, and neuromodulatory mechanisms that can be inferred from pupil size fluctuations.

Expansion and Light-Sheet Microscopy for Nanoscale 3D Imaging

Expansion Microscopy (ExM) and Light-Sheet Fluorescence Microscopy (LSFM) are forefront imaging techniques that enable high-resolution visualization of biological specimens. ExM enhances nanoscale investigation using conventional fluorescence microscopes, while LSFM offers rapid, minimally invasive imaging over large volumes. This review explores the joint advancements of ExM and LSFM, focusing on the excellent performance of the integrated modality obtained from the combination of the two, which is refer to as ExLSFM. In doing so, the chemical processes required for ExM, the tailored optical setup of LSFM for examining expanded samples, and the adjustments in sample preparation for accurate data collection are emphasized. It is delve into various specimen types studied using this integrated method and assess its potential for future applications. The goal of this literature review is to enrich the comprehension of ExM and LSFM, encouraging their wider use and ongoing development, looking forward to the upcoming challenges, and anticipating innovations in these imaging techniques.

Strategies for labelling of exogenous and endogenous extracellular vesicles and their application for in vitro and in vivo functional studies

This review presents a comprehensive overview of labelling strategies for endogenous and exogenous extracellular vesicles, that can be utilised both in vitro and in vivo. It covers a broad spectrum of approaches, including fluorescent and bioluminescent labelling, and provides an analysis of their applications, strengths, and limitations. Furthermore, this article presents techniques that use radioactive tracers and contrast agents with the ability to track EVs both spatially and temporally. Emphasis is also placed on endogenous labelling mechanisms, represented by Cre-lox and CRISPR-Cas systems, which are powerful and flexible tools for real-time EV monitoring or tracking their fate in target cells. By summarizing the latest developments across these diverse labelling techniques, this review provides researchers with a reference to select the most appropriate labelling method for their EV based research.

Orexin neurons play contrasting roles in itch and pain neural processing via projecting to the periaqueductal gray

Pain and itch are recognized as antagonistically regulated sensations; pain suppresses itch, whilst pain inhibition enhances itch. The neural mechanisms at the central nervous system (CNS) underlying these pain-itch interactions still need to be explored. Here, we revealed the contrasting role of orexin-producing neurons (ORX neurons) in the lateral hypothalamus (LH), which suppresses pain while enhancing itch neural processing, by applying optogenetics to the acute pruritus and pain model. We also revealed that the circuit of ORX neurons from LH to periaqueductal gray regions served in the contrasting modulation of itch and pain processing using optogenetic terminal inhibition techniques. Additionally, by using an atopic dermatitis model, we confirmed the involvement of ORX neurons in regulating chronic itch processing, which could lead to a novel therapeutic target for persistent pruritus in clinical settings. Our findings provide new insight into the mechanism of antagonistic regulation between pain and itch in the CNS.

Tip-enhanced Raman spectroscopy reveals the structural rearrangements of tau protein aggregates at the growth phase

Tau protein aggregates inside neurons in the course of Alzheimer's disease (AD). Because of the enormous number of people suffering from AD, this disease has become one of the world's major health and social problems. The presence of tau lesions clearly correlates with cognitive impairments in AD patients, thus, tau is the target of potential treatments for AD, next to amyloid-β. The exact mechanism of tau aggregation has not been understood in detail so far; especially little is known about the structural rearrangements of tau aggregates at the growth phase. The research into tau conformation at each step of the aggregation pathway will contribute to the design of effective therapeutic approaches. To follow the secondary structure of individual tau aggregates at the growth phase, we applied tip-enhanced Raman spectroscopy (TERS). The nanospectroscopic approach enabled us to follow the structure of individual aggregates occurring in the subsequent phases of tau aggregation. We applied multivariate data analysis to extract the spectral differences for tau aggregates at different aggregation phases. Moreover, atomic force microscopy (AFM) allowed the tracking of the morphological alterations for species occurring with the progression of tau aggregation.

Recent advances in the fabrication of organic solvent nanofiltration membranes using covalent/metal organic frameworks

Organic solvent nanofiltration (OSN) has evolved as a vital technological frontier with paramount significance in the separation and purification of organic solvents. Its implication is particularly prominent in industries such as pharmaceuticals, petrochemicals, and environmental remediation. This comprehensive review, meticulously navigates through the current state of research in OSN membranes, unveiling both the critical challenges and promising opportunities that beckon further exploration. The central focus of this review is on the unique utilization of covalent organic frameworks (COFs) and metal-organic frameworks (MOFs) in OSN membrane design, leveraging their distinctive structural attributes-tunable porosity, robust chemical stability, and molecular sieving capabilities. These qualities position them as exceptional candidates for crafting membranes tailored to the intricacies of organic solvent environments. Our investigation extends into the fundamental principles that render COFs and MOFs adept in OSN applications, dissecting their varied fabrication methods while offering insights into the advantages and limitations of each. Moreover, we address environmental and sustainability considerations in the use of COF and MOF-based OSN membranes. Furthermore, we meticulously present the latest advancements and innovations in this burgeoning field, charting a course toward potential future directions and emerging research areas. By underscoring the challenges awaiting exploration, this review not only provides a panoramic view of the current OSN landscape but also lays the groundwork for the evolution of efficient and sustainable OSN technologies, specifically harnessing the unique attributes of COFs and MOFs.

Subthalamic nucleus deep brain stimulation alleviates oxidative stress via mitophagy in Parkinson's disease

Subthalamic nucleus deep brain stimulation (STN-DBS) has the potential to delay Parkinson's disease (PD) progression. Whether oxidative stress participates in the neuroprotective effects of DBS and related signaling pathways remains unknown. To address this, we applied STN-DBS to mice and monkey models of PD and collected brain tissue to evaluate mitophagy, oxidative stress, and related pathway. To confirm findings in animal experiments, a cohort of PD patients was recruited and oxidative stress was evaluated in cerebrospinal fluid. When PD mice received STN stimulation, the mTOR pathway was suppressed, accompanied by elevated LC3 II expression, increased mitophagosomes, and a decrease in p62 expression. The increase in mitophagy and balance of mitochondrial fission/fusion dynamics in the substantia nigra caused a marked enhancement of the antioxidant enzymes superoxide dismutase and glutathione levels. Subsequently, fewer mitochondrial apoptogenic factors were released to the cytoplasm, which resulted in a suppression of caspase activation and reservation of dopaminergic neurons. While interfaced with an mTOR activator, oxidative stress was no longer regulated by STN-DBS, with no neuroprotective effect. Similar results to those found in the rodent experiments were obtained in monkeys treated with chronic STN stimulation. Moreover, antioxidant enzymes in PD patients were increased after the operation, however, there was no relation between changes in antioxidant enzymes and motor impairment. Collectively, our study found that STN-DBS was able to increase mitophagy via an mTOR-dependent pathway, and oxidative stress was suppressed due to removal of damaged mitochondria, which was attributed to the dopaminergic neuroprotection of STN-DBS in PD.

Identifying ligands for the PHD1 finger of KDM5A through high-throughput screening

PHD fingers are a type of chromatin reader that primarily recognize chromatin as a function of lysine methylation state. Dysregulated PHD fingers are implicated in various human diseases, including acute myeloid leukemia. Targeting PHD fingers with small molecules is considered challenging as their histone tail binding pockets are often shallow and surface-exposed. The KDM5A PHD1 finger regulates the catalytic activity of KDM5A, an epigenetic enzyme often misregulated in cancers. To identify ligands that disrupt the PHD1-histone peptide interaction, we conducted a high-throughput screen and validated hits by orthogonal methods. We further elucidated structure-activity relationships in two classes of compounds to identify features important for binding. Our investigation offers a starting point for further optimization of small molecule PHD1 ligands.

Genetic architecture of the structural connectome

Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.

Real-time screening of NixBy bifunctional electrocatalysts for overall NH3 synthesis via SG-TC SECM

Electrochemical ammonia synthesis, which couples oxygen evolution at the anode with nitrogen reduction at the cathode, holds great significance for future food and energy needs. Both of these half-cell reactions determine the overall cell potential and efficiency of the process. However, the employment of different catalysts on either side, due to discrete mechanisms, increases the complexity and material processing costs of the system, where the designing of a bifunctional catalyst active towards both the NRR and OER is of huge significance. Unfortunately, the initial screening of the designed catalysts via physical characterizations, optical methods and other techniques, does not provide details about the electrochemical activity. The scanning electrochemical microscopy (SECM) technique can be useful to screen multi-catalysts at the same time for their electrochemical activities. Herein, we employed the sample generation-tip collection (SG-TC) mode of SECM to screen the designed NixBy catalysts before half-cell investigations, which suggested that the catalyst synthesized via sonochemical reduction (SR), i.e. NixBy (SR), was a better catalyst. This inference was in accordance with the half-cell NRR and OER measurements (FE: 49% for NH3 production, OER overpotential: 300 mV). By virtue of this remarkable bifunctional activity, the NRR-OER coupled full cell was assembled, which initiated the NH3 production at just 1.7 V and produced NH3 (1.08 mg h-1 mgcat-1) at the cathode and O2 (0.81 mg h-1 mgcat-1) at the anode after 2 h of electrolysis at 1.9 V.

High-toughness, extensile and self-healing PDMS elastomers constructed by decuple hydrogen bonding

Elastomers are widely used in traditional industries and new intelligent fields. However, they are inevitably damaged by electricity, heat, force, etc. during the working process. With the continuous improvement of reliability and environmental protection requirements in human production and living, it is vital to develop elastomer materials with good mechanical properties that are not easily damaged and can self-heal after being damaged. Nevertheless, there are often contradictions between mechanical properties and self-healing as well as toughness, strength, and ductility. Herein, a strong and dynamic decuple hydrogen bonding based on carbon hydrazide (CHZ) is reported, accompanied with soft polydimethylsiloxane (PDMS) chains to prepare self-healing (efficiency 98.7%), recyclable, and robust elastomers (CHZ-PDMS). The strategy of decuple hydrogen bonding will significantly impact the study of the mechanical properties of elastomers. High stretchability (1731%) and a high toughness of 23.31 MJ m-3 are achieved due to the phase-separated structure and energy dissipation. The recyclability of CHZ-PDMS further supports the concept of environmental protection. The application of CHZ-PDMS as a flexible strain sensor exhibited high sensitivity.

Binary image encryption with a QR code-encoded optical beam having an array of vortices

In recent years, optical information processing has become increasingly important due to its ability to handle large amounts of data efficiently. Amplitude, phase, spatial frequency, wavelength, and polarization are the physical dimensions used for information encoding into the light beam. Information encoding using orbital angular momentum (OAM) carried by a vortex beam is gaining interest in this regard. Such beams provide high-dimensional orthogonal states for encoding and have shown more stability in turbulent media than Gaussian beams, especially in the case of free space propagation. This study demonstrates an image encryption method utilizing an array of OAM light modes. The approach uses a non-interferometric intensity recording-based encoding scheme, which offers ease of implementation. Quick response codes have been utilized for encoding to avoid information loss from non-uniform distribution of light and aberrations. The encryption scheme is highly secure because the encrypted light beam contains only partial information about the object, preventing complete information retrieval without proper key information.

Modulating the Structure and Composition of Single-Atom Electrocatalysts for CO2 reduction

Electrochemical CO2 reduction reaction (eCO2 RR) is a promising strategy to achieve carbon cycling by converting CO2 into value-added products under mild reaction conditions. Recently, single-atom catalysts (SACs) have shown enormous potential in eCO2 RR due to their high utilization of metal atoms and flexible coordination structures. In this work, the recent progress in SACs for eCO2 RR is outlined, with detailed discussions on the interaction between active sites and CO2 , especially the adsorption/activation behavior of CO2 and the effects of the electronic structure of SACs on eCO2 RR. Three perspectives form the starting point: 1) Important factors of SACs for eCO2 RR; 2) Typical SACs for eCO2 RR; 3) eCO2 RR toward valuable products. First, how different modification strategies can change the electronic structure of SACs to improve catalytic performance is discussed; Second, SACs with diverse supports and how supports assist active sites to undergo catalytic reaction are introduced; Finally, according to various valuable products from eCO2 RR, the reaction mechanism and measures which can be taken to improve the selectivity of eCO2 RR are discussed. Hopefully, this work can provide a comprehensive understanding of SACs for eCO2 RR and spark innovative design and modification ideas to develop highly efficient SACs for CO2 conversion to various valuable fuels/chemicals.

Ectopic colonization by oral bacteria as an emerging theme in health and disease

The number of research papers published on the involvement of the oral microbiota in systemic diseases has grown exponentially over the last 4 years clearly demonstrating the growing interest in this field. Indeed, accumulating evidence highlights the central role of ectopic colonization by oral bacteria in numerous noncommunicable diseases including inflammatory bowel diseases (IBDs), undernutrition, preterm birth, neurological diseases, liver diseases, lung diseases, heart diseases, or colonic cancer. There is thus much interest in understanding the molecular mechanisms that lead to the colonization and maintenance of ectopic oral bacteria. The aim of this review is to summarize and conceptualize the current knowledge about ectopic colonization by oral bacteria, highlight wherever possible the underlying molecular mechanisms and describe its implication in health and disease. The focus lies on the newly discovered molecular mechanisms, showcasing shared pathophysiological mechanisms across different body sites and syndromes and highlighting open questions in the field regarding the pathway from oral microbiota dysbiosis to noncommunicable diseases.

Joint spatio-temporal features constrained self-supervised electrocardiogram representation learning

The electrocardiogram (ECG) measurements with clinical diagnostic labels are intrinsically limited. We propose a generative learning based self-supervised method for general ECG representations applicable to various downstream tasks, thus achieving the goal of reducing the dependence on labeled data. However, existing self-supervised methods either fail to provide satisfactory ECG representations or require too much effort to curate a large amount of expert-annotated datasets. We propose a spatio-temporal joint detection based self-supervised method with little or no human supervision to label massive datasets. Considering the spatio-temporal characteristics of ECG signals, we dynamically randomly mask the original signal (temporal detection) and disrupt the order of leads (spatial detection) to complete the learning through reconstructing the original signal and predicting the lead numbers. To validate the effectiveness of the proposed method, we use several publicly available ECG databases as well as a private ECG data of ventricular tachycardia to pre-train our model. We use diagnostic classification of 27 arrhythmia types and localization of ventricular tachycardia origin sites as two downstream tasks, respectively. The results show that learning ECG representations with this method is effective. This effort demonstrates the feasibility of learning representations from ECG data by self-supervised learning. Our self-supervised method uses only 60% of the labeled data used by the supervised method to achieve the same performance. Using the same amount of data, our self-supervised approach shows 1.3% and 8.6% improvement in classification and localization accuracy compared to the model with random initialization on two types of downstream tasks, respectively.

Thermoelectric Generator Through Dual-Direction Thermal Regulation by Thermal Diodes for Waste Heat Harvesting

Thermal energy harvesting provides an opportunity for multi-node systems to achieve self-power autonomy. Thermoelectric generators (TEGs), either by thermocouple arrangement with higher-aspect-ratios or thermoelectric films overlay, are limited by the small temperature difference and its short-duration (less than dozens of minutes), hindering the harvesting efficiency. Here, by introducing thermal diodes with dual-direction thermal regulation ability to optimize the heat flux path, the proposed TEGs exhibit enhanced power-supply capability with unprecedented long-duration (more than hours). In contrast with conventional TEGs with fixed-leg dimensions enabled single output, these compact-TEGs can supply up to fourteen output-channels for selection, the produced power ranges from 1.11 to 921.99 µW, open circuit voltage ranges from 8.07 to 51.32 mV, when the natural temperature difference is 53.84 °C. Compared to the most recent TEGs, the proposed TEGs in this study indicate higher power (more than hundreds times) and much longer output duration (2.4-120 times) in a compact manner.

BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-Inspired Materials

The study of biological materials and bio-inspired materials science is well established; however, surprisingly little knowledge is systematically translated to engineering solutions. To accelerate discovery and guide insights, an open-source autoregressive transformer large language model (LLM), BioinspiredLLM, is reported. The model is finetuned with a corpus of over a thousand peer-reviewed articles in the field of structural biological and bio-inspired materials and can be prompted to recall information, assist with research tasks, and function as an engine for creativity. The model has proven that it is able to accurately recall information about biological materials and is further strengthened with enhanced reasoning ability, as well as with Retrieval-Augmented Generation (RAG) to incorporate new data during generation that can also help to traceback sources, update the knowledge base, and connect knowledge domains. BioinspiredLLM also has shown to develop sound hypotheses regarding biological materials design and remarkably so for materials that have never been explicitly studied before. Lastly, the model shows impressive promise in collaborating with other generative artificial intelligence models in a workflow that can reshape the traditional materials design process. This collaborative generative artificial intelligence method can stimulate and enhance bio-inspired materials design workflows. Biological materials are at a critical intersection of multiple scientific fields and models like BioinspiredLLM help to connect knowledge domains.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Changes in microstructural similarity of hippocampal subfield circuits in pathological cognitive aging

The hippocampal networks support multiple cognitive functions and may have biological roles and functions in pathological cognitive aging (PCA) and its associated diseases, which have not been explored. In the current study, a total of 116 older adults with 39 normal controls (NC) (mean age: 52.3 ± 13.64 years; 16 females), 39 mild cognitive impairment (MCI) (mean age: 68.15 ± 9.28 years, 14 females), and 38 dementia (mean age: 73.82 ± 8.06 years, 8 females) were included. The within-hippocampal subfields and the cortico-hippocampal circuits were assessed via a micro-structural similarity network approach using T1w/T2w ratio and regional gray matter tissue probability maps, respectively. An analysis of covariance was conducted to identify between-group differences in structural similarities among hippocampal subfields. The partial correlation analyses were performed to associate changes in micro-structural similarities with cognitive performance in the three groups, controlling the effect of age, sex, education, and cerebral small-vessel disease. Compared with the NC, an altered T1w/T2w ratio similarity between left CA3 and left subiculum was observed in the mild cognitive impairment (MCI) and dementia. The left CA3 was the most impaired region correlated with deteriorated cognitive performance. Using these regions as seeds for GM similarity comparisons between hippocampal subfields and cortical regions, group differences were observed primarily between the left subiculum and several cortical regions. By utilizing T1w/T2w ratio as a proxy measure for myelin content, our data suggest that the imbalanced synaptic weights within hippocampal CA3 provide a substrate to explain the abnormal firing characteristics of hippocampal neurons in PCA. Furthermore, our work depicts specific brain structural characteristics of normal and pathological cognitive aging and suggests a potential mechanism for cognitive aging heterogeneity.

Evolution and emergence of Mycobacterium tuberculosis

Tuberculosis (TB) remains one of the deadliest infectious diseases in human history, prevailing even in the 21st century. The causative agents of TB are represented by a group of closely related bacteria belonging to the Mycobacterium tuberculosis complex (MTBC), which can be subdivided into several lineages of human- and animal-adapted strains, thought to have shared a last common ancestor emerged by clonal expansion from a pool of recombinogenic Mycobacterium canettii-like tubercle bacilli. A better understanding of how MTBC populations evolved from less virulent mycobacteria may allow for discovering improved TB control strategies and future epidemiologic trends. In this review, we highlight new insights into the evolution of mycobacteria at the genus level, describing different milestones in the evolution of mycobacteria, with a focus on the genomic events that have likely enabled the emergence and the dominance of the MTBC. We also review the recent literature describing the various MTBC lineages and highlight their particularities and differences with a focus on host preferences and geographic distribution. Finally, we discuss on putative mechanisms driving the evolution of tubercle bacilli and mycobacteria in general, by taking the mycobacteria-specific distributive conjugal transfer as an example.

Bacteria in the blood of healthy stray dogs infested by ticks in northern Mexico

Objective

The objectives of this study were to determine the richness, abundance, and diversity of bacteria in stray dogs (Canis lupus familiaris) infested by ticks in Comarca Lagunera, northern Mexico, and to establish their pathogenic and or/zoonotic potential.

Materials and Methods

Blood samples from 12 dogs were collected, and their deoxyribonucleic acid was extracted. The V3-V4 region of the 16S ribosomal ribunocleic acid gene was amplified by polymerase chain reaction. Next-generation sequencing (NGS) was performed on a MiSeq Illumina platform, and the data were analyzed using quantitative insights into microbial ecology.

Results

The operational taxonomic units resulted in 23 phyla, 54 classes, 89 orders, 189 families, 586 genera, and 620 bacterial species; among them, 64 species and/or bacterial genera with pathogenic or zoonotic potential were identified, some of which have been reported in the literature as relevant to public health (Anaplasma phagocytophilum, Brucella spp., Clostridium spp., Corynebacterium affermentants, Cutibacterium spp., Dietzia spp., Ehrlichia canis, Fusobacterium necrophorum, Leptotrichia spp., Mycobacterium spp., Paracoccus spp., and Roseomonas gilardii).

Conclusion

This research offers relevant information on the prevalence of tick-borne diseases as well as other potential zoonotic diseases in the blood of stray dogs parasitized by ticks in northern Mexico. New molecular biology and massive NGS techniques may play an important role in the study and documentation of bacterial profiles from animals in close proximity to humans.

Poly(A) tale: From A to A; RNA polyadenylation in prokaryotes and eukaryotes

Most eukaryotic mRNAs and different non-coding RNAs undergo a form of 3' end processing known as polyadenylation. Polyadenylation machinery is present in almost all organisms except few species. In bacteria, the machinery has evolved from PNPase, which adds heteropolymeric tails, to a poly(A)-specific polymerase. Differently, a complex machinery for accurate polyadenylation and several non-canonical poly(A) polymerases are developed in eukaryotes. The role of poly(A) tail has also evolved from serving as a degradative signal to a stabilizing modification that also regulates translation. In this review, we discuss poly(A) tail emergence in prokaryotes and its development into a stable, yet dynamic feature at the 3' end of mRNAs in eukaryotes. We also describe how appearance of novel poly(A) polymerases gives cells flexibility to shape poly(A) tail. We explain how poly(A) tail dynamics help regulate cognate RNA metabolism in a context-dependent manner, such as during oocyte maturation. Finally, we describe specific mRNAs in metazoans that bear stem-loops instead of poly(A) tails. We conclude with how recent discoveries about poly(A) tail can be applied to mRNA technology. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution RNA Processing > 3' End Processing RNA Turnover and Surveillance > Regulation of RNA Stability.

Weak local adaptation to drought in seedlings of a widespread conifer

Tree seedlings from populations native to drier regions are often assumed to be more drought tolerant than those from wetter provenances. However, intraspecific variation in drought tolerance has not been well-characterized despite being critical for developing climate change mitigation and adaptation strategies, and for predicting the effects of drought on forests. We used a large-scale common garden drought-to-death experiment to assess range-wide variation in drought tolerance, measured by decline of photosynthetic efficiency, growth, and plastic responses to extreme summer drought in seedlings of 73 natural populations of the two main varieties of Douglas-fir (Pseudotsuga menziesii var. menziesii and var. glauca). Local adaptation to drought was weak in var. glauca and nearly absent in menziesii. Var. glauca showed higher tolerance to drought but slower growth than var. menziesii. Clinal variation in drought tolerance and growth species-wide was mainly associated with temperature rather than precipitation. A higher degree of plasticity for growth was observed in var. menziesii in response to extreme drought. Genetic variation for drought tolerance in seedlings within varieties is maintained primarily within populations. Selective breeding within populations may facilitate adaptation to drought more than assisted gene flow.

Microbiota modulation by dietary oat beta-glucan prevents steatotic liver disease progression

Background & Aims

Changes in gut microbiota in metabolic dysfunction-associated steatotic liver disease (MASLD) are important drivers of disease progression towards fibrosis. Therefore, reversing microbial alterations could ameliorate MASLD progression. Oat beta-glucan, a non-digestible polysaccharide, has shown promising therapeutic effects on hyperlipidemia associated with MASLD, but its impact on gut microbiota and most importantly MASLD-related fibrosis remains unknown.

Methods

We performed detailed metabolic phenotyping, including assessments of body composition, glucose tolerance, and lipid metabolism, as well as comprehensive characterization of the gut-liver axis in a western-style diet (WSD)-induced model of MASLD and assessed the effect of a beta-glucan intervention on early and advanced liver disease. Gut microbiota were modulated using broad-spectrum antibiotic treatment.

Results

Oat beta-glucan supplementation did not affect WSD-induced body weight gain or glucose intolerance and the metabolic phenotype remained largely unaffected. Interestingly, oat beta-glucan dampened MASLD-related inflammation, which was associated with significantly reduced monocyte-derived macrophage infiltration and fibroinflammatory gene expression, as well as strongly reduced fibrosis development. Mechanistically, this protective effect was not mediated by changes in bile acid composition or signaling, but was dependent on gut microbiota and was lost upon broad-spectrum antibiotic treatment. Specifically, oat beta-glucan partially reversed unfavorable changes in gut microbiota, resulting in an expansion of protective taxa, including Ruminococcus, and Lactobacillus followed by reduced translocation of Toll-like receptor ligands.

Conclusions

Our findings identify oat beta-glucan as a highly efficacious food supplement that dampens inflammation and fibrosis development in diet-induced MASLD. These results, along with its favorable dietary profile, suggest that it may be a cost-effective and well-tolerated approach to preventing MASLD progression and should be assessed in clinical studies.

Impact and Implications

Herein, we investigated the effect of oat beta-glucan on the gut-liver axis and fibrosis development in a mouse model of metabolic dysfunction-associated steatotic liver disease (MASLD). Beta-glucan significantly reduced inflammation and fibrosis in the liver, which was associated with favorable shifts in gut microbiota that protected against bacterial translocation and activation of fibroinflammatory pathways. Together, oat beta-glucan may be a cost-effective and well-tolerated approach to prevent MASLD progression and should be assessed in clinical studies.

Metabolomic Investigation of Brain and Liver in Rats Fed Docosahexaenoic Acid in Regio- and Enantiopure Triacylglycerols

SCOPE

N-3 polyunsaturated fatty acids (n-3 PUFAs) play important roles in cognitive functions. However, there is a lack of knowledge on the metabolic impact of regio- and stereo-specific positioning of n-3 PUFAs in dietary triacylglycerols.

METHODS AND RESULTS

Rats in a state of mild n-3 PUFA deficiency are fed daily with 360 mg triacylglycerols containing DHA (docosahexaenoic acid) at sn (stereospecific numbering)-1, 2, or 3 positions and 18:0 at remaining positions, or an equal amount of tristearin for 5 days. Groups fed with n-3 deficient diet and normal n-3 adequate diet are included as controls. The metabolic profiles of the brain and liver are studied using NMR (nuclear magnetic resonance)-based metabolomics. Several metabolites of significance in membrane integrity and neurotransmission, and glutamate, in particular, are significantly lower in the brain of the groups fed with sn-1 and sn-3 DHA compared to the sn-2 DHA group. Further, the tristearin and DHA groups show a lower lactate level compared to the groups fed on normal or n-3 deficient diet, suggesting a prominent role of C18:0 in regulating energy metabolism.

CONCLUSION

This study sheds light on the impact of stereospecific positioning of DHA in triacylglycerols and the role of dietary stearic acid on metabolism in the brain and liver.

Evaluating batch correction methods for image-based cell profiling

High-throughput image-based profiling platforms are powerful technologies capable of collecting data from billions of cells exposed to thousands of perturbations in a time- and cost-effective manner. Therefore, image-based profiling data has been increasingly used for diverse biological applications, such as predicting drug mechanism of action or gene function. However, batch effects pose severe limitations to community-wide efforts to integrate and interpret image-based profiling data collected across different laboratories and equipment. To address this problem, we benchmarked seven high-performing scRNA-seq batch correction techniques, representing diverse approaches, using a newly released Cell Painting dataset, the largest publicly accessible image-based dataset. We focused on five different scenarios with varying complexity, and we found that Harmony, a mixture-model based method, consistently outperformed the other tested methods. Our proposed framework, benchmark, and metrics can additionally be used to assess new batch correction methods in the future. Overall, this work paves the way for improvements that allow the community to make best use of public Cell Painting data for scientific discovery.

Synaptic Changes in Pallidostriatal Circuits Observed in the Parkinsonian Model Triggers Abnormal Beta Synchrony with Accurate Spatio-temporal Properties across the Basal Ganglia

Excessive oscillatory activity across basal ganglia (BG) nuclei in the β frequencies (12-30 Hz) is a hallmark of Parkinson's disease (PD). While the link between oscillations and symptoms remains debated, exaggerated β oscillations constitute an important biomarker for therapeutic effectiveness in PD. The neuronal mechanisms of β-oscillation generation however remain unknown. Many existing models rely on a central role of the subthalamic nucleus (STN) or cortical inputs to BG. Contrarily, neural recordings and optogenetic manipulations in normal and parkinsonian rats recently highlighted the central role of the external pallidum (GPe) in abnormal β oscillations, while showing that the integrity of STN or motor cortex is not required. Here, we evaluate the mechanisms for the generation of abnormal β oscillations in a BG network model where neuronal and synaptic time constants, connectivity, and firing rate distributions are strongly constrained by experimental data. Guided by a mean-field approach, we show in a spiking neural network that several BG sub-circuits can drive oscillations. Strong recurrent STN-GPe connections or collateral intra-GPe connections drive γ oscillations (>40 Hz), whereas strong pallidostriatal loops drive low-β (10-15 Hz) oscillations. We show that pathophysiological strengthening of striatal and pallidal synapses following dopamine depletion leads to the emergence of synchronized oscillatory activity in the mid-β range with spike-phase relationships between BG neuronal populations in-line with experiments. Furthermore, inhibition of GPe, contrary to STN, abolishes oscillations. Our modeling study uncovers the neural mechanisms underlying PD β oscillations and may thereby guide the future development of therapeutic strategies.

Cardiologist-level interpretable knowledge-fused deep neural network for automatic arrhythmia diagnosis

BACKGROUND

Long-term monitoring of Electrocardiogram (ECG) recordings is crucial to diagnose arrhythmias. Clinicians can find it challenging to diagnose arrhythmias, and this is a particular issue in more remote and underdeveloped areas. The development of digital ECG and AI methods could assist clinicians who need to diagnose arrhythmias outside of the hospital setting.

METHODS

We constructed a large-scale Chinese ECG benchmark dataset using data from 272,753 patients collected from January 2017 to December 2021. The dataset contains ECG recordings from all common arrhythmias present in the Chinese population. Several experienced cardiologists from Shanghai First People's Hospital labeled the dataset. We then developed a deep learning-based multi-label interpretable diagnostic model from the ECG recordings. We utilized Accuracy, F1 score and AUC-ROC to compare the performance of our model with that of the cardiologists, as well as with six comparison models, using testing and hidden data sets.

RESULTS

The results show that our approach achieves an F1 score of 83.51%, an average AUC ROC score of 0.977, and 93.74% mean accuracy for 6 common arrhythmias. Results from the hidden dataset demonstrate the performance of our approach exceeds that of cardiologists. Our approach also highlights the diagnostic process.

CONCLUSIONS

Our diagnosis system has superior diagnostic performance over that of clinicians. It also has the potential to help clinicians rapidly identify abnormal regions on ECG recordings, thus improving efficiency and accuracy of clinical ECG diagnosis in China. This approach could therefore potentially improve the productivity of out-of-hospital ECG diagnosis and provides a promising prospect for telemedicine.

The molecular machinery of meiotic recombination

Meiotic recombination, a cornerstone of eukaryotic diversity and individual genetic identity, is essential for the creation of physical linkages between homologous chromosomes, facilitating their faithful segregation during meiosis I. This process requires that germ cells generate controlled DNA lesions within their own genome that are subsequently repaired in a specialised manner. Repair of these DNA breaks involves the modulation of existing homologous recombination repair pathways to generate crossovers between homologous chromosomes. Decades of genetic and cytological studies have identified a multitude of factors that are involved in meiotic recombination. Recent work has started to provide additional mechanistic insights into how these factors interact with one another, with DNA, and provide the molecular outcomes required for a successful meiosis. Here, we provide a review of the recent developments with a focus on protein structures and protein-protein interactions.

In Situ Hydrolysis of Phosphate Enabling Sky-Blue Perovskite Light-Emitting Diode with EQE Approaching 16.32

The performance of blue perovskite light-emitting diodes (PeLEDs) lags behind the green and red counterparts owing to high trap density and undesirable red shift of the electroluminescence spectrum under operation conditions. Organic molecular additives were employed as passivators in previous reports. However, most commonly have limited functions, making it challenging to effectively address both efficiency and stability issues simultaneously. Herein, we reported an innovatively dynamic in situ hydrolysis strategy to modulate quasi-2D sky-blue perovskites by the multifunctional passivator phenyl dichlorophosphate that not only passivated the defects but also underwent in situ hydrolysis reaction to stabilize the emission. Moreover, hydrolysis products were beneficial for low-dimensional phase manipulation. Eventually, we obtained high-performance sky-blue PeLEDs with a maximum external quantum efficiency (EQE) of 16.32% and an exceptional luminance of 5740 cd m-2. More importantly, the emission peak of devices located at 485 nm remained stable under different biases. Our work signified the significant advancement toward realizing future applications of PeLEDs.

CircRNA identification and feature interpretability analysis

BACKGROUND

Circular RNAs (circRNAs) can regulate microRNA activity and are related to various diseases, such as cancer. Functional research on circRNAs is the focus of scientific research. Accurate identification of circRNAs is important for gaining insight into their functions. Although several circRNA prediction models have been developed, their prediction accuracy is still unsatisfactory. Therefore, providing a more accurate computational framework to predict circRNAs and analyse their looping characteristics is crucial for systematic annotation.

RESULTS

We developed a novel framework, CircDC, for classifying circRNAs from other lncRNAs. CircDC uses four different feature encoding schemes and adopts a multilayer convolutional neural network and bidirectional long short-term memory network to learn high-order feature representation and make circRNA predictions. The results demonstrate that the proposed CircDC model is more accurate than existing models. In addition, an interpretable analysis of the features affecting the model is performed, and the computational framework is applied to the extended application of circRNA identification.

CONCLUSIONS

CircDC is suitable for the prediction of circRNA. The identification of circRNA helps to understand and delve into the related biological processes and functions. Feature importance analysis increases model interpretability and uncovers significant biological properties. The relevant code and data in this article can be accessed for free at https://github.com/nmt315320/CircDC.git .

Towards a more accurate light transport model for non-line-of-sight imaging

Non-line-of-sight (NLOS) imaging systems involve the measurement of an optical signal at a diffuse surface. A forward model encodes the physics of these measurements mathematically and can be inverted to generate a reconstruction of the hidden scene. Some existing NLOS imaging techniques rely on illuminating the diffuse surface and measuring the photon time of flight (ToF) of multi-bounce light paths. Alternatively, some methods depend on measuring high-frequency variations caused by shadows cast by occluders in the hidden scene. While forward models for ToF-NLOS and Shadow-NLOS have been developed separately, there has been limited work on unifying these two imaging modalities. Dove et al introduced a unified mathematical framework capable of modeling both imaging techniques [Opt. Express27, 18016 (2019)10.1364/OE.27.018016]. The authors utilize this general forward model, known as the two frequency spatial Wigner distribution (TFSWD), to discuss the implications of reconstruction resolution for combining the two modalities but only when the occluder geometry is known a priori. In this work, we develop a graphical representation of the TFSWD forward model and apply it to novel experimental setups with potential applications in NLOS imaging. Furthermore, we use this unified framework to explore the potential of combining these two imaging modalities in situations where the occluder geometry is not known in advance.

Japanese wolves are most closely related to dogs and share DNA with East Eurasian dogs

Although the domestic dog's origin is still unclear, this lineage is believed to have been domesticated from an extinct population of gray wolves, which is expected to be more closely related to dogs than to other populations of gray wolves. Here, we sequence the whole genomes of nine Japanese wolves (7.5-100x: Edo to Meiji periods) and 11 modern Japanese dogs and analyze them together with those from other populations of dogs and wolves. A phylogenomic tree shows that, among the gray wolves, Japanese wolves are closest to the dog, suggesting that the ancestor of dogs is closely related to the ancestor of the Japanese wolf. Based on phylogenetic and geographic relationships, the dog lineage has most likely originated in East Asia, where it diverged from a common ancestor with the Japanese wolf. Since East Eurasian dogs possess Japanese wolf ancestry, we estimate an introgression event from the ancestor of the Japanese wolf to the ancestor of the East Eurasian dog that occurred before the dog's arrival in the Japanese archipelago.

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies.

Dynamic light manipulation via silicon-organic slot metasurfaces

Active metasurfaces provide the opportunity for fast spatio-temporal control of light. Among various tuning methods, organic electro-optic materials provide some unique advantages due to their fast speed and large nonlinearity, along with the possibility of using fabrication techniques based on infiltration. In this letter, we report a silicon-organic platform where organic electro-optic material is infiltrated into the narrow gaps of slot-mode metasurfaces with high quality factors. The mode confinement into the slot enables the placement of metallic electrodes in close proximity, thus enabling tunability at lower voltages. We demonstrate the maximum tuning sensitivity of 0.16nm/V, the maximum extinction ratio of 38% within ± 17V voltage at telecommunication wavelength. The device has 3dB bandwidth of 3MHz. These results provide a path towards tunable silicon-organic hybrid metasurfaces at CMOS-level voltages.

Nanoscale polymer discs, toroids and platelets: a survey of their syntheses and potential applications

Polymer self-assembly has become a reliable and versatile workhorse to produce polymeric nanomaterials. With appropriate polymer design and monomer selection, polymers can assemble into shapes and morphologies beyond well-studied spherical and cylindrical micellar structures. Steadfast access to anisotropic polymer nanoparticles has meant that the fabrication and application of 2D soft matter has received increasing attention in recent years. In this review, we focus on nanoscale polymer discs, toroids, and platelets: three morphologies that are often interrelated and made from similar starting materials or common intermediates. For each morphology, we illustrate design rules, and group and discuss commonly used self-assembly strategies. We further highlight polymer compositions, fundamental principles and self-assembly conditions that enable precision in bottom-up fabrication strategies. Finally, we summarise potential applications of such nanomaterials, especially in the context of biomedical research and template chemistry and elaborate on future endeavours in this space.

Development of a novel mycobiome diagnostic for fungal infection

BACKGROUND

Amplicon-based mycobiome analysis has the potential to identify all fungal species within a sample and hence could provide a valuable diagnostic assay for use in clinical mycology settings. In the last decade, the mycobiome has been increasingly characterised by targeting the internal transcribed spacer (ITS) regions. Although ITS targets give broad coverage and high sensitivity, they fail to provide accurate quantitation as the copy number of ITS regions in fungal genomes is highly variable even within species. To address these issues, this study aimed to develop a novel NGS fungal diagnostic assay using an alternative amplicon target.

METHODS

Novel universal primers were designed to amplify a highly diverse single copy and uniformly sized DNA target (Tef1) to enable mycobiome analysis on the Illumina iSeq100 which is a low cost, small footprint and simple to use next-generation sequencing platform. To enable automated analysis and rapid results, a streamlined bioinformatics workflow and sequence database were also developed. Sequencing of mock fungal communities was performed to compare the Tef1 assay and established ITS1-based method. The assay was further evaluated using clinical respiratory samples and the feasibility of using internal spike-in quantitative controls was assessed.

RESULTS

The Tef1 assay successfully identified and quantified Aspergillus, Penicillium, Candida, Cryptococcus, Rhizopus, Fusarium and Lomentospora species from mock communities. The Tef1 assay was also capable of differentiating closely related species such as A. fumigatus and A. fischeri. In addition, it outperformed ITS1 at identifying A. fumigatus and other filamentous pathogens in mixed fungal communities (in the presence or absence of background human DNA). The assay could detect as few as 2 haploid genome equivalents of A. fumigatus from clinical respiratory samples. Lastly, spike-in controls were demonstrated to enable semi-quantitation of A. fumigatus load in clinical respiratory samples using sequencing data.

CONCLUSIONS

This study has developed and tested a novel metabarcoding target and found the assay outperforms ITS1 at identifying clinically relevant filamentous fungi. The assay is a promising diagnostic candidate that could provide affordable NGS analysis to clinical mycology laboratories.