Miracle-dz/UniFAR-FTUs huggingface dataset:
Winding number and Cutting number of Harmonic cycle

A harmonic cycle $\lambda$, also called a discrete harmonic form, is a solution of the Laplace's equation with the combinatorial Laplace operator obtained from the boundary operators of a chain complex. By the combinatorial Hodge theory, harmonic spaces are isomorphic to the homology groups with real coefficients. In particular, if a cell complex has a one dimensional reduced homology, it has a unique harmonic cycle up to scalar, which we call the \emph{standard harmonic cycle}. In this paper, we will present a formula for the standard harmonic cycle $\lambda$ of a cell complex based on a high-dimensional generalization of cycletrees. Moreover, by using duality, we will define the standard harmonic cocycle $\lambda^*$, and show intriguing combinatorial properties of $\lambda$ and $\lambda^*$ in relation to (dual) spanning trees, (dual) cycletrees, winding numbers $w(\cdot)$ and cutting numbers $c(\cdot)$ in high dimensions.
Exploring the K isotope composition of Göttingen minipig brain regions, and implications for Alzheimer's disease

Abstract Natural stable metal isotopes have shown utility in differentiation between healthy and diseased brain states (e.g. Alzheimer's disease, AD). While the AD brain accumulates some metals, it purges others, namely K (accompanied by increased serum K, suggesting brain–blood transferal). Here, K isotope compositions of Göttingen minipig brain regions for two AD models at midlife are reported. Results indicate heavy K isotope enrichment where amyloid beta (Aβ) accumulation is observed, and this enrichment correlates with relative K depletion. These results suggest preferential efflux of isotopically light K+ from the brain, a linkage between brain K concentrations and isotope compositions, and linkage to Aβ (previously shown to purge cellular brain K+). Brain K isotope compositions differ from that for serum and brain K is much more abundant than in serum, suggesting that changes in brain K may transfer a measurable K isotope excursion to serum, thereby generating an early AD biomarker.
Profiling Cancer Patients Based on Their Motives for Seeking Informational and Emotional Support Online

ABSTRACT Understanding why patients seek informational and/or emotional support online is fundamental to providing patients with accurate and reliable support that is tailored to their needs, preferences, and personal situation. Based on the stress and coping theory and uses and gratifications theory (UGT), this study aimed to identify theoretically-founded profiles of cancer patients differing in their motives for seeking informational and/or emotional support online, and to compare the profiles in terms of patients’ psychological and background characteristics, and perception of health care services. Hierarchical cluster analysis was conducted, using questionnaire data from patients visiting a large Dutch health website (N = 181). This revealed three distinctive profiles, i.e., overall seekers (n = 83, 46.0%), occasional information seekers (n = 83, 46.0%), and contact exchangers (n = 15, 8.0%). Patients across these profiles differed in their eHealth literacy, with the contact exchangers being more eHealth literate than the overall seekers and occasional information seekers. The results can be used to create awareness among health care providers, web designers, and patient organizations on different types of cancer patients with different motives for seeking informational and/or emotional support online, and help them to tailor recommendations to and development of (online) sources that fit patients’ needs. Future research could further investigate the integration of stress and coping theory with UGT by acknowledging the interplay of different coping strategies and different gratifications.
Regular cannabis use modulates the impact of HIV on the neural dynamics serving cognitive control

Background: Cannabis use and HIV are independently associated with decrements in cognitive control. However, the combined effects of HIV and regular cannabis use on the brain circuitry serving higher-order cognition are unclear. Aims: Investigate the interaction between cannabis and HIV on neural interference effects during the flanker task and spontaneous activity in regions underlying higher-order cognition. Methods: The sample consisted of 100 participants, including people with HIV (PWH) who use cannabis, PWH who do not use cannabis, uninfected cannabis users, and uninfected nonusers. Participants underwent an interview regarding their substance use history and completed the Eriksen flanker task during magnetoencephalography (MEG). MEG data were imaged in the time–frequency domain and oscillatory maps depicting the neural flanker interference effect were probed for group differences. Voxel time series were then assessed for group-level differences in spontaneous activity. Results: Group differences in behavioral performance were identified along with group differences in theta and alpha neural interference responses in higher-order regions across the cortex, with nonusers with HIV generally exhibiting the most aberrant responses. Likewise, time series analyses indicated that nonusers with HIV also had significantly elevated spontaneous alpha activity in the left inferior frontal and dorsolateral prefrontal cortices (dlPFC). Finally, we found that spontaneous and oscillatory alpha activity were significantly coupled in the inferior frontal cortex and dlPFC among cannabis users, but not nonusers. Conclusions: Regular cannabis use appears to suppress the impact of HIV on spontaneous and oscillatory alpha deficits in the left inferior frontal cortex and dlPFC.
Simulation‐based team‐training in acute stroke: Is it safe to speed up?

In acute ischemic stroke (AIS), rapid treatment with intravenous thrombolysis (IVT) is crucial for good clinical outcome. Weekly simulation‐based team‐training of the stroke treatment team was implemented, resulting in faster treatment times. The aim of this study was to assess whether this time reduction led to a higher proportion of stroke mimics (SMs) among patients who received IVT for presumed AIS, and whether these SM patients were harmed by intracranial hemorrhage (ICH).
Myelofibrosis progression grading based on type I and type III collagen and fibrillin 1 expression boosted by whole slide image analysis

Aims: The progression of primary myelofibrosis is characterised by ongoing extracellular matrix deposition graded based on ‘reticulin’ and ‘collagen’ fibrosis, as revealed by Gomori's silver impregnation. Here we studied the expression of the major extracellular matrix proteins of fibrosis in relation to diagnostic silver grading supported by image analysis.
The Effects of Virtual Reality in Maternal Delivery: Systematic Review and Meta-analysis

Background Extreme labor pain has negative effects; pharmacologic analgesic modalities are effective but are accompanied by adverse effects. Virtual reality (VR) works as a distracting nonpharmacologic intervention for pain and anxiety relief; however, the effects of VR use in laboring women is unknown. Objective Our study aimed to determine the safety and effectiveness of VR technology during labor and delivery and investigate whether it impacts labor and patient satisfaction. Methods In all, 7 databases (PubMed, Embase, Web of Science, the Cochrane Library, CINAHL, China National Knowledge Infrastructure, and Wan-Fang Database) were systematically searched for randomized controlled trials of VR use in pregnancy and childbirth from the time of database construction until November 24, 2021. Two researchers extracted data and evaluated study quality using the Cochrane Risk of Bias tool 2.0. Outcome measures were labor pain, anxiety, duration, satisfaction, and adverse events. Meta-analyses were performed where possible. Results A total of 12 studies with 1095 participants were included, of which 1 and 11 studies were rated as “Low risk” and “Some concerns” for risk of bias, respectively. Of the 12 studies, 11 reported labor pain, 7 reported labor anxiety, and 4 reported labor duration. Meta-analysis revealed that VR use could relieve pain during labor (mean difference –1.81, 95% CI –2.04 to –1.57; P<.001) and the active period (standardized mean difference [SMD] –0.41, 95% CI –0.68 to –0.14; P=.003); reduce anxiety (SMD –1.39, 95% CI –1.99 to –0.78; P<.001); and improve satisfaction with delivery (relative risk 1.32, 95% CI 1.10-1.59; P=.003). The effects of VR on the duration of the first (SMD –1.12, 95% CI –2.38 to 0.13; P=.08) and second (SMD –0.22, 95% CI –0.67 to 0.24; P=.35) stages of labor were not statistically significant. Conclusions VR is safe and effective in relieving maternal labor pain and anxiety; however, due to the heterogeneity among studies conducted to date, more rigorous, large-scale, and standardized randomized controlled trials are required to provide a higher-quality evidence base for the use of VR technology in maternal labor, with the aim of improving experience and outcomes. Trial Registration PROSPERO CRD42021295410; https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=295410
Longitudinal associations of relationship support and strain and internalized homophobia with mental health among middle-aged and older gay and bisexual men

Abstract Objectives: Mental health concerns (e.g. depression, anxiety) that negatively impact gay, bisexual, and other men who have sex with men (GBMSM) persist over the life course and into old age, but less is known about potential contributors to GBMSM’s mental health. Close relationships can be a source of risk or resilience from stress, exerting direct relationships on mental health, and may mediate well-established associations between minority stress and mental health. This study examined whether primary partner relationship support and strain were uniquely associated with, and mediated the association between internalized homophobia, and mental health among older GBMSM. Methods: GBMSM (N = 517, M age = 60) from the Multicenter AIDS Cohort Study, who were in primary relationships with men, provided self-report data at four timepoints. We used multilevel modeling to examine longitudinal associations among relationship support and strain and internalized homophobia with depression and anxiety. Results: Relationship strain, but not support, was positively associated with mental health concerns longitudinally. There was a significant, positive indirect effect of internalized homophobia on depression and anxiety through strain, but no support. Internalized homophobia was positively associated with relationship strain, which was positively associated with mental health symptoms longitudinally. Conclusions: Relationship strain was associated with depression and anxiety longitudinally among middle-aged and older GBMSM and mediated associations of internalized homophobia with mental health. The role of partner support warrants further investigation. Mental health interventions are critically needed for older GBMSM and, for partnered GBMSM, should include strategies for reducing relationship strain to foster well-being.
Open systems in classical mechanics

Author(s): Baez, John C; Weisbart, David; Yassine, Adam | Abstract: Span categories provide a framework for formalizing mathematical models of open systems in classical mechanics. The categories appearing in classical mechanics do not have pullbacks, which requires the use of generalized span categories. We introduce categories $\LagSy$ and $\HamSy$ that respectively provide a categorical framework for the Lagrangian and Hamiltonian descriptions of open classical mechanical systems. The morphisms of $\LagSy$ and $\HamSy$ correspond to such open systems, and composition of morphisms models the construction of systems from subsystems. The Legendre transformation gives a functor from $\LagSy$ to $\HamSy$ that translates from the Lagrangian to the Hamiltonian perspective.
Impact of probiotics on muscle mass, muscle strength and lean mass: a systematic review and meta‐analysis of randomized controlled trials

Probiotics have shown potential to counteract sarcopenia, although the extent to which they can influence domains of sarcopenia such as muscle mass and strength in humans is unclear. The aim of this systematic review and meta‐analysis was to explore the impact of probiotic supplementation on muscle mass, total lean mass and muscle strength in human adults. A literature search of randomized controlled trials (RCTs) was conducted through PubMed, Scopus, Web of Science and Cochrane Library from inception until June 2022. Eligible RCTs compared the effect of probiotic supplementation versus placebo on muscle and total lean mass and global muscle strength (composite score of all muscle strength outcomes) in adults (>18 years). To evaluate the differences between groups, a meta‐analysis was conducted using the random effects inverse‐variance model by utilizing standardized mean differences. Twenty‐four studies were included in the systematic review and meta‐analysis exploring the effects of probiotics on muscle mass, total lean mass and global muscle strength. Our main analysis (k = 10) revealed that muscle mass was improved following probiotics compared with placebo (SMD: 0.42, 95% CI: 0.10–0.74, I2 = 57%, P = 0.009), although no changes were revealed in relation to total lean mass (k = 12; SMD: ‐0.03, 95% CI: −0.19 – 0.13, I2 = 0%, P = 0.69). Interestingly, a significant increase in global muscle strength was also observed among six RCTs (SMD: 0.69, 95% CI: 0.33–1.06, I2 = 64%, P = 0.0002). Probiotic supplementation enhances both muscle mass and global muscle strength; however, no beneficial effects were observed in total lean mass. Investigating the physiological mechanisms underpinning different ageing groups and elucidating appropriate probiotic strains for optimal gains in muscle mass and strength are warranted.
NONO enhances mRNA processing of super‐enhancer‐associated GATA2 and HAND2 genes in neuroblastoma

High‐risk neuroblastoma patients have poor survival rates and require better therapeutic options. High expression of a multifunctional DNA and RNA‐binding protein, NONO, in neuroblastoma is associated with poor patient outcome; however, there is little understanding of the mechanism of NONO‐dependent oncogenic gene regulatory activity in neuroblastoma. Here, we used cell imaging, biochemical and genome‐wide molecular analysis to reveal complex NONO‐dependent regulation of gene expression. NONO forms RNA‐ and DNA‐tethered condensates throughout the nucleus and undergoes phase separation in vitro, modulated by nucleic acid binding. CLIP analyses show that NONO mainly binds to the 5′ end of pre‐mRNAs and modulates pre‐mRNA processing, dependent on its RNA‐binding activity. NONO regulates super‐enhancer‐associated genes, including HAND2 and GATA2. Abrogating NONO RNA binding, or phase separation activity, results in decreased expression of HAND2 and GATA2. Thus, future development of agents that target RNA‐binding activity of NONO may have therapeutic potential in this cancer context.
Novel Functional Peptide for Next-Generation Vital Pulp Therapy

Although vital pulp therapy should be performed by promoting the wound-healing capacity of dental pulp, existing pulp-capping materials were not developed with a focus on the pulpal repair process. In previous investigations of wound healing in dental pulp, we found that organic dentin matrix components (DMCs) were degraded by matrix metalloproteinase-20, and DMC degradation products containing protein S100A7 (S100A7) and protein S100A8 (S100A8) promoted the pulpal wound-healing process. However, the direct use of recombinant proteins as pulp-capping materials may cause clinical problems or lead to high medical costs. Thus, we hypothesized that functional peptides derived from recombinant proteins could solve the problems associated with direct use of such proteins. In this study, we identified functional peptides derived from the protein S100 family and investigated their effects on dental pulp tissue. We first performed amino acid sequence alignments of protein S100 family members from several mammalian sources, then identified candidate peptides. Next, we used a peptide array method that involved human dental pulp stem cells (hDPSCs) to evaluate the mineralization-inducing ability of each peptide. Our results supported the selection of 4 candidate functional peptides derived from proteins S100A8 and S100A9. Direct pulp-capping experiments in a rat model demonstrated that 1 S100A8-derived peptide induced greater tertiary dentin formation compared with the other peptides. To investigate the mechanism underlying this induction effect, we performed liquid chromatography–tandem mass spectrometry analysis using hDPSCs and the S100A8-derived peptide; the results suggested that this peptide promotes tertiary dentin formation by inhibiting inflammatory responses. In addition, this peptide was located in a hairpin region on the surface of S100A8 and could function by direct interaction with other molecules. In summary, this study demonstrated that a S100A8-derived functional peptide promoted wound healing in dental pulp; our findings provide insights for the development of next-generation biological vital pulp therapies.
Prospective and retrospective values integrated in frontal cortex drive predictive choice

Significance Animals must flexibly estimate the value of their actions (action-value) to successfully adapt to a changing environment. The brain is thought to estimate action-values from two different sources, namely the action-outcome history (retrospective value) and the knowledge of the environment (prospective value), but how different estimates of action-values are reconciled to make a choice is not well understood. Here we found that as mice learn the state-transition structure of a decision-making task, retrospective and prospective values become jointly encoded in the preparatory activity of neurons in ALM. Suppressing this preparatory activity in expert mice returned their behavior to a naïve state. These results reveal the neural circuit that injects structural knowledge into action selection to promote predictive decision-making.
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel

We propose a novel deterministic sampling method to approximate a target distribution $\rho^*$ by minimizing the kernel discrepancy, also known as the Maximum Mean Discrepancy (MMD). By employing the general \emph{energetic variational inference} framework (Wang et al., 2021), we convert the problem of minimizing MMD to solving a dynamic ODE system of the particles. We adopt the implicit Euler numerical scheme to solve the ODE systems. This leads to a proximal minimization problem in each iteration of updating the particles, which can be solved by optimization algorithms such as L-BFGS. The proposed method is named EVI-MMD. To overcome the long-existing issue of bandwidth selection of the Gaussian kernel, we propose a novel way to specify the bandwidth dynamically. Through comprehensive numerical studies, we have shown the proposed adaptive bandwidth significantly improves the EVI-MMD. We use the EVI-MMD algorithm to solve two types of sampling problems. In the first type, the target distribution is given by a fully specified density function. The second type is a"two-sample problem", where only training data are available. The EVI-MMD method is used as a generative learning model to generate new samples that follow the same distribution as the training data. With the recommended settings of the tuning parameters, we show that the proposed EVI-MMD method outperforms some existing methods for both types of problems.
Global Results for Eikonal Hamilton-Jacobi Equations on Networks

We study a one-parameter family of Eikonal Hamilton-Jacobi equations on an embedded network, and prove that there exists a unique critical value for which the corresponding equation admits global solutions, in a suitable viscosity sense. Such a solution is identified, via an Hopf-Lax type formula, once an admissible trace is assigned on an intrinsic boundary. The salient point of our method is to associate to the network an abstract graph, encoding all of the information on the complexity of the network, and to relate the differential equation to a discrete functional equation on the graph. Comparison principles and representation formulae are proven in the supercritical case as well.
ActFormer: A GAN-based Transformer towards General Action-Conditioned 3D Human Motion Generation

We present a GAN-based Transformer for general action-conditioned 3D human motion generation, including not only single-person actions but also multi-person interactive actions. Our approach consists of a powerful Action-conditioned motion TransFormer (ActFormer) under a GAN training scheme, equipped with a Gaussian Process latent prior. Such a design combines the strong spatio-temporal representation capacity of Transformer, superiority in generative modeling of GAN, and inherent temporal correlations from the latent prior. Furthermore, ActFormer can be naturally extended to multi-person motions by alternately modeling temporal correlations and human interactions with Transformer encoders. To further facilitate research on multi-person motion generation, we introduce a new synthetic dataset of complex multi-person combat behaviors. Extensive experiments on NTU-13, NTU RGB+D 120, BABEL and the proposed combat dataset show that our method can adapt to various human motion representations and achieve superior performance over the state-of-the-art methods on both single-person and multi-person motion generation tasks, demonstrating a promising step towards a general human motion generator. The project website can be found at https://liangxuy.github. io/actformer/.
New limit theorems related to free multiplicative convolution

Let $\boxplus$, $\boxtimes$ and $\uplus$ be the free additive, free multiplicative, and boolean additive convolutions, respectively. For a probability measure $\mu$ on $[0,\infty)$ with finite second moment, we find the scaling limit of $(\mu^{\boxtimes N})^{\boxplus N}$ as $N$ goes to infinity. The $\mathcal{R}$--transform of the limit distribution can be represented by the Lambert's $W$ function. We also find similar limit theorem by replacing the free additive convolution with the boolean convolution.
Functional Connectome: Approximating Brain Networks with Artificial Neural Networks

We aimed to explore the capability of deep learning to approximate the function instantiated by biological neural circuits - the functional connectome. Using deep neural networks, we performed supervised learning with ﬁring rate observations drawn from synthetically constructed neural circuits, as well as from an empirically supported Boundary Vector Cell–Place Cell network. The performance of trained networks was quantiﬁed using a range of criteria and tasks. Our results show that deep neural networks were able to capture the computations performed by synthetic biological networks with high accuracy, and were highly data efﬁcient and robust to biological plasticity. We show that trained deep neural networks are able to perform zero-shot generalisation in novel environments, and allows for a wealth of tasks such as decoding the animal’s location in space with high accuracy. Our study reveals a novel and promising direction in systems neuroscience, and can be expanded upon with a multitude of downstream applications, for example, goal-directed reinforcement learning.