Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemogenetic Suppression of Medial Prefrontal-Dorsal Hippocampal Interactions Prevents Estrogenic Enhancement of Memory Consolidation in Female Mice

Visual Abstract The importance of the dorsal hippocampus (DH) in mediating the memory-enhancing effects of the sex-steroid hormone 17β-estradiol (E2) is well established. However, estrogen receptors (ERs) are highly expressed in other brain regions that support memory formation, including the medial prefrontal cortex (mPFC). The mPFC and DH interact to mediate the formation of several types of memory, and behavioral tasks that recruit the mPFC are enhanced by systemic E2 administration, making this region a prime candidate for investigating circuit-level questions regarding the estrogenic regulation of memory. Further, infusion of E2 directly into the DH increases dendritic spine density in both the DH and mPFC, and this effect depends upon rapid activation of cell-signaling pathways in the DH, demonstrating a previously unexplored interaction between the DH and mPFC that led us to question the role of the mPFC in object memory consolidation and the necessity of DH-mPFC interactions in the memory-enhancing effects of E2. Here, we found that infusion of E2 directly into the mPFC of ovariectomized mice increased mPFC apical spine density and facilitated object recognition and spatial memory consolidation, demonstrating that E2 in the mPFC increases spinogenesis and enhances on memory consolidation. Next, chemogenetic suppression of the mPFC blocked the beneficial effects of DH-infused E2 on memory consolidation, indicating that systems-level DH-mPFC interactions are necessary for the memory-enhancing effects of E2. Together, these studies provide evidence that E2 in the mPFC mediates memory formation, and reveal that the DH and mPFC act in concert to support the memory-enhancing effects of E2 in female mice.
Risks of budesonide/formoterol for the treatment of stable COPD: a meta-analysis

Purpose The aim of this study was to investigate the comparative risks of budesonide/formoterol, versus placebo or monotherapies, for the treatment of patients with stable COPD. Materials and methods We undertook a systematic search of the literature in PubMed, Embase, and the Cochrane Central Register of Controlled Trials, for randomized controlled trials (RCTs) comparing budesonide/formoterol with control regimens for the treatment of patients with stable COPD and at least 12 weeks of follow-up, meeting the inclusion criteria. Studies were reviewed, and OR with corresponding 95% CI was used to pool the results. Results A total of eight studies involving 9,254 patients met the inclusion criteria of this meta-analysis. Compared with placebo, combination therapy with budesonide/formoterol was associated with a significantly higher risk of adverse effects including oral candidiasis (OR: 3.09, 95% CI: 1.95–4.91) and dysphonia (OR: 2.76, 95% CI: 1.40–5.44), but not pneumonia (OR: 0.94, 95% CI: 0.64–1.37) or bronchitis (OR: 1.36, 95% CI: 0.95–1.95). A similar pattern was also evident for the comparison of formoterol with budesonide/formoterol, with increased occurrence of oral candidiasis (OR: 2.72, 95% CI: 1.33–5.58) and dysphonia (OR: 4.13, 95% CI: 1.95–8.76); however, there were no significant differences in pneumonia (OR: 1.31, 95% CI: 0.98–1.74) or bronchitis (OR: 1.05, 95% CI: 0.83–1.31). In contrast, compared with budesonide, combined budesonide/formoterol was associated with similar risks of adverse effects, including pneumonia (OR: 1.20, 95% CI: 0.60–2.39), bronchitis (OR: 0.95, 95% CI: 0.41–2.20), oral candidiasis (OR: 0.79, 95% CI: 0.41–1.53), and dysphonia (OR: 1.00, 95% CI: 0.40–2.47). Conclusion Combination therapy does not cause more adverse events, including pneumonia and bronchitis, than control (placebo, formoterol, or budesonide) treatment in patients with stable COPD, while there were higher risks of oral candidiasis and dysphonia compared with the non-inhaled corticosteroid group (placebo, formoterol).
PDES-A

In this article, we present experiences implementing a general Parallel Discrete Event Simulation (PDES) accelerator on a Field Programmable Gate Array (FPGA). The accelerator can be specialized to any particular simulation model by defining the object states and the event handling code, which are then synthesized into a custom accelerator for the given model. The accelerator consists of several event processors that can process events in parallel while maintaining the dependencies between them. Events are automatically sorted by a self-sorting event queue. The accelerator supports optimistic simulation by automatically keeping track of event history and supporting rollbacks. The architecture is limited in scalability locally by the communication and port bandwidth of the different structures. However, it is designed to allow multiple accelerators to be connected to scale up the simulation. We evaluate the design and explore several design trade-offs and optimizations. We show that the accelerator can scale to 64 concurrent event processors relative to the performance of a single event processor. At this point, the scalability becomes limited by contention on the shared structures within the datapath. To alleviate this bottleneck, we also develop a new version of the datapath that partitions the state and event space of the simulation but allows these partitions to share the use of the event processors. The new design substantially reduces contention and improves the performance with 64 processors from 49x to 62x relative to a single processor design. We went through two iterations of the design of PDES-A, first using Verilog and then using Chisel (for the partitioned version of the design). We report in this article on some observations in the differences in prototyping accelerators using these two different languages. PDES-A outperforms the ROSS simulator running on a 12-core Intel Xeon machine by a factor of 3.2x with less than 15% of the power consumption. Our future work includes building multiple interconnected PDES-A cores.
Origin of giant negative piezoelectricity in a layered van der Waals ferroelectric

Lattice topology and anisotropic chemical bonds underpin unusual negative longitudinal piezoelectricity in van der Waals solids. Recent research on piezoelectric materials is predominantly devoted to enhancing the piezoelectric coefficient, but overlooks its sign, largely because almost all of them exhibit positive longitudinal piezoelectricity. The only experimentally known exception is ferroelectric polymer poly(vinylidene fluoride) and its copolymers, which condense via weak van der Waals (vdW) interaction and show negative piezoelectricity. Here we report quantitative determination of giant intrinsic negative longitudinal piezoelectricity and electrostriction in another class of vdW solids—two-dimensional (2D) layered ferroelectric CuInP2S6. With the help of single crystal x-ray crystallography and density-functional theory calculations, we unravel the atomistic origin of negative piezoelectricity in this system, which arises from the large displacive instability of Cu ions coupled with its reduced lattice dimensionality. Furthermore, the sizable piezoelectric response and negligible substrate clamping effect of the 2D vdW piezoelectric materials warrant their great potential in nanoscale, flexible electromechanical devices.
Deep-learning jets with uncertainties and more

Bayesian neural networks allow us to keep track of uncertainties, for example in top tagging, by learning a tagger output together with an error band. We illustrate the main features of Bayesian versions of established deep-learning taggers. We show how they capture statistical uncertainties from finite training samples, systematics related to the jet energy scale, and stability issues through pile-up. Altogether, Bayesian networks offer many new handles to understand and control deep learning at the LHC without introducing a visible prior effect and without compromising the network performance.
Generalized Brewster Angle Effect in Thin-Film Optical Absorbers and Its Application for Graphene Hydrogen Sensing

The generalized Brewster angle (GBA) is the incidence angle at polarization by reflection for p- or s-polarized light. Realizing an s-polarization Brewster effect requires a material with magnetic response, which is challenging at optical frequencies since the magnetic response of materials at these frequencies is extremely weak. Here, we experimentally realize the GBA effect in the visible using a thin-film absorber system consisting of a dielectric film on an absorbing substrate. Polarization by reflection is realized for both p- and s-polarized light at different angles of incidence and multiple wavelengths. We provide a theoretical framework for the generalized Brewster effect in thin-film light absorbers. We demonstrate hydrogen gas sensing using a single-layer graphene film transferred on a thin-film absorber at the GBA with ∼1 fg/mm2 aerial mass sensitivity. The ultrahigh sensitivity stems from the strong phase sensitivity near the point of darkness, particularly at the GBA, and the strong light–matter interaction in planar nanocavities. These findings depart from the traditional domain of thin films as mere interference optical coatings and highlight its many potential applications including gas sensing and biosensing.
SN1991bg-like supernovae are associated with old stellar populations

Abstract SN1991bg-like supernovae are a distinct subclass of thermonuclear Type Ia supernovae (SNe Ia). Their spectral and photometric peculiarities indicate that their progenitors and explosion mechanisms differ from ‘normal’ SNe Ia. One method of determining information about supernova progenitors we cannot directly observe is to observe the stellar population adjacent to the apparent supernova explosion site to infer the distribution of stellar population ages and metallicities. We obtain integral field observations and analyse the spectra extracted from regions of projected radius $\sim\,\text{kpc}$ about the apparent SN explosion site for 11 91bg-like SNe in both early- and late-type galaxies. We utilise full-spectrum spectral fitting to determine the ages and metallicities of the stellar population within the aperture. We find that the majority of the stellar populations that hosted 91bg-like supernovae have little recent star formation. The ages of the stellar populations suggest that that 91bg-like SN progenitors explode after delay times of >6 Gyr, much longer than the typical delay time of normal SNe Ia, which peaks at $\sim$1 Gyr.
Genes Involved in Oxidative Stress Pathways Are Differentially Expressed in Circulating Mononuclear Cells Derived From Obese Insulin-Resistant and Lean Insulin-Sensitive Individuals Following a Single Mixed-Meal Challenge

Background: Oxidative stress induced by nutritional overload has been linked to the pathogenesis of insulin resistance, which is associated with metabolic syndrome, obesity, type 2 diabetes and diabetic vascular complications. Postprandial changes in expression of oxidative stress pathway genes in obese vs. lean individuals, following intake of different types of meals varying in macronutrient composition have not been characterized to date. Here we aimed to test whether/how oxidative stress responses in obese vs. lean individuals are modulated by meal composition. Methods: High-carbohydrate (HC), high-fat (HF), or high-protein (HP) liquid mixed meals were administered to study subjects (lean insulin-sensitive, n = 9 and obese insulin-resistant, n = 9). Plasma levels of glucose and insulin, lipid profile, urinary F2-isoprostanes (F2-IsoP), and expression levels of genes of oxidative stress pathways were assessed in mononuclear cells (MNC) derived from fresh peripheral blood, at baseline and up to 6-h postprandial states. Differences in these parameters were compared between insulin-sensitive/resistant groups undergoing aforementioned meal challenges. Results: Obese individuals exhibited increased pro-oxidant (i.e., CYBB and CYBA) and anti-oxidant (i.e., TXN RD1) gene expression in the postprandial state, compared with lean subjects, regardless of meal type (P interaction for group × time < 0.05). By contrast, lean subjects had higher expression of NCF-4 gene (pro-oxidant) after HC meal and SOD1 gene (anti-oxidant) after HC and HF meals (P interaction for group × meal < 0.05). There was an increase in postprandial level of urinary F2-IsoP in the obese (P < 0.05) but not lean group. Conclusions: These findings may represent an adaptive oxidative response to mitigate increased stress induced by acute nutritional excess. Further, the results suggest an increased predisposition of obese subjects to oxidative stress. Chronic nutritional excess resulting in increases in body weight and adiposity might lead to decompensation leading to worsening insulin resistance and its sequel. Insights from this study could impact on nutritional recommendations for obese subjects at high-risk of cardiovascular diseases.
Active learning for logistic regression

Which active learning methods can we expect to yield good performance in learning logistic regression classifiers? Addressing this question is a natural first step in providing robust solutions for active learning across a wide variety of exponential models including maximum entropy, generalized linear, loglinear, and conditional random field models. We extend previous work on active learning using explicit objective functions by developing a framework for implementing a wide class of loss functions for active learning of logistic regression, including variance (A-optimality) and log loss reduction. We then run comparisons against the most widely used heuristic schemes: query by committee and uncertainty sampling, to discover which methods work best for different classes of problems and why. Our empirical evaluations are the largest effort to date to evaluate explicit objective function methods in active learning. We employed ten data sets in the evaluation from domains such as image recognition and document classification. The data sets vary in number of categories from 2 to 26 and have as many as 6,191 predictors. This work establishes the benefits of these often cited (but rarely used) strategies, and counters the claim that experimental design methods are too computationally complex to run on interesting data sets. The two loss functions were the only methods we tested that always performed at least as well as a randomly selected training set. The same data were used to evaluate several heuristic methods including variants of uncertainty sampling and query by committee. Uncertainty sampling was tested using two different measures of uncertainty: Shannon entropy and margin size. Margin-based uncertainty sampling was found to be superior; however, both methods perform worse than random sampling at times. We show that these failures to match random sampling can be caused by predictor space regions of varying noise or model mismatch. The various heuristics produced mixed results overall in the evaluation, and it is impossible to select one as particularly better than the others when using classifier accuracy as the sole criterion for performance. Margin sampling is the favored approach when computational time is considered along with accuracy.
The Effect of Disease and Season to Hepatopancreas and Intestinal Mycobiota of Litopenaeus vannamei

Increasing evidence has manifested that the gut bacterial microbiota of shrimps is closely related to the environmental factors, host developmental stage and health status like that of humans and animals does. These studies have provided an important guidance for improving shrimp culture benefits. In practice, aside from bacteria, eukaryotic microorganisms dominated by fungal microbiota (mycobiota), also play a key role in host growth, metabolism and homeostasis. However, little so far is known about the mycobiota in the digestive tract of shrimp. In this study, we used high-throughput sequencing of internal transcribed spacer 1 region to characterize the hepatopancreas and intestinal mycobiota of Pacific white shrimp and their connections with disease incidence and seasonal variation. The results showed that the hepatopancreas and intestinal mycobiota of Litopenaeus vannamei are dominated by the phyla Ascomycota and Basidiomycota, and the genera Alternaria, Tuber, Hortaea, Sarocladium, and Stagonospora. The fungal microbiota significantly varies under the influence of disease and seasonal variation. Sick shrimps had a higher level of potential pathogenic fungus, Candida in the intestine. Healthy shrimps had a higher abundance of the genera Didymella and Filobasidium in the gut, and Pyrenochaetopsis in the hepatopancreas. Of note, most of the fungi carried by Pacific white shrimps were pathogens to humans. This study has revealed the intestinal and hepatopancreas mycobiota of L. vannamei and the effects of diseases and seasonal variation to the mycobiota. Our study provides important guidance for Pacific white shrimp farming and sheds further insight on the fungal microbiota.
VITAMIN-E: VIsual Tracking and MappINg With Extremely Dense Feature Points

In this paper, we propose a novel indirect monocular simultaneous localization and mapping (SLAM) algorithm called "VITAMIN-E," which is highly accurate and robust as a result of tracking extremely dense feature points. Typical indirect methods have difficulty in reconstructing dense geometry because of their careful feature point selection for accurate matching. Unlike conventional methods, the proposed method processes an enormous number of feature points using the tracking local extrema of curvature based on dominant flow estimation. Because this may lead to high computational cost during bundle adjustment, we propose a novel optimization technique called the "subspace Newton's method" that significantly improves the computational efficiency of bundle adjustment by partially updating the variables. We concurrently generate meshes from the reconstructed points and merge them for an entire three-dimensional(3D) model. Experimental results on the SLAM benchmark EuRoC demonstrated that the proposed method outperformed state-of-the-art SLAM methods such as DSO, ORB-SLAM, and LSD-SLAM, both in terms of accuracy and robustness in trajectory estimation. The proposed method simultaneously generated significantly detailed 3D geometry as a result of the dense feature points in real time using only a CPU.
Transgenic Exosomes for Thymus Regeneration

During senescence, Wnt4 expression is down-regulated (unlike their Frizzled receptors), while PPARgamma expression increases in the thymus. Together, these changes allow for thymic degeneration to occur, observed as adipose involution. However, when restored, Wnt4 can efficiently counteract PPARgamma and prevent thymic senescence from developing. The Wnt-pathway activator miR27b has also been reported to inhibit PPARgamma. Our goal was to evaluate the Wnt4 and miR27b levels of Wnt4-transgenic thymic epithelial cell (TEC)-derived exosomes, show their regenerative potential against age-related thymic degeneration, and visualize their binding and distribution both in vitro and in vivo. First, transgenic exosomes were harvested from Wnt4 over-expressing TECs and analyzed by transmission electron microscopy. This unveiled exosomes ranging from 50 to 100 nm in size. Exosomal Wnt4 protein content was assayed by ELISA, while miR27b levels were measured by TaqMan qPCR, both showing elevated levels in transgenic exosomes relative to controls. Of note, kit-purified TEI (total exosome isolate) outperformed UC (ultracentrifugation)-purified exosomes in these parameters. In addition, a significant portion of exosomal Wnt4 proved to be displayed on exosomal surfaces. For functional studies, steroid (Dexamethasone or DX)-induced TECs were used as cellular aging models in which DX-triggered cellular aging was efficiently prevented by transgenic exosomes. Finally, DiI lipid-stained exosomes were applied on the mouse thymus sections and also iv-injected into mice, for in vitro binding and in vivo tracking, respectively. We have observed distinct staining patterns using DiI lipid-stained transgenic exosomes on sections of young and aging murine thymus samples. Moreover, in vivo injected DiI lipid-stained transgenic exosomes showed detectable homing to the thymus. Of note, Wnt4-transgenic exosome homing outperformed control (Wnt5a-transgenic) exosome homing. In summary, our findings indicate that exosomal Wnt4 and miR27b can efficiently counteract thymic adipose involution. Although extrapolation of mouse results to the human setting needs caution, our results appoint transgenic TEC exosomes as promising tools of immune rejuvenation and contribute to the characterization of the immune-modulatory effects of extracellular vesicles in the context of regenerative medicine.
Multifractal Desynchronization of the Cardiac Excitable Cell Network During Atrial Fibrillation. II. Modeling

In a companion paper (I. Multifractal analysis of clinical data), we used a wavelet-based multiscale analysis to reveal and quantify the multifractal intermittent nature of the cardiac impulse energy in the low frequency range ≲ 2Hz during atrial fibrillation (AF). It demarcated two distinct areas within the coronary sinus (CS) with regionally stable multifractal spectra likely corresponding to different anatomical substrates. The electrical activity also showed no sign of the kind of temporal correlations typical of cascading processes across scales, thereby indicating that the multifractal scaling is carried by variations in the large amplitude oscillations of the recorded bipolar electric potential. In the present study, to account for these observations, we explore the role of the kinetics of gap junction channels (GJCs), in dynamically creating a new kind of imbalance between depolarizing and repolarizing currents. We propose a one-dimensional (1D) spatial model of a denervated myocardium, where the coupling of cardiac cells fails to synchronize the network of cardiac cells because of abnormal transjunctional capacitive charging of GJCs. We show that this non-ohmic nonlinear conduction 1D modeling accounts quantitatively well for the “multifractal random noise” dynamics of the electrical activity experimentally recorded in the left atrial posterior wall area. We further demonstrate that the multifractal properties of the numerical impulse energy are robust to changes in the model parameters.
BLITZ

Event-triggered wireless sensing systems are an important class of wireless sensor network, where the detection of non-deterministic events enables the monitoring and control of processes in industries such as manufacturing, healthcare, and agriculture. The system properties of low latency, energy efficiency, and adaptability make event-triggered wireless sensing systems a key technological enabler for the Industrial Internet of Things. Wireless sensing systems based on periodic multi-hop communication exhibit a fundamental trade-off between latency and energy efficiency, which is unfavorable for event-triggered application scenarios. To address this technological gap, we present Blitz, the first communication architecture that combines asynchronous and synchronous flooding primitives to facilitate low latency and energy-efficient multi-hop communication of non-deterministic events. Blitz also incorporates a novel scheme for mitigating erroneous wake-ups, which is shown analytically and experimentally to further reduce energy consumption. We present a prototype implementation of Blitz and evaluate its performance in an indoor testbed deployment. Experiments show that BLITZ supports a mean latency as low as 108.9ms for an 8-bit event packet and its associated data packet of 32 bytes through a 4-hop network, and a power dissipation of 16μW during periods of inactivity.