Miracle-dz/UniFAR-FTUs huggingface dataset:
Cucurbitacin B Exerts Significant Antidepressant-Like Effects in a Chronic Unpredictable Mild Stress Model of Depression: Involvement of the Hippocampal BDNF-TrkB System

Abstract Background Although depression has been a serious neuropsychiatric disorder worldwide, current antidepressants used in clinical practice have various weaknesses, including delayed onset and low rates of efficacy. Recently, the development of new antidepressants from natural herbal medicine has become one of the important research hotspots. Cucurbitacin B is a natural compound widely distributed in the Cucurbitaceae and Cruciferae families and has many pharmacological activities. The present study aimed to investigate whether cucurbitacin B possess antidepressant-like effects in mice. Methods The antidepressant-like effects of cucurbitacin B on mice behaviors were explored using the forced swim test, tail suspension test, open field test, sucrose preference test, and a chronic unpredictable mild stress model of depression together. Then, western blotting and immunofluorescence were used to examine the effects of cucurbitacin B on the brain-derived neurotrophic factor (BDNF)-tyrosine kinase B (TrkB) signaling cascade and neurogenesis in the hippocampus of mice. Furthermore, BDNF-short hairpin RNA, K252a, and p-chlorophenylalanine methyl ester were adopted together to determine the antidepressant mechanism of cucurbitacin B. Results It was found that administration of cucurbitacin B indeed produced notable antidepressant-like effects in mice, which were accompanied with significant promotion in both the hippocampal BDNF-TrkB pathway and neurogenesis. The antidepressant mechanism of cucurbitacin B involves the hippocampal BDNF-TrkB system but not the serotonin system. Conclusions Cucurbitacin B has the potential to be a novel antidepressant candidate.
PolyQ Database—an integrated database on polyglutamine diseases

Abstract Polyglutamine (polyQ) diseases are neurodegenerative disorders caused by abnormally expanded Cytosine, Adenine, Guanine (CAG) triplet repeat sequences in the coding region of otherwise unrelated genes. Until now, nine different polyQ diseases have been described: Huntington’s disease, dentatorubral-pallidoluysian atrophy, spinal and bulbar muscular atrophy and six types of spinocerebellar ataxias—1, 2, 3, 6, 7 and 17. The pathogenic expansion translates into an aberrant tract of glutamines in the encoded proteins, compromising several cellular functions and biological processes. There is currently no cure available for the progressive neurodegenerative disorders caused by the ensuing cytotoxic alterations. Although each disease is considered rare, polyQ diseases constitute the largest group of monogenic neurodegenerative disorders. Information about these disorders is scattered among several books, articles and general databases, hindering exploration by students and researchers, but also by patients and their families. Therefore, we aimed to develop a free online database to fill this gap, by centralizing relevant available information. The PolyQ Database is a platform that focuses on all nine polyQ diseases and offers information about topics that are pertinent for scientists, clinicians and the general public, including epidemiology, the characteristics of the causative genes and the codified proteins, the pathophysiology of the diseases and the main clinical manifestations. The database is available at https://polyq.pt/, and it is the first of its kind, focusing exclusively on this group of rare diseases. The database was conceived to be continuously updated and allow incorporation and dissemination of the latest information on polyQ diseases.
Dynamics of viral disease outbreaks: A hundred years (1918/19–2019/20) in retrospect ‐ Loses, lessons and emerging issues

Infectious diseases continue to be the leading cause of morbidity and mortality, and a formidable obstacle to the development and well‐being of people worldwide. Viruses account for more than half of infectious disease outbreaks that have plagued the world. The past century (1918/19–2019/20) has witnessed some of the worst viral disease outbreaks the world has recorded, with overwhelming impact especially in low‐ and middle‐income countries (LMIC). The frequency of viral disease outbreak appears to be increasing. Generally, although infectious diseases have afflicted the world for centuries and humankind has had opportunities to examine the nature of their emergence and mode of spread, almost every new outbreak poses a formidable challenge to humankind, beating the existing pandemic preparedness systems, if any, and causing significant losses. These underscore inadequacy in our understanding of the dynamics and preparedness against viral disease outbreaks that lead to epidemics and pandemics. Despite these challenges, the past 100 years of increasing frequencies of viral disease outbreaks have engendered significant improvements in response to epidemics and pandemics, and offered lessons to inform preparedness. Hence, the increasing frequency of emergence of viral outbreaks and the challenges these outbreaks pose to humankind, call for the continued search for effective ways to tackle viral disease outbreaks in real time. Through a PRISMA‐based approach, this systematic review examines the outbreak of viral diseases in retrospect to decipher the outbreak patterns, losses inflicted on humanity and highlights lessons these offer for meaningful preparation against future viral disease outbreaks and pandemics.
A study of programmed death‐1/programmed death ligand and iodine‐induced autoimmune thyroiditis in NOD.H‐2h4 mice

Excess iodine will trigger the occurrence of autoimmune thyroiditis (AIT), and programmed death‐1 (PD‐1)/programmed death ligand (PD‐L) will also contribute to the development of AIT. The purpose of this study was to explore the role that negative regulatory signals mediated by PD‐1/PD‐L play in the development of spontaneous autoimmune thyroiditis (SAT) in NOD.H‐2h4 mice when they are exposed to iodine. Programmed death ligand 1 (PD‐L1) antibody was administered intraperitoneally to NOD.H‐2h4 mice. The relevant indicators were determined by flow cytometry, real‐time quantitative polymerase chain reaction, enzyme‐linked immunosorbent assay, immunohistochemistry, pathological hematoxylin and eosin staining, and arsenic–cerium catalytic spectrophotometry. Results showed that the level of urinary iodine, the level of thyroid lymphocyte infiltration, the level of thyroglobulin antibodies (TgAb) and interferon (IFN‐γ)/tumor necrosis factor (TNF‐α)/interleukin (IL‐2)/IL‐17, and the relative expression of PD‐1/PD‐L1/programmed death‐2 (PD‐L2) increased with the intervention of excess iodine. After the intervention of the PD‐L1 antibody, the expression of PD‐1/PD‐L1/PD‐L2 in different degrees was inhibited, but the level of thyroid lymphocyte infiltration and serum TgAb/IFN‐γ/TNF‐α/ IL‐2/IL‐17 did not decrease. Collectively, although PD‐1/PD‐L participates in the occurrence of SAT and induces inflammation, administration of the PD‐L1 antibody does not effectively improve the pathological process of SAT. More research is needed to determine whether PD‐1/PD‐L intervention can treat autoimmune thyroid disease.
The effect of returning turfgrass clippings on turfgrass sward yield.

The aim of the study was to analyse the effect of returned clippings on the yield of a turfgrass sward. The study was carried out on a sward established with a 50/50 seed mixture of Festuca rubra rubra and Poa pratensis. Seven fertilizer treatments (kg ha -1 ) were used with N varying between N0 and N400, P between P0 and P45 and K between K0 and K240. The sward was cut fifteen to twenty times during the growing season at a height of 5 cm. The clippings were either removed or returned to the plots. The effect of clippings on the sward yield was variable and fairly weak. On only one of the seven fertilization treatments, N240P34K144, did returned clippings increase the yield of the sward significantly (P>0.05). A positive effect of returned clippings appears only in those years when moisture conditions were sufficient for plant growth.
Comparison of carbon and nitrogen accumulation rate between bog and fen phases in a pristine peatland with the fen‐bog transition

Long‐term carbon and nitrogen dynamics in peatlands are affected by both vegetation production and decomposition processes. Here, we examined the carbon accumulation rate (CAR), nitrogen accumulation rate (NAR) and δ13C, δ15N of plant residuals in a peat core dated back to ~8500 cal year BP in a temperate peatland in Northeast China. Impacted by the tephra during 1160 and 789 cal year BP and climate change, the peatland changed from a fen dominated by vascular plants to a bog dominated by Sphagnum mosses. We used the Clymo model to quantify peat addition rate and decay constant for acrotelm and catotelm layers during both bog and fen phases. Our studied peatland was dominated by Sphagnum fuscum during the bog phase (789 to −59 cal year BP) and lower accumulation rates in the acrotelm layer was found during this phase, suggesting the dominant role of volcanic eruption in the CAR of the peat core. Both mean CAR and NAR were higher during the bog phase than during the fen phase in our study, consistent with the results of the only one similar study in the literature. Because the input rate of organic matter was considered to be lower during the bog phase, the decomposition process must have been much lower during the bog phase than during the fen phase and potentially controlled CAR and NAR. During the fen phase, CAR was also lower under higher temperature and summer insolation, conditions beneficial for decomposition. δ15N of Sphagnum hinted that nitrogen fixation had a positive effect on nitrogen accumulation, particular in recent decades. Our study suggested that decomposition is more important for carbon and nitrogen sequestration than production in peatlands in most conditions and if future climate changes or human disturbance increase decomposition rate, carbon sequestration in peatlands will be jeopardized.
Timing of hormone therapy and its association with cardiovascular risk and metabolic parameters in 4-vinylcyclohexene diepoxide-induced primary ovarian insufficiency mouse model

Abstract Objective To evaluate the effects of various initiation time points and durations of hormone therapy (HT) on cardiovascular and metabolic parameters of premenarche, primary ovarian insufficiency (POI) mouse model, induced by 4-vinylcyclohexene diepoxide. Methods A total of 50 mice at 4 weeks of age were developed into POI mouse model, further randomly categorized into 5 groups: control group without any intervention; no HT group with only high-fat diet (NT); group 1 with delayed estradiol treatment (T1); group 2 with on-time, continuous estradiol treatment (T2); and group 3 with on-time estradiol treatment but early stop (T3). Cardiovascular risk and metabolic parameters were measured. Results Presenting with similar body weights, blood glucose levels of T1, T2, and T3 were all significantly lower than NT (p < .001). Serum total cholesterol and insulin were also significantly lower in all HT groups than in NT, especially in T2 (p < .001). For serum low-density lipoprotein-cholesterol, only T2 resulted in the statically lower level than those of NT, T1, and T3 (p < .001). Aortic thickness was significantly increased with aggravated fibrotic change of the intima in NT, and such consequence was significantly ameliorated in HT groups, mostly lowered in T2 (p < .05). Last, serum pro-inflammatory cytokines were significantly low in the HT groups than in NT, especially in T2 with the lowest level (p < .05). Conclusions On-time, continuous E2 treatment immediately after a biologic estrogen deprivation event significantly reduced metabolic and cardiovascular risks in young, pre-menarche female mouse models of POI, confirming decreased serum levels of pro-inflammatory cytokines.
Status Assessment of Laysan and Black-Footed Albatrosses, North Pacific Ocean, 1923-2005

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs. gov or call 1-888-ASK-USGS For an overview of USGS information products, including maps, imagery, and publications, visit To order this and other USGS information products, visit http://store.usgs. gov Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted materials contained within this report. Figure 7. Graphs showing observed growth rate distribution (Robs) for the Laysan albatross breeding population, Laysan Island …………………………………… 29 Figure 8. Graphs showing population projection (A, n = 30) and cumulative probability (B) that a given rate of population change is reached over 60 years using the exponential model and re-analysis of transect data for Laysan albatross, Laysan Island ……………………………………………………………………… 31 Figure 9. Graphs showing observed growth rate distribution (Robs) for the Laysan albatross breeding population, French Frigate Shoals …………………………… 31 Figure 10. Graphs showing projection (A, n = 30) and cumulative probability (B) that a given rate of population change is reached over 60 years using the exponential model for Laysan albatross, French Frigate Shoals ………………… 33 Figure 11. Graph showing World Laysan albatross breeding population trend as derived from estimates for each island …………………………………………………… 33 Figure 12. Graphs showing potential growth rate (A) and net growth (B) for the Laysan albatross ………………………………………………………………………… 35 Figure 13. Graphs showing number of black-footed albatross breeding pairs at colonies from the 1920s until 2005 ………………………………………………………… 37 Figure 14. Graphs showing number of breeding pairs of black-footed albatross on Midway, Laysan, and French Frigate Shoals from the 1950s to 2005. …………… 38 Figure 15. Graphs showing observed growth rate distribution (Robs) for the black-footed albatross breeding population, Midway Atoll …………………………………… 40 Figure 16. Graphs showing population projection (A, n = 30) and cumulative probability (B) that a given rate of population change is reached over 60 years using the exponential model for black-footed albatross, Midway Atoll …………………… 40 Figure 17. Graph showing population estimates for black-footed albatross, Laysan Island. … 41 Figure 18. Graphs showing observed growth rate distribution (Robs) for the black-footed albatross breeding population, Laysan Island …………………………………… 44 Figure 19. Graphs showing population projection (A, n = 30) and cumulative probability (B) …
How do maternal androgens and estrogens affect sex determination in reptiles with temperature‐dependent sex?

Temperature sex determination (TSD) in reptiles has been studied to elucidate the mechanisms by which temperature is transformed into a biological signal that determines the sex of the embryo. Temperature is thought to trigger signals that alter gene expression and hormone metabolism, which will determine the development of female or male gonads. In this review, we focus on collecting and discussing important and recent information on the role of maternal steroid hormones in sex determination in oviparous reptiles such as crocodiles, turtles, and lizards that possess TSD. In particular, we focus on maternal androgens and estrogens deposited in the egg yolk and their metabolites that could also influence the sex of offspring. Finally, we suggest guidelines for future research to help clarify the link between maternal steroid hormones and offspring sex.
Landsat Thematic Mapper digital information content for agricultural environments

Landsat Thematic Mapper (TM) data collected for Imperial Valley, California in December, 1982 were digitally examined to assess their utility to distinguish among agricultural and other land-covers. Statistics for thirty-seven training sites representing a variety of crops plus urban, water and desert land-covers were obtained and analyzed using transformed divergence (TD) calculations. TD values were employed to assess intraclass variability and the best bands for classification. Four subscenes were selected for clustering or unsupervised signature extraction. These areas were agriculture, urban, desert and water land-covers. The number of clusters for these subscenes were examined and the best TM bands for interclass separability were identified. The results of the clustering and training site analyses for interclass separability were compared. The TM data were useful for the digital delimitation of most crops and other cover types in this analysis. Four bands of data are adequate for classification with the best results obtained by the selection of one band from each of the available portions of the electromagnetic spectrum. Different band combinations are best for various land-cover intraclass separability.
Live Iterative Ptychography.

We demonstrate live-updating ptychographic reconstruction with the extended ptychographical iterative engine, an iterative ptychography method, during ongoing data acquisition. The reconstruction starts with a small subset of the total data, and as the acquisition proceeds the data used for reconstruction are extended. This creates a live-updating view of object and illumination that allows monitoring the ongoing experiment and adjusting parameters with quick turn around. This is particularly advantageous for long-running acquisitions. We show that such a gradual reconstruction yields interpretable results already with a small subset of the data. We show simulated live processing with various scan patterns, parallelized reconstruction, and real-world live processing at the hard X-ray ptychographic nanoanalytical microscope PtyNAMi at the PETRA III beamline.
We Don't Need No Adam, All We Need Is EVE: On The Variance of Dual Learning Rate And Beyond

In the rapidly advancing field of deep learning, optimising deep neural networks is paramount. This paper introduces a novel method, Enhanced Velocity Estimation (EVE), which innovatively applies different learning rates to distinct components of the gradients. By bifurcating the learning rate, EVE enables more nuanced control and faster convergence, addressing the challenges associated with traditional single learning rate approaches. Utilising a momentum term that adapts to the learning landscape, the method achieves a more efficient navigation of the complex loss surface, resulting in enhanced performance and stability. Extensive experiments demonstrate that EVE significantly outperforms existing optimisation techniques across various benchmark datasets and architectures.
Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification

Long-Term Person Re-Identification (LT-ReID) has become increasingly crucial in computer vision and biometrics. In this work, we aim to extend LT-ReID beyond pedestrian recognition to include a wider range of real-world human activities while still accounting for cloth-changing scenarios over large time gaps. This setting poses additional challenges due to the geometric misalignment and appearance ambiguity caused by the diversity of human pose and clothing. To address these challenges, we propose a new approach 3DInvarReID for (i) disentangling identity from non-identity components (pose, clothing shape, and texture) of 3D clothed humans, and (ii) reconstructing accurate 3D clothed body shapes and learning discriminative features of naked body shapes for person ReID in a joint manner. To better evaluate our study of LT-ReID, we collect a real-world dataset called CCDA, which contains a wide variety of human activities and clothing changes. Experimentally, we show the superior performance of our approach for person ReID. Code is available at http://cvlab.cse. msu.edu/project-reid3dinvar.html.
Software Architecture in Practice: Challenges and Opportunities

Software architecture has been an active research field for nearly four decades, in which previous studies make significant progress such as creating methods and techniques and building tools to support software architecture practice. Despite past efforts, we have little understanding of how practitioners perform software architecture related activities, and what challenges they face. Through interviews with 32 practitioners from 21 organizations across three continents, we identified challenges that practitioners face in software architecture practice during software development and maintenance. We reported on common software architecture activities at software requirements, design, construction and testing, and maintenance stages, as well as corresponding challenges. Our study uncovers that most of these challenges center around management, documentation, tooling and process, and collects recommendations to address these challenges.
Synergistic Integration of Large Language Models and Cognitive Architectures for Robust AI: An Exploratory Analysis

This paper explores the integration of two AI subdisciplines employed in the development of artificial agents that exhibit intelligent behavior: Large Language Models (LLMs) and Cognitive Architectures (CAs). We present three integration approaches, each grounded in theoretical models and supported by preliminary empirical evidence. The modular approach, which introduces four models with varying degrees of integration, makes use of chain-of-thought prompting, and draws inspiration from augmented LLMs, the Common Model of Cognition, and the simulation theory of cognition. The agency approach, motivated by the Society of Mind theory and the LIDA cognitive architecture, proposes the formation of agent collections that interact at micro and macro cognitive levels, driven by either LLMs or symbolic components. The neuro-symbolic approach, which takes inspiration from the CLARION cognitive architecture, proposes a model where bottom-up learning extracts symbolic representations from an LLM layer and top-down guidance utilizes symbolic representations to direct prompt engineering in the LLM layer. These approaches aim to harness the strengths of both LLMs and CAs, while mitigating their weaknesses, thereby advancing the development of more robust AI systems. We discuss the tradeoffs and challenges associated with each approach.
A Two-Part Machine Learning Approach to Characterizing Network Interference in A/B Testing

The reliability of controlled experiments, or"A/B tests,"can often be compromised due to the phenomenon of network interference, wherein the outcome for one unit is influenced by other units. To tackle this challenge, we propose a machine learning-based method to identify and characterize heterogeneous network interference. Our approach accounts for latent complex network structures and automates the task of"exposure mapping'' determination, which addresses the two major limitations in the existing literature. We introduce"causal network motifs'' and employ transparent machine learning models to establish the most suitable exposure mapping that reflects underlying network interference patterns. Our method's efficacy has been validated through simulations on two synthetic experiments and a real-world, large-scale test involving 1-2 million Instagram users, outperforming conventional methods such as design-based cluster randomization and analysis-based neighborhood exposure mapping. Overall, our approach not only offers a comprehensive, automated solution for managing network interference and improving the precision of A/B testing results, but it also sheds light on users' mutual influence and aids in the refinement of marketing strategies.