Miracle-dz/UniFAR-FTUs huggingface dataset:
Copepodamides in marine and freshwater copepods-similar but different

Marine copepods, the most abundant group of zooplankton in the worlds oceans, imprint their surrounding waters with chemical cues, called copepodamides. Copepodamides induce defensive traits such as toxin production, bioluminescence, and colony size plasticity in a variety of marine phytoplankton. The role of copepodamides in freshwater ecosystems is, however, unknown. Here we report the consistent presence of copepodamides in copepods from six Swedish lakes. Copepodamide concentrations in freshwater copepods are similar to those of marine copepods, around 0.1 ppt of dry mass in millimetre sized individuals. The composition substantially overlaps with marine copepodamides but is also distinctly different. Freshwater copepods are largely dominated by one of the two subgroups of copepodamides, the dihydro-copepodamides, whereas marine copepods more commonly contain representatives from both subgroups. We describe 10 new copepodamide structures, four of which only found in freshwater copepods. Taxonomic groups had consistent copepodamide profiles across sampling sites and timepoints, supporting the presence of species specific copepodamide signatures. The presence of copepodamides in freshwater environments warrants study into their potential function as predator alarm cues also in freshwater systems.
Testing of putative antiseizure drugs in a preclinical Dravet syndrome zebrafish model

Dravet syndrome (DS) is a severe genetic epilepsy primarily caused by de novo mutations in a voltage-activated sodium channel gene (SCN1A). Patients face life-threatening seizures that are largely resistant to available anti-seizure medications (ASM). Preclinical DS animal models are a valuable tool to identify candidate ASMs for these patients. Among these, scn1lab mutant zebrafish exhibiting spontaneous seizure-like activity are particularly amenable to large-scale drug screening. Prior screening in a scn1lab mutant zebrafish line generated using N-ethyl-N-nitrosourea (ENU) identified valproate, stiripentol, and fenfluramine e.g., Federal Drug Administration (FDA) approved drugs with clinical application in the DS population. Successful phenotypic screening in scn1lab mutant zebrafish consists of two stages: (i) a locomotion-based assay measuring high-velocity convulsive swim behavior and (ii) an electrophysiology-based assay, using in vivo local field potential (LFP) recordings, to quantify electrographic seizure-like events. Using this strategy more than 3000 drug candidates have been screened in scn1lab zebrafish mutants. Here, we curated a list of nine additional anti-seizure drug candidates recently identified in preclinical models: 1-EBIO, AA43279, chlorzoxazone, donepezil, lisuride, mifepristone, pargyline, soticlestat and vorinostat. First-stage locomotion-based assays in scn1lab mutant zebrafish identified only 1-EBIO, chlorzoxazone and lisuride. However, second-stage LFP recording assays did not show significant suppression of spontaneous electrographic seizure activity for any of the nine anti-seizure drug candidates. Surprisingly, soticlestat induced frank electrographic seizure-like discharges in wild-type control zebrafish. Taken together, our results failed to replicate clear anti-seizure efficacy for these drug candidates highlighting a necessity for strict scientific standards in preclinical identification of ASMs.
Only cortical prediction error signals are involved in visual learning, despite availability of subcortical prediction error signals

Both the midbrain systems, encompassing the ventral striatum (VS), and the cortical systems, including the dorsal anterior cingulate cortex (dACC), play roles in reinforcing and enhancing learning. However, the specific contributions of signals from these regions in learning remains unclear. To investigate this, we examined how VS and dACC are involved in visual perceptual learning (VPL) through an orientation discrimination task. In the primary experiment, subjects fasted for 5 hours before each of 14 days of training sessions and 3 days of test sessions. Subjects were rewarded with water for accurate trial responses. During the test sessions, BOLD signals were recorded from regions including VS and dACC. Although BOLD signals in both areas were associated with positive and negative RPEs, only those in dACC associated with negative RPE showed a significant correlation with performance improvement. Additionally, no significant correlation was observed between BOLD signals associated with RPEs in VS and dACC. These results suggest that although signals associated with positive and negative RPEs from both midbrain and cortical systems are readily accessible, only RPE signals in the prefrontal system, generated without linking to RPE signals in VS, are utilized for the enhancement of VPL.
Effects of berberine on growth performance, intestinal microbial, SCFAs, and immunity for Ira rabbits

Berberine (BBR), recognized for its anti-inflammatory and bactericidal properties, has been extensively studied for its effects on mammalian gut microbiota. This study specifically addresses the need for more research on the regulatory effects of BBR on the gut microbiota of Ira rabbits. To fill this gap, we administered varying concentrations of BBR to weaned Ira rabbits to assess its impact on their growth and gut microbiota. In our experiment, 245 healthy weaned rabbits, aged 33 days, were randomly assigned into five groups. The CG group received a standard diet, while groups I, II, III, and IV were given diets supplemented with BBR at doses of 5 mg/kg, 10 mg/kg, 20 mg/kg, and 40 mg/kg, respectively. A 7-day pre-feeding period was implemented for acclimatization, followed by a 30-day experimental phase. The results revealed that BBR significantly improved the Average Daily Feed Intake (ADFI) and Average Daily Gain (ADG) of the rabbits. Notably, group III showed a significantly higher final weight compared to other groups (P<0.05). BBR supplementation also increased serum levels of GSH-Px, SOD, and T-AOC, while decreasing MDA levels compared to the control group (P<0.05). It also upregulated pro-inflammatory mediators IL-1β, IL-6, and TNF-α, and downregulated anti-inflammatory mediators IL-10 and TGF-β1. Furthermore, BBR treatment led to a significant increase in Short-Chain Fatty Acids (SCFAs), specifically acetic and butyric acids (P<0.05). Regarding gut microbiota, BBR significantly enhanced the relative abundance of Bacteroidota and Verrucomicrobiota at the phylum level and reduced Firmicutes (P<0.05). At the genus level, there was a significant increase in Akkermansia and Alistipes and a decrease in Ruminococcus (P<0.05). Overall, BBR appears to promote the growth of Ira rabbits by enriching beneficial bacteria, modulating inflammatory mediators in the TLR4/NF-κB pathway, and reducing inflammation and oxidative stress. Among the tested dosages, 20 mg/kg BBR had the most substantial impact.
Mitochondria possess a large, non-selective ionic current that is enhanced during cardiac injury

Mitochondrial ion channels are essential for energy production and cell survival. To avoid depleting the electrochemical gradient used for ATP synthesis, channels so far described in the mitochondrial inner membrane open only briefly, are highly ion-selective, have restricted tissue distributions, or have small currents. Here, we identify a mitochondrial inner membrane conductance that has strikingly different behavior from previously described channels. It is expressed ubiquitously, and transports cations non-selectively, producing a large, up to nanoampere-level, current. The channel does not lead to inner membrane uncoupling during normal physiology because it only becomes active at depolarized voltages. It is inhibited by external Ca2+, corresponding to the intermembrane space, as well as amiloride. This large, ubiquitous, non-selective, amiloride-sensitive (LUNA) current appears most active when expression of the mitochondrial calcium uniporter is minimal, such as in the heart. In this organ, we find that LUNA current magnitude increases two- to threefold in multiple mouse models of injury, an effect also seen in cardiac mitochondria from human patients with heart failure with reduced ejection fraction. Taken together, these features lead us to speculate that LUNA current may arise from an essential protein that acts as a transporter under physiological conditions, but becomes a channel under conditions of mitochondrial stress and depolarization.
Convergent evolution of monocyte differentiation in adult skin permits repair of the Langerhans cell network

Langerhans cells (LCs) are a unique population of phagocytes programmed within embryonic skin to maintain tissue and immunological homeostasis at the epidermal barrier site. Unique amongst tissue-resident macrophages, LCs play roles in skin innervation and repair, while also functioning as migrating professional antigen presenting cells, a capability classically assigned to dendritic cells (DC). We currently lack insight into the molecular pathways that determine this dichotomy, when they are established, and whether precursors recruited to the adult skin niche access the same instructive signals laid down in utero . Tracking differentiation of monocyte-derived (m)LCs after destruction of embryo-derived cells in murine adult skin, we reveal intrinsic intra-epidermal heterogeneity and selection of MDP-monocytes to by-pass gene programs specifying a macrophage fate. Within the adult skin, we demonstrate that the hair follicle niche provides Notch signals that determine commitment to become resident mLCs. Using a unique human LC dataset, we show that embryo-derived (e)LCs in newborn human skin retain transcriptional evidence of their macrophage origin, but this is superseded by distinct DC-like immune modules after expansion of the eLC network. Thus, convergent differentiation of monocytes within adult skin replicates conditioning of eLC towards more immunogenic DC-like cells within post-natal skin.
Speeding up iterative applications of the BUILD supertree algorithm

The Open Tree of Life (OToL) project produces a supertree that summarizes phylogenetic knowledge from tree estimates published in the primary literature. The supetree construction algorithm iteratively calls Aho’s Build algorithm thousands of times in order to assess the compatability of different phylogenetic groupings. We describe an incrementalized version of the Build algorithm that is able to share work between successive calls to Build. We provide details that allow a programmer to implement the incremental algorithm BuildInc, including pseudo-code and a description of data structures. We assess the effect of BuildInc on our supertree algorithm by analyzing simulated data and by analyzing a supertree problem taken from the OToL 13.4 synthesis tree. We find that BuildInc provides up to 550-fold speedup for our supertree algorithm.
Age-related differences in affective behaviors in mice: possible role of prefrontal cortical-hippocampal functional connectivity and metabolomic profiles

The differential expression of emotional reactivity from early to late adulthood may involve maturation of prefrontal cortical responses to negative valence stimuli. In mice, age-related changes in affective behaviors have been reported, but the functional neural circuitry warrants further investigation. We assessed age variations in affective behaviors and functional connectivity in male and female C57BL6/J mice. Mice aged 10, 30 and 60 weeks (wo) were tested over 8 weeks for open field activity, sucrose preference, social interactions, fear conditioning, and functional neuroimaging. Prefrontal cortical and hippocampal tissues were excised for metabolomics. Our results indicate that young and old mice differ significantly in affective behavioral, functional connectome and prefrontal cortical-hippocampal metabolome. Young mice show a greater responsivity to novel environmental and social stimuli compared to older mice. Conversely, late middle-aged mice (60wo group) display variable patterns of fear conditioning and with re-testing with a modified context. Functional connectivity between a temporal cortical/auditory cortex network and subregions of the anterior cingulate cortex and ventral hippocampus, and a greater network modularity and assortative mixing of nodes was stronger in young versus older adult mice. Metabolome analyses identified differences in several essential amino acids between 10wo mice and the other age groups. The results support differential expression of ‘emotionality’ across distinct stages of the mouse lifespan involving greater prefrontal-hippocampal connectivity and neurochemistry.
Human RAD52 double-ring remodels replication forks restricting fork reversal

Human RAD521,2 is a multifunctional DNA repair protein involved in several cellular events that support genome stability including protection of stalled DNA replication forks from excessive degradation3-7. In its gatekeeper role, RAD52 binds to and stabilizes stalled replication forks during replication stress protecting them from reversal by SMARCAL15. The structural and molecular mechanism of the RAD52-mediated fork protection remains elusive. Here, using P1 nuclease sensitivity, biochemical and single-molecule analyses we show that RAD52 dynamically remodels replication forks through its strand exchange activity. The presence of the ssDNA binding protein RPA at the fork modulates the kinetics of the strand exchange without impeding the reaction outcome. Mass photometry and single-particle cryo-electron microscopy show that the replication fork promotes a unique nucleoprotein structure containing head-to-head arrangement of two undecameric RAD52 rings with an extended positively charged surface that accommodates all three arms of the replication fork. We propose that the formation and continuity of this surface is important for the strand exchange reaction and for competition with SMARCAL1.
A Method for Sampling the Living Wood Microbiome

Efforts to characterize microbial life across diverse environments have progressed tremendously, yet the microbiome of Earth’s largest biomass reservoir—the wood of living trees—has been largely unexplored. Current understanding of the tree microbiome is largely confined to roots and leaves, with little attention given to the endophytic microbiome of wood, even though emergent studies have indicated this zone as a niche for unique taxa, of consequence for ecosystem health and global biogeochemical cycles. The lack of investigation derives partly from the physical recalcitrance of wood, which presents challenges during sampling, homogenization, and the extraction of nucleic acids. In response to these issues, we present an optimized method for processing wood for use in microbial analyses, from sampling through to downstream analyses. Using methane-cycling taxa as model endophytes, we assess losses in recovery during our method, and determine a limit-of-detection of approximately 500 cells per 100 mg of (dry) wood. For all six species evaluated—which represented several diverse taxa of hardwoods and softwoods—PCR inhibition proved minimal, and we expect this method to be applicable for a majority of tree species. The methods presented herein can facilitate future investigation into the wood microbiome and global microbial ecology of methane cycling.
AFL-RL: A Reinforcement Learning Based Mutation Scheduling Optimization Method for Fuzzing

As the development paradigm of the next generation Internet, the metaverse aims to build a fully immersive, supra-temporal and self-sustaining virtual shared space, which is regarded as an important application for the next generation of people to socialize, entertain and work. However, the serious privacy violations and security vulnerabilities of the metaverse affect its extensive development and application deployment. In order to locate security vulnerabilities in metaverse software as early as possible, many vulnerability mining techniques have been applied to vulnerability detection, and fuzzing is one of the most effective techniques. However, the traditional fuzzing technology has great blindness when mutating samples, which seriously affects its work efficiency. To solve the above problems, this paper proposes a method based on improving TD3 deep reinforcement learning algorithm to improve traditional fuzzing technology, and conducts preliminary tests and evaluation on libtiff, ffmpeg and other software, which verifies the effectiveness and feasibility of this method. CCS CONCEPTS • Security and privacy∼Software and application security∼Software security engineering
Antibacterial Potential of Achyranthus aspera Linn Procured from Himachal Pradesh, Punjab and Haryana, India

Achyranthus aspera, Family: Amaranthaceae was procured from Himachal Pradesh, Punjab and Haryana regions in the month of January-2010. Methanol extract of dried whole plants of Achyranthus aspera was evaluated against bacterial species viz., Bacillus cereus, Escherchia coli, Acinetobacter baumanii Staphylococcus aureus, Klebsiella pneumoniae, Proteus mirabilis, Pseudomonas aeruginosa and Salmonella typhi. The plants procured from Himachal Pradesh showed the best antimicrobial activity followed by Punjab and Haryana region respectively. Escherchia coli was maximally inhibited (24mm±0.5) by the plants from Himachal Pradesh region followed by Klebsiella pneumoniae (23mm±0.7) and Bacillus cereus (20mm±0.51) at the concentration of 2000µg. The zone of inhibition could not be detected at 500 µg for Proteus mirabilis, Pseudomonas aeruginosa, from all the locations investigated and at 1000 µg also, no inhibition was observed in plant samples collected from Haryana region. All the bacterial species were found susceptible to methanolic extract of whole plants of Achyranthes aspera however at high concentrations.
A Moving Object Query Method Based on the Cache Hit Rate in the Domestic Platform

The GPS positioning sensors enable mobile devices to generate amounts of location-based data, such as trajectory, gyro, and GPS data. One meaningful work is efficient querying and managing moving objects. Querying moving objects are widely used in several applications, including shopping centers, tourist attractions, and location-based advertising. Traditional methods search for moving objects without good performance in the long-term moving objects. The strategies for processing moving objects are focused on trajectories. Besides, there is no support for querying the moving objects on the domestic platform. Thus, in this paper, we proposed a novel moving objects model and a new query method based on the cache hit rate in the domestic platform. First, we modeled different moving objects in the PostgreSQL database and designed the type of MPoint, MLineString, MPolygon, Mint, MDouble, etc. Then, we proposed the strategy of segmenting long-term moving objects, to reduce the time of traversals of long-term moving objects. Finally, we built the experiment evaluation by using the BerlinMOD benchmark, we compared our algorithm with SECONDO to verify the performance of the proposed algorithm in terms of query time.
Research on Optimization Method of Visual Odometer Based on Point Line Feature Fusion

In low-texture-scenes, point feature based simultaneous location and map (SLAM) building algorithms are difficult to extract enough valid feature points, so that the SLAM system cannot work properly. To solve such problems, this paper proposes a visual SLAM algorithm for fusion of point and line features. On the basis of ORB point feature extraction, the LSD line feature algorithm is introduced and the extracted line segments are represented by the Plücker coordinate method. In the online feature matching stage, the LBD line segment descriptor is introduced, and the quadtree algorithm is used to avoid the concentration problem of point feature extraction. The progressive sampling uniformity (PROSAC) algorithm and geometric constraints are used to filter out incorrect matching of point line features, thereby improving positioning accuracy. Then, in the process of feature fusion, the idea of point line feature weighting is introduced to construct a new error function for point line fusion, minimizing the error function to obtain more accurate positioning information. Finally, the publicly available dataset was used to conduct experiments.
Assessment of Mental Health Problems among Deaf and Mute Adolescents

: Deaf and mute adolescents suffer from psychological stress, depression, anxiety, low self -esteem and lack of psychological services provided for them. Aim: the study aims to assess mental health problems and services of deaf and mute adolescents. Design: A descriptive correlational design was utilized in the current study.Sample: Aconvenient purposive sample (n =200 deaf and mute adolescents). Setting: the study was conducted at El Amal deaf and mute school in Lebanon Square. Data collection tools: Socio demographic data sheet, manifest anxiety scale, stress scale, psychological needs scale, self -esteem scale, Beck depression scale psychological services scale. Main results: Deaf and mute adolescents suffer from high level of (anxiety, depression and psychological stress), and moderate level of psychological services which provided for them. Also represented that, there was positive significant relation between anxiety and psychological stress (p=.002), there was positive significant relation between depression and anxiety (p=.0001), there was positive significant relation between depression and psychological stress (p=.0001), there was positive significant relation between self-esteem and satisfaction of psychological needs (p=.005) and there was negative significant relation between depression and satisfaction of psychological needs. Conclusion: Mental health problems of deaf and mute adolescents might be increased due to limit special psychological foundation for them, and sign language is not familiar for all medical team. Recommendations: The study recommended that presence of an interpreter of sign language in all psychiatric clinics to decrease their mental health problems.
How can governments engage in adaptation tracking? A protocol for assessing national adaptation policies

A myriad of frameworks to track adaptation to climate change have been developed in recent years. They have been instrumental in advancing the conversation on assessing adaptation progress and effectiveness across national and global scales. Surprisingly, very little attention is given to how countries can leverage existing policies to engage in adaptation tracking. We developed a Protocol to assess the ability of national policies to deliver comprehensive, coherent, and robust information on adaptation, which would allow governments to leverage existing efforts for engaging in country-driven tracking processes. The Protocol establishes data collection and analytical steps, including document screening, data extraction, quality assurance, and coding rules to ensure consistent interpretation and comparability of results. We applied the Protocol in an assessment of Nationally Determined Contributions (NDCs) and National Adaptation Plans (NAPs) of African countries. The resulting dataset represents the most comprehensive overview available to date on existing entry points for adaptation tracking for Africa. While this can help show progress in adaptation planning, the real challenge lies in generating evidence of adaptation effectiveness. This requires complementary assessments of how intentions and plans translate into actions or results on the ground, aspects which our Protocol does not cover.