Miracle-dz/UniFAR-FTUs huggingface dataset:
Human monocyte subtype expression of neuroinflammation and regeneration-related genes is linked to age and sex

Stroke is a leading cause of disability and the third cause of death. The immune system plays an essential role in post-stroke recovery. After an ischemic stroke, monocytes infiltrate the injured brain tissue and can exacerbate or mitigate the damage. Ischemic stroke is more prevalent in the aged population, and the aging brain exhibits an altered immune response. There are also sex disparities in ischemic stroke incidence, outcomes, and recovery, and these differences may be hormone-driven and determined by genetic and epigenetic factors. Here, we studied whether human peripheral blood monocyte subtype (classical, intermediate, and non-classical) expression of neuronal inflammation- and regeneration-related genes depends on age and sex. A FACS analysis of blood samples from 44 volunteers (male and female, aged 28 to 98) showed that in contrast to other immune cells, the proportion of natural killer cells increased in females. The proportion of B-cells decreased in both sexes with age, and subtypes of monocytes were not linked to age or sex. Gene expression analysis by qPCR identified several genes differentially correlating with age and sex within different monocyte subtypes. Interestingly, ANXA1 and CD36 showed a consistent increase with aging in all monocytes, specifically in intermediate (CD36) and intermediate and non-classical (ANXA1) subtypes. Other genes (IL-1β, S100A8, TNFα, CD64, CD33, TGFβ1, TLR8, CD91) were differentially changed in monocyte subtypes with increased aging. Most age-dependent gene changes were differentially expressed in female monocytes. Our data shed light on the nuanced interplay of age and sex in shaping the expression of inflammation- and regeneration-related genes within distinct monocyte subtypes. Understanding these dynamics could pave the way for targeted interventions and personalized approaches in post-stroke care, particularly for the aging population and individuals of different sexes.
VISUALIZING THE NUCLEATING AND CAPPED STATES OF F-ACTIN BY Ca2+-GELSOLIN: SAXS DATA BASED STRUCTURES OF BINARY AND TERNARY COMPLEXES

Structural insight eludes on how full-length gelsolin depolymerizes and caps F-actin, while the same entity can nucleate polymerization of G-actins. Employing small angle X-ray scattering (SAXS) data analysis, we deciphered these two contrasting assemblies. Mixing Ca2+-gelsolin with F-actin in high salt F-buffer resulted in depolymerization of ordered F-actin rods to smaller sized species which became monodisperse upon dialysis with low salt G-buffer. These entities were the ternary (GA2) and binary (GA) complexes of gelsolin and actin with radius of gyration and maximum linear dimension of 4.55 and 4.68 nm, and 15 and 16 nm, respectively. In contrast, upon mixing G-actin with Ca2+-gelsolin in G-buffer, rapid association of higher order species started. Using size exclusion chromatography in-line with SAXS, we confirmed that initially GA and GA2 species are formed as seen upon depolymerization of F-actin, followed by dialysis. Interestingly, while GA2 could seed formation of native-like F-actin in both G- and F-buffer, GA failed in G-buffer. Thus, GA2 and GA are the central species formed via depolymerization or towards nucleation. SAXS profile referenced modeling revealed that: 1) in GA, actin is bound to the C-terminal half of gelsolin, and 2) in GA2, second actin binds to the open N-terminal half accompanied by dramatic rearrangements across gelsolin’s g1-g2 and g3-g4 linkers. Importantly, first structural insight is provided into the two probable models for GA2 with two actins in parallel, but differentially stacked: one in polymerization competent, and other in incompetent manner, suggesting latter to represent capped state along with the inert GA. TOC Abstract Highlights Orderly decrement in the length of F-actin by Ca2+-gelsolin was tracked by SAXS. Residual re-association in 1:2 ratio in F-buffer was quenched by dialysis in G-buffer. Identical GA and GA2 entities formed upon mixing F- or G-actin with Ca2+-gelsolin. Models of nucleation competent, GA2 showed differential stacking of two G-actins. N-terminal half of gelsolin reposition as GA2 changes to or from GA, the capped state.
Human-in-the-loop approach to identify functionally important residues of proteins from literature

We present a novel system that leverages curators in the loop to develop a dataset and model for detecting residue-level functional annotations and other protein structure features from standard publication text. Our approach involves the integration of data from multiple resources, including PDBe, EuropePMC, PubMedCentral, and PubMed, combined with annotation guidelines from UniProt, while employing LitSuggest and Huggingface models as tools in the annotation process. A team of seven annotators manually curated ten articles for named entities, which we utilized to train a starting PubmedBert model from Huggingface. Using a human-in-the-loop annotation system, we developed the best model with commendable performance metrics of 0.90 for precision, 0.92 for recall, and 0.91 for F1-measure. Our proposed system showcases a successful synergy of machine learning techniques and human expertise in curating a dataset for residue-level functional annotations and protein structure features. The results demonstrate the potential for broader applications in protein research, bridging the gap between advanced machine learning models and the indispensable insights of domain experts.
In vitro reconstitution reveals requirement of Nek2a and cyclin A2 for Wapl-dependent removal of cohesin from prophase chromatin

Sister chromatid cohesion is mediated by the cohesin complex. In mitotic prophase cohesin is removed from chromosome arms in a Wapl- and phosphorylation-dependent manner. Sgo1-PP2A protects pericentromeric cohesion by dephosphorylation of cohesin and its associated Wapl antagonist sororin. However, Sgo1-PP2A relocates to inner kinetochores well before sister chromatids are separated by separase, leaving pericentromeric regions unprotected. Why deprotected cohesin is not removed by Wapl remains enigmatic. By reconstituting Wapl-dependent cohesin removal from chromatin in vitro, we discovered a requirement for Nek2a and Cdk1/2-cyclin A2. These kinases phosphorylate cohesin-bound Pds5b, thereby converting it from a sororin- to a Wapl- interactor. Replacement of endogenous Pds5b by a phosphorylation mimetic variant causes premature sister chromatid separation (PCS). Conversely, phosphorylation- resistant Pds5b impairs chromosome arm separation in prometaphase-arrested cells and suppresses PCS in the absence of Sgo1. Early mitotic degradation of Nek2a and cyclin A2 may therefore explain why only separase, but not Wapl, can trigger anaphase.
A Mem-dELISA platform for dual color and ultrasensitive digital detection of colocalized proteins on extracellular vesicles

Accurate, multiplex, and ultrasensitive measurement of different colocalized protein markers on individual tumor-derived extracellular vesicles (EVs) and dimerized proteins with multiple epitopes could provide insights into cancer heterogeneity, therapy management and early diagnostics that cannot be extracted from bulk methods. However, current digital protein assays lack certain features to enable robust colocalization, including multi-color detection capability, large dynamic range, and selectivity against background proteins. Here, we report a lithography-free, inexpensive (< $0.1) and ultrasensitive dual-color Membrane Digital ELISA (Mem-dELISA) platform by using track-etched polycarbonate (PCTE) membranes to overcome these shortcomings. Their through-pores remove air bubbles through wicking before they are sealed on one side by adhesion to form microwells. Immunomagnetic bead-analyte complexes and substrate solution are then loaded into the microwells from the opposite side, with >80% loading efficiency, before sealing with oil. This enables duplex digital protein colorimetric assay with beta galactosidase and alkaline phosphatase enzymes. The platform achieves 5 logs of dynamic range with a limit of detection of 10 aM for both Biotinylated β-galactosidase (B-βG) and Biotin Alkaline Phosphatase Conjugated (B-ALP) proteins. We demonstrate its potential by showing that a higher dosage of paclitaxel suppresses EpCAM-positive EVs but not GPC-1 positive EVs from breast cancer cells, a decline in chemo-resistance that cannot be detected with Western blot analysis of cell lysate. The Mem-dELISA is poised to empower researchers to conduct ultrasensitive, high throughput protein colocalization studies for disease diagnostics, treatment monitoring and biomarker discovery.
Phylovar: toward scalable phylogeny-aware inference of single-nucleotide variations from single-cell DNA sequencing data

Abstract Motivation Single-nucleotide variants (SNVs) are the most common variations in the human genome. Recently developed methods for SNV detection from single-cell DNA sequencing data, such as SCIΦ and scVILP, leverage the evolutionary history of the cells to overcome the technical errors associated with single-cell sequencing protocols. Despite being accurate, these methods are not scalable to the extensive genomic breadth of single-cell whole-genome (scWGS) and whole-exome sequencing (scWES) data. Results Here, we report on a new scalable method, Phylovar, which extends the phylogeny-guided variant calling approach to sequencing datasets containing millions of loci. Through benchmarking on simulated datasets under different settings, we show that, Phylovar outperforms SCIΦ in terms of running time while being more accurate than Monovar (which is not phylogeny-aware) in terms of SNV detection. Furthermore, we applied Phylovar to two real biological datasets: an scWES triple-negative breast cancer data consisting of 32 cells and 3375 loci as well as an scWGS data of neuron cells from a normal human brain containing 16 cells and approximately 2.5 million loci. For the cancer data, Phylovar detected somatic SNVs with high or moderate functional impact that were also supported by bulk sequencing dataset and for the neuron dataset, Phylovar identified 5745 SNVs with non-synonymous effects some of which were associated with neurodegenerative diseases. Availability and implementation Phylovar is implemented in Python and is publicly available at https://github.com/NakhlehLab/Phylovar.
Assessment of the Impacts of Climate Change on Hydrological Characteristics of the Mbarali River Sub Catchment Using High Resolution Climate Simulations from CORDEX Regional Climate Models

This study assesses the impacts of climate change on water resources over Mbarali River sub-catchment using high resolution climate simulations from the Coordinated Regional Climate Downscaling Experiment Regional Climate Models (CORDEX_RCMs). Daily rainfall, minimum and maximum temperatures for historical climate (1971-2000) and for the future climate projection (2011-2100) under two Representative Concentration Pathways RCP 8.5 and RCP 4.5 were used as input into the Soil and Water Assessment Tool (SWAT) hydrological model to simulate stream flows and water balance components for the Mbarali River sub-catchment. The impacts of climate change on hydrological conditions over Mbarali river catchment were assessed by comparing the mean values of stream flows and water balance components during the present (2011-2040), mid (2041-2070) and end (2071-2100) centuries with their respective mean values in the baseline (1971-2000) climate condition. The results of the study indicate that, in the future, under both RCP 4.5 and RCP 8.5 emission scenarios, the four main components that determine change in catchment water balance (rainfall, ground water recharge, evaporation and surface runoff) over Mbarali river catchment are projected to increase. While the stream flows are projected to decline in the future by 13.33% under RCP 4.5 and 13.67% under RCP 8.5 emission scenarios, it is important to note that simulated surface runoff under RCP8.5 emission scenario is higher than that which is obtained under the RCP4.5 emission scenario.
Mesoscale Eddies Control the Timing of Spring Phytoplankton Blooms: A Case Study in the Japan Sea

Satellite Chlorophyll a (CHL) data were used to investigate the influence of mesoscale anticyclonic eddies (AEs) and cyclonic eddies (CEs) on the timing of spring phytoplankton bloom initiation around the Yamato Basin (133–139°E and 35–39.5°N) in the Japan Sea, for the period 2002–2011. The results showed significant differences between AEs and CEs in the timing and initiation mechanism of the spring phytoplankton bloom. Blooms were initiated earlier in CEs which were characterized by shallow mixed‐layer depths (< 100 m). The early blooming preceded the end of winter cooling (i.e., while net heat flux (Q0) is still negative) and is initiated by the increased average light within the shallow mixed‐layer depth. Conversely, blooms appeared in the AEs despite deeper mixed‐layer depth (> 100 m) but close to the commencement of positive Q0. This suggests that the relaxation of turbulent mixing is crucial for the bloom initiation in AEs.
The application of predictive geochemical modelling to determine backfill requirements at Turquoise Ridge Joint Venture, Nevada

Predictive geochemical modelling has been carried out for the Turquoise Ridge and Valmy pits, Getchell gold mine, Nevada (USA) as part of an updated evaluation of waste rock management. The purpose of the modelling exercise was to predict the concentrations of solutes that may emanate from the waste rock backfilled pits and to assess the impact of any seepage from the pits on underlying groundwater chemistry. The results of the geochemical modelling will be used to assess the level of cover required for the backfilled pits in order to ensure that no degradation of groundwater occurs. The assessment of geochemical reactivity was undertaken using laboratory column leaching utilizing alternating wet and dry cycles to simulate accelerated weathering in humidity cell tests (HCTs). The chemistry of the leaching solutions was used to develop source term solutions that were scaled from laboratory to field conditions and used as inputs for the geochemical models. Geochemical modelling was carried out using the USGS-developed software PHREEQC. Seepage water quality predictions were made based on the mass load mixing of waters contacting different lithologies in each of the backfilled pits. Water quality predictions were then made for a number of seepage scenarios, including 1%, 5%, 10%, 50% and 100% of mean annual precipitation that will infiltrate the backfill and report as seepage to groundwater. The results of the modelling exercise demonstrate that the impact of the pits on the underlying groundwater is largely dependent on the amount of seepage through the backfill. In general, significant changes in groundwater chemistry were noted when there was greater than 10% seepage from both the Turquoise Ridge and Valmy pits. Under the 100% seepage scenario, groundwater is likely to be characterised by elevated concentrations of arsenic, selenium, sulphate and manganese. However, the impact to groundwater will be negligible if less than 10% seepage occurs. This can be attained through placement of a thick alluvium cover on the backfill material and re-contouring of the area to natural topography.
Estimation of trapping efficiency of a vortex tube silt ejector

ABSTRACT This paper investigates the potential of an adaptive neuro-fuzzy inference system (ANFIS), Gaussian Process Regression, M5P tree model, Random Forest (RF) and Multi-Linear regression approaches in estimating the trapping efficiency of a vortex tube ejector. As many as 144 data sets were obtained by conducting experiments with a vortex tube ejector. Out of 144 data sets, 100 randomly selected data were used for training and the remaining 44 were used for testing the models. The input data set consists of sediment size (mm), concentration of sediment (ppm), ratio of slit thickness, diameter of tube (t/d) and extraction ratio (%) whereas trapping efficiency (%) was considered as the output. Three membership functions, i.e. triangular, generalized bell-shaped and Gaussian were used with ANFIS. A comparison of results suggests that the Gaussian membership function (MF) of ANFIS was the better of the two MFs of ANFIS. The major conclusion was that RF works better than other approaches and it could be successfully used in prediction of trapping efficiency of a vortex tube ejector. Sensitivity analyses suggest that extraction ratio was the most important parameter in estimating trapping efficiency of a vortex tube ejector.
SWAT BASED ASSESSMENT AND PREDICTION OF CLIMATE CHANGE AND ITS IMPACT IN THENPENNAI SUB-BASIN OF SOUTH INDIA

Abstract. Climate change impacts on watershed ecosystems and hydrologic processes are complex. The key significant parameters responsible for balancing the watershed ecosystems are temperature and rainfall. Though these parameters are uncertain, they play a prime role in the projections of dimensional climate change studies. The impact of climate change is more dependent on temperature and precipitation which contributes at a larger magnitude for characterising global warming issues. This paper aims to forecast the variations of temperature and precipitation during the period of 2020–2050 for the northern part of Thenpennar sub basin. This study is modelled using SWAT (Soil and Water Assessment Tool) – a scale model developed to predict the impact of changes that occurs in land, soil and water over a period of time. This study is validated using the base period from 1980–2000 which shows the distribution of rainfall and temperature among 38 watersheds. The results from this study show that there is a decrease in the rainfall for a maximum of about 20% in the month of December during the predicted period of 2020 and 2050. This study assesses the possible adverse impact of climate change on temperature and precipitation of Thenpennai sub-basin. This kind of predictions will help the government agencies, rulers and decision makers in policy making and implementing the adaptation strategies for the changing climatic conditions.
Initial tests on in situ vitrification using electrode feeding techniques

This report summarizes the results of an engineering-scale in situ vitrification (ISV) test conducted to demonstrate the potential for electrode feeding in soils with a high concentration of metals. The engineering-scale test was part of a Pacific Northwest Laboratory (PNL) program to assist Idaho National Engineering Laboratory (INEL) in conducting treatability studies of the potential for applying ISV to the mixed transuranic waste buried at the INEL subsurface disposal area. The purpose of this test was to evaluate the effectiveness of both gravity fed and operator-controlled electrode feeding in reducing or eliminating many of the potential problems associated with fixed-electrode processing of soils with high concentrations of metal. Actual site soils from INEL were mixed with representative concentrations of carbon steel and stainless steel for this engineering-scale test. 18 refs., 14 figs., 3 tabs.
Hierarchical Learning-Based Autonomy Simulator

This paper proposes a realistic urban-driving simulator to accurately model agent behaviors, a crucial component for self-driving car development. Most previous simulators focus on the plausibility of sensor data synthesis, whereas the plausibility of driving behaviors is poorly explored. To tackle this problem, we propose a hierarchical architecture, which comprises (i) a high-level intention simulation summarizing driving scenarios and (ii) a low-level policy trained by reinforcement algorithms to refine plans. Unlike existing simulators, our approach captures diverse behaviors, even sub-optimal ones, vital for robust policy training. We also highlight the importance of interactive simulations over static scenarios for realistic policy development. Extensive experiments demonstrate that our approach significantly improves long-term behavior prediction and closed-loop simulation, enhancing the realism and diversity of urban-driving simulations. The videos of this work are available in our project page: https://sites.google. com/ucsd.edu/h-sim/home.
PIDiffu: Pixel-aligned Diffusion Model for High-Fidelity Clothed Human Reconstruction

This paper presents the Pixel-aligned Diffusion Model (PIDiffu), a new framework for reconstructing high-fidelity clothed 3D human models from a single image. While existing PIFu variants have made significant advances us-ing more complicated 2D and 3D feature extractions, these methods still suffer from floating artifacts and body part duplication due to their reliance on point-wise occupancy field estimations. PIDiffu employs a diffusion-based strategy for line-wise estimation along the ray direction, conditioned by pixel-aligned features with a guided attention. This approach improves the local details and structural accuracy of the reconstructed body shape and is robust to unfamiliar and complex image features. Moreover, PIDiffu can be easily integrated with existing PIFu-based methods to leverage their advantages. The paper demonstrates that PIDiffu out-performs state-of-the-art methods that do not rely on parametric 3D body models. Especially, our method is superior in handling ’in-the-wild’ images, such as those with complex patterned clothes unseen in the training data.
Future Generation Computer Systems

Porting existing monoliths to the Function-as-a-Service (FaaS) ( FaaSification ) can be very challenging for software developers due to different architectural styles. For a successful porting, developers need to resolve various dependencies, such as method invocations of external packages or user-defined codes, as well as global and local variables used in and after the code block that should be faasified . To bridge the gap and automatize FaaSification, this paper introduces M 2 FaaS , a FaaSifier that automatically converts a Node.js monolith into a hybrid by faasifying annotated code blocks as serverless functions on multiple FaaS providers. M 2 FaaS is a novel FaaSifier that resolves many challenges for the resulting monolith to work properly after the FaaSification. Developers may annotate all dependencies that need to be resolved for the generated functions to run properly and specify variables that should be returned by the function to the monolith because they are used later in the monolith. Moreover, M 2 FaaS is the first FaaSifier that faasifies arbitrary code blocks. The current M 2 FaaS prototype supports FaaSification of individual functions on two FaaS providers, AWS Lambda and IBM Cloud Functions. Finally, M 2 FaaS introduces an optional annotation for alternative functions to be invoked in case the primary faasified function fails. The resulting hybrid application invokes the automatically deployed serverless functions, while the original code remains executable. Experiments with four complementary monoliths demonstrate that M 2 FaaS outperforms state-of-the-art FaaSifiers in terms of development effort by up to 73.3%. Moreover, with the fault tolerance support, M 2 FaaS finishes all submitted functions, thereby achieving by 18.5% higher throughput than the other FaaSifiers. © 2022TheAuthor(s). PublishedbyElsevierB.V. ThisisanopenaccessarticleundertheCCBY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).