Miracle-dz/UniFAR-FTUs huggingface dataset:
Aggify: Lifting the Curse of Cursor Loops using Custom Aggregates

Loops that iterate over SQL query results are quite common, both in application programs that run outside the DBMS, as well as User Defined Functions (UDFs) and stored procedures that run within the DBMS. It can be argued that set-oriented operations are more efficient and should be preferred over iteration; but from real world use cases, it is clear that loops over query results are inevitable in many situations, and are preferred by many users. Such loops, known as cursor loops, come with huge trade-offs and overheads w.r. t. performance, resource consumption and concurrency. We present Aggify, a technique for optimizing loops over query results that overcomes these overheads. It achieves this by automatically generating custom aggregates that are equivalent in semantics to the loop. Thereby, Aggify completely eliminates the loop by rewriting the query to use this generated aggregate. This technique has several advantages such as: (i) pipelining of entire cursor loop operations instead of materialization, (ii) pushing down loop computation from the application layer into the DBMS, closer to the data, (iii) leveraging existing work on optimization of aggregate functions, resulting in efficient query plans. We describe the technique underlying Aggify, and present our experimental evaluation over benchmarks as well as real workloads that demonstrate the significant benefits of this technique.
Multi-Task Spatial-Temporal Graph Attention Network for Taxi Demand Prediction

Taxi demand prediction is of much importance, which enables the building of intelligent systems and smart city. It is necessary to predict taxi demand accurately to schedule taxi fleet in a reasonable and efficient way and to reduce the pressure of traffic jam. However, the taxi demand involves complex and non-linear spatial-temporal impacts. The superiority of deep learning makes people explore the possibility to apply it to traffic prediction. State-of-the-art methods on taxi demand prediction only capture static spatial correlations between regions (e.g., Using static graph embedding) and only take taxi demand data into consideration. We propose a Multi-Task Spatial-Temporal Graph Attention Network (MSTGAT-Net) framework which models the correlations between regions dynamically with graph-attention network and captures the correlation between taxi pick up and taxi drop off with multi-task training. To the best of our knowledge, it is the first paper to address the taxi demand prediction problem with graph attention network and multi-task learning. Experiments on real-world taxi data show that our model is superior to state-of-the-art methods.
NK cells and CTLs are required to clear solid tumor in a novel model of patient-derived-xenograft

Existing patient-derived-xenograft (PDX) mouse models of solid tumors lack a fully tumor-donor matched “syngeneic” and functional immune system. We developed such a model by engrafting lymphopenic recipient mice with a fresh undisrupted piece of solid tumor, whereby tumor-infiltrating lymphocytes (TIL) expanded in the recipient mice for several weeks. Tumors engrafted in about seventy to eighty percent of syngeneic-immune-system-PDX (SIS-PDX) mice, which harbored tumor-exhausted immune-effector and functional immune-regulatory cells persisting for at least six-months post-engraftment. Interleukin-15 (IL-15)-stimulation in addition to immune checkpoint inhibition (ICI), prevented resistance, resulting in complete or partial response to combined treatment. Further, the depletion of Cytotoxic T lymphocytes (CTLs) and/or Natural Killer (NK) cells from combined immunotherapy in SIS-PDX mice revealed that both cell types are required for the maximal response to tumor. Our novel SIS-PDX model provides a valuable resource for powerful mechanistic and therapeutic studies designed to eradicate solid tumors.
Functional near-infrared spectroscopy in conjunction with electroencephalography of cerebellar transcranial direct current stimulation responses in the latent neurovascular coupling space – a chronic stroke study

Cerebellar transcranial direct current stimulation (ctDCS) can facilitate motor learning; however, ctDCS effects have not been investigated using portable neuroimaging vis-à-vis lobular electric field strength. This is important since the subject-specific residual architecture for cerebellar interconnections with the cerebral cortex, including the prefrontal cortex (PFC) and the sensorimotor cortex (SMC), can influence the ctDCS effects on the cerebral functional activation. In this study, we investigated functional near-infrared spectroscopy (fNIRS) in conjunction with electroencephalography (EEG) to measure the changes in the brain activation at the PFC and the SMC following virtual reality (VR)-based Balance Training (VBaT), before and after ctDCS treatment in 12 hemiparetic chronic stroke survivors. Furthermore, we performed general linear modeling (GLM) that can putatively associate the lobular electric field strength due to ctDCS priming with the changes in the fNIRS-EEG measures in the chronic stroke survivors. Here, fNIRS-EEG based measures were investigated in their latent space found using canonical correlation analysis (CCA) that is postulated to capture neurovascular coupling. We found that the ctDCS electrode montage, as well as the state (pre-intervention, during intervention, post-intervention), had a significant (p<0.05) effect on the changes in the canonical scores of oxy-hemoglobin (O2Hb) signal measured with fNIRS. Also, skill acquisition during first exposure to VBaT decreased the activation (canonical score of O2Hb) of PFC of the non-lesioned hemisphere in the novices at their first exposure before the ctDCS intervention. Moreover, ctDCS intervention targeting the leg representation in the cerebellum led to a decrease in the canonical scores of O2Hb at the lesioned SMC, which is postulated to be related to the cerebellar brain inhibition. Furthermore, ctDCS electrode montage, as well as the state, had a significant (p<0.05) interaction effect on the canonical scores of log10-transformed EEG bandpower. Our current study showed the feasibility of fNIRS-EEG imaging of the ctDCS responses in the latent neurovascular coupling space that can not only be used for monitoring the dynamical changes in the brain activation associated with ctDCS-facilitated VBaT, but may also be useful in subject-specific current steering for tDCS to target the cerebral fNIRS-EEG sources to reduce inter-individual variability.
Pro-inflammatory response of non-inflammatory Classical monocytes stimulated with LPS in vitro

BACKGROUND CD14 (Monocyte identifying Toll-Like Receptor) and CD16 (FcyRIII co-receptor, marker of inflammatory monocytes) were used to define 3 subpopulations of circulating monocytes with different attributes in terms of inflammatory and phagocytic capabilities. There are contradictory reports regarding response of circulating monocytes to pro-inflammatory or non-inflammatory stimuli in vitro. Here we aimed to analyze the phenotypic changes in circulating monocytes when stimulated with pro and non-inflammatory stimuli. METHODS Whole blood from 9 healthy donors was extracted and studied. Monocyte subpopulations were directly measured using flow cytometry with PBMC Ficoll extraction method. Pro-inflammatory interleukin IL-1β was measured by intracellular cytometry. Whole blood-extracted monocytes were stimulated using LPS and IL-4 as previously described. Changes against non-stimulated (N-S) populations were statistically analyzed. RESULTS Compared to N-S, LPS-stimulated monocytes display a singular milieu of markers, with higher levels of intracellular IL-1β in parallel raise of CD14+CD163-/CD14+CD163+ ratio. CD163 shows positive correlation with levels of IL-1β. In t-SNE (T-distributed Stochastic Neighbor Embedding) analysis, after LPS stimulation, subpopulation CD14+CD16-CD163-, containing mainly classical monocytes, show a higher number of IL-1β+ cells. CONCLUSION Classical monocytes, the non-inflammatory subset, show higher levels of IL-1β in response to LPS narrowing down to a new subpopulation of monocytes CD14+CD16-CD163-, which correlates better with this interleukin response than widely used monocytes classification. Using CD163 in addition to CD16, we were able to show that classical monocytes display the most intense response to LPS. Additionally, CD163 appears to be a suitable addition to CD14-CD16 classification to improve its performance.
Features Of Hippocampal Astrocytic Domains And Their Spatial Relation To Excitatory And Inhibitory Neurons

The mounting evidence for the involvement of astrocytes in neuronal circuits function and behavior stands in stark contrast to the lack of detailed anatomical description of these cells and the neurons in their domains. To fill this void, we imaged >30,000 astrocytes in cleared hippocampi, and employed converging genetic, histological and computational tools to determine the elaborate structure, distribution and neuronal content of astrocytic domains. First, we characterized the spatial distribution of >19,000 astrocytes across CA1 lamina, and analyzed the detailed morphology of thousands of reconstructed domains. We then determined the excitatory content of CA1 astrocytes, averaging above 13 pyramidal neurons per domain and increasing towards CA1 midline. Finally, we discovered that somatostatin neurons are found in close proximity to astrocytes, compared to parvalbumin and VIP inhibitory neurons. This resource expands our understanding of fundamental hippocampal design principles, and provides the first quantitative foundation for neuron-astrocyte interactions in this region.
Simeprevir Potently Suppresses SARS-CoV-2 Replication and Synergizes with Remdesivir

The outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global threat to human health. Using a multidisciplinary approach, we identified and validated the hepatitis C virus (HCV) protease inhibitor simeprevir as an especially promising repurposable drug for treating COVID-19. Simeprevir potently reduces SARS-CoV-2 viral load by multiple orders of magnitude and synergizes with remdesivir in vitro. Mechanistically, we showed that simeprevir inhibits the main protease (Mpro) and unexpectedly the RNA-dependent RNA polymerase (RdRp). Our results thus reveal the viral protein targets of simeprevir, and provide preclinical rationale for the combination of simeprevir and remdesivir for the pharmacological management of COVID-19 patients. One Sentence Summary Discovery of simeprevir as a potent suppressor of SARS-CoV-2 viral replication that synergizes with remdesivir.
Comparative physiology of five tropical montane songbirds reveals differential seasonal acclimatisation and cold adaption

The physiology of tropical birds is poorly understood, particularly in how it relates to local climate and changes between seasons. This is particularly true of tropical montane species, which may have sensitive thermal tolerances to local microclimates. We studied metabolic rates (using open flow respirometry), body mass and haemoglobin concentrations of five sedentary Mesoamerican songbirds between the summer and winter at two elevations (1550 m and 1950 m, respectively). We asked whether there were uniform seasonal shifts in physiological traits across species, and whether higher elevation species displayed evidence for cold tolerance. Seasonal shifts in metabolic rates differed between the three species for which data were collected. Basal metabolic rates in one species – black-headed nightingalethrushes Catharus mexicanus – were up-regulated in summer (~19% increase of winter metabolism), however two other species displayed no seasonal regulation. No species exhibited shifts in haemoglobin concentrations across season or across elevation, whereas body mass in two species was significantly higher in the summer. One species restricted to higher elevations – ruddy-capped nightingale-thrushes C. frantzii – displayed physiological traits indicative of cold-tolerance. Although only summer data were available for this species (C. frantzii), metabolic rates were constant across temperatures tested (5-34°C) and haemoglobin concentrations were significantly higher compared to the other four species. Our results suggest that seasonal acclimatisation in physiological traits is variable between species and appear unrelated to changes in local climate. As such, the distinct physiological traits observed in ruddy-capped nightingale-thrushes likely relate to historic isolation and conserved physiological traits rather than contemporary climatic adaption.
Both p38αMAPK and JNK/SAPK Pathways Are Important for Induction of Nitric-oxide Synthase by Interleukin-1β in Rat Glomerular Mesangial Cells*

Interleukin 1β (IL-1β) induces expression of the inducible nitric-oxide synthase (iNOS) with concomitant release of nitric oxide (NO) from glomerular mesangial cells. These events are preceded by activation of the c-Jun NH2-terminal kinase/stress-activated protein kinase (JNK/SAPK) and p38MAPK. Our current study demonstrates that overexpression of the dominant negative form of JNK1 or p54 SAPKβ/JNK2 significantly reduces the iNOS protein expression and NO production induced by IL-1β. Similarly, overexpression of the kinase-dead mutant form of p38αMAPK also inhibits IL-1β-induced iNOS expression and NO production. In previous studies we demonstrated that IL-1β can activate MKK4/SEK1, MKK3, and MKK6 in renal mesangial cells; therefore, we examined the role of these MAPK kinases in the modulation of iNOS induced by IL-1β. Overexpression of the dominant negative form of MKK4/SEK1 decreases IL-1β-induced iNOS expression and NO production with inhibition of both SAPK/JNK and p38MAPKphosphorylation. Overexpression of the kinase-dead mutant form of MKK3 or MKK6 demonstrated that either of these two mutant kinase inhibited IL-1β-induced p38MAPK (but not JNK/SAPK) phosphorylation and iNOS expression. Interestingly overexpression of wild type MKK3/6 was associated with phosphorylation of p38MAPK; however, in the absence of IL-1β, iNOS expression was not enhanced. This study suggests that the activation of both SAPK/JNK and p38αMAPK signaling cascades are necessary for the IL-1β-induced expression of iNOS and production of NO in renal mesangial cells.
Predicting individual variability in task‐evoked brain activity in schizophrenia

BACKGROUND Patients suffering from schizophrenia demonstrate abnormal brain activity, as well as alterations in patterns of functional connectivity assessed by functional magnetic resonance imaging (fMRI). Previous studies in healthy participants suggest a strong association between resting-state functional connectivity and task-evoked brain activity that could be detected at an individual level, and show that brain activation in various tasks could be predicted from task-free fMRI scans. In the current study we aimed to predict brain activity in patients diagnosed with schizophrenia, using a prediction model based on healthy individuals exclusively. This offers novel insights regarding the interrelations between brain connectivity and activity in schizophrenia. METHODS We generated a prediction model using a group of 80 healthy controls that performed the well-validated N-back task, and used it to predict individual variability in task-evoked brain activation in 20 patients diagnosed with schizophrenia. RESULTS We demonstrated a successful prediction of individual variability in the task-evoked brain activation based on resting-state functional connectivity. The predictions were highly sensitive, reflected by high correlations between predicted and actual activation maps (Median = 0.589, SD = 0.193) and specific, evaluated by a Kolomogrov-Smirnov test (D = 0.25, p < 0.0001). CONCLUSIONS A Successful prediction of brain activity from resting-state functional connectivity highlights the strong coupling between the two. Moreover, our results support the notion that even though resting-state functional connectivity and task-evoked brain activity are frequently reported to be altered in schizophrenia, the relations between them remains unaffected. This may allow to generate task activity maps for clinical populations without the need the actually perform the task.
Evidence for the agricultural origin of antimicrobial resistance in a fungal pathogen of humans

Resistance to clinical antimicrobials is an urgent problem, reducing our ability to combat deadly pathogens of humans. Azole antimicrobials target ergosterol synthesis and are highly effective against fungal pathogens of both humans and plants leading to their widespread use in clinical and agricultural settings1,2. The fungus Aspergillus fumigatus causes 300,000 life-threatening infections in susceptible human hosts annually and azoles are the most effective treatment3. Resistance to clinical azole antifungals has become a major problem in Europe and India over the last decade, where identical mutations in cyp51A, an ergosterol biosynthetic gene, have been found in strains from both clinical and agricultural settings4. Shared cyp51A genotypes suggest that clinical azole resistance might have had an agricultural origin; however, until now, independent origins of clinical and agricultural mutations could not be ruled out. Here we show that azole-resistant isolates of A. fumigatus from clinical and agricultural settings also carry mutations conferring resistance to quinone outside inhibitor (QoI) fungicides, which are used exclusively in agricultural settings. This is the first report of a clear marker for the agricultural origin of resistance to a clinical antifungal. We anticipate that our work will increase the understanding of interactions between pathogens of plants and pathogens of humans.
Imaging 3T3 cells in photonic crystal fibers

Microfluidic cell cultures are of research interest to the biomedical engineering community. These types of cultures are able to expedite pathogen detection and pharmaceutical development using very small sample volumes ranging from nanoliters to microliters. These tiny cell culture volumes reduce the analytical process times and allow for the rapid development of medical treatments customized to the individual patient. The low permeability of the biocompatible-glass microfluidic cultures limits evaporation of culture serums, unlike conventional polydimethylsiloxane (PDMS). Microfluidic optical fiber tools may also compliment flow-cytometry tools. Challenges exist, however, in delivering cell samples to the air channels of the optical fiber. The technical challenges of delivering 3T3 cells to air-channels in photonic crystal fibers (PCF) are discussed in this proceeding. The difficulty of cells entering the microstructured fiber for optical detection of the cells is linked to cell deformation and rupturing due to pumping techniques. Experimental results include microscopy images of shredded cells clumping inside the fiber. To investigate cell transport in PCFs, 3T3 cells were employed. These cells are an embryonic mouse cell line and are commonly used in cell biology. The benefit of this cell line is that the cells grow in flat monolayers making them ideal candidates for cell culture studies. The individual cell-size ranges from 5 μm to 15 μm. The air channels in the PCF are 22 μm in diameter, allowing 3T3 cell transport. The findings of this study will be of interest to microfluidic cell culture and flow-cytometry technical communities.
Molecular and Biomechanical Clues From Cardiac Tissue Decellularized Extracellular Matrix Drive Stromal Cell Plasticity

Decellularized-organ-derived extracellular matrix (dECM) has been used for many years in tissue engineering and regenerative medicine. The manufacturing of hydrogels from dECM allows to make use of the pro-regenerative properties of the ECM and, simultaneously, to shape the material in any necessary way. The objective of the present project was to investigate differences between cardiovascular tissues (left ventricle, mitral valve, and aorta) with respect to generating dECM hydrogels and their interaction with cells in 2D and 3D. The left ventricle, mitral valve, and aorta of porcine hearts were decellularized using a series of detergent treatments (SDS, Triton-X 100 and deoxycholate). Mass spectrometry-based proteomics yielded the ECM proteins composition of the dECM. The dECM was digested with pepsin and resuspended in PBS (pH 7.4). Upon warming to 37°C, the suspension turns into a gel. Hydrogel stiffness was determined for samples with a dECM concentration of 20 mg/mL. Adipose tissue-derived stromal cells (ASC) and a combination of ASC with human pulmonary microvascular endothelial cells (HPMVEC) were cultured, respectively, on and in hydrogels to analyze cellular plasticity in 2D and vascular network formation in 3D. Differentiation of ASC was induced with 10 ng/mL of TGF-β1 and SM22α used as differentiation marker. 3D vascular network formation was evaluated with confocal microscopy after immunofluorescent staining of PECAM-1. In dECM, the most abundant protein was collagen VI for the left ventricle and mitral valve and elastin for the aorta. The stiffness of the hydrogel derived from the aorta (6,998 ± 895 Pa) was significantly higher than those derived from the left ventricle (3,384 ± 698 Pa) and the mitral valve (3,233 ± 323 Pa) (One-way ANOVA, p = 0.0008). Aorta-derived dECM hydrogel drove non-induced (without TGF-β1) differentiation, while hydrogels derived from the left ventricle and mitral valve inhibited TGF-β1-induced differentiation. All hydrogels supported vascular network formation within 7 days of culture, but ventricular dECM hydrogel demonstrated more robust vascular networks, with thicker and longer vascular structures. All the three main cardiovascular tissues, myocardium, valves, and large arteries, could be used to fabricate hydrogels from dECM, and these showed an origin-dependent influence on ASC differentiation and vascular network formation.
Partial Dominance for Many-Objective Optimization

Many optimisation problems have more than three objectives, referred to as many-objective optimisation problems (MaOPs). As the number of objectives increases, the number of solutions that are non-dominated with regards to one another also increases. Therefore, multi-objective optimisation algorithms (MOAs) that use Pareto-dominance struggle to converge to the Pareto-optimal front (POF) and to find a diverse set of solutions on the POF. This article investigates the use of MOAs to solve MaOPs by guiding the search through Pareto-dominance on three randomly selected objectives. This approach is applied to the non-dominated sorting genetic algorithm II (NSGA-II) and a multi-objective particle swarm optimisation (OMOPSO) algorithm, where three objectives are randomly selected at either every iteration or every five iterations. These algorithms are compared against the original versions of these algorithms. The results indicate that the proposed partial dominance approach outperformed the original versions of these algorithms, especially on benchmarks with 8 and 10 objectives.
Vertica-ML: Distributed Machine Learning in Vertica Database

A growing number of companies rely on machine learning as a key element for gaining a competitive edge from their collected Big Data. An in-database machine learning system can provide many advantages in this scenario, e.g., eliminating the overhead of data transfer, avoiding the maintenance costs of a separate analytical system, and addressing data security and provenance concerns. In this paper, we present our distributed machine learning subsystem within the Vertica database. This subsystem, Vertica-ML, includes machine learning functionalities with SQL API which cover a complete data science workflow as well as model management. We treat machine learning models in Vertica as first-class database objects like tables and views; therefore, they enjoy a similar mechanism for archiving and managing. We explain the architecture of the subsystem, and present a set of experiments to evaluate the performance of the machine learning algorithms implemented on top of it.