Miracle-dz/UniFAR-FTUs huggingface dataset:
Dopamine-iron homeostasis interaction rescues mitochondrial fitness in Parkinson’s disease

Imbalances of iron and dopamine metabolism along with mitochondrial dysfunction have been linked to the pathogenesis of Parkinson’s disease (PD). We have previously suggested a direct link between iron homeostasis and dopamine metabolism, as dopamine can increase cellular uptake of iron into macrophages thereby promoting oxidative stress responses. In this study, we investigated the interplay between iron, dopamine, and mitochondrial activity in neuroblastoma SH-SY5Y cells and human induced pluripotent stem cell (hiPSC)-derived dopaminergic neurons differentiated from a healthy control and a PD patient with a mutation in the α-synuclein (SNCA) gene. In SH-SY5Y cells, dopamine treatment affected the expression of transmembrane iron transporters and cellular iron accumulation. Furthermore, dopamine supplementation led to decreased mitochondrial respiration and reduced mitochondrial fitness, including reduced mtDNA copy number and citrate synthase activity, increased oxidative stress and impaired aconitase activity. In dopaminergic neurons derived from a healthy control individual, dopamine showed comparable effects as observed in SH-SY5Y cells. The hiPSC-derived PD neurons harboring an endogenous SNCA mutation demonstrated altered mitochondrial iron homeostasis, reduced mitochondrial capacity along with increased oxidative stress and alterations of tricarboxylic acid cycle linked metabolic pathways compared with control neurons. Importantly, dopamine treatment of these PD neurons promoted a rescue effect by increasing mitochondrial respiration, activating antioxidant stress response, and normalizing altered metabolite levels linked to mitochondrial function. These observations provide evidence that dopamine affects iron homeostasis, intracellular stress responses and mitochondrial function in healthy cells, while dopamine supplementation can restore this disturbed regulatory network in PD cells.
Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 donor lungs with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage (DAD). We identify changes in cellular composition across progressive DAD, including waves of molecularly distinct macrophages and depleted epithelial and endothelial populations throughout different types of tissue damage. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early DAD, and fibrosis-related collagens in organised DAD. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early DAD. These results provide the first comprehensive, spatially resolved atlas of DAD stages, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways across alveolar damage progression.
Oryza CLIMtools: An Online Portal for Investigating Genome-Environment Associations in Rice

Elite crop varieties display an evident mismatch between their current distributions and the suitability of the local climate for their productivity. To this end, we present Oryza CLIMtools, (https://gramene.org/CLIMtools/oryza_v1.0/) the first pan-genome prediction of climate-associated genetic variants in a crop species. This resource consists of interactive web-based databases that allow the user to: i) explore the local environment and its interaction with natural existing genetic variation in local rice varieties (landraces) in South-Eastern Asia, and; ii) investigate the environment × genome associations for 658 Indica and 283 Japonica rice landrace accessions included in the 3K Rice Genomes Project and previously collected from their geo-referenced local environments. We exemplify the value of these resources, identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by maladaptive variation in OsSOC1 . Prior QTL analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing Potential Evapotranspiration gradient and their regulation of key agronomic traits including plant height, seed, and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce crops that are climate-change-ready.
NOT YET SUBJECT TO PEER REVIEW

19 1. Distance measures are widely used for examining genetic structure in datasets that 20 comprise many individuals scored for a very large number of attributes. Genotype 21 datasets composed of single nucleotide polymorphisms (SNPs) typically contain bi-22 allelic scores for tens of thousands if not hundreds of thousands of loci. 23 2. We examine the application of distance measures to SNP data (both genotypes and 24 sequence tag presence-absence) and use real datasets and simulated data to illustrate 25 pitfalls in the application of genetic distances and their visualization. 26 3. Missing values arise from ascertainment issues in the SNP discovery process (null 27 alleles in the case of SNP genotyping; true missing data in the case of sequence tag 28 presence-absence data). Missing values can cause displacement of affected 29 individuals from their natural groupings and artificial inflation of confidence 30 envelopes, leading to potential misinterpretation. Failure of a distance measure to 31 conform to metric and Euclidean properties is important but only likely to create 32 unacceptable outcomes in extreme cases. Lack of randomness in the selection of 33 individuals (e.g. inclusion of sibs) and lack of independence of both individuals and 34 loci (e.g. polymorphic haploblocks), can lead to substantial and otherwise 35 inexplicable distortions of the visual representations and again, potential 36 misinterpretation. 37 4. Euclidean Distance is the metric of choice in many distance studies. However, other 38 measures may be preferable because of underlying models of divergence, population 39 demographic history, linkage disequilibrium, because it is desirable to down-weight 40 joint absences, or because of other characteristics specific to the data or analyses. 41 Distance measures for SNP genotype data that depend on the arbitrary choice of 42 reference and alternate alleles (e.g. Bray-Curtis distance) should be avoided. Careful 43 consideration should be given to which state is scored zero when applying binary 44 distance measures to fragment presence-absence data (e.g. Jaccard distance). Filtering 45 on missing values then imputing those that remain avoids distortion in visual 46 representations. Presence of closely related individuals or polymorphic haploblocks in 47 the genomes of target species with limited genomic information occasionally emerge 48 as challenges.
Astro Teller

Most interesting problems do not have solutions that are simple mappings from the inputs to the correct outputs; some kind of internal state or memory is needed to operate well or optimally in these domains. Traditionally, genetic programming has concentrated on solving problems in the functional/reactive arena. This may be due in part to the absence of a natural way to incorporate memory into the paradigm. This chapter proposes a simple, Turingcomplete addition to the genetic programming paradigm that seamlessly incorporates the evolution of the effective gathering, storage, and retrieval of arbitrarily complicated state information. A new environment is presented and used to evaluate this addition to the paradigm. Experimental results show that the effective production and use of complex memory structures can be evolved and that functions evolving the intelligent use of state quickly and permanently displace purely reactive and non-deterministic functions. These results may aid future research into the causes and constituents of mental models and are shown to open the field of genetic programming to include all learning strategies that are Turing-possible.
Wealth Effects and Operating Performance of Spin-Offs: International Evidence

This paper investigates the wealth effects of 239 spin-off announcements that took place between January 2000 and December 2009 in the USA and Europe. First, we explore the short-term stock price behavior of firms announcing a spin-off. We also analyze whether industrial and geographical diversification creates wealth effects for firms deciding to detach business activities. In a second stage, the operating performance of parent firms and their subsidiaries is investigated in the pre-and post-spin-off period. The results reveal a strong positive market reaction of 3.47% on the spin-off announcement date. However, the share price reaction differs when US and European spin-off deals are considered. The US spin-offs seem to send stronger signals to the market compared with the European spin-offs. Consistent with previous studies, we find that firms disposing unrelated businesses (industrial focus) reap significant abnormal returns. On the other hand, geographical focus seems to convey neutral signal to the market producing insignificant abnormal returns. The operating performance dramatically deteriorates in the post spin-off period for parent firms. Unlike to US parent firms, European parents increase the level of capital expenditure in the year of the spin-off and the subsequent years. Regression analysis confirms that industrial focus, relative size and operating performance play significant role in explaining abnormal returns at the announcement date.
embeddings for Arabic Sentiment Analysis

Research and industry are more and more focusing in ﬁnding automatically the polarity of an opinion regarding a speciﬁc subject or entity. Paragraph vector has been recently proposed to learn embeddings which are leveraged for English sentiment analysis. This paper focuses on Arabic sentiment analysis and investigates the use of paragraph vector within a machine learning techniques to determine the polarity of a given text. We tested some preprocessing method, and we show that light stemming enhance the performance of classiﬁcation.
GPR84-mediated signal transduction affects metabolic function by promoting brown adipocyte activity

in GPR84-KO mice. The activation of GPR84 induced an increase in intracellular Ca 2+ levels, which intricately influenced mitochondrial respiration. By modulating mitochondrial Ca 2+ levels and respiration, GPR84 acts as a potent molecule involved in BAT activity. These findings suggest that GPR84 is a potential therapeutic target for invigorating BAT and ameliorating metabolic disorders
Comparison of transperitoneal and retroperitoneal robot partial nephrectomy for kidney tumors

Background: Surgical techniques for small kidney tumors have been developed for decades, from open to robotic surgery. There are two approaches for partial nephrectomy: transperitoneal and retroperitoneal. We divided robotic partial nephrectomy cases into transperitoneal robotic partial nephrectomy (TRPN) and retroperitoneal robotic partial nephrectomy (RRPN) and compared the outcomes. Methods: We retrospectively evaluated patients who underwent robotic partial nephrectomy at our hospital between November 2019 and
The Baseline Approach to Agent Evaluation

An important aspect of agent evaluation in stochastic games, especially poker, is the need to reduce the outcome variance in order to get accurate and significant results. The current method used in the Annual Computer Poker Competition’s analysis is that of duplicate poker, an approach that leverages the ability to deal sets of cards to agents in order to reduce variance. This work explores a different approach to variance reduction by using a control variate based approach known as baseline. The baseline approach involves using an agent’s outcome in self play to create an unbiased estimator for use in agent evaluation and has been shown to work well in both poker and trading agent competition domains. Baseline does not require that the agents are able to be dealt sets of cards, making it a more robust technique than duplicate. This approach is compared to the current duplicate method, as well as other variations of duplicate poker on the results of the 2011 two player no-limit and three player limit Texas Hold’em ACPC tournaments.
Four North American glaciers advanced past their modern positions thousands of years apart in the Holocene

Abstract. There is unambiguous evidence that glaciers have retreated from their 19th century positions, but it is less clear how far glaciers have retreated relative to their long-term Holocene fluctuations. Glaciers in western North America are thought to have advanced from minimum positions in the Early Holocene to maximum positions in the Late Holocene. We assess when four North American glaciers, located between 38–60∘ N, were larger or smaller than their modern (2018–2020 CE) positions during the Holocene. We measured 26 paired cosmogenic in situ 14C and 10Be concentrations in recently exposed proglacial bedrock and applied a Monte Carlo forward model to reconstruct plausible bedrock exposure–burial histories. We find that these glaciers advanced past their modern positions thousands of years apart in the Holocene: a glacier in the Juneau Icefield (BC, Canada) at ∼2 ka, Kokanee Glacier (BC, Canada) at ∼6 ka, and Mammoth Glacier (WY, USA) at ∼1 ka; the fourth glacier, Conness Glacier (CA, USA), was likely larger than its modern position for the duration of the Holocene until present. The disparate Holocene exposure–burial histories are at odds with expectations of similar glacier histories given the presumed shared climate forcings of decreasing Northern Hemisphere summer insolation through the Holocene followed by global greenhouse gas forcing in the industrial era. We hypothesize that the range in histories is the result of unequal amounts of modern retreat relative to each glacier's Holocene maximum position, rather than asynchronous Holocene advance histories. We explore the influence of glacier hypsometry and response time on glacier retreat in the industrial era as a potential cause of the non-uniform burial durations. We also report mean abrasion rates at three of the four glaciers: Juneau Icefield Glacier (0.3±0.3 mm yr−1), Kokanee Glacier (0.04±0.03 mm yr−1), and Mammoth Glacier (0.2±0.2 mm yr−1).
Climatology of the terms and variables of transformed Eulerian-mean (TEM) equations from multiple reanalyses: MERRA-2, JRA-55, ERA-Interim, and CFSR

A 30-year (1980–2010) climatology of the major variables and terms of the transformed Eulerian-mean (TEM) 20 momentum and thermodynamic equations is constructed by using four global atmospheric reanalyses, MERRA-2, JRA-55, ERA-Interim, and CFSR. Both the reanalysis ensemble mean (REM) and the differences of each reanalysis from the REM are investigated in the latitude-pressure domain for December-January-February and for June-July-August. For the REM investigation, two residual vertical velocities (the original one and one evaluated from residual meridional velocity) and two mass streamfunctions
Transfer Learning for Nonparametric Regression: Non-asymptotic Minimax Analysis and Adaptive Procedure

Transfer learning for nonparametric regression is considered. We first study the non-asymptotic minimax risk for this problem and develop a novel estimator called the confidence thresholding estimator, which is shown to achieve the minimax optimal risk up to a logarithmic factor. Our results demonstrate two unique phenomena in transfer learning: auto-smoothing and super-acceleration, which differentiate it from nonparametric regression in a traditional setting. We then propose a data-driven algorithm that adaptively achieves the minimax risk up to a logarithmic factor across a wide range of parameter spaces. Simulation studies are conducted to evaluate the numerical performance of the adaptive transfer learning algorithm, and a real-world example is provided to demonstrate the benefits of the proposed method.
Safety and efficacy of acarbose in the treatment of diabetes in Chinese patients

: Acarbose is an α -glucosidase inhibitor that is commonly used to control postprandial blood glucose. It functions as a competitive and reversible inhibitor of small intestinal brush border glucosidase, blocks the degradation of starch and sucrose, and delays the absorption of glucose and fructose in the alimentary tract. The starch content of a diet might alter the hypoglycemic effects of acarbose because of its mechanism of action. Chinese individuals consume a typical Eastern diet, which is characterized by a high intake of whole grains, legumes, vegetables, fruits, and fish. These dietary habits allow acarbose to be used extensively in the People’s Republic of China. Several Chinese-based studies have demonstrated that the use of acarbose as a monotherapy had similar effects on other anti-diabetes agents in decreasing glycosylated hemoglobin (HbA 1c ) and blood glucose levels, and acarbose in combination with other anti-diabetic drugs could further reduce blood glucose and decrease the mean amplitude of glycemic excursions. Importantly, acarbose is safe and well tolerated, with a low incidence of adverse effects. This article provides a comprehensive review of the safety and efficacy of acarbose for the treatment of diabetes in Chinese patients. Dietary starch content might alter the hypoglycemic effect of acarbose because of its mechanism of action. A meta-analysis was performed to compare the differences in the hypoglycemic effect of acarbose in Eastern and Western individuals according to the starch content of their diets. The results suggested that acarbose exerts more potent hypoglycemic effects in T2DM patients who consume an Eastern diet than in those consuming a Western diet; its effects were similar to sulfonylureas, metformin, and glinides. 17
Learning Market Equilibria Preserving Statistical Privacy Using Performative Prediction

—We consider a peer-to-peer electricity market modeled as a network game, where End Users (EUs) minimize their cost by computing their demand and generation while satisfying a set of local and coupling constraints. Their nominal demand constitutes sensitive information, that they might want to keep private. We prove that the network game admits a unique Variational Equilibrium, which depends on the private information of all the EUs. A data aggregator (DA) is introduced, which aims to learn the EUs’ private information, while remunerating them depending on the quality of the readings they report to the DA. The EUs might have incentives to report biased and noisy readings to preserve their privacy. Relying on performative prediction, we define a decision-dependent game G stoch , to explicitly take into account the shift caused by the EUs’ strategic information on their strategies and market equilibria. To compute market equilibria solutions of G stoch , two variants of the Repeated Stochastic Gradient Method (RSGM) and a two-time-scale stochastic approximation algorithm are proposed. We prove the convergence of each algorithm. Finally, the algorithms performance is assessed on a numerical example, by comparing the achieved efficiency loss, privacy preservation capabilities, convergence rates, and EUs’ utility functions at equilibrium. The results highlight the benefits for the EUs to model performative effects.
Overview of the NTCIR-17 Session Search (SS-2) Task

This is an overview of the NTCIR-17 Session Search (SS-2) task. The task features the Fully Observed Session Searchsubtask (FOSS), the Partially Observed Session Search subtask (POSS) and the Session-level Search Effectiveness Estimation subtask(SSEE). This year, we received 16 runs from 2 teams in total. This paper will describe the task background, data, subtasks, evaluation measures, and the evaluation results, respectively.
Identification of Potential Sources of Measurement Errors in an Isokinetic Dynamometer

The evaluation of shoulder abduction and flexion strength is important in the rehabilitation after rotator cuff tear. The purpose of this work is to assess the intra and inter-rater reliability of measurement data from an isokinetic dynamometer used to evaluate shoulder abduction and flexion strength, with the aim to identify sources of measurement errors and suggest improvements. The measurement data was collected by a research group at Karolinska Institute and contained load and torque data from thirteen healthy subjects in the ages of 25 to 87 years. The measurements were carried out on two occasions, one week apart. Systematic differences between occasions are analyzed using the Shapiro Wilk test, the paired t-test, and Wilcoxon signed rank test. The agreement of the measurements is analyzed quantitatively using the coefficient of variation and the Bland Altman plot, and quantitively, using the intraclass correlation coefficient. A significant systematic difference in shoulder abduction and flexion load measurements was found, and the recommendation to prevent this is that components should be calibrated in a standardized way. The measurements showed varying reliability within and between measurement occasions and that after familiarization with the isokinetic dynamometer, repeatability improved. The findings indicate a need of a standardized protocol for patient education and placement. Measurements from the position sensor contributed to more random torque values. To improve the repeatability in measurements from the position sensor, axis of rotation should be kept aligned. An increasing variability in measurements with increasing load and torque was found. The recommendation is to use a preload for patients using more force in the movement, to make sure a preset speed is not exceeded, which contributes to more reliable measurements.