Miracle-dz/UniFAR-FTUs huggingface dataset:
High-throughput Kinetics using Capillary Electrophoresis and Robotics (HiKER) platform used to Study T7, T3, and Sp6 RNA Polymerase Misincorporation

T7 RNA Polymerase (RNAP) is a well-studied and widely used enzyme with recent applications in the production of RNA vaccines. For over 50 years denaturing sequencing gels have been used as a key analysis tool for probing the kinetic mechanism of T7 RNAP nucleotide addition. However, sequencing gels are both slow and low throughput limiting their utility for comprehensive enzyme analysis. Here, we report the development of HiKER; (High-throughput Kinetics using Capillary Electrophoresis and Robotics) a high-throughput pipeline to quantitatively measure enzyme kinetics. We adapted a traditional polymerase misincorporation assay for fluorescent detection at scale allowing rapid estimates of RNAP misincorporation in different experimental conditions. In addition, high-throughput kinetics reactions were automated using an open-source OT-2 liquid handling robot. The platform allows multiple weeks’ worth of data to be collected in mere days. Using this platform, ∼1500 time points were collected in a single workday. T7 RNAP exhibited dramatic differences in both observed rate constant and amplitude depending on the mismatch examined. An average misincorporation frequency of ∼45 misincorporations per million bases was estimated using HiKER and is consistent with previous observations from next generation sequencing studies. Misincorporation time courses for T3 RNAP and Sp6 RNAP were similar to T7 RNAP suggesting conserved kinetic mechanisms. Interestingly, dramatic changes in the extent of misincorporation were observed in the three RNAPs depending on the mismatch. Extension from base mismatch experiments showed differences between T7, T3, and Sp6 RNAP. Sp6 RNAP was the slowest to extend from a mismatch followed by T7 RNAP and then T3 RNAP. Taken together the results presented here demonstrate the capabilities of HiKER to carry out high-throughput enzymology studies. Importantly, this pipeline and the corresponding analysis strategies are affordable, open-source, and broadly applicable to many enzymes.
Causally-motivated Shortcut Removal Using Auxiliary Labels

Robustness to certain distribution shifts is a key requirement in many ML applications. Often, relevant distribution shifts can be formulated in terms of interventions on the process that generates the input data. Here, we consider the problem of learning a predictor whose risk across such shifts is invariant. A key challenge to learning such risk-invariant predictors is shortcut learning, or the tendency for models to rely on spurious correlations in practice, even when a predictor based on shift-invariant features could achieve optimal iid generalization in principle. We propose a flexible, causally-motivated approach to address this challenge. Specifically, we propose a regularization scheme that makes use of auxiliary labels for potential shortcut features, which are often available at training time. Drawing on the causal structure of the problem, we enforce a conditional independence between the representation used to predict the main label and the auxiliary labels. We show both theoretically and empirically that this causally-motivated regularization scheme yields robust predictors that generalize well both in-distribution and under distribution shifts, and does so with better sample efficiency than standard regularization or weighting approaches.
Quantized optimal control of discrete-time systems

In this paper we consider a quantized discrete-time linear quadratic regulator (DLQR) problem, namely a DLQR problem where the input u may only take values in a given finite set 14. Eased on our previous results on the optimal control of hybrid systems we show that the optimal control law for the quantized DLQR problem takes the form of a feedback control law, that can be obtained from a partition of the state space C, computed off-line. The numerical simulations carried out enabled us to observe a particular structure of C, related to the solution of the non-quantized DLQR problem. The lines of our future research in this topic are described in details in the last section, devoted to conclusions and future work
Dynamic vaccine blocks relapse to compulsive intake of heroin

Heroin addiction, a chronic relapsing disorder characterized by excessive drug taking and seeking, requires constant psychotherapeutic and pharmacotherapeutic interventions to minimize the potential for further abuse. Vaccine strategies against many drugs of abuse are being developed that generate antibodies that bind drug in the bloodstream, preventing entry into the brain and nullifying psychoactivity. However, this strategy is complicated by heroin’s rapid metabolism to 6-acetylmorphine and morphine. We recently developed a “dynamic” vaccine that creates antibodies against heroin and its psychoactive metabolites by presenting multihaptenic structures to the immune system that match heroin’s metabolism. The current study presents evidence of effective and continuous sequestration of brain-permeable constituents of heroin in the bloodstream following vaccination. The result is efficient blockade of heroin activity in treated rats, preventing various features of drugs of abuse: heroin reward, drug-induced reinstatement of drug seeking, and reescalation of compulsive heroin self-administration following abstinence in dependent rats. The dynamic vaccine shows the capability to significantly devalue the reinforcing and motivating properties of heroin, even in subjects with a history of dependence. In addition, targeting a less brain-permeable downstream metabolite, morphine, is insufficient to prevent heroin-induced activity in these models, suggesting that heroin and 6-acetylmorphine are critical players in heroin’s psychoactivity. Because the heroin vaccine does not target opioid receptors or common opioid pharmacotherapeutics, it can be used in conjunction with available treatment options. Thus, our vaccine represents a promising adjunct therapy for heroin addiction, providing continuous heroin antagonism, requiring minimal medical monitoring and patient compliance.
Evolutionarily conserved and diverged alternative splicing events show different expression and functional profiles

To better decipher the functional impact of alternative splicing, we classified alternative splicing events in 10 818 pairs of human and mouse genes based on conservation at genome and transcript levels. Expression levels of conserved alternative splices in human and mouse expressed sequence tag databases show strong correlation, indicating that alternative splicing is similarly regulated in both species. A total of 43% (8921) of mouse alternative splices could be found in the human genome but not in human transcripts. Five of eleven tested mouse predictions were observed in human tissues, demonstrating that mouse transcripts provide a valuable resource for identifying alternative splicing events in human genes. Combining gene-specific measures of conserved and diverged alternative splicing with both gene classification based on Gene Ontology (GO) and microarray-determined gene expression in 52 diverse human tissues and cell lines, we found conserved alternative splicing most enriched in brain-expressed signaling pathways. Diverged alternative splicing is more prevalent in testis and cancerous cell line up-regulated processes, including protein biosynthesis, responses to stress and responses to endogenous stimuli. Using conservation as a surrogate for functional significance, these results suggest that alternative splicing plays an important role in enhancing the functional capacity of central nervous systems, while non-functional splicing more frequently occurs in testis and cell lines, possibly as a result of cellular stress and rapid proliferation.
The Best of Both Worlds: Accessing Emerging Economies via Developed Markets

A growing body of evidence suggests that the benefits of international diversification via developed markets have dramatically declined. While emerging markets still offer diversification opportunities, their public equity indices capture only a fraction of economic activity of emerging countries. We propose a diversification approach that exploits the global connectedness of developed countries to gain exposure to emerging countries overall economies rather than their shallow equity markets. In doing so, we demonstrate that developed markets still offer substantial diversification benefits beyond those available through equity indices. Our results suggest that relying on equity indices to assess diversification benefits understates diversification gains.
Glucose infusion partially attenuates glucose production and increases uptake during intense exercise.

Glucose infusion can prevent the increase in glucose production (Ra) and increase glucose uptake (Rd) during exercise of moderate intensity. We postulated that 1) because in postabsorptive intense exercise (>80% maximal O2 uptake) the eightfold increase in Ra may be mediated by catecholamines rather than by glucagon and insulin, exogenous glucose infusion would not prevent the Ra increment, and 2) such infusion would cause greater Rd. Fit young men were exercised at >85% maximal O2 uptake for 14 min in the postabsorptive state [controls (Con), n = 12] or at minute 210 of a 285-min glucose infusion. In seven subjects, the infusion was constant (CI; 4 mg . kg-1 . min-1), and in seven subjects it was varied (VI) to mimic the exercise Ra response in Con. Although glucose suppressed Ra to zero (with glycemia approximately 6 mM and insulin approximately 150 pM), an endogenous Ra response to exercise occurred, to peak increments two-thirds those in Con, in both CI and VI. Glucagon was unchanged, and very small increases in the glucagon-to-insulin ratio occurred in all three groups. Catecholamine responses were similar in all three groups, and correlation coefficients of Ra with plasma norepinephrine and epinephrine were significant in all. In all CI and VI, Rd at rest was 2x Con, increased earlier in exercise, and was higher for the 1 h of recovery with glucose infusion. Thus the Ra response was only partly attenuated, and the catecholamines are likely to be the regulators. This suggests that an acute endogenous Ra rise is possible even in the postprandial state. Furthermore, the fact that more circulating glucose is used by muscle during exercise and early recovery suggests that muscle glycogen is spared.
Isolated Avulsion Fracture of the Lesser Tuberosity of the Humerus: A Case Report

An extremely rare isolated avulsion fracture of the lesser tuberosity, not complicated with other proximal humeral fractures or posterior shoulder dislocations, occurred in a 12-year-old girl. The avulsion fracture of the upper part of the lesser tuberosity appears to have been caused by hyperextension and hyperexternal rotation of the shoulder. In this position, the coracohumeral ligament, superior glenohumeral ligament, and subscapularis tendon could have pulled out the upper part of the lesser tuberosity. She gained full recovery of left shoulder function after three months of conservative treatment, although follow-up roentgenograms show nonunion of the fracture. An isolated avulsion fracture of the
Peroxynitrite and protein nitration in the pathogenesis of diabetic peripheral neuropathy

Peroxynitrite, a product of the reaction of superoxide with nitric oxide, causes oxidative stress with concomitant inactivation of enzymes, poly(ADP‐ribosylation), mitochondrial dysfunction and impaired stress signalling, as well as protein nitration. In this study, we sought to determine the effect of preventing protein nitration or increasing peroxynitrite decomposition on diabetic neuropathy in mice after an extended period of untreated diabetes.
Metabolic Profiles Reveal Changes in Wild and Cultivated Soybean Seedling Leaves under Salt Stress

Clarification of the metabolic mechanisms underlying salt stress responses in plants will allow further optimization of crop breeding and cultivation to obtain high yields in saline-alkali land. Here, we characterized 68 differential metabolites of cultivated soybean (Glycine max) and wild soybean (Glycine soja) under neutral-salt and alkali-salt stresses using gas chromatography-mass spectrometry (GC-MS)-based metabolomics, to reveal the physiological and molecular differences in salt tolerance. According to comparisons of growth parameters under the two kinds of salt stresses, the level of inhibition in wild soybean was lower than in cultivated soybean, especially under alkali-salt stress. Moreover, wild soybean contained significantly higher amounts of phenylalanine, asparagine, citraconic acid, citramalic acid, citric acid and α-ketoglutaric acid under neutral-salt stress, and higher amounts of palmitic acid, lignoceric acid, glucose, citric acid and α-ketoglutaric acid under alkali-salt stress, than cultivated soybean. Further investigations demonstrated that the ability of wild soybean to salt tolerance was mainly based on the synthesis of organic and amino acids, and the more active tricarboxylic acid cycle under neutral-salt stress. In addition, the metabolite profiling analysis suggested that the energy generation from β-oxidation, glycolysis and the citric acid cycle plays important roles under alkali-salt stress. Our results extend the understanding of mechanisms involved in wild soybean salt tolerance and provide an important reference for increasing yields and developing salt-tolerant soybean cultivars.
Correlation of in vivo neuroimaging abnormalities with postmortem human immunodeficiency virus encephalitis and dendritic loss.

BACKGROUND In the absence of significant opportunistic infection, the most common alterations on neuroimaging in the brains of patients with AIDS include enlarged cerebrospinal fluid spaces, white-matter loss, volume loss in striatal structures, and white-matter signal abnormalities. Although previous studies have linked brain viral levels to these alterations, other neuropathological mechanisms might also contribute to them. OBJECTIVE To examine the relationship between findings on premortem magnetic resonance images and postmortem neuropathologic evidence of human immunodeficiency virus (HIV) encephalitis and neurodegeneration. DESIGN Morphometric analysis of magnetic resonance imaging in seropositive cases with matched seronegative controls, and the correlation of these volumes to neuropathological measures in autopsied seropositive cases. SETTING University of California, San Diego, HIV Neurobehavioral Research Center. SUBJECTS Twenty-one seropositive subjects studied at autopsy and 19 seronegative cases. MAIN OUTCOME MEASURES In vivo structural magnetic resonance imaging data analyzed by quantitative methods, with comparison of volumes from magnetic resonance imaging and neuropathological data from autopsies. RESULTS The HIV-seropositive subjects demonstrated cerebrospinal fluid increases relative to seronegative controls. These increases were associated with a significant decrease in the volumes of cerebral and cerebellar white matter, caudate nucleus, hippocampus, and, to a lesser extent, cerebral cortex. The volume of cerebral white-matter tissue with elevated signal was also increased. This signal elevation in white matter predicted the autopsy diagnosis of HIV encephalitis, as well as the extent of dendritic loss as assessed by analysis of microtubule-associated protein 2 immunoreactivity. CONCLUSIONS White-matter and cortical damage resulting from HIV disease are closely related. In vivo magnetic resonance imaging may be a valuable adjunct in the assessment of patients at risk for developing HIV encephalitis.
Explainable artificial intelligence for precision medicine in acute myeloid leukemia

Artificial intelligence (AI) can unveil novel personalized treatments based on drug screening and whole-exome sequencing experiments (WES). However, the concept of “black box” in AI limits the potential of this approach to be translated into the clinical practice. In contrast, explainable AI (XAI) focuses on making AI results understandable to humans. Here, we present a novel XAI method -called multi-dimensional module optimization (MOM)- that associates drug screening with genetic events, while guaranteeing that predictions are interpretable and robust. We applied MOM to an acute myeloid leukemia (AML) cohort of 319 ex-vivo tumor samples with 122 screened drugs and WES. MOM returned a therapeutic strategy based on the FLT3, CBFβ-MYH11, and NRAS status, which predicted AML patient response to Quizartinib, Trametinib, Selumetinib, and Crizotinib. We successfully validated the results in three different large-scale screening experiments. We believe that XAI will help healthcare providers and drug regulators better understand AI medical decisions.
Reading Faces. Using Hard Multi-Task Metric Learning for Kernel Regression. (Analyse de visages à l'aide d'une régularisation multi-tâches contrainte pour un apprentissage de métrique adaptée à un régresseur par noyaux)

Collecting and labeling various and relevant data for training automatic facial information prediction systems is both hard and time-consuming. As a consequence, available data is often of limited size compared to the difficulty of the prediction tasks. This makes overfitting a particularly important issue in several face-related machine learning applications. In this PhD, we introduce a novel method for multi-dimensional label regression, namely Hard Multi-Task Metric Learning for Kernel Regression (H-MT-MLKR). Our proposed method has been designed taking a particular focus on overfitting reduction. The Metric Learning for Kernel Regression method (MLKR) that has been proposed by Kilian Q. Weinberger in 2007 aims at learning a subspace for minimizing the quadratic training error of a Nadaraya-Watson estimator. In our method, we extend MLKR for multi-dimensional label regression by adding a novel multi-task regularization that reduces the degrees of freedom of the learned model along with potential overfitting. We evaluate our regression method on two different applications, namely landmark localization and Action Unit intensity prediction. We also present our work on automatic emotion prediction in a continuous space which is based on the Nadaraya-Watson estimator as well. Two of our frameworks let us win international data science challenges, namely the Audio-Visual Emotion Challenge (AVEC’12) and the fully continuous Facial Expression Recognition and Analysis challenge (FERA’15).
New treatments for acute humoral rejection of kidney allografts

Acute antibody-mediated rejection (acute humoral rejection; AHR) of organ allografts usually presents as severe dysfunction with a high risk of allograft loss. Peritubular capillary complement C4d deposition with renal dysfunction, associated with circulating donor-specific anti-human leukocyte antigen alloantibodies, is diagnostic of AHR in kidney allografts. Removal of alloantibodies with suppression of antibody production and rejection reversal is now possible. Therapeutic strategies that include combinations of plasmapheresis (or immunoadsorption), tacrolimus, mycophenolate mofetil and/or intravenous immunoglobulins, as well as rituximab or splenectomy, have been recently used to successfully treat AHR. However, the optimal protocol to treat AHR still remains to be defined. Anti-CD20+ monoclonal antibody therapy (rituximab) aiming at depleting B cells and suppressing antibody production has been used as rescue therapy in some episodes of steroid- and antilymphocyte-resistant humoral rejection. Plasmapheresis and/or intravenous polyclonal immunoglobulin, as well as rituximab, have also been used to successfully desensitize selected high-immunological risk patients in anticipation of a previously cross-match positive (or ABO incompatible) kidney transplantation. In the near future, the possible role of new specific anti-B-cell approaches or, possibly, of new anti-T-cell activation approaches using selective agents such as belatacept should be assessed to further refine the present treatment of humoral rejection.
IAES International Journal of Artificial Intelligence (IJ-AI)

Received Aug 14, 2021 Revised Feb 2, 2022 Accepted Feb 20, 2022 The classical job shop scheduling (JSS) problem can be extended by allowing processing of an operation by any machine from a given set. This type of scheduling is known as flexible job shop scheduling (FJSS) problem. It incorporates all the difficulties and complexities of its predecessor classical problem. However, it is more complex as it is required to determine the assignment of operations to the machine. Swarm intelligence techniques proved their effectiveness in solving a wide range of complex NP-Hard real world problems. One of these techniques is the meerkat clan algorithm (MCA) that has been successfully applied to various optimization problems. This paper presents a modified MCA for solving the FJSS problem. The modification is based on using harmony search (HS). The introduction of HS provides more exploitation and intensification. HS generates various solutions, which are provided to the MCA. As a result, the exploitation of the local optimum is increased, which in turn increases the convergence rate. The experimental results show that the improved method achieves higher quality schedules. Additionally, the convergence rate is speeded up compared with the standalone algorithm. This gives the proposed method the superiority over the original algorithm.
Septin assemblies form by diffusion-driven annealing on membranes

Significance The mechanisms and location of polymerization and disassembly direct the function of cytoskeletal proteins. Septins are far less understood than other cytoskeletal elements such as actin and microtubules, yet they have a conserved function acting as scaffolds at cell membranes and are implicated in cancers, neurodegenerative diseases, and microbial pathogenesis. We have defined a key role of the membrane in directing septin filament formation in live cells and reconstituted dynamic septin polymerization, using purified components. We find that septins grow into filaments and form higher-order structures by diffusing, colliding, and annealing on the plasma membrane. This work is important because it defines previously unidentified basic steps of polymerization and construction of higher-order assemblies of septin proteins. Septins assemble into filaments and higher-order structures that act as scaffolds for diverse cell functions including cytokinesis, cell polarity, and membrane remodeling. Despite their conserved role in cell organization, little is known about how septin filaments elongate and are knitted together into higher-order assemblies. Using fluorescence correlation spectroscopy, we determined that cytosolic septins are in small complexes, suggesting that septin filaments are not formed in the cytosol. When the plasma membrane of live cells is monitored by total internal reflection fluorescence microscopy, we see that septin complexes of variable size diffuse in two dimensions. Diffusing septin complexes collide and make end-on associations to form elongated filaments and higher-order structures, an assembly process we call annealing. Septin assembly by annealing can be reconstituted in vitro on supported lipid bilayers with purified septin complexes. Using the reconstitution assay, we show that septin filaments are highly flexible, grow only from free filament ends, and do not exchange subunits in the middle of filaments. This work shows that annealing is a previously unidentified intrinsic property of septins in the presence of membranes and demonstrates that cells exploit this mechanism to build large septin assemblies.