Tierkreis: A Dataflow Framework for Hybrid Quantum-Classical Computing

We present Tierkreis, a higher-order dataflow graph program representation and runtime designed for compositional, quantum-classical hybrid algorithms. The design of the system is motivated by the remote nature of quantum computers, the need for hybrid algorithms to involve cloud and distributed computing, and the long-running nature of these algorithms. The graph-based representation reflects how designers reason about and visualise algorithms, and allows automatic parallelism and asynchronicity. A strong, static type system and higher-order semantics allow for high expressivity and compositionality in the program. The flexible runtime protocol enables third-party developers to add functionality using any language or environment. With Tierkreis, quantum software developers can easily build, visualise, verify, test, and debug complex hybrid workflows, and immediately deploy them to the cloud or a custom distributed environment.Comment: Submitted to SC22 Workshop: Quantum Computing Softwar

Quantitative tandem affinity purification, an effective tool to investigate protein complex composition in plant hormone signaling : strigolactones in the spotlight

Phytohormones tightly regulate plant growth by integrating changing environmental and developmental cues. Although the key players have been identified in many plant hormonal pathways, the molecular mechanisms and mode of action of perception and signaling remain incompletely resolved. Characterization of protein partners of known signaling components provides insight into the formed protein complexes, but, unless quantification is involved, does not deliver much, if any, information about the dynamics of the induced or disrupted protein complexes. Therefore, in proteomics research, the discovery of what actually triggers, regulates or interrupts the composition of protein complexes is gaining importance. Here, tandem affinity purification coupled to mass spectrometry (TAP-MS) is combined with label-free quantification (LFQ) to a highly valuable tool to detect physiologically relevant, dynamic protein-protein interactions in Arabidopsis thaliana cell cultures. To demonstrate its potential, we focus on the signaling pathway of one of the most recently discovered phytohormones, strigolactones

Molecular imaging with engineered physiology

In vivo imaging techniques are powerful tools for evaluating biological systems. Relating image signals to precise molecular phenomena can be challenging, however, due to limitations of the existing optical, magnetic and radioactive imaging probe mechanisms. Here we demonstrate a concept for molecular imaging which bypasses the need for conventional imaging agents by perturbing the endogenous multimodal contrast provided by the vasculature. Variants of the calcitonin gene-related peptide artificially activate vasodilation pathways in rat brain and induce contrast changes that are readily measured by optical and magnetic resonance imaging. CGRP-based agents induce effects at nanomolar concentrations in deep tissue and can be engineered into switchable analyte-dependent forms and genetically encoded reporters suitable for molecular imaging or cell tracking. Such artificially engineered physiological changes, therefore, provide a highly versatile means for sensitive analysis of molecular events in living organisms.National Institute of Mental Health (U.S.) (R01-MH103160)National Institute of Mental Health (U.S.) (R01-NS076462)BRAIN Initiative (award R24-MH109081)Massachusetts Institute of Technology. Simons Center for the Social BrainBoehringer Ingelheim Fonds (predoctoral fellowships)McGovern Institute for Brain Research at MI

Chemistry And Pharmacological Characterization Of Novel Nitrogen Analogues Of Amop-H-Oh (Sazetidine-A 6-[5-(Azetidin-2-Ylmethoxy)Pyridin-3-Yl]Hex-5-Yn-1- Ol) As α4β2-Nicotinic Acetylcholine Receptor-Selective Partial Agonists

In order to advance therapeutic applications of nicotinic ligands, continuing research efforts are being directed toward the identification and characterization of novel nicotinic acetylcholine receptor (nAChR) ligands that are both potent and subtype selective. Herein we report the synthesis and pharmacological evaluation of members of a new series of 3-alkoxy-5- aminopyridine derivatives that display good selectivity for the α4β2-nAChR subtype based on ligand binding and functional evaluations. The most potent ligand in this series, compound 64, showed high radioligand binding affinity and selectivity for rat α4β2-nAChR with a Ki value of 1.2 nM and 4700-fold selectivity for α4β2- over α3β4-nAChR, and ∼100-fold selectivity for functional, high-sensitivity, human α4β2-nAChR over α3β4*-nAChR. In the mouse forced swim test, compound 64 exhibited antidepressant-like effects. Structure-activity relationship (SAR) analyses suggest that the introduction of additional substituents to the amino group present on the pyridine ring of the N-demethylated analogue of compound 17 can provide potent α4β2-nAChR-selective ligands for possible use in treatment of neurological and psychiatric disorders including depression. © 2010 American Chemical Society

Flexible Group Fairness Metrics for Survival Analysis

Algorithmic fairness is an increasingly important field concerned with detecting and mitigating biases in machine learning models. There has been a wealth of literature for algorithmic fairness in regression and classification however there has been little exploration of the field for survival analysis. Survival analysis is the prediction task in which one attempts to predict the probability of an event occurring over time. Survival predictions are particularly important in sensitive settings such as when utilising machine learning for diagnosis and prognosis of patients. In this paper we explore how to utilise existing survival metrics to measure bias with group fairness metrics. We explore this in an empirical experiment with 29 survival datasets and 8 measures. We find that measures of discrimination are able to capture bias well whereas there is less clarity with measures of calibration and scoring rules. We suggest further areas for research including prediction-based fairness metrics for distribution predictions.Comment: Accepted in DSHealth 2022 (Workshop on Applied Data Science for Healthcare

The New Zealand Kauri (Agathis Australis) Research Project: A Radiocarbon Dating Intercomparison of Younger Dryas Wood and Implications for IntCal13

We describe here the New Zealand kauri (Agathis australis) Younger Dryas (YD) research project, which aims to undertake Δ14C analysis of ~140 decadal floating wood samples spanning the time interval ~13.1–11.7 kyr cal BP. We report 14C intercomparison measurements being undertaken by the carbon dating laboratories at University of Waikato (Wk), University of California at Irvine (UCI), and University of Oxford (OxA). The Wk, UCI, and OxA laboratories show very good agreement with an interlaboratory comparison of 12 successive decadal kauri samples (average offsets from consensus values of –7 to +4 14C yr). A University of Waikato/University of Heidelberg (HD) intercomparison involving measurement of the YD-age Swiss larch tree Ollon505, shows a HD/Wk offset of ~10–20 14C yr (HD younger), and strong evidence that the positioning of the Ollon505 series is incorrect, with a recommendation that the 14C analyses be removed from the IntCal calibration database

The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stress

The Multimodal Sentiment Analysis Challenge (MuSe) 2022 is dedicated to multimodal sentiment and emotion recognition. For this year's challenge, we feature three datasets: (i) the Passau Spontaneous Football Coach Humor (Passau-SFCH) dataset that contains audio-visual recordings of German football coaches, labelled for the presence of humour; (ii) the Hume-Reaction dataset in which reactions of individuals to emotional stimuli have been annotated with respect to seven emotional expression intensities, and (iii) the Ulm-Trier Social Stress Test (Ulm-TSST) dataset comprising of audio-visual data labelled with continuous emotion values (arousal and valence) of people in stressful dispositions. Using the introduced datasets, MuSe 2022 2022 addresses three contemporary affective computing problems: in the Humor Detection Sub-Challenge (MuSe-Humor), spontaneous humour has to be recognised; in the Emotional Reactions Sub-Challenge (MuSe-Reaction), seven fine-grained `in-the-wild' emotions have to be predicted; and in the Emotional Stress Sub-Challenge (MuSe-Stress), a continuous prediction of stressed emotion values is featured. The challenge is designed to attract different research communities, encouraging a fusion of their disciplines. Mainly, MuSe 2022 targets the communities of audio-visual emotion recognition, health informatics, and symbolic sentiment analysis. This baseline paper describes the datasets as well as the feature sets extracted from them. A recurrent neural network with LSTM cells is used to set competitive baseline results on the test partitions for each sub-challenge. We report an Area Under the Curve (AUC) of .8480 for MuSe-Humor; .2801 mean (from 7-classes) Pearson's Correlations Coefficient for MuSe-Reaction, as well as .4931 Concordance Correlation Coefficient (CCC) and .4761 for valence and arousal in MuSe-Stress, respectively.Comment: Preliminary baseline paper for the 3rd Multimodal Sentiment Analysis Challenge (MuSe) 2022, a full-day workshop at ACM Multimedia 202

Pleiotropic Effects of Biguanides on Mitochondrial Reactive Oxygen Species Production

Metformin is widely prescribed as a first-choice antihyperglycemic drug for treatment of type 2 diabetes mellitus, and recent epidemiological studies showed its utility also in cancer therapy. Although it is in use since the 1970s, its molecular target, either for antihyperglycemic or antineoplastic action, remains elusive. However, the body of the research on metformin effect oscillates around mitochondrial metabolism, including the function of oxidative phosphorylation (OXPHOS) apparatus. In this study, we focused on direct inhibitory mechanism of biguanides (metformin and phenformin) on OXPHOS complexes and its functional impact, using the model of isolated brown adipose tissue mitochondria. We demonstrate that biguanides nonspecifically target the activities of all respiratory chain dehydrogenases (mitochondrial NADH, succinate, and glycerophosphate dehydrogenases), but only at very high concentrations (10−2–10−1 M) that highly exceed cellular concentrations observed during the treatment. In addition, these concentrations of biguanides also trigger burst of reactive oxygen species production which, in combination with pleiotropic OXPHOS inhibition, can be toxic for the organism. We conclude that the beneficial effect of biguanides should probably be associated with subtler mechanism, different from the generalized inhibition of the respiratory chain

Recent Developments In Novel Antidepressants Targeting α4β2-Nicotinic Acetylcholine Receptors

Nicotinic acetylcholine receptors (nAChRs) have been investigated for developing drugs that can potentially treat various central nervous system disorders. Considerable evidence supports the hypothesis that modulation of the cholinergic system through activation and/or desensitization/inactivation of nAChR holds promise for the development of new antidepressants. The introductory portion of this Miniperspective discusses the basic pharmacology that underpins the involvement of α4β2-nAChRs in depression, along with the structural features that are essential to ligand recognition by the α4β2-nAChRs. The remainder of this Miniperspective analyzes reported nicotinic ligands in terms of drug design considerations and their potency and selectivity, with a particular focus on compounds exhibiting antidepressant-like effects in preclinical or clinical studies. This Miniperspective aims to provide an in-depth analysis of the potential for using nicotinic ligands in the treatment of depression, which may hold some promise in addressing an unmet clinical need by providing relief from depressive symptoms in refractory patients

Enantiopure Cyclopropane-Bearing Pyridyldiazabicyclo[3.3.0]Octanes As Selective α4β2-Nachr Ligands

We report the synthesis and characterization of a series of enantiopure 5-cyclopropane-bearing pyridyldiazabicyclo[3.3.0]octanes that display low nanomolar binding affinities and act as functional agonists at α4β2-nicotinic acetylcholine receptor (nAChR) subtype. Structure-activity relationship studies revealed that incorporation of a cyclopropane-containing side chain at the 5-position of the pyridine ring provides ligands with improved subtype selectivity for nAChR β2 subunit-containing nAChR subtypes (β2∗-nAChRs) over α4∗-nAChRs compared to the parent compound 4. Compound 15 exhibited subnanomolar binding affinity for α4β2-and α4β2∗-nAChRs with negligible interaction. Functional assays confirm selectivity for α4β2-nAChRs. Furthermore, using the SmartCube assay system, this ligand showed antidepressant, anxiolytic, and antipsychotic features, while mouse forced-swim assay further confirm the antidepressant-like property of 15