Miracle-dz/UniFAR-FTUs huggingface dataset:
Internalizing Indistinguishability with Dependent Types

In type systems with dependency tracking, programmers can assign an ordered set of levels to computations and prevent information flow from high-level computations to the low-level ones. The key notion in such systems is indistinguishability: a definition of program equivalence that takes into account the parts of the program that an observer may depend on. In this paper, we investigate the use of dependency tracking in the context of dependently-typed languages. We present the Dependent Calculus of Indistinguishability (DCOI), a system that adopts indistinguishability as the definition of equality used by the type checker. DCOI also internalizes that relation as an observer-indexed propositional equality type, so that programmers may reason about indistinguishability within the language. Our design generalizes and extends prior systems that combine dependency tracking with dependent types and is the first to support conversion and propositional equality at arbitrary observer levels. We have proven type soundness and noninterference theorems for DCOI and have developed a prototype implementation of its type checker.
Monotonicity and the Precision of Program Analysis

It is widely known that the precision of a program analyzer is closely related to intensional program properties, namely, properties concerning how the program is written. This explains, for instance, the interest in code obfuscation techniques, namely, tools explicitly designed to degrade the results of program analysis by operating syntactic program transformations. Less is known about a possible relation between what the program extensionally computes, namely, its input-output relation, and the precision of a program analyzer. In this paper we explore this potential connection in an effort to isolate program fragments that can be precisely analyzed by abstract interpretation, namely, programs for which there exists a complete abstract interpretation. In the field of static inference of numeric invariants, this happens for programs, or parts of programs, that manifest a monotone (either non-decreasing or non-increasing) behavior. We first formalize the notion of program monotonicity with respect to a given input and a set of numerical variables of interest. A sound proof system is then introduced with judgments specifying whether a program is monotone relatively to a set of variables and a set of inputs. The interest in monotonicity is justified because we prove that the family of monotone programs admits a complete abstract interpretation over a specific class of non-trivial numerical abstractions and inputs. This class includes all non-relational abstract domains that refine interval analysis (i.e., at least as precise as the intervals abstraction) and that satisfy a topological convexity hypothesis.
API-Driven Program Synthesis for Testing Static Typing Implementations

We introduce a novel approach for testing static typing implementations based on the concept of API-driven program synthesis. The idea is to synthesize type-intensive but small and well-typed programs by leveraging and combining application programming interfaces (APIs) derived from existing software libraries. Our primary insight is backed up by real-world evidence: a significant number of compiler typing bugs are caused by small test cases that employ APIs from the standard library of the language under test. This is attributed to the inherent complexity of the majority of these APIs, which often exercise a wide range of sophisticated type-related features. The main contribution of our approach is the ability to produce small client programs with increased feature coverage, without bearing the burden of generating the corresponding well-formed API definitions from scratch. To validate diverse aspects of static typing procedures (i.e., soundness, precision of type inference), we also enrich our API-driven approach with fault-injection and semantics-preserving modes, along with their corresponding test oracles. We evaluate our implemented tool, Thalia on testing the static typing implementations of the compilers for three popular languages, namely, Scala, Kotlin, and Groovy. Thalia has uncovered 84 typing bugs (77 confirmed and 22 fixed), most of which are triggered by test cases featuring APIs that rely on parametric polymorphism, overloading, and higher-order functions. Our comparison with state-of-the-art shows that Thalia yields test programs with distinct characteristics, offering additional and complementary benefits.
Timely Inference over Networks

Brief Biography: Md Kamran Chowdhury Shisher is a final-year Ph.D. candidate in the Department of Electrical and Computer Engineering at Auburn University, Auburn, AL, USA. He expects to graduate by May 2024. His Ph.D. works are advised by Yin Sun. Shisher's research interests include Information Freshness, Wireless Networks, Semantic Communications, and Machine Learning. His Ph.D. works focus on designing low-complexity optimal scheduling algorithms for remote inference systems. He also developed an information-theoretic tool to analyze the impact of freshness on the performance of real-time applications. He received his M.Sc. degree in Electrical Engineering at Auburn University in 2022. He completed his B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology in 2017.
FANCJ promotes PARP1 activity during DNA replication that is essential in BRCA1 deficient cells

Single-stranded DNA gaps are postulated to be fundamental to the mechanism of anti-cancer drugs. Gaining insights into their induction could therefore be pivotal for advancing therapeutic strategies. For poly (ADP-ribose) polymerase inhibitors (PARPi) to be effective, the presence of FANCJ helicase is required. However, the relationship between FANCJ dependent gaps and PARP1 catalytic inhibition or trapping—both linked to PARPi toxicity in BRCA deficient cells—is yet to be elucidated. Here, we find that the efficacy of PARPi is contingent on S-phase PARP1 activity, which is compromised in FANCJ deficient cells because PARP1, along with MSH2, is “sequestered” by G-quadruplexes. PARP1’s replication activity is also diminished in cells missing a FANCJ-MLH1 interaction, but in such cells, depleting MSH2 can release sequestered PARP1, restoring PARPi-induced gaps and sensitivity. Our observations indicate that sequestered and trapped PARP1 are different chromatin-bound forms, with FANCJ loss increasing PARPi resistance in cells susceptible to canonical PARP1 trapping. However, in BRCA1 null cells, the loss of FANCJ mirrors the effects of PARP1 loss or inhibition, with the common detrimental factor being the loss of PARP1 activity during DNA replication, not trapping. These insights underline the crucial role of PARP1 activity during DNA replication in BRCA deficient cells and emphasize the importance of understanding drug mechanisms for enhancing precision medicine.
Next-generation mapping of the salicylic acid signaling hub and transcriptional cascade

For over 60 years, salicylic acid (SA) has been known as a plant immune signal required for both basal and systemic acquired resistance (SAR). SA activates these immune responses by reprogramming up to 20% of the transcriptome through the function of NPR1. However, components in the NPR1-signaling hub, which appears as nuclear condensates, and the NPR1-signaling cascade remained elusive due to difficulties in studying transcriptional cofactors whose chromatin associations are often indirect and transient. To overcome this challenge, we applied TurboID to divulge the NPR1-proxiome, which detected almost all known NPR1-interactors as well as new components of transcription-related complexes. Testing of new components showed that chromatin remodeling and histone demethylation contribute to SA-induced resistance. Globally, NPR1-proxiome shares a striking similarity to GBPL3-proxiome involved in SA synthesis, except associated transcription factors (TFs), suggesting that common regulatory modules are recruited to reprogram specific transcriptomes by transcriptional cofactors, like NPR1, through binding to unique TFs. Stepwise greenCUT&RUN analyses showed that, upon SA-induction, NPR1 initiates the transcriptional cascade primarily through association with TGA TFs to induce expression of secondary TFs, predominantly WRKYs. WRKY54 and WRKY70 then play a major role in inducing immune-output genes without interacting with NPR1 at the chromatin. Moreover, a loss of NPR1 condensate formation decreases its chromatin-association and transcriptional activity, indicating the importance of condensates in organizing the NPR1-signaling hub and initiating the transcriptional cascade. This study demonstrates how combinatorial applications of TurboID and stepwise greenCUT&RUN transcend traditional genetic methods to globally map signaling hubs and transcriptional cascades.
How much warming can mosquito vectors tolerate?

While climate warming is expected to substantially impact the global landscape of mosquito-borne disease, impacts will vary across disease systems and regions. Understanding which diseases, and where within their distributions, these impacts are most likely to occur is critical for preparing public health interventions. While research has centered on potential warming-driven expansions in vector transmission, less is known about the potential for vectors to experience warming-driven stress or even local extirpations. In conservation biology, species risk from climate warming is often quantified through vulnerability indices such as thermal safety margins – the difference between an organism’s upper thermal limit and its habitat temperature. Here, we estimated thermal safety margins for 12 major mosquito species (including Aedes aegypti and Anopheles gambiae) that are the major vectors of malaria, dengue, chikungunya, Zika, West Nile and other major arboviruses, across their known ranges to investigate which mosquitoes and regions are most and least vulnerable to climate warming. We find that most mosquito vector species have large positive thermal safety margins across the majority of their range, when realistic assumptions of mosquito behavioral thermoregulation are incorporated. For species with distributions spanning both hemispheres, we find the lowest climate vulnerability, in terms of both the magnitude and duration of thermal safety, just south of the equator, as well as at their northern temperate range edges, and the highest climate vulnerability in the subtropics. Underlying these broad scale patterns, we find clear biogeographical differences in vector thermal safety with regions such as the Middle East, India, northwestern Africa, southeastern Australia, and the southwestern U.S., and desert and xeric shrubland biomes having the highest climate vulnerability across vector species.
SEX-SPECIFIC IMPACTS OF EARLY LIFE SLEEP DISRUPTION: ETHANOL SEEKING, SOCIAL INTERACTION, AND ANXIETY ARE DIFFERENTIALLY ALTERED IN ADOLESCENT PRAIRIE VOLES

Early life sleep is important for neuronal development and maturation. Using the highly social prairie vole rodent model, we have previously reported that early-life sleep disruption (ELSD) during the pre-weaning period postnatal day (P)14 to 21 results in adult interference with social bonding and increases ethanol consumption following a stressor. Furthermore, we have reported increased parvalbumin expression and reduced glutamatergic neurotransmission in cortical regions in adult prairie voles that experienced this paradigm. To understand the impact of ELSD on the lifespan, examination of an earlier time in life is necessary. Thus, the aim of the present study was to examine the behavioral outcomes of ELSD on adolescent prairie voles. Here we hypothesized that anxiety and reward related behaviors, as measured by light/dark box, 2-bottle choice and social interactions, would be negatively impacted by ELSD in adolescent male and female prairie voles. Male ELSD voles were no different from control voles in measures of anxiety and ethanol preference or consumption, but affiliative social interactions were significantly reduced. ELSD differentially impacted female prairie voles, with increased anxiety-like behavior and reductions in ethanol consumption compared to Controls, but no impact on ethanol preference or social interactions. Together, these results suggest both male and female prairie voles experience differential changes to reward seeking behaviors, but only female prairie voles showed increases in anxiety-like behavior. These results further suggest that early-life sleep is critically important for neurotypical behaviors in adolescence, a time where reward-seeking and risky behaviors are adaptive for learning and promoting survival.
Altered Socio-Affective Communication and Amygdala Development in mice with Protocadherin10-deficient Interneurons

Autism Spectrum Disorder (ASD) is a group of neurodevelopmental conditions associated with deficits in social interaction and communication, together with repetitive behaviors. The cell adhesion molecule Protocadherin10 (Pcdh10) has been implicated in the etiology of ASD. Pcdh10 is expressed in the nervous system during embryonic and early postnatal development and has been linked to neural circuit formation. Here, we show strong expression of Pcdh10 in the ganglionic eminences and in the basolateral complex of the amygdala at mid and late embryonic stages, respectively. Both inhibitory and excitatory neurons expressed Pcdh10 in the basolateral complex at perinatal stages and genes linked to vocalization behavior were enriched in Pcdh10- expressing neurons in adult mice. To further investigate the involvement of Pcdh10 in neurodevelopment with relevance to ASD, and to assess the functional and behavioral consequences of loss of Pcdh10 in basolateral amygdala interneurons, we combined a ubiquitous and a conditional Pcdh10 knockout mouse model. Conditional knockout of Pcdh10 reduced the number of interneurons in the basolateral complex. Both models exhibited altered developmental trajectories of socio-affective communication through isolation-induced ultrasonic vocalizations in neonatal pups, characterized by increased emission rates in heterozygous pups. Furthermore, acoustic call features were affected and heterozygous conditional knockout pups emitted calls characterized by reduced peak frequencies but increased frequency modulation. Additionally, we identified distinct clusters of call subtypes with specific developmental trajectories, suggesting the vocalization repertoire is extensive and dynamic during early life. The nuanced alterations in socio-affective communication at the level of call emission rates, acoustic call features, and clustering of call subtypes were primarily seen in heterozygous pups of the conditional knockout and less prominent in the ubiquitous Pcdh10 knockout, suggesting that changes in anxiety levels associated with Gsh2-lineage interneurons might drive the observed behavioral effects. Together, this demonstrates that loss of Pcdh10 specifically in interneurons contributes to behavioral alterations in socio-affective communication with relevance to ASD.
Reconstructing cell histories in space with image-readable base editor recording

Knowing the ancestral states and lineage relationships of individual cells could unravel the dynamic programs underlying development. Engineering cells to actively record information within their own genomic DNA could reveal these histories, but existing recording systems have limited information capacity or disrupt spatial context. Here, we introduce baseMEMOIR, which combines base editing, sequential hybridization imaging, and Bayesian inference to allow reconstruction of high-resolution cell lineage trees and cell state dynamics while preserving spatial organization. BaseMEMOIR stochastically and irreversibly edits engineered dinucleotides to one of three alternative image-readable states. By genomically integrating arrays of editable dinucleotides, we constructed an embryonic stem cell line with 792 bits of recordable, image-readable memory, a 50-fold increase over the state of the art. Simulations showed that this memory size was sufficient for accurate reconstruction of deep lineage trees. Experimentally, baseMEMOIR allowed precise reconstruction of lineage trees 6 or more generations deep in embryonic stem cell colonies. Further, it also allowed inference of ancestral cell states and their quantitative cell state transition rates, all from endpoint images. baseMEMOIR thus provides a scalable framework for reconstructing single cell histories in spatially organized multicellular systems.
Linking brain-heart interactions to emotional arousal in immersive virtual reality

The subjective experience of emotions is rooted in the contextualized perception of changes in bodily (e.g., heart) activity. Increased emotional arousal (EA) has been related to lower high- frequency heart rate variability (HF-HRV), lower EEG parieto-occipital alpha power, and higher heartbeat-evoked potential (HEP) amplitudes. We studied EA-related brain-heart interactions (BHIs) using immersive virtual reality (VR) for naturalistic yet controlled emotion induction. 29 healthy adults (13 women, age: 26±3) completed a VR experience that included rollercoasters while EEG and ECG were recorded. Continuous EA ratings were collected during a video replay immediately after. We analyzed EA-related changes in HF-HRV as well as in BHIs using HEPs and directional functional BHI modeling. Higher EA was associated with lower HEP amplitudes in a left fronto-central electrode cluster. While parasympathetic modulation of the heart (HF-HRV) and parieto-occipital EEG alpha power were reduced during higher EA, there was no evidence for the hypothesized EA-related changes in bidirectional information flow between them. Whole-brain exploratory analyses in additional EEG (delta, theta, alpha, beta and gamma) and HRV (low-frequency, LF, and HF) frequency bands indicated a temporo-occipital cluster, in which higher EA was linked to decreased brain-to-heart (gamma→HF-HRV) and increased heart-to-brain (LF-HRV→gamma) information flow. Our results confirm previous findings from less naturalistic experiments and suggest EA-related BHI changes in temporo-occipital gamma power.
The Interpretable Multimodal Machine Learning (IMML) framework reveals pathological signatures of distal sensorimotor polyneuropathy

Distal sensorimotor polyneuropathy (DSPN) is a common neurological disorder in elderly adults and people with obesity, prediabetes and diabetes and is associated with high morbidity and premature mortality. DSPN is a multifactorial disease and not fully understood yet. In order to address this, we developed the Interpretable Multimodal Machine Learning (IMML) framework for predicting DSPN prevalence and incidence based on sparse multimodal data. Exploiting IMMLs interpretability further empowered biomarker identification. We leveraged the population-based KORA F4/FF4 cohort including 1,091 participants and their deep multimodal characterisation, i.e. clinical data, genomics, methylomics, transcriptomics, proteomics, inflammatory proteins and metabolomics. Clinical data alone was sufficient to stratify individuals with and without DSPN (AUROC = 0.752), whilst predicting DSPN incidence 6.5±0.2 years later strongly benefitted from clinical data complemented with two or more molecular modalities (improved ΔAUROC >0.1, achieved AUROC of 0.714). Important and interpretable features of the prediction of incident DSPN included up-regulation of proinflammatory cytokines, down-regulation of SUMOylation pathway and essential fatty acids, thus yielding novel insights in the disease pathophysiology. These may become biomarkers for incident DSPN, guide prevention strategies and serve as proof of concept for the utility of IMML in studying complex diseases.
Mutation of highly conserved residues in loop 2 of the coronavirus macrodomain demonstrates that enhanced ADP-ribose binding is detrimental to infection

All coronaviruses (CoVs) encode for a conserved macrodomain (Mac1) located in nonstructural protein 3 (nsp3). Mac1 is an ADP-ribosylhydrolase that binds and hydrolyzes mono-ADP-ribose from target proteins. Previous work has shown that Mac1 is important for virus replication and pathogenesis. Within Mac1, there are several regions that are highly conserved across CoVs, including the GIF (glycine-isoleucine-phenylalanine) motif. To determine how the biochemical activities of these residues impact CoV replication, the isoleucine and the phenylalanine residues were mutated to alanine (I-A/F-A) in both recombinant Mac1 proteins and recombinant CoVs, including murine hepatitis virus (MHV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The F-A mutant proteins had ADP-ribose binding and/or hydrolysis defects that led to attenuated replication and pathogenesis in cell culture and mice. In contrast, the I-A mutations had normal enzyme activity and enhanced ADP-ribose binding. Despite increased ADP-ribose binding, I-A mutant MERS-CoV and SARS-CoV-2 were highly attenuated in both cell culture and mice, indicating that this isoleucine residue acts as a gate that controls ADP-ribose binding for efficient virus replication. These results highlight the function of this highly conserved residue and provide unique insight into how macrodomains control ADP-ribose binding and hydrolysis to promote viral replication and pathogenesis.
Synaptic Proteomes of Cortical Interneuron Classes Revealed by Antibody Directed Proximity Labeling

Subtypes of inhibitory interneurons play diverse roles within neural circuits in cerebral cortex. Defining the molecular underpinnings of interneuron functions within cortical circuits will require identification of interneuron synaptic proteomes. In this study, we first combined genetically directed expression of tdTomato-synaptophysin with antibody-directed proximity labeling and tandem mass spectrometry to identify synaptic proteomes of three major interneuron classes in mouse cortex: parvalbumin (PV), somatostatin (SS), and vasoactive intestinal peptide (VIP). After stringent filtering we identified 581 proteins: 228 identified in all cell classes and 353 in one or two of three classes. The PV class had the largest number of uniquely identified proteins (141), followed by VIP (30) and SST (20). Consistent with previously reported electrophysiological evidence, PV presynaptic proteomes were enriched for NMDA receptor subunits and scaffolding proteins. We used antibodies against synaptotagmin 2 (Syt2), a presynaptic protein present at PV synapses, to confirm NMDAR localization, and to find that the mu-opioid receptor agonist buprenorphine rapidly caused reorganization of the PV presynaptic proteome. Overall, our results reveal proteomes of PV, SST, and VIP interneurons in cortex that likely underlie distinct and dynamic interneuron synaptic properties.
La topographie comme marqueur de la déformation de la lithosphère

L’objectif de ma recherche est de contribuer a la comprehension des processus geodynamiques a l’origine des chaines de montagnes par l’etude des mouvements tectoniques. Ces derniers se decomposent en deplacements horizontaux qui decalent les rivieres, et en deplacements verticaux de la topographie en reponse a un amincissement ou un epaississement de la lithosphere, ou encore en raison des mouvements dans le manteau inferieur a l’origine de la topographie dynamique. Les deplacements verticaux de la topographie correspondent au surface uplift comme l’ont defini England et Molnar (1990), c'est-a-dire le rock uplift moins l’erosion. Dans les chaines actives, le rock uplift est genere par la tectonique qui force les rivieres a inciser. Meme si l’erosion depend egalement du flux d’eau et qu’elle est donc modulee par le climat, elle est surtout controlee par la tectonique. Je me suis jusqu’a present interesse a la dynamique du surface uplift dans les chaines, et a son influence sur le reseau de drainage et le remplissage des bassins sedimentaires.