Miracle-dz/UniFAR-FTUs huggingface dataset:
The Synaptic Architecture of Layer 5 Thick Tufted Excitatory Neurons in the Visual Cortex of Mice

The neocortex is one of the most critical structures that makes us human, and it is involved in a variety of cognitive functions from perception to sensory integration and motor control. Composed of repeated modules, or microcircuits, the neocortex relies on distinct cell types as its fundamental building blocks. Despite significant progress in characterizing these cell types 1–5, an understanding of the complete synaptic partners associated with individual excitatory cell types remain elusive. Here, we investigate the connectivity of arguably the most well recognized and studied excitatory neuron in the neocortex: the thick tufted layer 5 pyramidal cell 6–10 also known as extra telencephalic (ET) 11 neurons. Although the synaptic interactions of ET neurons have been extensively explored, a comprehensive characterization of their local connectivity remains lacking. To address this knowledge gap, we leveraged a 1 mm3 electron microscopic (EM) dataset. We found that ET neurons primarily establish connections with inhibitory cells in their immediate vicinity. However, when they extend their axons to other cortical regions, they tend to connect more with excitatory cells. We also find that the inhibitory cells targeted by ET neurons are a specific group of cell types, and they preferentially inhibit ET cells. Finally, we observed that the most common excitatory targets of ET neurons are layer 5 IT neurons and layer 6 pyramidal cells, whereas synapses with other ET neurons are not as common. These findings challenge current views of the connectivity of ET neurons and suggest a circuit design that involves local competition among ET neurons and collaboration with other types of excitatory cells. Our results also highlight a specific circuit pattern where a subclass of excitatory cells forms a network with specific inhibitory cell types, offering a framework for exploring the connectivity of other types of excitatory cells.
c-Maf and Mafb function combinatorially to establish SGN subtype-specific synaptic properties

Diverse types of synapses transmit the vast information encoded in the nervous system. Even neurons of the same type can exhibit synaptic heterogeneity that alters circuit output. For instance, in the auditory system, each inner hair cell (IHC) signals to multiple Type I spiral ganglion neurons (SGNs) via glutamatergic synapses with heterogeneous properties, thereby communicating information about the frequency, timing, and intensity of the sounds we hear. Type I SGNs fall into three molecularly distinct subtypes (Ia, Ib and Ic) that make synapses with predictable differences in the position and volume of the glutamate receptor puncta, as well as the size of the apposing pre-synaptic ribbon in the IHC. To define the intrinsic mechanisms that determine subtype-appropriate synaptic properties, we investigated Maf family transcription factors, which play known roles in synapse development. Loss of c-Maf or Mafb from SGNs led to opposing effects on synaptic morphology and auditory responses, whereas loss of both c-Maf and Mafb led to formation of dysmorphic synapses and abnormal auditory responses. Further, although c-Maf and Mafb are both expressed in all SGNs, their levels differ across SGN subtypes. Single-cell RNA sequencing of single mutant SGNs revealed that c-Maf and Mafb have both shared and unique effects on subtype-specific programs of gene expression, including molecules associated with synaptic function and neuronal excitability. Double mutant SGNs, on the other hand, failed to diversify and showed dramatic changes in gene expression that included genes not changed in either single mutant. Together, these findings suggest that a combinatorial code of c-Maf and Mafb acts across SGN subtypes to establish synaptic heterogeneity that is critical for normal hearing function.
Dogs’ sensory-motor tuning shapes dog-human vocal interactions

Within species, vocal and auditory systems co-evolve to converge on a critical temporal acoustic structure that can be best produced and perceived. While dogs cannot produce articulated sounds, they respond to speech, raising the question as to whether this heterospecific receptive ability is shaped by exposure to speech or bounded by their own sensorimotor capacity. Acoustic analyses of vocalisations show that dogs’ main production rhythm is slower than the dominant (syllabic) speech rate, and that human dog-directed speech falls halfway in between. Comparative exploration of neural (electroencephalography) and behavioural responses to speech reveals that comprehension in dogs relies on a slower speech rhythm tracking (delta) than humans’ (theta), even though dogs are equally sensitive to human speech content and prosody. Thus, the dog audio-motor tuning differs from humans’, who vocally adjust their speech rate to this shared temporal channel.
Nearly half of all bacterial gene families are biased toward specific chromosomal positions

Many bacterial genes encoding components of the translation and transcription machinery occupy genomic positions close to the origin of genome replication. These positional biases are thought to result from selection for high expression levels, as genes close to the origin are the first to be duplicated after the initiation of DNA replication. However, recent work indicates that positional biases of RNA genes involved in translation have evolved to support optimal growth rate dependence of expression levels rather than high expression per se. We hypothesized that, more generally, natural selection may have favored the location of different genes at specific chromosomal positions to optimize the growth rate dependence of their relative gene copy numbers. Here we show that 49% of bacterial gene families are preferentially localized to specific chromosomal regions, with most families biased toward either the origin or the terminus of replication. From our hypothesis, we derive six specific predictions regarding the genes’ chromosomal positioning and functional categories, as well as the minimum cellular doubling times. All six predictions are robustly supported by comparative genomic analyses of 773 bacterial species and by proteomics data from Escherichia coli and Bacillus subtilis. Our findings reveal a complex relationship between bacterial growth, resource allocation and genome organization, and they provide new insights into the physiological significance and potential functions of a large number of gene families.
Passive multi-static SAR with GNSS transmitters: first theoretical and experimental results with point targets

This paper investigates the potential in using a passive multi-static Synthetic Aperture Radar (SAR) with Global Navigation Satellite Systems (GNSS) as transmitters of opportunity. The motivation for this research is based on the concept that a non-coherent combination between multiple bistatic images, obtained by satellites with essentially different angular separations, may yield multi-static imagery with a drastically improved resolution in the range dimension. This concept is confirmed by analytically deriving the multi-static Point Spread Function (MPSF) for this topology. The validity of the analytical results is verified with experimental data.
Stability of Neural Oscillations Supports Auditory-Motor Synchronization

Previous findings suggest that musical training leads to increased coactivation of auditory and motor brain networks, as well as enhanced auditory-motor synchronization. Less is known about the temporal dynamics of auditory-motor network interactions and how these temporal dynamics are shaped by musical training. The current study applied Recurrence Quantification Analysis, a nonlinear technique for characterizing the temporal dynamics of complex systems, to participants’ neurophysiological activity recorded via electroencephalography (EEG) during an auditory-motor synchronization task. We investigated changes in neural predictability and stability with musical training, and how these changes were related to synchronization accuracy and consistency. EEG was recorded while musicians and nonmusicians first tapped a familiar melody at a comfortable rate, called Spontaneous Production Rate (SPR). Then participants synchronized their taps with an auditory metronome presented at each participant’s SPR and at rates 15% and 30% slower than their SPR. EEG-based outcomes of determinism (predictability) and meanline (stability) were compared with behavioral synchronization measures. Musicians synchronized more consistently overall than nonmusicians. Both groups of participants showed decreased synchronization accuracy at slower rates, and higher EEG-based determinism (predictability) at slower rates. Furthermore, neural meanline (stability) measures correlated with synchronization consistency across all participants and stimulus rates; as neural stability increased, so did synchronization consistency. Neural stability may be a general mechanism supporting the maintenance of synchronization across rates, which may improve with musical training.
Characterization of landscape-scale habitat use by timber rattlesnakes (Crotalus horridus) within the ridge and valley and highlands regions of New Jersey

OF THE THESIS ii ACKNOWLEDGEMENTS iv TABLE OF CONTENTS vi LIST OF TABLES ix LIST OF ILLUSTRATIONS xi CHAPTER 1: INTRODUCTION 1 Study Species: 3 Objectives: 5 Background: 6 Research 6 Habitat Modeling and Conservation 9 CHAPTER 2: MODEL DEPICTING SUITABLE HABITAT FOR TIMBER RATTLESNAKE HIBERNACULA 16 MATERIALS AND METHODS: 17 Study Area 17 Data Collection and Compilation 18 Model Preparation 18 Field Reconnaissance 22 Model Development 23 RESULTS: 25 DISCUSSION: 29 Model Suitability 29
The role of theta and gamma oscillations in item memory, source memory, and memory confidence

Theta and gamma oscillations have been linked to episodic memory processes in various studies. Both oscillations seem to be vital for processes guided by the medial temporal lobe, such as the retrieval of information from memory. While theta oscillations increase with successful memory, it is unclear what the unique contribution of theta is to various subcomponents of memory. On the other hand, memory-related gamma oscillations have been mainly reported in the hippocampus, leaving the role of neocortical gamma in memory underexplored. In the current study, we explored how unique variability in memory accuracy and memory confidence contributes to fluctuations in theta and gamma power. To this end, we recorded EEG from 54 participants while they performed a source memory task. From this task we obtained their item memory accuracy, source memory accuracy, item memory confidence, and source memory confidence. These behavioral measures were put in a trial-by-trial linear mixed effects model to uncover their unique contribution to the oscillatory power in frontal and parietal regions. Our results are in line with the involvement of theta oscillations in both memory accuracy and confidence, but seem to indicate a main role for theta oscillations in memory-related confidence. In addition, we found that gamma oscillations play various roles in memory-processing, dependent of brain region.
Deciphering circulating tumor cells binding in a microfluidic system thanks to a parameterized mathematical model

Metastatic spread is a crucial process in which some questions remain unanswered. In this work, we focus on tumor cells circulating in the bloodstream, so-called Circulating Tumor Cells (CTCs). We aim to characterize their trajectories under the influence of hemodynamic forces and adhesion forces resulting from interaction with an endothelial layer using in vitro measurements performed with a microfluidic device. This essential step in tumor spread precedes intravascular arrest and metastatic extravasation. Our strategy is based on a differential equation model – a Poiseuille model for the fluid velocity and an ODE system for the cell adhesion model – and allows us to separate the two phenomena underlying cell motion: transport of the cell through the fluid and adhesion to the endothelial layer. A robust calibration procedure enables us to characterize the dynamics. Our strategy reveals the expected role of the glycoprotein CD44 compared to the integrin ITGB1 in the deceleration of CTCs and quantifies the strong impact of the fluid velocity in the protein binding.
Trypanosoma brucei gambiense group 2 experimental in vivo life cycle: from procyclic to bloodstream form

Trypanosoma brucei gambiense (Tbg) group 2 is a subgroup of trypanosomes able to infect humans in West and Central Africa. Unlike other agents causing sleeping sickness such as Tbg group 1 and Trypanosoma brucei rhodesiense, Tbg2 lacks the typical molecular markers associated with resistance to human serum. Only thirty-six strains of Tbg2 have been documented, and therefore, very limited research has been conducted despite its zoonotic nature. Some of these strains are only available in their procyclic form which hinders human serum resistance assays and mechanistic studies. Furthermore, the understanding of Tbg2’s potential to infect tsetse flies and mammalian hosts is limited. In this study, 165 Glossina palpalis gambiensis flies were experimentally infected with procyclic Tbg2 parasites. 35 days post-infection, 43 flies out of the 80 still alive flies were found Tbg2 PCR-positive in the saliva. These flies were able to infect 3 out of the 4 mice used for blood-feeding. Dissection revealed that only six flies really carried mature infections in their midguts and salivary glands. Importantly, a single fly with a mature infection was sufficient to infect a mammalian host. This Tbg2 transmission success confirms that Tbg2 strains can establish in tsetse flies and infect mammalian hosts. The study describes an effective in vivo protocol for transforming Tbg2 from procyclic to bloodstream form, reproducing the complete Tbg2 cycle from G. p. gambiensis to mice. These findings provide valuable insights into Tbg2’s host infectivity, and will facilitate further research on mechanisms of human serum resistance.
Dissolved gases from pressure changes in the lungs elicit an immune response in human peripheral blood

Conventional dogma suggests that decompression sickness (DCS) is caused by nitrogen bubble nucleation in the blood vessels and/or tissues; however, the abundance of bubbles does not correlate with DCS severity. Since immune cells respond to chemical and environmental cues, we hypothesized that the elevated partial pressures of dissolved gases drive aberrant immune cell phenotypes in the alveolar vasculature. To test this hypothesis, we measured immune responses within human lung-on–a-chip devices established with primary alveolar cells and microvascular cells. Devices were pressurized to 1.0 or 3.5 atm and surrounded by normal alveolar air or oxygen-reduced air. Phenotyping of neutrophils, monocytes, and dendritic cells as well as multiplexed ELISA revealed that immune responses occur within 1 hour and that normal alveolar air (i.e., hyperbaric oxygen and nitrogen) confer greater immune activation. This work strongly suggests innate immune cell reactions initiated at elevated partial pressures contribute to the etiology of DCS. Translational Impact Statement Our work reveals that the elevated partial pressures of dissolved gases within the vasculature drives immune cell activation. These findings have broad implications in identifying novel biomarkers for high-risk individuals (e.g., divers, pilots) through screening differential immune markers across patients. Further, this work offers a lens through which novel strategies to mitigate DCS in clinical scenarios may be employed by the delivery of prophylactic drugs that temper immune reactions.
Electrosensory and metabolic responses of weakly electric fish to changing water conductivity

Weakly electric Gymnotiform fishes use self-generated electric organ discharges (EODs) to navigate and communicate. The electrosensory range for these processes is a function of EOD amplitude, determined by the fish’s electric organ (EO) output and the electrical conductivity of the surrounding water. Anthropogenic activity, such as deforestation, dams, and industrial/agricultural runoff, are known to increase water conductivity in neotropical habitats, likely reducing the electrosensory range of these fish. We investigated whether fish modulate EO output as means of re-expanding electrosensory range after a rapid increase in water conductivity in the pulse-type Brachyhypopomus gauderio and the wave-type Eigenmannia virescens. Furthermore, because EOD production incurs significant metabolic costs, we assessed whether such compensation is associated with an increase in metabolic rate. Following the conductivity increase B. gauderio increased EOD amplitude by 20.2 ± 4.3% over six days but with no associated increase in metabolic rate, whereas the EOD amplitude of E. virescens remained constant, accompanied by an unexpected decrease in metabolic rate. Our results suggest that B. gauderio uses a compensation mechanism that requires no metabolic investment, such as impedance matching, or a physiological tradeoff wherein energy is diverted from other physiological processes to increase EO output. These divergent responses between species could be the result of differences in reproductive life history or evolutionary adaptations to different aquatic habitats. Continued investigation of electrosensory responses to changing water conditions will be essential for understanding the effects of anthropogenic disturbances on gymnotiforms, and potential physiological mechanisms for adapting to a rapidly changing aquatic environment.
Ultrahigh-Pressure Metamorphism in the Western Gneiss Region of the Norwegian Caledonides

The distribution and characterization of UHP rocks within the Western Gneiss Region (WGR) of the Norwegian Caledonides is reviewed. While recent studies have documented a significantly increased number of eclogite localities preserving mineralogical evidence for Scandian-aged UHP metamorphism, much uncertainty remains over the regional extent of any UHP province because of the widespread overprinting by retrograde amphibolite-facies assemblages (especially in the dominant gneisses) during exhumation of the terrain. Based on current observations, the UHP metamorphic province may be limited to a northwest region of only∼4000 km2, although an enigmatic mixed zone of HP (quartz-stable) and UHP (coesite-stable) eclogites extends a minimum of 5 km farther south and east in the Outer Nordfjord area. Quantitative P-T evaluation of key mineral reaction equilibria for eclogites sampled across the WGR indicates an overall regional trend of increased T and P to the northwest. This is consistent with Baltic plate rock.
UZH_Pandas at SimpleText@CLEF-2023: Alpaca LoRA 7B and LENS Model Selection for Scientific Literature Simplification

In this study, we advance the field of scientific text simplification by harnessing the capabilities of Alpaca LoRA 7B [1], a large language model derivative of the 7B LLaMA [2]. We expand the dataset for Task 3 of SimpleText@CLEF-2023 [3] by integrating data from Task 2, aiming to identify complex terms in need of explanation for better text comprehension. Our methodology involves rigorous fine-tuning, prompt engineering, and the application of the LENS score [4] as a tool for model reranking and evaluation. Our findings suggest the efficacy of our approach in creating a more effective text simplification system. Our final model demonstrates expertise not only in expanding abbreviations, but also in explaining complex terms present in the input sentence. This ability allows it to create texts that are both easy to understand and simple to comprehend, making the information presented more accessible and opening the door for more efficient communication. However, the study also highlights several challenges and areas of improvement, providing a valuable contribution to future research in text simplification. Our research underscores the potential of large language models like Alpaca LoRA 7B in transforming complex terminologies into more accessible language, ultimately enhancing the public’s understanding of scientific literature.
Profiling Cryptocurrency Influencers with Few-shot Learning

This overview presents the Author Profiling shared task at PAN2023. This year the main aim is identifying cryptocurrency influencers in social media from a low-resource perspective. We focused on English Twitter posts for three different sub-tasks: (1) SubTask1. Low-resource influencer profiling ; (2) SubTask2. Low-resource influencer interest profiling ; and (3) SubTask3. Low-resource influencer intent profiling . For this purpose, three English datasets have been provided to the participants. A total of 27 teams participated in the shared task, and we compared their performance with four baseline approaches. This overview paper reviews the approaches of the participants and presents a detailed discussion of the evaluation results.
A Prompt Engineering Approach to Scientific Text Simplification: CYUT at SimpleText2023 Task3

This paper reports our approach to the SimpleText lab. In year 2023, we focus on the Task 3: Rewrite this! , Our system adopts the GPT3.5 and GPT4 generation models to rewrite the original sentences. We used different prompts to guide the model to generate simplified sentence with different guidelines. During system development, we used three metrics to evaluate the results. The official results are also reported.
Orchestrated Excitatory and Inhibitory Learning Rules Lead to the Unsupervised Emergence of Up-states and Balanced Network

Self-sustaining dynamics maintained through recurrent connections are of fundamental importance to cortical function. We show that Up-states—an example of self-sustained network dynamics—autonomously emerge in cortical circuits across three weeks of ex vivo development, establishing the presence of unsupervised synaptic learning rules that lead to globally stable emergent dynamics. Computational models of excitatory-inhibitory networks have established that four sets of weights (WE←E, WE←I, WI←E, WI←I) cooperate to generate stable self-sustained dynamics, but have not addressed how a family of learning rules can operate in parallel at all four weight classes to achieve self-sustained inhibition-stabilized regimes. Using numerical and analytical methods we show that standard homeostatic rules cannot account for the emergence of self-sustained dynamics due to the paradoxical effect. We derived a novel family of homeostatic learning rules that operate in parallel at all four synaptic classes, which robustly lead to the emergence of Up-states and balanced excitation-inhibition.
IUEXIST: Multilingual Pre-trained Language Models for Sexism Detection on Twitter in EXIST2023

We describe an approach towards sexism detection in tweets, for the EXIST 2023-Task 1, a shared task on sexism identification. The dataset for this task consists of English and Spanish tweets. Task 1 is a binary classification task, where our system needs to decide whether a given tweet contains sexist expressions or behaviors. We describe our experiments with different machine learning algorithms and vector lengths, algorithms including Multinomial Naive Bayes, SVM, XGBoost, transformers, and Distilbert. The best model performance was achieved by an ensemble of transformers including XLM-Roberta small and large and TwHIN-BERT base and large, combined using XGBoost. The ensemble was trained on the original tweets dataset plus additional training data from the 2021 shared task.