Miracle-dz/UniFAR-FTUs huggingface dataset:
Internal noise promotes heterogeneous synaptic dynamics important for working memory in recurrent neural networks

Recurrent neural networks (RNNs) based on model neurons that communicate via continuous signals have been widely used to study how cortical neurons perform cognitive tasks. Training such networks to perform tasks that require information maintenance over a brief period (i.e., working memory tasks) remains a challenge. Critically, the training process becomes difficult when the synaptic decay time constant is not fixed to a large constant number for all the model neurons. We hypothesize that the brain utilizes intrinsic cortical noise to generate a reservoir of heterogeneous synaptic decay time constants optimal for maintaining information. Here, we show that introducing random, internal noise to the RNNs not only speeds up the training but also produces stable models that can maintain information longer than the RNNs trained without internal noise. Importantly, this robust working memory performance induced by incorporation of internal noise during training is attributed to an increase in synaptic decay time constants of a sub-population of inhibitory units.
Electrophysiological signatures of targeted memory reactivation during sleep are not accompanied by motor performance improvements in older adults

Targeted memory reactivation (TMR) during post-learning sleep enhances memory consolidation in young adults by modulating electrophysiological markers of plasticity (i.e., slow waves (SW) and slow/sigma oscillation coupling). Interestingly, older adults are known to exhibit deficits in motor memory consolidation, an impairment that has been linked to age-related degradations in the same sleep features sensitive to TMR interventions. We thus hypothesized that TMR would enhance motor memory consolidation in older adults via the modulation of these electrophysiological markers. Seventeen healthy older participants (age range: 50-74) were trained on a bimanual motor task involving two sequences that were cued by different sounds. Participants were retested after a 90-minute nap and the following morning. During non-rapid eye movement sleep of the post-learning nap, two different auditory cues were played: one sound associated to a learned – and thus reactivated – sequence and one control sound not associated to learning. Results indicated that changes in performance did not differ between reactivated and non-reactivated sequences. Yet, analyses of electrophysiological data revealed that TMR increased SW density. Moreover, phase-amplitude coupling between slow (0.5-2 Hz) and beta (around 20 Hz) oscillations before the SW trough was strengthened by the presentation of the unassociated sounds. Furthermore, the increase in slow/sigma (12-16 Hz) oscillation coupling around 1.75 sec post-SW trough for unassociated (as compared to associated) sounds was related to higher TMR-induced performance enhancement. Our results collectively demonstrate that, in older adults, TMR did not impact motor performance but modulated sleep-related markers of plasticity likely involved in protection against irrelevant information. results suggest that the coupling between slow oscillations and beta (but not sigma) oscillations was stronger just before the onset of the SW during the unassociated as compared to the rest intervals but that the preferred coupling phase was not modulated by the type of auditory cue. oscillations following the negative SW peak during unassociated intervals was associated to a TMR-induced performance enhancement. These findings collectively suggest that the temporal coordination between SWs and sigma/beta oscillations plays a role in the protection of memories against irrelevant stimuli.
Deep learning algorithms reveal a new visual-semantic representation of familiar faces in human perception and memory

Recent studies show significant similarities between the representations humans and deep neural networks (DNNs) generate for faces. However, two critical aspects of human face recognition are overlooked by these networks. First, human face recognition is mostly concerned with familiar faces, which are encoded by visual and semantic information, while current DNNs solely rely on visual information. Second, humans represent familiar faces in memory, but representational similarities with DNNs were only investigated for human perception. To address this gap, we combined visual (VGG-16), visual-semantic (CLIP), and natural language processing (NLP) DNNs to predict human representations of familiar faces in perception and memory. The visual-semantic network substantially improved predictions beyond the visual network, revealing a new visual-semantic representation in human perception and memory. The NLP network further improved predictions of human representations in memory. Thus, a complete account of human face recognition should go beyond vision and incorporate visual-semantic, and semantic representations.
Determinants and Mechanisms of the Low Fusogenicity and Endosomal Entry of Omicron Subvariants

The rapid spread and strong immune evasion of the SARS-CoV-2 Omicron subvariants has raised serious concerns for the global COVID-19 pandemic. These new variants exhibit reduced fusogenicity and increased endosomal entry pathway utilization compared to the ancestral D614G variant, the underlying mechanisms of which remain elusive. Here we show that the C-terminal S1 mutations of the BA.1. 1 subvariant, H655Y and T547K, critically govern the low fusogenicity of Omicron. Notably, H655Y also dictates the enhanced endosome entry pathway utilization. Mechanistically, T547K and H655Y likely stabilize the spike trimer conformation, as shown by increased molecular interactions in structural modeling as well as reduced S1 shedding. Importantly, the H655Y mutation also determines the low fusogenicity and high dependence on the endosomal entry pathway of other Omicron subvariants, including BA.2, BA.2. 12.1, BA.4/5 and BA.2. 75. These results uncover mechanisms governing Omicron subvariant entry and provide insights into altered Omicron tissue tropism and pathogenesis.
Development and validation of an AI/ML platform for the discovery of splice-switching oligonucleotide targets

This study demonstrates the value that artificial intelligence/machine learning (AI/ML) provides for the identification of novel and verifiable splice-switching oligonucleotide (SSO) targets in-silico. SSOs are antisense compounds that act directly on pre-mRNA to modulate alternative splicing (AS). To leverage the potential of AS research for therapeutic development, we created SpliceLearn™, an AI/ML algorithm for the identification of modulatory SSO binding sites on pre-mRNA. SpliceLearn also predicts the identity of specific splicing factors whose binding to pre-mRNA is blocked by SSOs, adding considerable transparency to AI/ML-driven drug discovery and informing biological insights useful in further validation steps. Here we predicted NEDD4L exon 13 (NEDD4Le13) as a novel target in triple negative breast cancer (TNBC) and computationally designed an SSO to modulate NEDD4Le13. Targeting NEDD4Le13 with this SSO decreased the proliferative and migratory behavior of TNBC cells via downregulation of the TGFβ pathway. Overall, this study illustrates the ability of AI/ML to extract actionable insights from RNA-seq data. SpliceLearn is part of the SpliceCore® platform, an AI/ML predictive ensemble for AS-based drug target discovery.
Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Intraductal papillary mucinous neoplasms (IPMNs) are cystic precursor lesions to pancreatic ductal adenocarcinoma (PDAC). IPMNs undergo multistep progression from low grade (LG) to high grade (HG) dysplasia, culminating in invasive neoplasia. While patterns of IPMN progression have been analyzed using multi-region sequencing for somatic mutations, there is no integrated assessment of molecular events, including copy number alterations (CNAs) and transcriptomics changes, that accompany IPMN progression. We performed laser capture microdissection on surgically resected IPMNs of varying grades of histological dysplasia obtained from 24 patients (total of 74 independent histological lesions), followed by whole exome and whole transcriptome sequencing. Overall, HG IPMNs displayed a significantly greater aneuploidy score than LG lesions, with chromosome 1q amplification, in particular, being associated with HG progression and with cases that harbored cooccurring PDAC. Furthermore, the combined assessment of single nucleotide variants (SNVs) and CNAs identified both linear and branched evolutionary trajectories, underscoring the heterogeneity in the progression of LG lesions to HG and PDAC. At the transcriptome level, upregulation of MYC-regulated targets and downregulation of transcripts associated with the MHC class I antigen presentation machinery was a common feature of progression to HG. Taken together, this work emphasizes the role of 1q copy number amplification as a putative biomarker of high-risk IPMNs, underscores the importance of immune evasion even in non-invasive precursor lesions, and supports a previously underappreciated role of CNA-driven branching evolution as an avenue for IPMN progression. Our study provides important molecular context for risk stratification and cancer interception opportunities in IPMNs. Significance Integrated molecular analysis of genomic and transcriptomic alterations in the multistep progression of intraductal papillary mucinous neoplasms (IPMNs), which are bona fide precursors of pancreatic cancer, identifies features associated with progression of low-risk lesions to high-risk lesions and cancer, which might enable patient stratification and cancer interception strategies.
Single-cell transcriptomics of the immune system in ME/CFS at baseline and following symptom provocation

ME/CFS is a serious and poorly understood disease. To understand immune dysregulation in ME/CFS, we used single-cell RNA-seq (scRNA-seq) to examine immune cells in cohorts of patients and controls. Post-exertional malaise (PEM), an exacerbation of symptoms following strenuous exercise, is a characteristic symptom of ME/CFS. Thus, to detect changes coincident with PEM, we also performed scRNA-seq on the same cohorts following exercise. At baseline, ME/CFS patients displayed dysregulation of classical monocytes suggestive of inappropriate differentiation and migration to tissue. We were able to identify both diseased and more normal monocytes within patients, and the fraction of diseased cells correlated with metrics of disease severity. Comparing the transcriptome at baseline and post-exercise challenge, we discovered patterns indicative of improper platelet activation in patients, with minimal changes elsewhere in the immune system. Taken together, these data identify immunological defects present at baseline in patients and an additional layer of dysregulation following exercise. Highlights ME/CFS is a debilitating disease with unknown causes. Here, we provide, for the first time, an extensive single cell resolution dataset detailing the gene expression programs of circulating immune cells of ME/CFS cases at baseline and after symptom provocation. We were able to detect robust dysregulation in certain immune cells from patients, with dysregulation of classical monocytes manifesting the strongest signal. Indeed, the fraction of aberrant monocytes in ME/CFS patients correlated with the degree of disease severity. Surprisingly, platelet transcriptomes were also altered in ME/CFS, and they were the only component of the immune system that showed large-scale changes following symptom provocation.
Isolation and characterization of a neoxanthin synthase gene functioning in fucoxanthin biosynthesis of Phaeodactyum tricornutum

Golden-brown xanthophyll fucoxanthin in marine organisms, especially in diatoms, has attracted widespread attention because of its diverse biological activities. However, the biosynthetic pathway of fucoxanthin remains unclear in diatoms. Fucoxanthin may derive from either neoxanthin or diadinoxanthin pathway. However, the key point is whether neoxanthin and its synthesizing genes exist or not. In this study, we successfully identified a few xanthophylls in trace amounts in the concentrated fraction of carotenoids of diatom Phaeodactylum tricornutum cultured at different light intensities with the co-chromatography method, and cloned the neoxanthin synthase (NXS) gene which was not annotated in diatom genome. The NXS knockdown and knockout experiment show a positive correlation in the accumulation of neoxanthin and zeaxanthin while a negative correlation in violaxanthin and fucoxanthin with the expression of NXS. In vitro assay evidenced that neoxanthin is the precursor for fucoxanthin biosynthesis, indicating that other molecules intermediate the conversion between violaxanthin and fucoxanthin. Overall, we cloned a novel gene functioning in neoxanthin biosynthesis, which should aid to clarifying the fucoxanthin biosynthetic pathway in diatom.
Direct Brain Recordings Suggest a Causal Subsequent-Memory Effect

Endogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analyzing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output—a biomarker of successful encoding—tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas in the prefrontal cortex HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall, and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brain’s ability to learn new information.
Chronic activation of dopaminergic neurons via bioluminescence-optogenetics provides neuroprotection in a rodent model of Parkinson’s disease

Previous studies in human patients and rodent models of Parkinson’s disease (PD) have established neuroprotection of dopaminergic (DA) neurons in substantia nigra pars compacta (SNC) by physical exercise, but the precise origin of this neuroprotective effect has yet to be elucidated. In this study, we tested a hypothesis that enhanced activity of DA neurons in SNC results in neuroprotection using the unilateral 6-hydroxydopamine (6-OHDA) injection model in mice. To increase activity of DA neurons chronically and specifically, we injected an adeno-associated viral vector carrying a step-function luminopsin (SFL) – a fusion protein of light-emitting Gaussia luciferase and light-sensing step-function channelrhodopsin 2 – into SNC ipsilateral to 6-OHDA using the pan-neuronal human synapsin I promoter or the Cre-lox system in transgenic mice expressing the recombinase under control of the tyrosine hydroxylase (TH) promoter. Upon application of SFL substrate, coelenterazine (CTZ), the luciferase moiety of luminopsin emits bioluminescence which in turn activate the opsin moiety. Daily injection of CTZ for 4 weeks ameliorated a stereotypical behavior, namely ipsiversive rotations, induced by unilateral 6-OHDA. In addition, postmortem immunohistochemistry against TH revealed less severe neurodegeneration of DA neurons compared to vehicle-injected control animals. Furthermore, when mice were pretreated with ANA-12, a selective antagonist for tropomyosin receptor kinase B (TrkB), the behavioral improvement and neuroprotective effect were diminished. These results suggest that increased neuronal activity of DA neurons provides neuroprotection against 6-OHDA injury and alleviates its symptoms through the brain-derived neurotrophic factor-TrkB pathway.
Development of Multi-Bundle Virtual Ligaments to Simulate Knee Mechanics after Total Knee Arthroplasty

Preclinical evaluation of total knee arthroplasty (TKA) components is essential to understanding their mechanical behavior and developing strategies for improving joint stability. While preclinical testing of TKA components has been useful in quantifying their effectiveness, such testing can be criticized for lacking clinical relevance, as the important contributions of surrounding soft tissues are either neglected or greatly simplified. The purpose of our study was to develop and determine if subject-specific virtual ligaments reproduce the same kinematics as native ligaments surrounding TKA joints. Five TKA knees were mounted to a motion simulator. Each was subjected to tests of anterior-posterior (AP), internal-external (IE), and varus-valgus (VV) laxity. The forces transmitted through major ligaments were measured using a sequential resection technique. By tuning the measured ligament forces and elongations to a generic non-linear elastic ligament model, virtual ligaments were designed and used to simulate the soft tissue envelope around isolated TKA components. The average root mean square error (RMSE) between the laxity results of TKA joints with native versus virtual ligaments was 2.9 mm during AP translation, 6.5° during IE rotations, and 2.0° during VV rotations, and there was no statistically significant difference between the results of both methods. Interclass correlation coefficients (ICCs) indicated a good level of reliability for AP and IE laxity (0.85 and 0.84). To conclude, a virtual ligament envelope around TKA joints can mimic natural knee behavior and is an effective method for the preclinical testing of TKA components.
The Calpain-7 protease functions together with the ESCRT-III protein IST1 within the midbody to regulate the timing and completion of abscission

The Endosomal Sorting Complexes Required for Transport (ESCRT) machinery mediates the membrane fission step that completes cytokinetic abscission and separates dividing cells. Filaments composed of ESCRT-III subunits constrict membranes of the intercellular bridge midbody to the abscission point. These filaments also bind and recruit cofactors whose activities help execute abscission and/or delay abscission timing in response to mitotic errors via the NoCut/Abscission checkpoint. We previously showed that the ESCRT-III subunit IST1 binds the cysteine protease CAPN7 (Calpain-7) and that CAPN7 is required for both efficient abscission and NoCut checkpoint maintenance (Wenzel et al., 2022). Here, we report biochemical and crystallographic studies showing that the tandem MIT domains of CAPN7 bind simultaneously to two distinct IST1 MIT interaction motifs. Structure-guided point mutations in either CAPN7 MIT domain disrupted IST1 binding in vitro and in cells, and depletion/rescue experiments showed that the CAPN7-IST1 interaction is required for: 1) CAPN7 recruitment to midbodies, 2) efficient abscission, and 3) NoCut checkpoint arrest. CAPN7 proteolytic activity is also required for abscission and checkpoint maintenance. Hence, IST1 recruits CAPN7 to midbodies, where its proteolytic activity is required to regulate and complete abscission.
Connectome-based predictive modeling of empathy in adolescents with and without the low-prosocial emotion specifier

Empathy impairments are an important part of a broader affective impairments defining the youth antisocial phenotype callous-unemotional (CU) traits and the DSM-5 low prosocial emotion (LPE) specifier. While functional connectivity underlying empathy and CU traits have been well studied, less is known about what functional connections underly differences in empathy amongst adolescents qualifying for the LPE specifier. Such information can provide mechanistic distinctions for this clinically relevant specifier. The present study uses connectome-based predictive modeling that uses whole-brain resting-state functional connectivity data to predict cognitive and affective empathy for those meeting the LPE specifier (n= 29) and those that do not (n= 57). Additionally, we tested if models of empathy generalized between groups as well as density differences for each model of empathy between groups. Results indicate the LPE group had lower cognitive and affective empathy as well as higher CU traits and conduct problems. Negative and positive models were identified for affective empathy for both groups, but only the negative model for the LPE and positive model for the normative group reliably predicted cognitive empathy. Models predicting empathy did not generalize between groups. Density differences within the default mode, salience, executive control, limbic, and cerebellar networks were found as well as between the executive control, salience, and default mode networks. And, importantly, connections between the executive control and default mode networks characterized empathy differences the LPE group such that more positive connections characterized cognitive differences and less negative connections characterized affective differences. These findings indicate neural differences in empathy for those meeting LPE criteria that may explain decrements in empathy amongst these youth. These findings support theoretical accounts of empathy decrements in the LPE clinical specifier and extend them to identify specific circuits accounting for variation in empathy impairments. The identified negative models help understand what connections inhibit empathy whereas the positive models reveal what brain patterns are being used to support empathy in those with the LPE specifier. LPE differences from the normative group and could be an appropriate biomarker for predicting CU trait severity. Replication and validation using other large datasets are important next steps.