Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain-derived neurotrophic factor contributes to neurogenesis after intracerebral hemorrhage: a rodent model and human study

Background and purpose Intracerebral hemorrhage (ICH) enhances neurogenesis in the subventricular zone (SVZ); however, the mechanism is not fully understood. We investigated the role of brain-derived neurotrophic factor (BDNF) in post-ICH neurogenesis in a rodent model and in patients with ICH using cerebrospinal fluid (CSF). Methods A rat model of ICH was constructed via stereotaxic injection of collagenase into the left striatum. Patients with ICH receiving an external ventricular drain were prospectively enrolled. CSF was collected from rats and patients at different post-ICH times. Primary cultured rat neural stem cells (NSCs) were treated with CSF with or without BDNF-neutralized antibody. Immunohistochemistry and immunocytochemistry were used to detect NSC proliferation and differentiation. The BDNF concentration in CSF was quantified using enzyme-linked immunosorbent assays (ELISA). Results In the rat model of ICH, the percentage of proliferating NSCs and neuroblasts in SVZ was elevated in bilateral hemispheres. The cultured rat NSCs treated with CSF from both rats and patients showed an increased capacity for proliferation and differentiation toward neuroblasts. BDNF concentration was higher in CSF collected from rats and patients with ICH than in controls. Blocking BDNF decreased the above-noted promotion of proliferation and differentiation of cultured NSCs by CSF treatment. In patients with ICH, the BDNF concentration in CSF and the neurogenesis-promoting capacity of post-ICH CSF correlated positively with ICH volume. Conclusion BDNF in CSF contributes to post-ICH neurogenesis, including NSC proliferation and differentiation toward neuroblasts in a rat model and patients with ICH.
Electrophysiological hallmarks for event relations and event roles in working memory

The ability to maintain events (i.e. interactions between/among objects) in working memory is crucial for our everyday cognition, yet the format of this representation is poorly understood. The current ERP study was designed to answer two questions: How is maintaining events (e.g., the tiger hit the lion) neurally different from maintaining item coordinations (e.g., the tiger and the lion)? That is, how is the event relation (present in events but not coordinations) represented? And how is the agent, or initiator of the event encoded differently from the patient, or receiver of the event during maintenance? We used a novel picture-sentence match-across-delay approach in which the working memory representation was ‘pinged’ during the delay, in two ERP experiments with Chinese and English materials. First, we found that maintenance of events elicited a long-lasting late sustained difference in posterior-occipital electrodes relative to non-events. This effect resembled the negative slow wave reported in previous studies of working memory, suggesting that the maintenance of events in working memory may impose a higher cost compared to coordinations. Second, in order to elicit a hallmark for agent vs. patient representation in working memory, we pinged agent or patient characters during the delay. Although planned comparisons did not reveal significant differences in the ERPs elicited by the agent pings vs. patient pings, we found that the ping appeared to dampen the ongoing sustained difference, suggesting a shift from sustained activity to activity silent mechanisms. These results represent one of the uses of ERPs to elucidates the format of neural representation for events in working memory.
Representational drift as a result of implicit regularization

Recent studies show that, even in constant environments, the tuning of single neurons changes over time in a variety of brain regions. This representational drift has been suggested to be a consequence of continuous learning under noise, but its properties are still not fully understood. To investigate the underlying mechanism, we trained an artificial network on a simplified navigational task. The network quickly reached a state of high performance, and many units exhibited spatial tuning. We then continued training the network and noticed that the activity became sparser with time. Initial learning was orders of magnitude faster than ensuing sparsification. This sparsification is consistent with recent results in machine learning, in which networks slowly move within their solution space until they reach a flat area of the loss function. We analyzed four datasets from different labs, all demonstrating that CA1 neurons become sparser and more spatially informative with exposure to the same environment. We conclude that learning is divided into three overlapping phases: (i) Fast familiarity with the environment; (ii) slow implicit regularization; (iii) a steady state of null drift. The variability in drift dynamics opens the possibility of inferring learning algorithms from observations of drift statistics.
RNase H genes cause distinct impacts on RNA:DNA hybrid formation and mutagenesis genome-wide

RNA:DNA hybrids such as R-loops affect genome integrity and DNA replication fork progression. The overall impacts of naturally occurring RNA:DNA hybrids on genome integrity, and the relative contributions of ribonucleases H to mitigating the negative effects of hybrids, remain unknown. Here, we investigate the contributions of RNases HII (RnhB) and HIII (RnhC) to hybrid removal, DNA replication, and mutagenesis genome-wide. Deletion of either rnhB or rnhC triggers RNA:DNA hybrid accumulation, but with distinct patterns of mutagenesis and hybrid accumulation. Across all cells, hybrids accumulate most strongly in non-coding RNAs and 5′-UTRs of coding sequences. For ΔrnhB, hybrids accumulate preferentially in untranslated regions and early in coding sequences. Hybrid accumulation is particularly sensitive to gene expression in ΔrnhC; in cells lacking RnhC, DNA replication is disrupted leading to transversions and structural variation. Our results resolve the outstanding question of how hybrids in native genomic contexts interact with replication to cause mutagenesis and shape genome organization.
PLANT UNCOUPLING MITOCHONDRIAL PROTEIN 2 localizes to the Golgi

Mitochondria act as cellular hubs of energy transformation and metabolite conversion in most eukaryotes. Plant mitochondrial electron transport chains are particularly flexible, featuring alternative components, such as ALTERNATIVE NAD(P)H DEHYDROGENASES and ALTERNATIVE OXIDASES (AOXs), that can bypass proton translocation steps. PLANT UNCOUPLING MITOCHONDRIAL PROTEINS (named PUMPs or plant UCPs) have been identified in plants as homologues of mammalian Uncoupling Proteins (UCPs), and their biochemical and physiological roles have been investigated in the context of mitochondrial energy metabolism. To dissect UCP function in Arabidopsis, the two most conserved (UCP1 and UCP2) have been targeted in recent work by combining mutant lines to circumvent potential functional redundancy in vivo. Such approaches rely on the assumption that both proteins reside in the inner mitochondrial membrane as a prerequisite for functional redundancy. Yet, contradicting results have been reported on UCP2 localization in plants. Here we provide evidence that, conversely to UCP1, which is an abundant inner mitochondrial membrane protein, UCP2 localizes to the Golgi rather than to mitochondria. Based on multiple lines of new and prior evidence, we summarize the consensus view that we have reached and provide an example of how open, critical exchange within the research community is able to constructively address ambiguities. Our observations and considerations provide direction to the ongoing discussion about the functions of UCP proteins. They further offer new perspectives for the study of Golgi membrane transport and subcellular targeting principles of membrane proteins. Since 20 to 30 % of genes in plant genomes are predicted to encode transmembrane proteins and the function of most of those proteins has not been experimentally investigated, we highlight the importance of using independent evidence for localization as a prerequisite for understanding physiological function of membrane proteins.
Conformational ensembles of the human intrinsically disordered proteome: Bridging chain compaction with function and sequence conservation

Intrinsically disordered proteins and regions (collectively IDRs) are pervasive across proteomes in all kingdoms of life, help shape biological functions, and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures, yet defy commonly held sequence-structure-function relationships. Recent developments in protein structure prediction have led to the ability to predict the three-dimensional structures of folded proteins at the proteome scale, and have enabled large-scale studies of structure-function relationships. In contrast, knowledge of the conformational properties of IDRs is scarce, in part because the sequences of disordered proteins are poorly conserved and because only few have been characterized experimentally. We have developed an efficient model to generate conformational ensembles of IDRs, and thereby to predict their conformational properties from sequence only. Here, we applied this model to simulate all IDRs of the human proteome. Examining conformational ensembles of 29,998 IDRs, we show how chain compaction is correlated with cellular function and localization, including in different types of biomolecular condensates. We train a model to predict compaction from sequence and use this to show conservation of structural properties across orthologs. Our results recapitulate observations from previous studies of individual protein systems, and enable us to study the relationship between sequence, conservation, conformational ensembles, biological function and disease variants at the proteome scale.
Spatiotemporal Dynamics of Single-stranded DNA Intermediates in Escherichia coli

Single-stranded DNA gaps form within the E. coli chromosome during replication, repair and recombination. However, information about the extent of ssDNA creation in the genome is limited. To complement a recent whole-genome sequencing study revealing ssDNA gap genomic distribution, size, and frequency, we used fluorescence microscopy to monitor the spatiotemporal dynamics of single-stranded DNA within live E. coli cells. The ssDNA was marked by a functional fluorescent protein fusion of the SSB protein that replaces the wild type SSB. During log-phase growth the SSB fusion produces a mixture of punctate foci and diffuse fluorescence spread throughout the cytosol. Many foci are clustered. Fluorescent markers of DNA polymerase III frequently co-localize with SSB foci, often localizing to the outer edge of the large SSB features. Novel SSB-enriched features form and resolve regularly during normal growth. UV irradiation induces a rapid increase in SSB foci intensity and produces large features composed of multiple partially overlapping foci. The results provide a critical baseline for further exploration of ssDNA generation during DNA metabolism. Alterations in the patterns seen in a mutant lacking RecB function tentatively suggest associations of particular SSB features with the repair of double strand breaks and post-replication gaps.
Revealing and reshaping attractor dynamics in large networks of cortical neurons

Attractors play a key role in a wide range of processes including learning and memory. Due to recent innovations in recording methods, there is increasing evidence for the existence of attractor dynamics in the brain. Yet, our understanding of how these attractors emerge or disappear in a biological system is lacking. By following the spontaneous network bursts of cultured cortical networks, we are able to define a vocabulary of spatiotemporal patterns and show that they function as discrete attractors in the network dynamics. We show that electrically stimulating specific attractors eliminates them from the spontaneous vocabulary, while they are still robustly evoked by the electrical stimulation. This seemingly paradoxical finding can be explained by a Hebbian-like strengthening of specific pathways into the attractors, at the expense of weakening non-evoked pathways into the same attractors. We verify this hypothesis and provide a mechanistic explanation for the underlying changes supporting this effect. Author summary There are many hints that could evoke the same memory. There are many chains of evidence that could lead to the same decision. The mathematical object describing such dynamics is called an attractor, and is believed to be the neural basis for many cognitive phenomena. In this study, we aimed to deepen our understanding of the existence and plasticity of attractors in the dynamics of a biological neural network. We explored the spontaneous activity of cultured neural networks and identified a set of patterns that function as discrete attractors in the network dynamics. To understand how these attractors evolve, we stimulated the network to repeatedly visit some of them. Surprisingly, we observed that the stimulated patterns became less common in the spontaneous activity, while still being reliably evoked by the stimulation. This paradoxical finding was explained by the strengthening of specific pathways leading to these attractors, alongside the weakening of other pathways. These findings provide valuable insights into the mechanisms underlying attractor plasticity in biological neural networks.
TRAIP plays an essential role in the dissociation of PCNA from chromatin during mitosis, required to precise DNA replication initiation

Loading PCNA onto chromatin is a pivotal step in DNA replication, cell cycle progression, and genome integrity. Conversely, unloading PCNA from chromatin is also a crucial step for maintaining genome stability. Cells defect of the PCNA unloader ATAD5-RFC exhibit a high level of chromatin-bound PCNA, delayed S phase progression, abnormal association/dissociation of chromatin-bound proteins, and aberrant chromosome structures, but exhibit dissociation of PCNA from chromatin in mitosis. Here, we found that TRAIP, an E3 ubiquitin ligase, plays critical roles in the removal of PCNA from chromatin during mitosis. TRAIP-depleted cells exhibited chromatin- bound PCNA even during mitosis and delayed mitotic progression and exit. Although TRAIP-depleted cells with chromatin-bound PCNA progressed into the next G1 phase, they showed reduced levels of the replication licensing factor Cdt1, is the key regulator of DNA replication licensing, and impaired S phase entry. These results demonstrate that TRAIP functions independently of ATAD5-RFC for the removal of PCNA from chromatin during mitosis, and is required for precise cell cycle progression from mitosis to G1 phase, as well as for pre-RC formation for faithful initiation of DNA replication.
Expecting the unexpected: A reanalysis of a multi-laboratory study provides evidence for prediction in language

The present study aimed to investigate the extent of prediction in language, by reanalysing Nieuwland and colleagues' (2018) replication of DeLong et al. (2005). Participants (n = 356) viewed sentences containing articles and nouns of varying predictability, while their electroencephalogram (EEG) was recorded. We measured pre-stimulus and N400 event-related activity in the Nieuwland et al. (2018) data and calculated lexical surprisal using Generative Pre-trained Transformer-2 (GPT-2), to capture word predictability. Our results demonstrate increases in N400 amplitude as article surprisal increased, supporting DeLong et al.’s (2005) findings. N400 amplitudes following surprising articles were also reduced when prior word surprisal was high, suggesting that surprising information may impair the brain’s ability to form precise predictions about upcoming words. These findings have important implications for existing understandings of prediction, as they provide evidence for prediction during language comprehension and support the proposal that prediction is an adaptive and unified mechanism of cognition.
Direct measurements of collagen fiber recruitment in the posterior pole of the eye

Collagen is the main load-bearing component of the peripapillary sclera (PPS) and lamina cribrosa (LC) in the eye. Whilst it has been shown that uncrimping and recruitment of the PPS and LC collagen fibers underlies the macro-scale nonlinear stiffening of both tissues with increased intraocular pressure (IOP), the uncrimping and recruitment as a function of local stretch have not been directly measured. This knowledge is crucial for the development of constitutive models associating micro and macro scales. In this project we measured local stretch-induced collagen fiber bundle uncrimping and recruitment curves of the PPS and LC. Thin coronal samples of PPS and LC of sheep eyes were mounted and stretched biaxially quasi-statically using a custom system. At each step, we imaged the PPS and LC with instant polarized light microscopy and quantified pixel-level (1.5 μ m/pixel) collagen fiber orientations. We used digital image correlation to measure the local stretch and quantified collagen crimp by the circular standard deviation of fiber orientations, or waviness. Local stretch-recruitment curves of PPS and LC approximated sigmoid functions. PPS recruited more fibers than the LC at the low levels of stretch. At 10% stretch the curves crossed with 75% bundles recruited. The PPS had higher uncrimping rate and waviness remaining after recruitment than the LC: 0.9° vs. 0.6° and 3.1° vs. 2.7°. Altogether our findings support describing fiber recruitment of both PPS and LC with sigmoid curves, with the PPS recruiting faster and at lower stretch than the LC, consistent with a stiffer tissue. Statement of Significance Peripapillary sclera (PPS) and lamina cribrosa (LC) collagen recruitment behaviors are central to the nonlinear mechanical behavior of the posterior pole of the eye. How PPS and LC collagen fibers recruit under stretch is crucial to develop constitutive models of the tissues but remains unclear. We used image-based stretch testing to characterize PPS and LC collagen fiber bundle recruitment under local stretch. We found that fiber-level stretch-recruitment curves of PPS and LC approximated sigmoid functions. PPS recruited more fibers at a low stretch, but at 10% bundle stretch the two curves crossed with 75% bundles recruited. We also found that PPS and LC fibers had different uncrimping rates and non-zero waviness’s when recruited.
Genome-wide analysis of Respiratory burst oxidase homolog (Rboh) genes in Aquilaria species and its association with agarwood formation

Respiratory burst oxidase homolog (Rboh), generate reactive oxygen species (ROS) to maintain normal growth and pathogen induced defence responses in plants. In Aquilaria plants, wounding and fungal invasion results in the biosynthesis of secondary metabolites as a defence response which with due course develop into agarwood. During pathogen invasion, Aquilaria tree accumulate ROS species through the action of Rboh enzymes. Although in agarwood formation role of Rboh gene family has been implicated, an comprehensives study on Rboh gene family and information of its role during agarwood formation in missing. In this study, seven Rboh genes were identified from the genomes of two Aquilaria species viz., Aquilaria agallocha and Aquilaria sinensis and phylogenetically classified into five groups. Stress response, hormone regulation, and development related regulatory elements were identified in the promoter regions. The protein sequences comprised of four conserved domains, an EF-hand domain, and a transmembrane region which they probably utilise for MAPK signaling, plant-pathogen interaction and plant hormone signal transduction pathways. Expression analyses revealed that among the seven members, AaRbohA and AaRhobC were involved in generation of ROS species, and also probably play role in agarwood formation. These findings provide valuable information regarding the Rboh members of A. agallocha which can be further used for functional analyses for in-depth understanding of ROS mediated signalling and regulation of agarwood formation. Graphical abstract
Toll-like receptor 7 (TLR7)-mediated antiviral response protects mice from lethal SARS-CoV-2 infection

SARS-CoV-2-induced impaired antiviral and excessive inflammatory responses cause fatal pneumonia. However, the key pattern recognition receptors that elicit effective antiviral and lethal inflammatory responses in-vivo are not well defined. CoVs possess single-stranded RNA (ssRNA) genome that is abundantly produced during infection and stimulates both antiviral interferon (IFN) and inflammatory cytokine/ chemokine responses. Therefore, in this study, using wild-type control and TLR7 deficient BALB/c mice infected with a mouse-adapted SARS-COV-2 (MA-CoV-2), we evaluated the role of TLR7 signaling in MA-CoV-2-induced antiviral and inflammatory responses and disease outcome. We show that TLR7-deficient mice are more susceptible to MA-CoV-2 infection as compared to infected control mice. Further evaluation of MA-CoV-2 infected lungs showed significantly reduced mRNA levels of antiviral type I (IFNα/β) and type III (IFNλ) IFNs, IFN stimulated genes (ISGs, ISG15 and CXCL10), and several pro-inflammatory cytokines/chemokines in TLR7 deficient compared to control mice. Reduced lung IFN/ISG levels and increased morbidity/mortality in TLR7 deficient mice correlated with high lung viral titer. Detailed examination of total cells from MA-CoV-2 infected lungs showed high neutrophil count in TLR7 deficient mice compared to control mice. Additionally, blocking TLR7 activity post-MA-CoV-2 infection using a specific inhibitor also enhanced disease severity. In summary, our results conclusively establish that TLR7 signaling is protective during SARS-CoV-2 infection, and despite robust inflammatory response, TLR7-mediated IFN/ISG responses likely protect the host from lethal disease. Given similar outcomes in control and TLR7 deficient humans and mice, these results show that MA-CoV-2 infected mice serve as excellent model to study COVID-19.
Temporally organized representations of reward and risk in the human brain

The value and uncertainty associated with choice alternatives constitute critical features along which decisions are made. While the neural substrates supporting reward and risk processing have been investigated, the temporal organization by which these computations are encoded remains elusive. Here we leverage the high spatiotemporal precision of intracranial electroencephalography (iEEG) to uncover how representations of decision-related computations unfold in time. We present evidence of locally distributed representations of reward and risk variables that are temporally organized across multiple regions of interest. Reward outcome representations across wide-spread regions follow a temporally cascading order along the anteroposterior axis of the brain. In contrast, expected value can be decoded from multiple regions at the same time, and error signals in both reward and risk domains reflect a mixture of sequential and parallel encoding. We highlight the role of the anterior insula in generalizing between reward prediction error (RePE) and risk prediction error (RiPE), within which the encoding of RePE in the distributed iEEG signal predicts RiPE. Together our results emphasize the utility of uncovering temporal dynamics in the human brain for understanding how computational processes critical for value-based decisions under uncertainty unfold.