Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Negative Periocular Pressure on Biomechanics of the Optic Nerve Head and Cornea: A Computational Modeling Study

Purpose To evaluate the effects of negative periocular pressure (NPP), and concomitant intraocular pressure (IOP) lowering, on the biomechanics of the optic nerve head (ONH) and cornea. Methods We developed a validated finite element (FE) model of the eye to compute tissue biomechanical strains induced in response to NPP delivered using the Multi-Pressure Dial (MPD) system. The model was informed by clinical measurements of IOP lowering and was based on published tissue properties. We also conducted sensitivity analyses by changing pressure loads and tissue properties. Results Application of -7.9 mmHg NPP decreased strain magnitudes in the ONH by c. 50% while increasing corneal strain magnitudes by c. 25%. Comparatively, a similar increase in corneal strain was predicted to occur due to an increase in IOP of 4 mmHg. Sensitivity studies indicated that NPP lowers strain in the ONH by reducing IOP and that these effects persisted over a range of tissue stiffnesses and spatial distributions of NPP. Conclusions NPP is predicted to considerably decrease ONH strain magnitudes. It also increases corneal strain but to an extent expected to be clinically insignificant. Thus, using NPP to lower IOP and hence decrease ONH mechanical strain is likely biomechanically beneficial for glaucoma patients. Translational Relevance This study provides the first description of how NPP affects ONH biomechanics and explains the underlying mechanism of ONH strain reduction. It complements current empirical knowledge about the MPD system and guides future studies of NPP as a treatment for glaucoma.
Neural learning rules for generating flexible predictions and computing the successor representation

The predictive nature of the hippocampus is thought to be useful for memory-guided cognitive behaviors. Inspired by the reinforcement learning literature, this notion has been formalized as a predictive map called the successor representation (SR). The SR captures a number of observations about hippocampal activity. However, the algorithm does not provide a neural mechanism for how such representations arise. Here, we show the dynamics of a recurrent neural network naturally calculate the SR when the synaptic weights match the transition probability matrix. Interestingly, the predictive horizon can be flexibly modulated simply by changing the network gain. We derive simple, biologically plausible learning rules to learn the SR in a recurrent network. We test our model with realistic inputs and match hippocampal data recorded during random foraging. Taken together, our results suggest that the SR is more accessible in neural circuits than previously thought and can support a broad range of cognitive functions.
States measurement in a context of intelligent connected furnitures

The concept of intelligent connected furnitures opens new possibilities for the interaction between non animated objects. Actually intelligent connected furnitures are able to perceive their environment and can globally act as a measuring system. This paper presents how a community of objects acquire its own state. In this system, the measurement value is a weighted spatial ontology.
Septin-mediated RhoA activation engages the exocyst complex to recruit the cilium transition zone

Septins are filamentous GTPases that play important, but poorly characterized roles in ciliogenesis. Here, we show that SEPTIN9 regulates RhoA signaling at the base of cilia by binding and activating the RhoA guanine nucleotide exchange factor, ARHGEF18. GTP-RhoA is known to activate the membrane targeting exocyst complex, and suppression of SEPTIN9 causes disruption of ciliogenesis and mislocalization of an exocyst subunit, SEC8. Using basal body-targeted proteins we show that upregulating RhoA signaling at the cilium can rescue ciliary defects and mislocalization of SEC8 caused by global SEPTIN9 depletion. Moreover, we demonstrate that transition zone components, RPGRIP1L and TCTN2 fail to accumulate at the transition zone in cells lacking SEPTIN9 or depleted of the exocyst complex. Thus, SEPTIN9 regulates the recruitment of transition zone proteins on Golgi-derived vesicles by activating the exocyst via RhoA to allow the formation of primary cilia.
Effects of netarsudil-family Rho kinase inhibitors on human trabecular meshwork cell contractility and actin remodeling using a bioengineered ECM hydrogel

Interactions between trabecular meshwork (TM) cells and their extracellular matrix (ECM) are critical for normal outflow function in the healthy eye. Multifactorial dysregulation of the TM is the principal cause of elevated intraocular pressure that is strongly associated with glaucomatous vision loss. Key characteristics of the diseased TM are pathologic contraction and actin stress fiber assembly, contributing to overall tissue stiffening. Among first-line glaucoma medications, the Rho-associated kinase inhibitor (ROCKi) netarsudil is known to directly target the stiffened TM to improve outflow function via tissue relaxation involving focal adhesion and actin stress fiber disassembly. Yet, no in vitro studies have explored the effect of netarsudil on human TM (HTM) cell contractility and actin remodeling in a 3D ECM environment. Here, we use our bioengineered HTM cell-encapsulated ECM hydrogel to investigate the efficacy of different netarsudil-family ROCKi compounds on reversing pathologic contraction and actin stress fibers. Netarsudil and all related experimental ROCKi compounds exhibited significant ROCK1/2 inhibitory and focal adhesion disruption activities. Furthermore, all ROCKi compounds displayed potent contraction-reversing effects on HTM hydrogels upon glaucomatous induction in a dose-dependent manner, relatively consistent with their biochemical/cellular inhibitory activities. At their tailored EC50 levels, netarsudil-family ROCKi compounds exhibited distinct effect signatures of reversing pathologic HTM hydrogel contraction and actin stress fibers, independent of the cell strain used. Netarsudil outperformed the experimental ROCKi compounds in support of its clinical status. In contrast, at uniform EC50-levels using netarsudil as reference, all ROCKi compounds performed similarly. Collectively, our data suggest that netarsudil exhibits high potency to rescue HTM cell pathobiology in a tissue-mimetic 3D ECM microenvironment, solidifying the utility of our bioengineered hydrogel model as a viable screening platform to further our understanding of TM pathophysiology in glaucoma.
A single closed head injury in mice induces chronic, progressive white matter atrophy and increased phospho-tau expressing oligodendrocytes

Traumatic brain injury (TBI) acutely damages the brain; this injury can evolve into chronic neurodegeneration. While much is known about the chronic effects arising from multiple mild TBIs, far less is known about the long-term effects of a single moderate to severe TBI. We found that a single moderate closed head injury to mice induces diffuse axonal injury within 1-day post-injury (DPI). At 14 DPI, injured animals have atrophy of ipsilesional cortex, thalamus, and corpus callosum, with bilateral atrophy of the dorsal fornix. Atrophy of the ipsilesional corpus callosum is accompanied by decreased fractional anisotropy and increased mean and radial diffusivity that remains unchanged between 14 and 180 DPI. Injured animals increased density of phospho-tau immunoreactive (pTau+) cells in the ipsilesional cortex and thalamus, and bilaterally in corpus callosum. Between 14 and 180 DPI, atrophy occurs in the ipsilesional ventral fornix, contralesional corpus callosum, and bilateral internal capsule. Diffusion tensor MRI parameters remain unchanged in white matter regions with delayed atrophy. Between 14 and 180 DPI, pTau+ cell density increases bilaterally in corpus callosum, but decreases in cortex and thalamus. The location of pTau+ cells within the ipsilesional corpus callosum changes between 14 and 180 DPI; density of all cells increases including pTau+ or pTau- cells. Greater than 90% of the pTau+ cells are in the oligodendrocyte lineage in both gray and white matter. Density of thioflavin-S+ cells in thalamus increases by 180 DPI. These data suggest a single closed head impact produces multiple forms of chronic neurodegeneration. Gray and white matter regions proximal to the impact site undergo rapid atrophy. More distal white matter regions undergo chronic, progressive white matter atrophy with an increasing density of oligodendrocytes containing pTau. These data suggest that the chronic neurodegeneration arising from a single moderate CHI differs greatly from the chronic traumatic encephalopathy produced by multiple mild head injuries. Highlights Gray and white matter atrophy begins within 14 days after a single closed head injury White matter atrophy progresses between 14 and 180 days post injury with minimal changes in diffusion tensor MRI parameters. CHI increases the density of oligodendrocytes with perinuclear accumulation of phosphorylated tau Thioflavin-S+ cells increase in thalamus at 180 days post injury
Precision motor timing via scalar input fluctuations

Complex motor skills like playing piano require precise timing over long periods, without errors accumulating between subprocesses like the left and right hand movements. While biological models can produce motor-like sequences, how the brain quenches timing errors is not well understood. Motivated by songbirds, where the left and right brain nuclei governing song sequences do not connect but may receive low-dimensional thalamic input, we present a model where timing errors in an autonomous sequence generator are continually corrected by one-dimensional input fluctuations. We show in a spiking neural network model how such input can rapidly correct temporal offsets in a propagating spike pulse, recapitulating the precise timing seen in songbird brains. In a reduced, more general model, we show that such timing correction emerges when the spatial profile of the input over the sequence sufficiently reflects its temporal fluctuations, yielding time-locking attractors that slow advanced sequences and hasten lagging ones, up to the input timescale. Unlike models without fluctuating input, our model predicts anti-correlated durations of adjacent segments of the output sequence, which we verify in recorded zebra finch songs. This work provides a bioplausible picture of how temporal precision could arise in extended motor sequences and generally how low-dimensional input could continuously coordinate time-varying output signals. Significance Complex motor skills like playing piano require precision timing over long periods, often among multiple components like left and right muscle groups. Although brain-like network models can produce motor-like outputs, timing regulation is not well understood. We introduce a model, inspired by songbird brains, where imprecise timing in a cortical-like system is corrected by a single thalamic input regulating the sequential propagation, or tempo, of cortical activity. This model illuminates a relation between the input’s spatial structure and temporal variation that lets lagging activity hasten and advanced activity slow, which makes a prediction about output timing that we verify in real birdsong. This work reveals a simple, neuroplausible mechanism that may play a role in precision cortical or motor timing.
Pdx1 expression in hematopoietic cells activates Kras-mutation to drive leukemia in KC (Pdx1-Cre; LSL-KrasG12D/+ ) mice

Abstract The highly utilized KC model has a reported lethality rate of about 30%, which has been attributed to pancreas cancer. However, a competing cause of lethality in KC mice is due to the activation of mutant-Kras gene (KrasG12D/+ ) in the multipotent progenitor cells (MPP), and subsequent development of Kras-mutant T-cell acute lymphoblastic leukemia (T-ALL). Overall, 20% (5/25) of KC mice developed T-ALL by 9 months of age. Transplantation of pooled bone marrow from KC mice into CD45 congenic mice caused T-ALL in 100% of recipient mice, confirming that mutant-Kras expression in the hematologic compartment is driving the development of T-ALL in the KC mouse model. These results are an essential consideration for investigators using this model. Further, the lower penetrance of T-ALL in KC mice (versus existing leukemia models) suggests this model could be considered as an alternative research model to evaluate onset and factors that exacerbate the development of T-ALL.
Quantitative Characterization of Duodenal Gastrinoma Autofluorescence using Multi-photon Microscopy

Duodenal gastrinomas (DGASTs) are neuroendocrine tumors that develop in the submucosa of the duodenum and produce the hormone gastrin. Surgical resection of DGASTs is complicated by the small size of these tumors and the tendency for them to develop diffusely in the duodenum. Endoscopic mucosal resection of DGASTS is an increasingly popular method for treating this disease due to its low complication rate but suffers from poor rates of pathologically negative margins. Multiphoton microscopy (MPM) is capable of capturing high-resolution images of biological tissue with contrast generated from endogenous fluorescence (autofluorescence) through two-photon excited fluorescence (2PEF). Second harmonic generation (SHG) is another popular method of generating image contrast with MPM and is a light-scattering phenomenon that occurs predominantly from structures such as collagen in biological samples. Some molecules that contribute to autofluorescence change in abundance from processes related to the cancer disease process (e.g., metabolic changes, oxidative stress, angiogenesis). MPM was used to image 12 separate patient samples of formalin-fixed and paraffinized DGAST slides with a SHG channel 4 2PEF channels, each tuned to capture fluorescence from NADH, FAD, lipofuscin, and porphyrin. We found that there was a significant difference in the relative abundance of signal generated in the 2PEF in comparison to the neighboring tissues of the duodenum. Texture extraction was used to create linear discriminant classifiers for tumor vs all other tissue classes before and after principal component analysis (PCA) of the texture feature dataset. PCA improved the classifier accuracy and reduced the number of features required to achieve maximum accuracy of the classifier. The LDA classifier after PCA distinguished between tumor and other tissue types with an accuracy of 90.6 - 93.8%. These results suggest that MPM 2PEF and SHG imaging is a promising label-free method for discriminating between DGAST tumors and normal duodenal tissue which has implications for future applications of in vivo assessment of resection margins with endoscopic MPM.
The Adaptor Protein 2 (AP2) complex modulates habituation and behavioral selection across multiple pathways and time windows

Animals constantly perceive and integrate information across sensory modalities, and their nervous systems must select behavioral responses appropriate to the current situation and prior experience. Genetic factors supporting this behavioral flexibility are often disrupted in neuropsychiatric conditions, and our previous work revealed the disease-associated ap2s1 gene critically supports habituation learning in acoustically-evoked escape behavior of zebrafish. ap2s1 encodes a subunit of the AP2 endocytosis adaptor complex and has been linked to autism spectrum disorder, though its mechanism and direct behavioral importance have not been established. Here, we show that multiple subunits of the AP2 complex regulate acoustically-evoked behavior selection and habituation learning. Furthermore, ap2s1 biases the choice between distinct escape behaviors in sensory modality-specific manners, and more broadly regulates action selection across different sensory contexts. Using tissue-specific and inducible transgenic rescue, we demonstrate that the AP2 complex functions acutely and in the nervous system to modulate acoustically-evoked habituation learning, suggesting several spatially and/or temporally distinct mechanisms through which AP2 regulates different aspects of escape behavior selection and performance. Altogether, we demonstrate that the AP2 complex coordinates action selection across stimulus modalities and contexts, providing a new vertebrate model for the role of ap2s1 in human conditions including autism spectrum disorder. SIGNIFICANCE STATEMENT The AP2S1 gene has been linked to learning disabilities and autism spectrum disorders (ASD), though the mechanisms underlying its impact on human behavior are unknown. We explored how, when, and where this gene regulates vertebrate behavior, developing a zebrafish model to identify the roles and mechanisms through which ap2s1 modulates behavior. We find that ap2s1 regulates simple acoustically-evoked learning, as well as how individuals bias behavioral choice in a wide variety of contexts. We show that ap2s1 acts at multiple distinct time periods and locations both within and outside of neuronal tissues, revealing the diverse mechanisms and pathways through which it modulates vertebrate behavior.
An Optimized Buffer for Repeatable Multicolor STORM

STORM microscopy is one of the most popular method of super-resolution microscopy, due to moderate requirements on the optical setup, and high achievable resolution. However, since its inception more than 15 years ago, protocols have barely evolved, and despite some recent progress, multicolor imaging can still be complex without the right equipment. We decided to optimize the buffer composition to improve the blinking of the most popular red dye CF-568 while maintaining good performance for far-red fluorophores such as Alexa-647 using the concentration of three chemicals and the pH as 4 optimization parameters. We developed a simple, cheap and stable buffer, that can be stored several weeks and frozen for longer term storage that allow high quality 3-color STORM imaging.
Optimal population turnover regimes for cultural evolution depend 1 on network size, density and behavioral transmissibility 2

12 Culture’s substrate is the social network, linking social factors and dynamics to cultural evolution 13 in a variety of ways. Yet while extensive attention has been given to the eﬀects of population size 14 and network structure, little is known of the eﬀect of population turnover—the cyclic replacement of 15 individuals in ﬁssion-fusion social systems. Here, we present a generative model to explore how population 16 turnover aﬀects a core criteria for cultural evolution, the selective retention of more adaptive traits. We 17 let a novel, high payoﬀ behavior compete against an established, low payoﬀ behavior in populations of 18 networked agents who can socially learn behavior and make behavioral decisions. We simulate this process 19 across diﬀerent turnover regimes, varying the intervals between replacement events and the number of 20 agents replaced. We ﬁnd that there are optimal turnover regimes that promote selection for higher payoﬀ 21 behaviors beyond what’s possible in static populations. The optimal regime depends on network size, 22 density, behavioral transmissibility, as well as characteristics of the learners. Our model demonstrates that 23 information loss, combined with the enhanced ability of incoming naive agents to sample the behavior 24 space, are key mechanisms that link turnover to cultural outcomes. Our study provides theoretical support 25 and predictions for the important role of naive learners for cultural evolution, identiﬁed by previous 26 experimental studies.
Cell Survival Enabled by Leakage of a Labile Metabolic Intermediate

Many metabolic pathways are of ancient origin and have evolved over long periods of time (Noda-Garcia et al., 2018). Yet, new pathways can also emerge in short time scales in response, for instance, to the presence of anthropogenic chemicals in the environment (Copley, 2009). Models of metabolic pathway emergence and evolution often emphasize the acquisition of new reactions through horizontal gene transfer and promiscuous enzyme functionalities (Pál et al., 2005; Schulenburg & Miller, 2014; Copley, 2015; Noda-Garcia et al., 2018; Peracchi, 2018). A fundamentally different mechanism of metabolic innovation is revealed by the evolutionary repair experiments reported here. A block in the proline biosynthetic pathway that compromises cell survival is efficiently rescued by many single mutations (12 at least) in the gene of glutamine synthetase. The mutations cause the leakage to the intracellular milieu of a sequestered phosphorylated intermediate common to the biosynthetic pathways of proline and glutamine, thus generating a new route to proline. Metabolic intermediates may undergo a variety of chemical and enzymatic transformations, but are typically protected as shielded reaction intermediates or through channeling in multi-enzyme complexes and metabolons (Srere, 1987; Huang et al., 2001; Grunwald, 2018; Pareek et al., 2021). Our results show that intermediate leakage can readily occur and contribute to organismal adaptation. Enhanced availability of reactive molecules may enable the generation of new biochemical pathways. We therefore anticipate applications of mutation-induced leakage in metabolic engineering.
Trait-dependent diversification in angiosperms: patterns, models and data

Variation in species richness across the tree of life, accompanied by the incredible variety of ecological and morphological characteristics found in nature, has inspired many studies to link traits with species diversification. Angiosperms are a highly diverse group that has fundamentally shaped life on earth since the Cretaceous, and illustrate how species diversification affects ecosystem functioning. Numerous traits and processes have been linked to differences in species richness within this group, but we know little about how these interact and their relative importance. Here, we synthesized data from 152 studies that used state-dependent speciation and extinction (SSE) models on angiosperm clades. Intrinsic traits related to reproduction and morphology were often linked to diversification but a set of universal drivers did not emerge as traits did not have consistent effects across clades. Importantly, dataset properties were correlated to SSE model results - trees that were larger, older, or less well-sampled tended to yield trait-dependent outcomes. We compared these properties to recommendations for SSE model use and provide a set of best practices to follow when designing studies and reporting results. Finally, we argue that SSE model inferences should be considered in a larger context incorporating species’ ecology, demography and genetics.
NON-TARGETED METABOLOMICS REVEAL DIFFERENCES IN THE METABOLIC PROFILE OF THE FALL ARMYWORM STRAINS WHEN FEEDING DIFFERENT FOOD SOURCES

Spodoptera frugiperda, the fall armyworm (FAW), is an important polyphagous agricultural pest feeding on nearly 350 host plants. FAW is undergoing incipient speciation with two well-characterized host-adapted strains, the “corn” (CS) and “rice” (RS) strains, which are morphologically identical but carry several genes under positive selection for host adaptation. We used non-targeted metabolomics based on gas chromatography/mass spectrometry to identify differences in metabolite profiles of the larval gut of CS and RS feeding on different host plants. Larvae were fed on artificial diet, maize, rice, or cotton leaves from eclosion to the sixth instar, when they had their midgut dissected for the analysis. This study revealed that the midgut metabolome of FAW varied due to larval diet and differed between the FAW host-adapted strains. Additionally, we identified several candidate metabolites that may be involved in the adaptation of CS and RS to their host plants. Our findings provide clues toward the gut metabolic activities of the FAW strains.