Diameter-dependent phase selectivity in 1D-confined tungsten phosphides.

Topological materials confined in 1D can transform computing technologies, such as 1D topological semimetals for nanoscale interconnects and 1D topological superconductors for fault-tolerant quantum computing. As such, understanding crystallization of 1D-confined topological materials is critical. Here, we demonstrate 1D template-assisted nanowire synthesis where we observe diameter-dependent phase selectivity for tungsten phosphides. A phase bifurcation occurs to produce tungsten monophosphide and tungsten diphosphide at the cross-over nanowire diameter regime of 35-70 nm. Four-dimensional scanning transmission electron microscopy is used to identify the two phases and to map crystallographic orientations of grains at a few nm resolution. The 1D-confined phase selectivity is attributed to the minimization of the total surface energy, which depends on the nanowire diameter and chemical potentials of precursors. Theoretical calculations are carried out to construct the diameter-dependent phase diagram, which agrees with experimental observations. Our findings suggest a crystallization route to stabilize topological materials confined in 1D.

TPPB modulates PKC activity to attenuate neuroinflammation and ameliorate experimental multiple sclerosis.

Protein kinase C (PKC) plays a key role in modulating the activities of the innate immune cells of the central nervous system (CNS). A delicate balance between pro-inflammatory and regenerative activities by microglia and CNS-associated macrophages is necessary for the proper functioning of the CNS. Thus, a maladaptive activation of these CNS innate immune cells results in neurodegeneration and demyelination associated with various neurologic disorders, such as multiple sclerosis (MS) and Alzheimer's disease. Prior studies have demonstrated that modulation of PKC activity by bryostatin-1 (bryo-1) and its analogs (bryologs) attenuates the pro-inflammatory processes by microglia/CNS macrophages and alleviates the neurologic symptoms in experimental autoimmune encephalomyelitis (EAE), an MS animal model. Here, we demonstrate that (2S,5S)-(E,E)-8-(5-(4-(trifluoromethyl)phenyl)-2,4-pentadienoylamino)benzolactam (TPPB), a structurally distinct PKC modulator, has a similar effect to bryo-1 on CNS innate immune cells both in vitro and in vivo, attenuating neuroinflammation and resulting in CNS regeneration and repair. This study identifies a new structural class of PKC modulators, which can therapeutically target CNS innate immunity as a strategy to treat neuroinflammatory and neurodegenerative disorders.

A Multimodal Generative AI Copilot for Human Pathology.

The field of computational pathology[1,2] has witnessed remarkable progress in the development of both task-specific predictive models and task-agnostic self-supervised vision encoders[3,4]. However, despite the explosive growth of generative artificial intelligence (AI), there has been limited study on building general purpose, multimodal AI assistants and copilots[5] tailored to pathology. Here we present PathChat, a vision-language generalist AI assistant for human pathology. We build PathChat by adapting a foundational vision encoder for pathology, combining it with a pretrained large language model and finetuning the whole system on over 456,000 diverse visual language instructions consisting of 999,202 question-answer turns. We compare PathChat against several multimodal vision language AI assistants and GPT4V, which powers the commercially available multimodal general purpose AI assistant ChatGPT-4[7]. PathChat achieved state-of-the-art performance on multiple-choice diagnostic questions from cases of diverse tissue origins and disease models. Furthermore, using open-ended questions and human expert evaluation, we found that overall PathChat produced more accurate and pathologist-preferable responses to diverse queries related to pathology. As an interactive and general vision-language AI Copilot that can flexibly handle both visual and natural language inputs, PathChat can potentially find impactful applications in pathology education, research, and human-in-the-loop clinical decision making.

Influence of empirically derived filtering parameters, ASV, and OTU pipelines on assessing rumen microbial diversity.

Microbes play an important role in human and animal health as well as animal productivity. The host microbial interactions within ruminants play a critical role in animal health and productivity and provide up to 70% of the animal's energy need in the form of fermentation products. As such, many studies have investigated microbial community composition to understand microbial community changes and factors that affect microbial colonization and persistence. The advances in next generation sequencing (NGS) technologies and low cost of sequencing have gravitated many studies to utilize 16S rDNA-based analysis tools for interrogation of microbiomes at a much finer scale than traditional culturing. However, such methods that rely on single base pair differences for bacterial taxa clustering may inflate or underestimate diversity leading to inaccurate identification of bacterial diversity. Therefore, in this study, we sequenced mock communities of known membership and abundance to establish filtration parameters to reduce inflation of microbial diversity due to PCR and sequencing errors. Additionally, we evaluated the effect of the resulting filtering parameters proposed using established bioinformatic pipelines on a study consisting of Holstein and Jersey cattle to identify bread and treatment effects on the bacterial community composition and the impact of the filtering on global microbial community structure analysis and results. Filtration resulted in a sharp reduction in bacterial taxa identified, yet retain most sequencing data (retaining > 79% of sequencing reads) when analyzed using 3 different microbial analysis pipelines (DADA2, Mothur, USEARCH). After filtration, conclusions from α and ß-diversity tests show very similar results across all analysis methods. The mock community-based filtering parameters proposed in this study help provide a more realistic estimation of bacterial diversity. Additionally, the filtration reduced the variation between microbiome analysis methods and help identify microbial community differences that could have been missed due to large animal to animal variation observed in the unfiltered data. As such, we believe, the new filtering parameters described in this study will help obtain diversity estimates closer to realistic values and will improve the ability of detecting microbial community differences and help better understand microbial community changes in 16S rDNA-based studies.

Lithiation Induced Phases in 1T'-MoTe2 Nanoflakes.

Multiple polytypes of MoTe2 with distinct structures and intriguing electronic properties can be accessed by various physical and chemical approaches. Here, we report electrochemical lithium (Li) intercalation into 1T'-MoTe2 nanoflakes, leading to the discovery of two previously unreported lithiated phases. Distinguished by their structural differences from the pristine 1T' phase, these distinct phases were characterized using in situ polarization Raman spectroscopy and in situ single-crystal X-ray diffraction. The lithiated phases exhibit increasing resistivity with decreasing temperature, and their carrier densities are two to 4 orders of magnitude smaller than the metallic 1T' phase, as probed through in situ Hall measurements. The discovery of these gapped phases in initially metallic 1T'-MoTe2 underscores electrochemical intercalation as a potent tool for tuning the phase stability and electron density in two-dimensional (2D) materials.

Towards a general-purpose foundation model for computational pathology.

Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks, requiring the objective characterization of histopathological entities from whole-slide images (WSIs). The high resolution of WSIs and the variability of morphological features present significant challenges, complicating the large-scale annotation of data for high-performance applications. To address this challenge, current efforts have proposed the use of pretrained image encoders through transfer learning from natural image datasets or self-supervised learning on publicly available histopathology datasets, but have not been extensively developed and evaluated across diverse tissue types at scale. We introduce UNI, a general-purpose self-supervised model for pathology, pretrained using more than 100 million images from over 100,000 diagnostic H&E-stained WSIs (>77 TB of data) across 20 major tissue types. The model was evaluated on 34 representative CPath tasks of varying diagnostic difficulty. In addition to outperforming previous state-of-the-art models, we demonstrate new modeling capabilities in CPath such as resolution-agnostic tissue classification, slide classification using few-shot class prototypes, and disease subtyping generalization in classifying up to 108 cancer types in the OncoTree classification system. UNI advances unsupervised representation learning at scale in CPath in terms of both pretraining data and downstream evaluation, enabling data-efficient artificial intelligence models that can generalize and transfer to a wide range of diagnostically challenging tasks and clinical workflows in anatomic pathology.

Development and characterization of a Gucy2d-cre mouse to selectively manipulate a subset of inhibitory spinal dorsal horn interneurons.

Recent transcriptomic studies identified Gucy2d (encoding guanylate cyclase D) as a highly enriched gene within inhibitory dynorphin interneurons in the mouse spinal dorsal horn. To facilitate investigations into the role of the Gucy2d+ population in somatosensation, Gucy2d-cre transgenic mice were created to permit chemogenetic or optogenetic manipulation of this subset of spinal neurons. Gucy2d-cre mice created via CRISPR/Cas9 genomic knock-in were bred to mice expressing a cre-dependent reporter (either tdTomato or Sun1.GFP fusion protein), and the resulting offspring were characterized. Surprisingly, a much wider population of spinal neurons was labeled by cre-dependent reporter expression than previous mRNA-based studies would suggest. Although the cre-dependent reporter expression faithfully labeled ~75% of cells expressing Gucy2d mRNA in the adult dorsal horn, it also labeled a substantial number of additional inhibitory neurons in which no Gucy2d or Pdyn mRNA was detected. Moreover, cre-dependent reporter was also expressed in various regions of the brain, including the spinal trigeminal nucleus, cerebellum, thalamus, somatosensory cortex, and anterior cingulate cortex. Injection of AAV-CAG-FLEX-tdTomato viral vector into adult Gucy2d-cre mice produced a similar pattern of cre-dependent reporter expression in the spinal cord and brain, which excludes the possibility that the unexpected reporter-labeling of cells in the deep dorsal horn and brain was due to transient Gucy2d expression during early stages of development. Collectively, these results suggest that Gucy2d is expressed in a wider population of cells than previously thought, albeit at levels low enough to avoid detection with commonly used mRNA-based assays. Therefore, it is unlikely that these Gucy2d-cre mice will permit selective manipulation of inhibitory signaling mediated by spinal dynorphin interneurons, but this novel cre driver line may nevertheless be useful to target a broader population of inhibitory spinal dorsal horn neurons.

TPPB modulates PKC activity to attenuate neuroinflammation and ameliorate experimental multiple sclerosis.

Protein kinase C (PKC) plays a key role in modulating the activities of the innate immune cells of the central nervous system (CNS). A delicate balance between pro-inflammatory and regenerative activities by microglia and CNS-associated macrophages is necessary for the proper functioning of the CNS. Thus, a maladaptive activation of these CNS innate immune cells results in neurodegeneration and demyelination associated with various neurologic disorders, such as multiple sclerosis (MS) and Alzheimer's disease. Prior studies have demonstrated that modulation of PKC activity by bryostatin-1 (bryo-1) and its analogs (bryologs) attenuates the pro-inflammatory processes by microglia/CNS macrophages and alleviates the neurologic symptoms in experimental autoimmune encephalomyelitis (EAE), an MS animal model. Here, we demonstrate that (2S,5S)-(E,E)-8-(5-(4(trifluoromethyl)phenyl)-2,4-pentadienoylamino)benzolactam (TPPB), a structurally distinct PKC modulator, has a similar effect to bryo-1 on CNS innate immune cells both in vitro and in vivo, attenuating neuroinflammation and resulting in CNS regeneration and repair. This study identifies a new structural class of PKC modulators, which can therapeutically target CNS innate immunity as a strategy to treat neuroinflammatory and neurodegenerative disorders.

Nanomolding of Two-Dimensional Materials.

Lateral confinement of layered, two-dimensional (2D) materials has uniquely enabled the exploration of several topological phenomena in electron transport due to the well-defined nanoscale cross-sections and perimeters. At present, research on laterally confined 2D materials is constrained by the lack of synthesis methods that can reliably and controllably produce nanostructures with narrow widths and high aspect ratios. We demonstrate the use of thermomechanical nanomolding (TMNM) to fabricate nanowires of six layered materials (Te, In2Se3, Bi2Te3, Bi2Se3, GaSe, and Sb2Te3) with widths of 40 nm and aspect ratios above 100. During molding, the van der Waals (vdW) layers rotate by 90° from the horizontal direction in the bulk feedstock to the vertical direction in the molded nanowire, such that the layers are aligned along the nanowire length. We find that interfacial diffusion and surface energy minimization drive nanowire formation during TMNM, often resulting in single-crystalline nanowires with consistent crystallographic orientation.

In operando cryo-STEM of pulse-induced charge density wave switching in TaS2.

The charge density wave material 1T-TaS2 exhibits a pulse-induced insulator-to-metal transition, which shows promise for next-generation electronics such as memristive memory and neuromorphic hardware. However, the rational design of TaS2 devices is hindered by a poor understanding of the switching mechanism, the pulse-induced phase, and the influence of material defects. Here, we operate a 2-terminal TaS2 device within a scanning transmission electron microscope at cryogenic temperature, and directly visualize the changing charge density wave structure with nanoscale spatial resolution and down to 300 µs temporal resolution. We show that the pulse-induced transition is driven by Joule heating, and that the pulse-induced state corresponds to the nearly commensurate and incommensurate charge density wave phases, depending on the applied voltage amplitude. With our in operando cryogenic electron microscopy experiments, we directly correlate the charge density wave structure with the device resistance, and show that dislocations significantly impact device performance. This work resolves fundamental questions of resistive switching in TaS2 devices, critical for engineering reliable and scalable TaS2 electronics.

Wafer-Scale Fabrication of 2D Nanostructures via Thermomechanical Nanomolding.

With shrinking dimensions in integrated circuits, sensors, and functional devices, there is a pressing need to develop nanofabrication techniques with simultaneous control of morphology, microstructure, and material composition over wafer length scales. Current techniques are largely unable to meet all these conditions, suffering from poor control of morphology and defect structure or requiring extensive optimization or post-processing to achieve desired nanostructures. Recently, thermomechanical nanomolding (TMNM) has been shown to yield single-crystalline, high aspect ratio nanowires of metals, alloys, and intermetallics over wafer-scale distances. Here, TMNM is extended for wafer-scale fabrication of 2D nanostructures. Using In, Al, and Cu, nanomold nanoribbons with widths < 50 nm, depths ≈0.5-1 µm and lengths ≈7 mm into Si trenches at conditions compatible is successfully with back end of line processing . Through SEM cross-section imaging and 4D-STEM grain orientation maps, it is shown that the grain size of the bulk feedstock is transferred to the nanomolded structures up to and including single crystal Cu. Based on the retained microstructures of molded 2D Cu, the deformation mechanism during molding for 2D TMNM is discussed.

A General-Purpose Self-Supervised Model for Computational Pathology.

Tissue phenotyping is a fundamental computational pathology (CPath) task in learning objective characterizations of histopathologic biomarkers in anatomic pathology. However, whole-slide imaging (WSI) poses a complex computer vision problem in which the large-scale image resolutions of WSIs and the enormous diversity of morphological phenotypes preclude large-scale data annotation. Current efforts have proposed using pretrained image encoders with either transfer learning from natural image datasets or self-supervised pretraining on publicly-available histopathology datasets, but have not been extensively developed and evaluated across diverse tissue types at scale. We introduce UNI, a general-purpose self-supervised model for pathology, pretrained using over 100 million tissue patches from over 100,000 diagnostic haematoxylin and eosin-stained WSIs across 20 major tissue types, and evaluated on 33 representative CPath clinical tasks in CPath of varying diagnostic difficulties. In addition to outperforming previous state-of-the-art models, we demonstrate new modeling capabilities in CPath such as resolution-agnostic tissue classification, slide classification using few-shot class prototypes, and disease subtyping generalization in classifying up to 108 cancer types in the OncoTree code classification system. UNI advances unsupervised representation learning at scale in CPath in terms of both pretraining data and downstream evaluation, enabling data-efficient AI models that can generalize and transfer to a gamut of diagnostically-challenging tasks and clinical workflows in anatomic pathology.

PKC modulator bryostatin-1 therapeutically targets CNS innate immunity to attenuate neuroinflammation and promote remyelination.

In multiple sclerosis (MS), microglia and macrophages within the central nervous system (CNS) play an important role in determining the balance between myelin repair and demyelination/neurodegeneration. Phagocytic and regenerative functions of these CNS innate immune cells support remyelination, whereas chronic and maladaptive inflammatory activation promotes lesion expansion and disability, particularly in the progressive forms of MS. No currently approved drugs convincingly target microglia and macrophages within the CNS, contributing to the critical lack of therapies promoting remyelination and slowing progression in MS. Here, we found that the protein kinase C (PKC)-modulating drug bryostatin-1 (bryo-1), a CNS-penetrant compound with an established human safety profile, produces a shift in microglia and CNS macrophage transcriptional programs from pro-inflammatory to regenerative phenotypes, both in vitro and in vivo. Treatment of microglia with bryo-1 prevented the activation of neurotoxic astrocytes while stimulating scavenger pathways, phagocytosis, and secretion of factors that promote oligodendrocyte differentiation. In line with these findings, systemic treatment with bryo-1 augmented remyelination following a focal demyelinating injury in vivo. Our results demonstrate the potential of bryo-1 and functionally related PKC modulators as myelin regenerative and neuroprotective agents in MS and other neurologic diseases through therapeutic targeting of microglia and CNS-associated macrophages.

Deletion of Ascl1 in pancreatic ß-cells improves insulin secretion, promotes parasympathetic innervation, and attenuates dedifferentiation during metabolic stress.

OBJECTIVE: ASCL1, a pioneer transcription factor, is essential for neural cell differentiation and function. Previous studies have shown that Ascl1 expression is increased in pancreatic ß-cells lacking functional KATP channels or after feeding of a high fat diet (HFD) suggesting that it may contribute to the metabolic stress response of ß-cells. METHODS: We generated ß-cell-specific Ascl1 knockout mice (Ascl1ßKO) and assessed their glucose homeostasis, islet morphology and gene expression after feeding either a normal diet or HFD for 12 weeks, or in combination with a genetic disruption of Abcc8, an essential KATP channel component. RESULTS: Ascl1 expression is increased in response to both a HFD and membrane depolarization and requires CREB-dependent Ca2+ signaling. No differences in glucose homeostasis or islet morphology were observed in Ascl1ßKO mice fed a normal diet or in the absence of KATP channels. However, male Ascl1ßKO mice fed a HFD exhibited decreased blood glucose levels, improved glucose tolerance, and increased ß-cell proliferation. Bulk RNA-seq analysis of islets from Ascl1ßKO mice from three studied conditions showed alterations in genes associated with the secretory function. HFD-fed Ascl1ßKO mice showed the most extensive changes with increased expression of genes necessary for glucose sensing, insulin secretion and ß-cell proliferation, and a decrease in genes associated with ß-cell dysfunction, inflammation and dedifferentiation. HFD-fed Ascl1ßKO mice also displayed increased expression of parasympathetic neural markers and cholinergic receptors that was accompanied by increased insulin secretion in response to acetylcholine and an increase in islet innervation. CONCLUSIONS: Ascl1 expression is induced by stimuli that cause Ca2+-signaling to the nucleus and contributes in a multifactorial manner to the loss of ß-cell function by promoting the expression of genes associated with cellular dedifferentiation, attenuating ß-cells proliferation, suppressing acetylcholine sensitivity, and repressing parasympathetic innervation of islets. Thus, the removal of Ascl1 from ß-cells improves their function in response to metabolic stress.

Chikungunya virus cell-to-cell transmission is mediated by intercellular extensions in vitro and in vivo.

Chikungunya virus (CHIKV) has recently emerged to cause millions of human infections worldwide. Infection can induce the formation of long intercellular extensions that project from infected cells and form stable non-continuous membrane bridges with neighbouring cells. The mechanistic role of these intercellular extensions in CHIKV infection was unclear. Here we developed a co-culture system and flow cytometry methods to quantitatively evaluate transmission of CHIKV from infected to uninfected cells in the presence of neutralizing antibody. Endocytosis and endosomal acidification were critical for virus cell-to-cell transmission, while the CHIKV receptor MXRA8 was not. By using distinct antibodies to block formation of extensions and by evaluation of transmission in HeLa cells that did not form extensions, we showed that intercellular extensions mediate CHIKV cell-to-cell transmission. In vivo, pre-treatment of mice with a neutralizing antibody blocked infection by direct virus inoculation, while adoptive transfer of infected cells produced antibody-resistant host infection. Together our data suggest a model in which the contact sites of intercellular extensions on target cells shield CHIKV from neutralizing antibodies and promote efficient intercellular virus transmission both in vitro and in vivo.

Emergent layer stacking arrangements in c-axis confined MoTe2.

The layer stacking order in 2D materials strongly affects functional properties and holds promise for next-generation electronic devices. In bulk, octahedral MoTe2 possesses two stacking arrangements, the ferroelectric Weyl semimetal Td phase and the higher-order topological insulator 1T' phase. However, in thin flakes of MoTe2, it is unclear if the layer stacking follows the Td, 1T', or an alternative stacking sequence. Here, we use atomic-resolution scanning transmission electron microscopy to directly visualize the MoTe2 layer stacking. In thin flakes, we observe highly disordered stacking, with nanoscale 1T' and Td domains, as well as alternative stacking arrangements not found in the bulk. We attribute these findings to intrinsic confinement effects on the MoTe2 stacking-dependent free energy. Our results are important for the understanding of exotic physics displayed in MoTe2 flakes. More broadly, this work suggests c-axis confinement as a method to influence layer stacking in other 2D materials.

Algorithmic fairness in artificial intelligence for medicine and healthcare.

In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspective, we outline fairness in machine learning through the lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation and intra-observer labelling variability, in particular) arise in clinical workflows and the resulting healthcare disparities. We also review emerging technology for mitigating biases via disentanglement, federated learning and model explainability, and their role in the development of AI-based software as a medical device.

Early-Life Iron Deficiency Persistently Alters Nociception in Developing Mice.

Clinical association studies have identified early-life iron deficiency (ID) as a risk factor for the development of chronic pain. While preclinical studies have shown that early-life ID persistently alters neuronal function in the central nervous system, a causal relationship between early-life ID and chronic pain has yet to be established. We sought to address this gap in knowledge by characterizing pain sensitivity in developing male and female C57Bl/6 mice that were exposed to dietary ID during early life. Dietary iron was reduced by ∼90% in dams between gestational day 14 and postnatal day (P)10, with dams fed an ingredient-matched, iron-sufficient diet serving as controls. While cutaneous mechanical and thermal withdrawal thresholds were not altered during the acute ID state at P10 and P21, ID mice were more sensitive to mechanical pressure at P21 independent of sex. During adulthood, when signs of ID had resolved, mechanical and thermal thresholds were similar between early-life ID and control groups, although male and female ID mice displayed increased thermal tolerance at an aversive (45 °C) temperature. Interestingly, while adult ID mice showed decreased formalin-induced nocifensive behaviors, they showed exacerbated mechanical hypersensitivity and increased paw guarding in response to hindpaw incision in both sexes. Collectively, these results suggest that early-life ID elicits persistent changes in nociceptive processing and appears capable of priming developing pain pathways. PERSPECTIVE: This study provides novel evidence that early-life ID evokes sex-independent effects on nociception in developing mice, including an exacerbation of postsurgical pain during adulthood. These findings represent a critical first step towards the long-term goal of improving health outcomes for pain patients with a prior history of ID.

Social Media Reflection Assignment: a Simple Classroom Intervention To Help Students Examine Scientific Claims in Social Media.

Social media has the power to spread information faster than any other news source. The science community has experienced this firsthand during recent years, unfortunately to its detriment. When scientific and medical claims are made without responsible examination of scientific evidence, misinformation is allowed to spread. While all users are likely faced with misleading claims on social media, this is especially troublesome for young adults. As the most prevalent users, many in this age group have never known a time without social media. Educators have an opportunity to use social media as a real-world application to teach students how to critically analyze scientific and medical information. The Social Media Reflection Assignment (SMRA) was created to help students develop such scientific literacy skills. This intervention requires students to find social media posts that make scientific claims, citing published scientific data. Students locate the corresponding research article and describe the results in their own words. Finally, a comparison is drawn between scientific findings in the research article and the interpretation described in the social media post. Students are taught to judge whether social media claims are supported by the scientific evidence. This activity is adaptable and applicable in a variety of classroom settings, from upper-level majors courses to science courses for nonmajors to disciplines outside the sciences. Importantly, the SMRA helps students question claims in social media while training them to find and elucidate answers from reliable resources.