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The upstream mechanobiological pathways that regulate the downstream mineralization rates in periodontal tissues are limitedly understood. Herein, we spatially colocalized and correlated compression and tension strain profiles with the expressions of mechanosensory ion channels (MS-ion) TRPV4 and PIEZO1, biometal zinc, mitochondrial function marker (MFN2), cell senescence indicator (p16), and oxygen status marker hypoxia-inducible factor-1α (HIF-1α) in rats fed hard and soft foods. The observed zinc and related cellular homeostasis in vivo were ascertained by TRPV4 and PIEZO1 agonists and antagonists on human periodontal ligament fibroblasts ex vivo. Four-week-old male Sprague-Dawley rats were fed hard (n= 3) or soft (n= 3) foods for 4 wk (in vivo). Significant changes in alveolar socket and root shapes with decreased periodontal ligament space and increased cementum volume fraction were observed in maxillae on reduced loads (soft food). Reduced loads impaired distally localized compression-stimulated PIEZO1 and mesially localized tension-stimulated TRPV4, decreased mitochondrial function (MFN2), and increased cell senescence in mesial and distal periodontal regions. The switch inHIF-1αfrom hard food–distal to soft food–mesial indicated a plausible effect of shear-regulated blood and oxygen flows in the periodontal complex. Blunting or activating TRPV4 or PIEZO1 MS-ion channels by channel-specific antagonists or agonists in human periodontal ligament fibroblast cultures (in vitro) indicated a positive correlation between zinc levels and zinc transporters but not with MS-ion channel expressions. The effects of reduced chewing loads in vivo were analogous to TRPV4 and PIEZO1 antagonists in vitro. Study results collectively illustrated that tension-induced TRPV4 and compression-induced PIEZO1 activations are necessary for cell metabolism. An increased hypoxic state with reduced functional loads can be a conducive environment for cementum growth. From a practical standpoint, dose rate–controlled loads can modulate tension and compression-specific MS-ion channel activation, cellular zinc, andHIF-1αtranscription. These mechanobiochemical events indicate the plausible catalytic role of biometal zinc in mineralization, periodontal maintenance, and dentoalveolar joint function. 

Student engagement is a key predictor of academic achievement and is closely linked to career awareness, interest, and preparedness. Measuring student engagement during STEM learning is challenging for teachers, given the dynamic and ever-changing nature of these learning environments. Even when engagement data can be collected, leveraging this information to refine and personalize instruction requires significant experience and time. To address this, we are developing Scoutlier EngagEd, a digital teaching assistant that embeds in existing Learning Management Systems (LMS) to automatically and invisibly gather multidimensional data on student engagement and performance during STEM learning. These data are being leveraged to model student learning and generate insights that produce human-like, actionable recommendations through a Large Language Model (LLM) for teachers to improve STEM learning outcomes. 

Histopathology plays a critical role in the diagnosis and surgical management of cancer. However, access to histopathology services, especially frozen section pathology during surgery, is limited in resource-constrained settings because preparing slides from resected tissue is time-consuming, labor-intensive, and requires expensive infrastructure. Here, we report a deep-learning-enabled microscope, named DeepDOF-SE, to rapidly scan intact tissue at cellular resolution without the need for physical sectioning. Three key features jointly make DeepDOF-SE practical. First, tissue specimens are stained directly with inexpensive vital fluorescent dyes and optically sectioned with ultra-violet excitation that localizes fluorescent emission to a thin surface layer. Second, a deep-learning algorithm extends the depth-of-field, allowing rapid acquisition of in-focus images from large areas of tissue even when the tissue surface is highly irregular. Finally, a semi-supervised generative adversarial network virtually stains DeepDOF-SE fluorescence images with hematoxylin-and-eosin appearance, facilitating image interpretation by pathologists without significant additional training. We developed the DeepDOF-SE platform using a data-driven approach and validated its performance by imaging surgical resections of suspected oral tumors. Our results show that DeepDOF-SE provides histological information of diagnostic importance, offering a rapid and affordable slide-free histology platform for intraoperative tumor margin assessment and in low-resource settings. 

The development of modern birds provides a window into the biology of their dinosaur ancestors. We investigated avian postnatal development and found that sterile inflammation drives formation of the pygostyle, a compound structure resulting from bone fusion in the tail. Inflammation is generally induced by compromised tissue integrity, but here is involved in normal bone development. Transcriptome profiling and immuno/histochemistry reveal a robust inflammatory response that resembles bone fracture healing. The data suggest the involvement of necroptosis and multiple immune cell types, notably heterophils (the avian equivalent of neutrophils). Additionally, nucleus pulposus structures, heretofore unknown in birds, are involved in disc remodeling. Anti-inflammatory corticosteroid treatment inhibited vertebral fusion, substantiating the crucial role of inflammation in the ankylosis process. This study shows that inflammation can drive developmental skeletogenesis, in this case leading to the formation of a flight-adapted tail structure on the evolutionary path to modern avians. 

The purpose of this report is to share a conceptual model useful in the design of professional learning about teaching for university mathematics faculty. The model is illustrated by examples from a particular design effort: the development of an online shortcourse for faculty new to teaching mathematics courses for prospective primary school teachers. How novice mathematics teacher educators grow as instructors is an emerging area of research and development in the United States. At the same time, it is well established that effective instructional design of any course, including a course for faculty, requires breadth first: understanding and anticipating the needs of the learner. Therefore, given the sparse knowledge base in the new arena of mathematics teacher educator professional growth, effective design requires leveraging the scant existing research while also exploring and iteratively refining broad goals and objectives for faculty learning. Only after a conceptual foundation is articulated for what is to be learned and what will constitute evidence of learning, can cycles of design productively examine and test-bed particular course features such as lesson content, structures (like scope and sequence), and processes (like communication and evaluation). In the example used in this report, several researchbased perspectives on learning in/for/about teaching guided design goals and short-course objectives. These valued perspectives informed creation and prioritization of principles for short-course design which, in turn, informed evaluation of faculty learning. With these conceptual foundations in place, design of lessons to realize the goals, principles, and objectives rapidly followed. The work reported here contributes to the knowledge base in two ways: (1) it addresses faculty professional development directly by describing and illustrating a model for supporting instructional improvement and (2) it provides metanarrative to scaffold the professional growth of those who design professional learning opportunities for post-secondary mathematics faculty. 

Abstract In Neurospora crassa, expression from an unpaired gene is suppressed by a mechanism known as meiotic silencing by unpaired DNA (MSUD). MSUD utilizes common RNA interference (RNAi) factors to silence target mRNAs. Here, we report that Neurospora CAR-1 and CGH-1, homologs of two Caenorhabditis elegans RNA granule components, are involved in MSUD. These fungal proteins are found in the perinuclear region and P-bodies, much like their worm counterparts. They interact with components of the meiotic silencing complex (MSC), including the SMS-2 Argonaute. This is the first time MSUD has been linked to RNA granule proteins. 

While the ultimate goal of natural-language based Human-Robot Interaction (HRI) may be free-form, mixed-initiative dialogue,social robots deployed in the near future will likely primarily engage in wakeword-driven interaction, in which users’ commands are prefaced by a wakeword such as “Hey, Robot.” This style of interaction helps to allay user privacy concerns, as the robot’s full speech recognition module need not be employed until the target wakeword is used. Unfortunately, there are a number of concerns in the popular media surrounding this style of interaction, with consumers fearing that it is training users (in particular,children) to be rude towards technology, and by extension, rude towards other humans. In this paper, we present a study that demonstrates how an alternate style of wakeword, i.e., “Excuse me, Robot” may allay this concern, by priming users to phrase commands as Indirect Speech Acts 

Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained, and imaged to determine whether surgical margins are free of tumor cells—a costly and time- and labor-intensive procedure. Here, we introduce a deep-learning extended DOF (DeepDOF) microscope to quickly image large areas of freshly resected tissue to provide histologic-quality images of surgical margins without physical sectioning. The DeepDOF microscope consists of a conventional fluorescence microscope with the simple addition of an inexpensive (less than $10) phase mask inserted in the pupil plane to encode the light field and enhance the depth-invariance of the point-spread function. When used with a jointly optimized image-reconstruction algorithm, diffraction-limited optical performance to resolve subcellular features can be maintained while significantly extending the DOF (200 µm). Data from resected oral surgical specimens show that the DeepDOF microscope can consistently visualize nuclear morphology and other important diagnostic features across highly irregular resected tissue surfaces without serial refocusing. With the capability to quickly scan intact samples with subcellular detail, the DeepDOF microscope can improve tissue sampling during intraoperative tumor-margin assessment, while offering an affordable tool to provide histological information from resected tissue specimens in resource-limited settings.