3,863 research outputs found
Alien Registration- Graham, Sarah A. (Greenville, Piscataquis County)
https://digitalmaine.com/alien_docs/11560/thumbnail.jp
The Role of Osteocytes in Targeted Bone Remodeling: A Mathematical Model
Until recently many studies of bone remodeling at the cellular level have
focused on the behavior of mature osteoblasts and osteoclasts, and their
respective precursor cells, with the role of osteocytes and bone lining cells
left largely unexplored. This is particularly true with respect to the
mathematical modeling of bone remodeling. However, there is increasing evidence
that osteocytes play important roles in the cycle of targeted bone remodeling,
in serving as a significant source of RANKL to support osteoclastogenesis, and
in secreting the bone formation inhibitor sclerostin. Moreover, there is also
increasing interest in sclerostin, an osteocyte-secreted bone formation
inhibitor, and its role in regulating local response to changes in the bone
microenvironment. Here we develop a cell population model of bone remodeling
that includes the role of osteocytes, sclerostin, and allows for the
possibility of RANKL expression by osteocyte cell populations. This model
extends and complements many of the existing mathematical models for bone
remodeling but can be used to explore aspects of the process of bone remodeling
that were previously beyond the scope of prior modeling work. Through numerical
simulations we demonstrate that our model can be used to theoretically explore
many of the most recent experimental results for bone remodeling, and can be
utilized to assess the effects of novel bone-targeting agents on the bone
remodeling process
Crying in Psychotherapy: The Perspective of Therapists and Clients
Eighteen U.S.-based doctoral students in counseling or clinical psychology were interviewed by phone regarding experiences of crying in therapy. Specifically, they described crying as therapists with their clients, as clients with their therapists, and experiences when their therapists cried in the participants’ therapy. Data were analyzed using consensual qualitative research. When crying with their clients, therapists expressed concern about the appropriateness/impact of crying, cried only briefly and because they felt an empathic connection with their clients, thought that the crying strengthened the relationship, discussed the event with their supervisor, and wished they had discussed the event more fully with clients. Crying as clients was triggered by discussing distressing personal events, was accompanied by a mixture of emotions regarding the tears, consisted of substantial crying to express pain or sadness, and led to multiple benefits (enhanced therapy relationship, deeper therapy, and insight). When their therapists cried, the crying was brief, was triggered by discussions of termination, arose from therapists’ empathic connection with participants, and strengthened the therapy relationship. Implications for research, training, and practice are presented
Removal of AMPA receptors (AMPARs) from synapses is preceded by transient endocytosis of extrasynaptic AMPARs
AMPA receptors (AMPARs) are dynamically regulated at synapses, but the time course and location of their exocytosis and endocytosis are not known. Therefore, we have used ecliptic pHluorin-tagged glutamate receptor 2 to visualize changes in AMPAR surface expression in real time. We show that synaptic and extrasynaptic AMPARs respond very differently to NMDA receptor activation; there is a rapid internalization of extrasynaptic AMPARs that precedes the delayed removal of synaptic AMPARs
Recommended from our members
Role of angiopoietin-like protein 3 in sugar-induced dyslipidemia in rhesus macaques: suppression by fish oil or RNAi.
Angiopoietin-like protein 3 (ANGPTL3) inhibits lipid clearance and is a promising target for managing cardiovascular disease. Here we investigated the effects of a high-sugar (high-fructose) diet on circulating ANGPTL3 concentrations in rhesus macaques. Plasma ANGPTL3 concentrations increased ∼30% to 40% after 1 and 3 months of a high-fructose diet (both P < 0.001 vs. baseline). During fructose-induced metabolic dysregulation, plasma ANGPTL3 concentrations were positively correlated with circulating indices of insulin resistance [assessed with fasting insulin and the homeostatic model assessment of insulin resistance (HOMA-IR)], hypertriglyceridemia, adiposity (assessed as leptin), and systemic inflammation [C-reactive peptide (CRP)] and negatively correlated with plasma levels of the insulin-sensitizing hormone adropin. Multiple regression analyses identified a strong association between circulating APOC3 and ANGPTL3 concentrations. Higher baseline plasma levels of both ANGPTL3 and APOC3 were associated with an increased risk for fructose-induced insulin resistance. Fish oil previously shown to prevent insulin resistance and hypertriglyceridemia in this model prevented increases of ANGPTL3 without affecting systemic inflammation (increased plasma CRP and interleukin-6 concentrations). ANGPTL3 RNAi lowered plasma concentrations of ANGPTL3, triglycerides (TGs), VLDL-C, APOC3, and APOE. These decreases were consistent with a reduced risk of atherosclerosis. In summary, dietary sugar-induced increases of circulating ANGPTL3 concentrations after metabolic dysregulation correlated positively with leptin levels, HOMA-IR, and dyslipidemia. Targeting ANGPTL3 expression with RNAi inhibited dyslipidemia by lowering plasma TGs, VLDL-C, APOC3, and APOE levels in rhesus macaques
Recommended from our members
Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.
Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is the use of computational algorithms that mimic human cognitive functions to analyze complex medical data. AI technologies like machine learning (ML) support the integration of biological, psychological, and social factors when approaching diagnosis, prognosis, and treatment of disease. This paper serves to acquaint clinicians and other stakeholders with the use, benefits, and limitations of AI for predicting, diagnosing, and classifying mild and major neurocognitive impairments, by providing a conceptual overview of this topic with emphasis on the features explored and AI techniques employed. We present studies that fell into six categories of features used for these purposes: (1) sociodemographics; (2) clinical and psychometric assessments; (3) neuroimaging and neurophysiology; (4) electronic health records and claims; (5) novel assessments (e.g., sensors for digital data); and (6) genomics/other omics. For each category we provide examples of AI approaches, including supervised and unsupervised ML, deep learning, and natural language processing. AI technology, still nascent in healthcare, has great potential to transform the way we diagnose and treat patients with neurocognitive disorders
Data for Elimination of visceral leishmaniasis in the Indian subcontinent: a comparison of predictions from three transmission models: Warwick model description and parameter uncertainty analysis
We present three transmission models of visceral leishmaniasis (VL) in the Indian subcontinent (ISC) with structural differences regarding the disease stage that provides the main contribution to transmission, including models with a prominent role of asymptomatic infection, and fit them to recent case data from 8 endemic districts in Bihar, India. Following a geographical cross-validation of the models, we compare their predictions for achieving the WHO VL elimination targets with ongoing treatment and vector control strategies. All the transmission models suggest that the WHO elimination target (<1 new VL case per 10,000 capita per year at sub-district level) is likely to be met in Bihar, India, before or close to 2020 in sub-districts with a pre-control incidence of 10 VL cases per 10,000 people per year or less, when current intervention levels (60% coverage of indoor residual spraying (IRS) of insecticide and a delay of 40 days from onset of symptoms to treatment (OT)) are maintained, given the accuracy and generalizability of the existing data regarding incidence and IRS coverage. In settings with a pre-control endemicity level of 5/10,000, increasing the effective IRS coverage from 60 to 80% is predicted to lead to elimination of VL 1–3 years earlier (depending on the particular model), and decreasing OT from 40 to 20 days to bring elimination forward by approximately 1 year. However, in all instances the models suggest that L. donovani transmission will continue after 2020 and thus that surveillance and control measures need to remain in place until the longer-term aim of breaking transmission is achieved
Recommended from our members
The State of Digital Media Data Research, 2024
The purpose of this report is to reflect on the state of digital media data research in 2024. This is the second in a series of reports on the state of digital media research, which we originally published in 2023. We reflect on changes to digital media research since our report in 2023.
Specifically, we highlight the following trends:
1. From 2023 to 2024, access to digital media data changed drastically. Researchers were largely priced out of the Twitter API, and Pushshift–a commonly used archive for Reddit data–went private to comply with Reddit’s API policies. Meta also announced the imminent sunsetting of CrowdTangle, a transparency tool popular amongst researchers and journalists alike. At the same time, however, many platforms announced academic programs for data access, including the YouTube researcher program, TikTok’s Research API, and the Meta Content Library.
2. Federated social media platforms became more popular. Following Elon Musk’s purchase of Twitter, Twitter users flocked to Mastodon, Threads, BlueSky, and other federated (or soon to be federated) platforms. This presents unique challenges for researchers studying digital media data. As new platforms are created, researchers must build new tools to analyze them or wait for third parties or the platforms themselves to make data available.
3. Generative AI’s explosion may change how we study digital media. First, researchers using computational methods to measure social media content have turned to OpenAI’s ChatGPT and other Large Language Models (LLMs) to classify content. Second, researchers and civil society groups are increasingly concerned about the possibility for Generative AI to flood the information environment with fake content.
4. In February 2024, the EU Digital Services Act (DSA) went into effect, mandating that large platforms give researchers near real-time access to public data. We don’t yet know how these policies will impact data access in the United States, and it remains unclear what this data access will look like in practice. In the United States, legislative efforts to mandate researcher access stalled.
While the last year brought many welcome and unwelcome changes to digital media data research, the findings in this report renew our encouragement that digital media data research should be guided by collaboration, transparency, preparation, and consistency.Journalism and Medi
The Relationship Between Residential Learning Communities and Student Engagement
Residential learning communities (RLCs) are residence hall environments designed to deliver academic and social benefits. For decades, many have argued RLCs are an effective means for increasing student success. Yet substantial changes in the defining characteristics of campus housing and student diversity have led to new questions about the impact of living on campus and the benefits of RLCs in particular. Consequently, we investigated the continued efficacy of RLCs as an effective educational practice. Using data from a diverse, multi-institution sample of first-year and sophomore students, this study provides insight into the relationships between RLC participation, student engagement, and perceived gains in learning
- …