Search

Access to maker technologies has catalyzed and amplified the possibilities for creating physical materials that are responsive to the needs of students. Opportunities for design and fabrication of original mathematics manipulatives have been incorporated into the teacher education program at Montclair State University. Participating preservice elementary teachers design and make original mathematics manipulatives. Three case studies examine ways in which this process enhances students' mathematical reasoning, sense-making, and understanding. The designs created are made available through links to the open source Educational CAD Model Repository, enabling others to replicate the objects described.

An Educational CAD Model Library (CAD Library) is being developed by collaborating educational associations affiliated with the National Technology Leadership Summit coalition. The CAD Library's Curators' Council has developed descriptive metadata fields that will be associated with each educational object published in the library. These fields are designed to facilitate search and discovery of objects by teachers who are increasingly well positioned to use these objects in their instruction due to the increasing presence of school-based makerspaces and the 3D printers, digital die cutters, and other fabrication tools. The publication of these metadata standards makes them available to the members of the educational associations participating in the development of the CAD Library and to other relevant stakeholders for feedback to inform ongoing revisions.

While traditionally teachers have been positioned as implementers of curricular materials designed by others, this work positions them as designers of their own curricular resources, thereby inviting opportunities for their exploration at the intersection of content, pedagogy, and design. As researchers accepting greater responsibility for preparing teachers to maintain a commitment to their pedagogical vision in practice, this work seeks to cultivate the imagination of humanistic forms of mathematics teaching and learning by supporting these explorations. Toward that end, this paper reports on research that examines connections between the pedagogical/conceptual knowledge that prospective teachers embed in the designs of original manipulatives and how those designs mediate the pedagogical moves they make in teaching situations. The promise of this work is in connections that may offer a viable means to support bolder connections between teacher preparation and practice. We share findings from the analysis of prospective teachers’ design activity that conveys (1) the diversity of design decisions, rationales, and mediating resources that it entailed, and (2) how the designed manipulative act as anchors for their conceptual/pedagogical moves. The implications of these findings for teacher preparation and professional learning are considered.

Abstract Background The relationship between burden of disease and research funding has been examined cross-sectionally, but temporal patterns have not been investigated. It is logical to assume that temporal improvements in disability-adjusted life-years (DALYs) reflect benefits from research funding; such assumptions are tempered by an unknown lag time for emergence of benefits from research. Methods We studied National Institutes of Health (NIH) research fund allocations and United States DALY estimates for overlapping disease categories (matched disease categories, MDC, N = 38). Using a general linear model, we separately analysed DALYs for MDCs in 2017 in relation to NIH research allocations in 2017 and 2007. We also examined how changes in DALYs were related to cumulative NIH research funding (2006–2017). After regressing DALY change on summed funding, we obtained model residuals as estimates of the discrepancy for each MDC between observed and expected change in burden, given funding. Results In 2017, there was a positive association between NIH research fund allocations and DALYs for the same year (F 1,36 = 16.087, p = 0.0002921; slope = 0.35020; model R 2 = 0.3088), suggesting proportionate allocation. There was a positive association between 2017 DALYs and 2007 NIH research allocation, implying a beneficial impact of research (F 1,36 = 15.754, p = 0.0003; slope = 0.8845; model R 2 = 0.3044). In contrast, there was a nonsignificant association between summed NIH funding and percent change in DALYs over 2006–2017 (F 1,36 = 0.199; p = 0.65; beta coefficient = −1.144). When MDCs were ordered based on residuals, HIV/AIDS ranked first. Mental, neurologic or substance abuse (MNS) disorders comprised most residuals in the lower half. Conclusions NIH fund allocation is proportional to DALYs for MDCs. Temporal changes in DALYs vary by MDCs, but they are not significantly related to cumulative research outlays. Further analysis of temporal changes in DALYs could help to inform research outlays for MDCs and to study the impact of research.

The purpose of this study was to investigate the difference in oculomotor functioning between Olympic-level contact and non-contact sports participants. In total, 67 male and female Olympic-level contact (n = 27) and non-contact (n = 40) athletes completed oculomotor tasks, including Horizontal Saccade (HS), Circular Smooth Pursuit (CSP), Horizontal Smooth Pursuit (HSP), and Vertical Smooth Pursuit (VSP) using a remote eye tracker. No significant differences for sex or age occurred. Each variable indicated higher scores for contact compared to non-contact athletes (p <.05) except for VSP Pathway differences and CSP Synchronization. A logistic regression was performed to determine the degree that HS measures, CSP synchronization, and VSP pathway predicted sport type. The model was significant, χ2(6) = 37.08, p <.001, explaining 57.4% of the variance and correctly classified 88.1% of cases. The sensitivity was 87.5% and specificity was 88.9%. CSP synchronization did not increase the likelihood of participating in a contact sport. This was the first study to identify oculomotor differences between Olympic athletes of contact and non-contact sports, which adds to the growing evidence that oculomotor functioning may be a reliable, quick, real-time tool to help detect mTBI in sport. [ABSTRACT FROM AUTHOR]

Before initiating therapy for patients with periodontitis, clinicians need to consider diagnostic issues in light of current knowledge regarding a number of factors, including the etiology of periodontal diseases, patterns of periodontal disease progression, interpretations of bleeding on probing, hypermobility, radiographs, and probing assessments. Scaling and root planing to reduce biofilms and the bacterial challenge is an effective mode of therapy for treating many cases of periodontitis. Subsequent to tooth instrumentation, signs of gingival inflammation are reduced, and the magnitude of probing depth reductions and clinical attachment gains are related to initial pocket depths. Root debridement can be accomplished with manual instrumentation or power devices (eg, ultrasonic) in one quadrant at a time or via full-mouth debridement. Root planing should be limited to areas that are inflamed or have calculus to avoid removal of cementum and inducing root sensitivity. Endotoxins can be decreased through washing or use of an ultrasonic device. Periodic professional maintenance visits should be based on the patient's periodontal status and his or her ability to comply with maintenance protocols. Practical application of current concepts with respect to the diagnosis and treatment of periodontitis enhances periodontal therapy. [ABSTRACT FROM AUTHOR]

This study explores effects of teaching experience and specialized mathematics education on mathematics anxiety and mathematics teaching anxiety. Fifty-nine female pre-service and in-service mathematics primary school teachers with varied specialized mathematics education and teaching experience responded to a questionnaire measuring mathematics anxiety and mathematics teaching anxiety. The results illustrate that specialized mathematics education affects in-service primary school teachers' mathematics anxiety, and that teaching experience is associated with mathematics teaching anxiety. Moreover, mathematics anxiety of some in-service primary teachers without specialization does not fade with time. The discussion highlights the importance of identifying mathematics anxiety in primary school teachers with no specialized mathematics education, aiming to lower it. The small sample and participants' background limit the power of the findings. This study recommends conducting further studies according to the suggested mathematics anxiety cognitive-behavioral model; addressing cultural differences, teachers with and without specialized mathematics education, and comparing middle and secondary teachers.

As an approach-oriented emotion, anger appears to affect behavioral thresholds in a range of contexts. The current work consists of three experiments examining this in the context of eyewitness identification procedures. Experiments 1 and 2 examined the relationship between a witness' anger and identification reliability, and Experiment 3 examined the relationship between a lineup creator's anger and the quality of selected lineup fillers. Experiments 1 and 2 showed that anger during an identification procedure is associated with increased risk of false identifications and reduced confidence-accuracy calibration. Experiment 3 showed that anger is associated with lower quality of fillers selected by lineup creators. Together, these experiments suggest that anger may undermine the quality of eyewitness evidence, even when the witnesses themselves are not the ones experiencing anger and even when anger is not directed at the perpetrator or suspect.

Abstract Objectives Data from radiological departments provide important information on overall quantities of medical care provided. With this study we used a comprehensive analysis of radiological examinations as a surrogate marker to quantify the effect of the different COVID-19 waves on medical care provided. Methods Radiological examination volumes during the different waves of infection were compared among each other as well as to time-matched control periods from pre-pandemic years using a locally weighted scatterplot smoothing as well as negative binominal regression models. Results A total of 1,321,119 radiological examinations were analyzed. Examination volumes were reduced by about 10% over the whole study period (IRR = 0.90; 95% CI 0.89–0.92), with a focus on acute medical care (0.84; 0.83–0.85) and outpatients (0.93: 0.90–0.97). When compared to wave 1, examination volumes were about 17% higher during wave 2 (1.17; 1.10–1.25), and 33% higher in wave 3 of the pandemic (1.33; 1.24–1.42). Conclusions This study shows the severe effect of COVID-19 pandemic and related shutdown measures on overall provided medical care as measured by radiological examinations. When compared, the decrease of medical care was more pronounced in the earlier waves of the pandemic.

Background: Nocturnal wakefulness has emerged as a potential predictor of short-term suicide risk. This analysis used dynamic temporal patterns in alpha and beta power and global sleep metrics to explore the possible link between next-day suicidal ideation (NDSI) and wakefulness measures in unmedicated participants with treatment-resistant depression. Methods: Thirty-three medication-free participants with treatment-resistant depression completed overnight polysomnography. Alpha and beta spectral power as functions over time were used to represent arousal-related components of the dynamic sleep process. A functional data analytic approach (multilevel functional principal component analysis [MFPCA]) was used to preserve the oscillatory nature of the data; MFPCA PC scores were then associated with NDSI. Associations between NDSI and polysomnography-defined wakefulness after sleep onset, sleep efficiency, and total sleep time were also evaluated. Results: NDSI had the strongest relationship with the second beta PC score (slope = 0.09 [90% credible interval, 0.03 to 0.14]), which represented an oscillating pattern that reflected disturbed sleep. The first PCs from both alpha and beta MFPCAs represented the overall magnitude of power and were most closely associated with traditional polysomnography metrics but were not related to NDSI. Results were equivocal for wakefulness after sleep onset with NDSI and did not support a relationship between NDSI and either sleep efficiency or total sleep time, highlighting the value of information contained in oscillating electroencephalogram patterns for identifying physiological links between nocturnal wakefulness and NDSI. Conclusions: This study leveraged the dynamic nature of wakefulness-related electroencephalogram frequencies and provides a potential electrophysiological link between suicidal ideation and wakefulness during sleep in individuals with treatment-resistant depression.

BackgroundA significant number of patients do not adhere to their prescribed course of physical therapy or discharge themselves from care. Adhering to prescribed physical therapy, including attending physical therapy clinic appointments, contributes to patients achieving the goals of therapy including reducing pain and increasing functionality. Web-based platforms have been demonstrated to be effective means for managing clinical patients with musculoskeletal pain, similar to managing them in person. Behavior change techniques introduced through digital or web-based platforms can reduce nonadherence with prescribed physical therapy and improve patient outcomes. Literature also indicates that a phone-based app provided to patients, which includes a reward-incentive gamification to complement their care, contributed to a greater number of kept appointments in a physical therapy clinic. ObjectiveThis study aims to compare the rate of provider discharge with self-discharge and the number of clinic visits among patients attending a physical health clinic who did and did not choose to adopt a phone-based app to complement their care. A secondary purpose was to compare the revenue generated by patients attending a physical health clinic who did and did not choose to adopt a phone-based app to complement their care. MethodsA retrospective analysis of all new outpatient medical records (N=5328) from a multisite physical health practice was conducted between January 2018 and December 2019. Patients in the sample self-selected the 2018 Usual Care, the 2019 Usual Care, or the 2019 Kanvas App groups. Kanvas is a customized private practice app, designed for patient engagement with their specific health care provider. This app included a gamification system that provided rewards to the patient for attending their scheduled clinic appointments. According to their medical record, each patient was classified as completing their prescribed therapy (provider discharged) or not completing their prescribed therapy (self-discharged). Additionally, the total number of clinic visits each patient attended, the total charges for services, and the total payments received by the clinic per patient were extracted from each patient’s medical record. ResultsPatients in the 2019 Kanvas App Group exhibited a higher rate of provider discharge compared to patients who did not adopt the app. This greater rate of provider discharges among the patients who adopted the Kanvas app likely contributed to this group attending more clinic visits (13.21, SD 12.09) than the other study groups who did not download the app (10.72, SD 9.80 to 11.35, SD 11.10). This greater number of clinic visits in turn contributed to the patients who adopted the app generating more clinic charges and payments. ConclusionsFuture investigators need to employ more rigorous methods to confirm these findings, and clinicians need to weigh the anticipated benefits against the cost and staff involvement in managing the Kanvas app.

RationaleAcute respiratory failure is a life-threatening clinical outcome in critically ill pediatric patients. In severe cases, patients can require mechanical ventilation (MV) for survival. Early recognition of these patients can potentially help clinicians alter the clinical course and lead to improved outcomes.ObjectivesTo build a data-driven model for early prediction of the need for mechanical ventilation in pediatric intensive care unit (PICU) patients.MethodsThe study consists of a single-center retrospective observational study on a cohort of 13,651 PICU patients admitted between 1/01/2010 and 5/15/2018 with a prevalence of 8.06% for MV due to respiratory failure. XGBoost (extreme gradient boosting) and a convolutional neural network (CNN) using medication history were used to develop a prediction model that could yield a time-varying "risk-score"-a continuous probability of whether a patient will receive MV-and an ideal global threshold was calculated from the receiver operating characteristics (ROC) curve. The early prediction point (EPP) was the first time the risk-score surpassed the optimal threshold, and the interval between the EPP and the start of the MV was the early warning period (EWT). Spectral clustering identified patient groups based on risk-score trajectories after EPP.ResultsA clinical and medication history-based model achieved a 0.89 area under the ROC curve (AUROC), 0.6 sensitivity, 0.95 specificity, 0.55 positive predictive value (PPV), and 0.95 negative predictive value (NPV). Early warning time (EWT) median [inter-quartile range] of this model was 9.9[4.2-69.2] hours. Clustering risk-score trajectories within a six-hour window after the early prediction point (EPP) established three patient groups, with the highest risk group's PPV being 0.92.ConclusionsThis study uses a unique method to extract and apply medication history information, such as time-varying variables, to identify patients who may need mechanical ventilation for respiratory failure and provide an early warning period to avert it.

Although dementia research has been dominated by Alzheimer's disease (AD), most dementia in older people is now recognised to be due to mixed pathologies, usually combining vascular and AD brain pathology. Vascular cognitive impairment (VCI), which encompasses vascular dementia (VaD) is the second most common type of dementia. Models of VCI have been delayed by limited understanding of the underlying aetiology and pathogenesis. This review by a multidisciplinary, diverse (in terms of sex, geography and career stage), cross-institute team provides a perspective on limitations to current VCI models and recommendations for improving translation and reproducibility. We discuss reproducibility, clinical features of VCI and corresponding assessments in models, human pathology, bioinformatics approaches, and data sharing. We offer recommendations for future research, particularly focusing on small vessel disease as a main underpinning disorder.

One of the feats of adaptive immunity is its ability to recognize foreign pathogens while sparing the self. During maturation in the thymus, T cells are selected through the binding properties of their antigen-specific T-cell receptor (TCR), through the elimination of both weakly (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of their development, including cells that do not pass selection. We combine high-throughput repertoire sequencing with statistical inference techniques to characterize the selection of the TCR in these distinct subsets. We find small but significant differences in the TCR repertoire parameters between the maturation stages, which recapitulate known differentiation pathways leading to the CD4+ and CD8+ subtypes. These differences can be simulated by simple models of selection acting linearly on the sequence features. We find no evidence of specific sequences or sequence motifs or features that are suppressed by negative selection. These results favour a collective or statistical model for T-cell self non-self discrimination, where negative selection biases the repertoire away from self recognition, rather than ensuring lack of self-reactivity at the single-cell level.

There have been over 621 million cases of COVID-19 worldwide with over 6.5 million deaths. Despite the high secondary attack rate of COVID-19 in shared households, some exposed individuals do not contract the virus. In addition, little is known about whether the occurrence of COVID-19 resistance differs among people by health characteristics as stored in the electronic health records (EHR). In this retrospective analysis, we develop a statistical model to predict COVID-19 resistance in 8,536 individuals with prior COVID-19 exposure using demographics, diagnostic codes, outpatient medication orders, and count of Elixhauser comorbidities in EHR data from the COVID-19 Precision Medicine Platform Registry. Cluster analyses identified 5 patterns of diagnostic codes that distinguished resistant from non-resistant patients in our study population. In addition, our models showed modest performance in predicting COVID-19 resistance (best performing model AUROC = 0.61). Monte Carlo simulations conducted indicated that the AUROC results are statistically significant (p < 0.001) for the testing set. We hope to validate the features found to be associated with resistance/non-resistance through more advanced association studies.

Combination therapy is necessary to treat tuberculosis to decrease the rate of disease relapse and prevent the acquisition of drug resistance, and shorter regimens are urgently needed. The adaptation of Mycobacterium tuberculosis to various lesion microenvironments in infection induces various states of slow replication and non-replication and subsequent antibiotic tolerance. This non-heritable tolerance to treatment necessitates lengthy combination therapy. Therefore, it is critical to develop combination therapies that specifically target the different types of drug-tolerant cells in infection. As new tools to study drug combinations earlier in the drug development pipeline are being actively developed, we must consider how to best model the drug-tolerant cells to use these tools to design the best antibiotic combinations that target those cells and shorten tuberculosis therapy. In this review, we discuss the factors underlying types of drug tolerance, how combination therapy targets these populations of bacteria, and how drug tolerance is currently modeled for the development of tuberculosis multidrug therapy. We highlight areas for future studies to develop new tools that better model drug tolerance in tuberculosis infection specifically for combination therapy testing to bring the best drug regimens forward to the clinic.

Beta cell replacement has the potential to restore euglycemia in patients with insulin-dependent diabetes. Although great progress has been made in establishing allogeneic islet transplantation from deceased donors as the standard of care for those with the most labile diabetes, it is also clear that the deceased donor organ supply cannot possibly treat all those who could benefit from restoration of a normal beta cell mass, especially if immunosuppression were not required. Against this background, the International Pancreas and Islet Transplant Association in collaboration with the Harvard Stem Cell Institute, the Juvenile Diabetes Research Foundation (JDRF), and the Helmsley Foundation held a 2-day Key Opinion Leaders Meeting in Boston in 2016 to bring together experts in generating and transplanting beta cells derived from stem cells. The following summary highlights current technology, recent significant breakthroughs, unmet needs and roadblocks to stem cell-derived beta cell therapies, with the aim of spurring future preclinical collaborative investigations and progress toward the clinical application of stem cell-derived beta cells.

The heterochromatin spreading reaction is a central contributor to the formation of gene-repressive structures, which are re-established with high positional precision, or fidelity, following replication. How the spreading reaction contributes to this fidelity is not clear. To resolve the origins of stable inheritance of repression, we probed the intrinsic character of spreading events in fission yeast using a system that quantitatively describes the spreading reaction in live single cells. We show that spreading triggered by noncoding RNA-nucleated elements is stochastic, multimodal, and fluctuates dynamically across time. This lack of stability correlates with high histone turnover. At the mating type locus, this unstable behavior is restrained by an accessory cis-acting element REIII, which represses histone turnover. Further, REIII safeguards epigenetic memory against environmental perturbations. Our results suggest that the most prevalent type of spreading, driven by noncoding RNA-nucleators, is epigenetically unstable and requires collaboration with accessory elements to achieve high fidelity.

OBJECTIVE: To systematically review evidence regarding ataxia treatment. METHODS: A comprehensive systematic review was performed according to American Academy of Neurology methodology. CONCLUSIONS: For patients with episodic ataxia type 2, 4-aminopyridine 15 mg/d probably reduces ataxia attack frequency over 3 months (1 Class I study). For patients with ataxia of mixed etiology, riluzole probably improves ataxia signs at 8 weeks (1 Class I study). For patients with Friedreich ataxia or spinocerebellar ataxia (SCA), riluzole probably improves ataxia signs at 12 months (1 Class I study). For patients with SCA type 3, valproic acid 1,200 mg/d possibly improves ataxia at 12 weeks. For patients with spinocerebellar degeneration, thyrotropin-releasing hormone possibly improves some ataxia signs over 10 to 14 days (1 Class II study). For patients with SCA type 3 who are ambulatory, lithium probably does not improve signs of ataxia over 48 weeks (1 Class I study). For patients with Friedreich ataxia, deferiprone possibly worsens ataxia signs over 6 months (1 Class II study). Data are insufficient to support or refute the use of numerous agents. For nonpharmacologic options, in patients with degenerative ataxias, 4-week inpatient rehabilitation probably improves ataxia and function (1 Class I study); transcranial magnetic stimulation possibly improves cerebellar motor signs at 21 days (1 Class II study). For patients with multiple sclerosis-associated ataxia, the addition of pressure splints possibly has no additional benefit compared with neuromuscular rehabilitation alone (1 Class II study). Data are insufficient to support or refute use of stochastic whole-body vibration therapy (1 Class III study).