University of Natural Medicine

To facilitate high spatial-temporal resolution fMRI (≦1mm3) at more broadly available field strengths (3T) and to better understand the neural underpinnings of joy, we used SE-based generalized Slice Dithered Enhanced Resolution (gSLIDER). This sequence increases SNR efficiency utilizing sub-voxel shifts along the slice direction. To improve the effective temporal resolution of gSLIDER, we utilized the temporal information within individual gSLIDER RF encodings to develop gSLIDER with Sliding Window Accelerated Temporal resolution (gSLIDER-SWAT). We first validated gSLIDER-SWAT using a classic hemifield checkerboard paradigm, demonstrating robust activation in primary visual cortex even with stimulus frequency increased to the Nyquist frequency of gSLIDER (i.e., TR = block duration). gSLIDER provided ~2× gain in tSNR over traditional SE-EPI. GLM and ICA results suggest improved signal detection with gSLIDER-SWAT's nominal 5-fold higher temporal resolution that was not seen with simple temporal interpolation. Next, we applied gSLIDER-SWAT to investigate the neural networks underlying joy using naturalistic video stimuli. Regions significantly activated during joy included the left amygdala, specifically the basolateral subnuclei, and rostral anterior cingulate, both part of the salience network; the hippocampus, involved in memory; the striatum, part of the reward circuit; prefrontal cortex, part of the executive network and involved in emotion processing and regulation [bilateral mPFC/BA10/11, left MFG (BA46)]; and throughout visual cortex. This proof of concept study demonstrates the feasibility of measuring the networks underlying joy at high resolutions at 3T with gSLIDER-SWAT, and highlights the importance of continued innovation of imaging techniques beyond the limits of standard GE fMRI.

Management of mandibular condylar and subcondylar fractures is heavily debated due to the proximity of important structures and complication risks. This study reviews the outcomes of 4 different treatment approaches: conservative, closed reduction with maxillomandibular fixation, open reduction and internal fixation, and open reduction and internal fixation with maxillomandibular fixation. A retrospective chart review of all patients with a facial fracture seen at a level one trauma center between 2012 and 2022 was performed. Demographics, fracture etiology, fracture type, treating team (plastic surgery versus otolaryngology), surgical approach and intervention, and complications were collected. Most condylar and subcondylar fractures were treated with closed reduction (60 of 103 condylar fractures, 58.25%, and 117 of 168 subcondylar fractures, 69.64%) followed by conservative management (36 of 103 condylar fractures, 34.95%, and 18 of 168 subcondylar fractures 10.71%), open reduction and internal fixation (without maxillomandibular fixation) (4 of 103 condylar fractures, 3.88%, and 16 of 168 subcondylar fractures, 9.52%, respectively), and open reduction and internal fixation with maxillomandibular fixation (3 of 103 condylar fractures, 2.91%, and 17 of 168 subcondylar fractures, 10.12%). Compared with condylar fractures, more subcondylar fractures were treated with open reduction and internal fixation (P<0.001), which led to an increased incidence of postoperative complications (P<0.001). Our findings demonstrate that closed reduction is the most common management of condylar and subcondylar fractures. Future directions include ideal timing for operative management and long-term follow-up for temporomandibular joint complications in closed reduction patients.

Objective: Both the United Nations and the World Health Organization have identified antimicrobial resistance as a significant threat to global health. The Centers for Disease Control and Prevention identified five pediatric respiratory conditions as requiring particular scrutiny in terms of antibiotic stewardship. This study sought to identify strategies used by experienced naturopathic practitioners to treat acute respiratory infections in children. The authors theorize that naturopathic strategies safely fill the gap between watchful waiting and antibiotic prescription, thus reducing the use of antibiotics. Methods: Naturopathic practitioners in Canada, the United States, and Australia with a minimum of 5 years of experience in clinical naturopathic care of children were recruited for a modified Delphi study. A 14-person panel of practitioners was selected to complete a series of four iterative surveys assessing agreement to statements in five domains of knowledge/attitudes, assessment/diagnosis, management, monitoring, and education. Items were deemed to have reached consensus if they reached a predetermined threshold of 70% agreement, or failed to reach a threshold of 40% agreement. Items between these boundaries were modified and retested until either consensus was reached or the four surveys had been completed. Results: Results yielded a large degree of agreement on core naturopathic approaches to the management of acute pediatric respiratory infections, especially lifestyle strategies, including adequate rest and dietary recommendations. The use of vitamins C and D was strongly supported, as were herbs, particularly echinacea and elderberry. Some hydrotherapy and topical applications specific to the individual focus on infection also reached consensus. Results suggested that most respondents, even if they have the authority to prescribe antibiotics, rarely deem it necessary to do so. Conclusion: Findings of this study provide (1) clarity on the role of naturopathic doctors in the management of pediatric health concerns and the stewardship of antibiotics; and (2) initial guidance to less experienced naturopathic practitioners. The findings also identify key priorities for research into the safety and effectiveness of naturopathic interventions to reduce the unnecessary prescribing of antibiotics.

Low self-efficacy is a problem that hinders the success of addicts to leave drugs. Self-talk is one form of intervention that can affect the increase in self-efficacy in drug addicts. This study aims to determine the effectiveness of self-talk in increasing the self-efficacy of clients undergoing rehabilitation programs at BNN Baddoka Makassar. This research is a quasi-experimental one-group pretest-posttest design. This study used 5 subjects who were drug addicts with very low minimum self-efficacy. The measuring instrument used in this study is a self-efficacy scale adapted from Supriyanto and Hendiani, showing a reliability value of 0.905. This study uses nonparametric statistical analysis Wilcoxon test. The results of the study indicate that self-talk is effective in increasing the client's self-efficacy at the BNN Baddoka Makassar rehabilitation center, the results can be seen from the significant difference between the self-efficacy scores of the pretest and posttest (W= 0.00, p=0.015). Subjects in this study experienced an increase in self-efficacy scores. Thus, self-talk can be used to increase the self-efficacy of drug addicts.

Due to the complex interplay of various meteorological phenomena, simulating weather is a challenging and open research problem. In this contribution, we propose a novel physics-based model that enables simulating weather at interactive rates. By considering atmosphere and pedosphere we can define the hydrologic cycle - and consequently weather - in unprecedented detail. Specifically, our model captures different warm and cold clouds, such as mammatus, hole-punch, multi-layer, and cumulonimbus clouds as well as their dynamic transitions. We also model different precipitation types, such as rain, snow, and graupel by introducing a comprehensive microphysics scheme. The Wegener-Bergeron-Findeisen process is incorporated into our Kessler-type microphysics formulation covering ice crystal growth occurring in mixed-phase clouds. Moreover, we model the water run-off from the ground surface, the infiltration into the soil, and its subsequent evaporation back to the atmosphere. We account for daily temperature changes, as well as heat transfer between pedosphere and atmosphere leading to a complex feedback loop. Our framework enables us to interactively explore various complex weather phenomena. Our results are assessed visually and validated by simulating weatherscapes for various setups covering different precipitation events and environments, by showcasing the hydrologic cycle, and by reproducing common effects such as Foehn winds. We also provide quantitative evaluations creating high-precipitation cumulonimbus clouds by prescribing atmospheric conditions based on infrared satellite observations. With our model we can generate dynamic 3D scenes of weatherscapes with high visual fidelity and even nowcast real weather conditions as simulations by streaming weather data into our framework.

Aim: The aim of this study was to evaluate the in vivo antiplasmodial activities of the methanol mesocarp extract of Citrillus lanatus in mice infected with Plasmodium berghei berghei. Materials and Methods: The extract (125, 250, and 500 mg/kg) was administered orally to mice and were assessed in suppressive, repository and curative tests using Chloroquine (5 mg/kg) and Pyrimethamine (1.2 mg/kg) as positive controls. Results: A dose-dependent, significant (p &lt; 0.001) antiplasmodial effect was recorded in the suppressive test relative to control. The extract also demonstrated a dose-dependent, significant (p &lt; 0.01 – 0.001) prophylactic and curative effects when compared to the controls. These antiplasmodial effects of the extract compared favourably with those of the standard drugs. The extract in addition, increased the mean survival times of the infected mice. Conclusions: The methanol mesocarp extract of C. lanatus possesses antiplasmodial activities, thereby corroborating its use in natural medicine in the treatment of malaria.

Purpose: To determine whether practitioner-endorsed and practitioner-suggested items for a patient-centered complementary and alternative medicine (CAM) outcomes questionnaire that became the Self-Assessment of Change instrument (developed under the NIH-NCCAM grant R01AT0033214) differ by CAM discipline.Methods: In-depth semi-structured interviews (n=24), one focus group (n=4), and two group discussions (n=108) were conducted with a convenience sample of CAM practitioners, including naturopathic physicians, Traditional Chinese Medicine practitioners, massage therapists, homeopaths, and energy healers. Qualitative analysis focused on patient outcomes practitioners said they observed in their practice. Outcome items and related comments by practitioners were further distilled for similarities and contrasts by practitioner type. These were then organized into the following pre-existing domains established by the research team: Physical, Cognitive, Emotional, Social, Spiritual, and Whole Person (outcomes that transcend any single outcome domain or construct). Overarching themes that encompassed outcome items were derived when possible.Results: Considerable overlap was observed among practitioners from different CAM disciplines with regard to types of patient outcomes assessed.Conclusions: Practitioner data assembled from multiple sources suggest outcome measures derived from a single CAM tradition are likely to overlap considerably with other CAM systems, with some non-generalizable items possible. These data enhance our understanding of diverse issues in questionnaire development, and suggest the need for a few tailored items to capture outcomes for specific CAM disciplines.

Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms, such as L$_1$/L$_2$ measure, have been shown to model sparsity robustly, based on intuitive attributes that such measures need to satisfy. This is in contrast to computationally cheaper alternatives such as the plain L$_1$ norm. However, present algorithms designed for optimizing the mixed norm L$_1$/L$_2$ are slow and other formulations for sparse NMF have been proposed such as those based on L$_1$ and L$_0$ norms. Our proposed algorithm allows us to solve the mixed norm sparsity constraints while not sacrificing computation time. We present experimental evidence on real-world datasets that shows our new algorithm performs an order of magnitude faster compared to the current state-of-the-art solvers optimizing the mixed norm and is suitable for large-scale datasets.