University of North Texas
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Use of an Integrated Collaborative Care Model for Pediatric Mental Health Care
No full textPurpose
This study evaluates the effectiveness of collaborative care models in pediatric psychiatry aimed at addressing the mental health (MH) needs of children and adolescents within the primary care setting. The model integrates primary care clinicians and mental health professionals to provide comprehensive, patient-centered MH care. In addition to reviewing existing literature on collaborative care models, this study aims to describe the unique collaborative care model implemented at the University of North Texas Health Science Center (UNTHSC) Department of Pediatrics and Women’s Health.
Methods
The collaborative care model at UNTHSC involves a team structure comprising Pediatricians, Behavioral Health Care Managers, and Child and Adolescent Psychiatric consultants. Patients eligible for the model receive initial assessments, treatment plans, and routine interventions tailored to their MH needs. The treatment process involves regular case reviews, interventions, and relapse planning, with specific adaptations to align with the needs and resources available within the UNTHSC pediatric department.
Results
Previous studies on integrated care models, including the TEAM UP and Behavioral Health Integration Program, have demonstrated improved treatment effectiveness and patient outcomes. In these models, warm handoffs, increased visits, and enhanced competence in managing MH conditions were observed. Collaborative care has been shown to significantly reduce depression scores, with 55% achieving remission in one study. The findings from the UNTHSC collaborative care model are anticipated to complement existing literature, offering insights into the specific strategies and outcomes achievable within a pediatric primary care setting.
Conclusions
The findings demonstrate the effectiveness of the collaborative care model in treating pediatric MH conditions within primary care settings. Patients enrolled in this model are expected to experience improved treatment outcomes, while healthcare professionals benefit from enhanced satisfaction and coordination of care. This study aims to provide detailed insights into the logistics, fiscal considerations, patient population, and staff involved, including the unique collaborative care model implemented at UNTHSC Department of Pediatrics, enabling the replication of similar collaborative care approaches in pediatric primary care settings to address MH needs comprehensively
Infant Somatic Dysfunction and Breastfeeding LATCH Assessments following Osteopathic Manipulative Treatment
No full textPurpose
Importance: Breastmilk is known to be beneficial for newborns but challenges with latching can provide a significant barrier for breastfeeding. Such challenges may possibly stem from biomechanical and neurological restrictions inhibiting proper latching and sucking in infants. Osteopathic Manipulative Treatment (OMT) may address somatic dysfunctions associated with these restrictions and improve breastfeeding outcomes.
Objective: To evaluate changes in infant somatic dysfunctions after a single OMT treatment and assess correlation with changes in latching using the LATCH assessment tool.
Methods
OMT was performed on 40 participants seen at the For Babies’ Sake clinic in Fort Worth, Texas between October 2022-July 2023. Eligible patients under 6 months old met at least one of the following criteria: feeding difficulty, ankyloglossia, or difficulty maintaining weight. Exclusion criteria included neurologic conditions, cleft lip or palate, lingual frenectomy within 72 hours of visit, hospital admission, and any conditions in which OMT would be contraindicated.
Intervention: During two visits 1 week apart, an Osteopathic physician assessed participants’ somatic dysfunctions in the following regions: OA/condyles, occiput and OM, frontal bones, nasion, maxilla/premaxilla, zygomas/TMJ/temporals, tongue/pterygoids, anterior cervical muscles/hyoid, trunk/viscera, ribs/mediastinum, sacrum, pelvis, hips, knees, and navicular regions. Somatic dysfunctions were rated as 0=no somatic dysfunction, 1=mild, 2=moderate, 3=severe, marked or resistant. Somatic dysfunctions were addressed with treatments including: myofascial release, balanced ligamentous tension, balanced membranous tension, osteopathic cranial manipulative medicine, or vibratory treatment by percussion hammer. Parents completed a standardized LATCH assessment during visits 1 and 2, and responded to a LATCH questionnaire after visit 2. The LATCH questionnaire was shown to be a validated measure of latch, audible swallowing, nipple type, comfort, and hold and results in scores of 0-10, with higher scores indicating better breastfeeding outcomes.
Main Outcomes and Measures: Rated somatic dysfunctions were compared between visit 1 and 2 to assess for statistically significant improvement. Changes in somatic dysfunction and LATCH scores were also assessed for correlation using t-tests.
Results
Mean age was 7.14 weeks (standard deviation=4.44). The following regions showed significant reduction in somatic dysfunction (p<.05) from visits 1 to 2, with mean change values shown here: OA/Condyles: -.75, Tongue/Pterygoids: -0.58, Trunk/viscera: -0.50, and Navicular: -0.38. The mean sum of all somatic dysfunctions was also significantly reduced by 4.15 between visit 1 and 2 (p<.01). The sacrum region was related to LATCH score change, with lower sacrum improvement across visits negatively correlated to more improvement LATCH scores from visits 1-3 (p<.01) and visits 2-3 (p<.05).
Conclusions
These results suggest that a single osteopathic treatment may reduce somatic dysfunction in newborns in multiple body regions. The connection of somatic dysfunctions and LATCH scores needs further research. Though helpful for assessing latch quality, the LATCH assessment does not assess actual infant milk intake or weight gain. Future studies could compare weight gain between OMT treated infants and a control group. It would also be beneficial to replicate this study with additional Osteopathic physicians to determine if improved somatic dysfunction results are repeatable between physicians.American Academy of Osteopath
Making Dementia Blood-based Biomarker Data More Interpretable Through Machine Learning
No full textBackground: Research and data have linked many possible factors that contribute to the cause and progression of Alzeheimer’s disease and dementia. These include traits such as age, gender, ethnicity, and specific blood-based biomarkers. There has been a great deal of work gathering this information, but comparatively less work has been done to consolidate and present it in an easily coherent and comprehensible form. This study aims to use and sort relevant data related to Alzheimer’s disease with machine learning and make it more interpretable through visualization. Methods: The data being analyzed was collected from n = 1705 Hispanic and Non-Hispanic participants with and without cognitive impairment (n = 1328 NC, n = 261 MCI, n = 116 AD) from the HABS-HD cohort. Associated factors measured and considered from each participant included: gender, Hispanic or Non-hispanic ethnicity, education level, and various blood biomarker levels (CRP, FABP3, IL-10, IL-6, Ab40, Ab42, Tau, NFL, PPY, sICAM-1, sVCAM-1, TNF-alpha, GLP-1, Glucagon, PYY, Insulin, HOMA-IR). The Decision Tree classifier tool was applied to the dataset incorporating the scikit-learn Python coding program and the use of multiple parameters in generating the decision tree. The dtreeviz method was also applied in order to provide further visualization to the data. Results: Decision trees were capable of being generated from the given data set of participants based on cognitive status and blood-based biomarkers for Alzheimer’s disease and dementia. Visualized versions of these decision trees were also capable of being successfully generated. The quality and parameters of the decision trees as well as the appearance of the visualization could also be modified. There appears to be some limitations in the Scikit-learn and dtreeviz package that could warrant further troubleshooting or acknowledgement. Conclusion: Based on the results, it appears that visualized decision trees are capable of being generated from a large set of data. Such visualized decision trees compared to the raw data tables or decision trees themselves are much simpler to interpret and recognize patterns. Such patterns could prove useful in determining future areas of study to focus on or affirm already completed studies
Exocrine pancreatic insufficiency following asparaginase-induced pancreatitis in pediatric acute lymphoblastic leukemia patients: A case report
No full textBackground: Asparaginase is an essential agent in the treatment of acute lymphoblastic leukemia (ALL) in pediatric patients. Despite its clinical benefits, patients are at risk for adverse effects including but not limited to asparaginase-associated pancreatitis (AAP). Exocrine pancreatic insufficiency (EPI) is a related condition that involves impaired secretion of digestive enzymes. Case presentations: A 14-year-old male with T cell lymphoblastic leukemia was tolerating chemotherapy well until day 21 of induction therapy when he was brought to the emergency room for generalized weakness and severe abdominal pain. Notably, his appetite had decreased in association with the abdominal pain. Due to his symptoms and recent PEG asparaginase administration, serum lipase was evaluated. Additionally, lipase was evaluated at 1371 U/L, so he was diagnosed with pancreatitis and initially made NPO. Weeks later, he had ongoing difficulties with weight gain and given that his abdominal pain and lipase had improved, the diet was liberalized to a regular diet. Difficulty with adequate intake and weight loss persisted, prompting evaluation of fecal elastase. The results showed a fecal elastase level of less than 10 (normal >/= 201 ug/g), indicating severe exocrine pancreatic insufficiency. The patient was started on pancreatic enzyme replacement therapy (PERT). Fecal elastase was repeated 4 months after EPI diagnosis. While the level had improved slightly (32 ug/g), it still indicated severe pancreatic insufficiency. Five months later, the fecal elastase was re-evaluated again, and it had improved to 131 ug/g, indicating moderate pancreatic insufficiency. The family was instructed to reduce PERT dosing by half with lower fat meals and snacks while monitoring for recurrence of malabsorption symptoms. The patient remained on the lower PERT dosing for three months until he began to have weight loss, abdominal pain, and intermittent loose stools. He was due for an updated fecal elastase level, which had reduced to 85 ug/g. Given the patient’s symptoms and low fecal elastase, PERT was increased to previous dosing using 24,000 UL/capsule. A 6-year-old female patient with preexisting obesity and recently diagnosed Pre-B acute lymphoblastic leukemia presented to the emergency room on day 12 of induction chemotherapy with complaints of severe abdominal pain, nausea, and vomiting. Her symptoms and recent PEG asparaginase administration, warranted serum lipase evaluation. She was diagnosed with pancreatitis due to her supporting symptoms and elevated lipase. Her nutritional intake improved, but the patient continued to experience diarrhea and abdominal pain, prompting evaluation of fecal elastase. Fecal elastase level was 22 ug/g, and PERT was started. Following a week on pancreatic enzyme replacement, the patient’s oral intake had increased. The patient had no complaints of oily stools despite not taking enzymes. She was able to trial off enzyme replacement therapy Conclusion: EPI is an important and often undiagnosed clinical condition with potential deleterious effects on the nutritional status of patients with pancreatitis. It is critical to evaluate for signs of malabsorption, such as oily stools, weight loss, abdominal pain, and bloating in patients with AAP
Assessing the Reliability of Current AI Platforms in Delivering Health Information Related to Crohn Disease, Ulcerative Colitis, and Colorectal Cancer
No full textPurpose
In recent years, the advancements in artificial intelligence (AI) have revolutionized the way we seek and access health information. With more people turning towards AI for answers to their problems, it is important to question how safe it is to rely on AI for answers to health-related issues. We explored the accuracy of ChatGPT—a language model developed by OpenAI—and Gemini—Google’s AI platform—in providing health information related to Crohn disease, ulcerative colitis, and colorectal cancer.
Methods
We generated 10 questions relating to Crohn disease, ulcerative colitis, and colorectal cancer in relation to the social, psychological, economic, and physical aspects that patients with these diseases may face. Each query was remastered for each disease, resulting in 30 total questions which were posed to the two separate AI models. We then regenerated the responses for a total of three times ending up with 90 generated responses per AI model. We also measured the Flesch-Kincaid Readability scores for each response and analyzed the sentiment of the text using natural language processing and computational linguistics. The Centers of Disease Control and Prevention (CDC) recommend that medical information for the public be written at no higher than an eighth-grade reading level. Generated AI responses were evaluated by six gastroenterologist attendings and fellows for accuracy within the context of a patient seeking information. Sets were deemed inappropriate if any of the three responses contained inaccurate or misleading information, based on clinical judgment. Evaluators were blinded to model names and prices. Interrater agreement (94%) and reliability (κ score, 0.87) were ideal. The study was performed in July 2023.
Results
Of the 60 questions posed to the two different AI language models, 45% (n = 27) of the responses were found to be inaccurate. When the two AI models were compared, 43.33% (n = 13) of ChatGPT’s responses were accurate while 46.7% (n = 14) of Gemini’s responses were deemed accurate. ChatGPT also had a 13.20 average Flesch Kincaid Reading grade level and a 31.06 average Flesch Kincaid Readability score. Gemini’s responses received an average Flesch Kincaid Reading grade level of 8.34 and an average Flesch Kincaid Readability score of 56.92. ChatGPT’s average sentiment score was a 1.23 while Gemini’s average score was a 0.92.
Conclusion
While OpenAI’s ChatGPT and Google's Gemini platform can serve as valuable resources for information retrieval, they possess certain limitations when it comes to health-related information for Crohn disease, ulcerative colitis, and colorectal cancer. Importantly, both AI models in the study provided inappropriate responses to common patient questions regarding these conditions. Medical professionals should be aware of these limitations as they may lead to the spread of misinformation in populations with limited access to health care
Every breath you take: Experimentally investigating respiratory responses to hot environments
No full textResearch Appreciation Day Award Winner - School of Biomedical Sciences, 2024 Department of Physiology & Anatomy (Structural Anatomy & Rehabilitation Sciences) Award - 2nd PlaceThe human body loses heat to the environment through two mechanisms: the skin and the respiratory system. Accordingly, it has previously been hypothesized that respiration may play an important role in overall thermoregulatory responses to heat stress. However, previous studies investigating respiratory responses to heat have generally failed to account for variation in humidity levels seen across hot environments (i.e., hot-humid vs. hot-dry conditions). Thus, the goal of this study was to experimentally test for potential differences in respiratory responses to heat stress given variation in air humidity. A mixed-sex sample of human volunteers (5 females, 6 males) were subjected to three different climatic conditions: room temperature (22°C, 50% relative humidity (RH)), hot-dry (44°C, 15% RH), and hot-humid (37°C, 85% RH).Test subjects were exposed to each climatic condition for 45 minutes, with metabolic and respiratory data collected for 30 minutes using a wearable COSMED K-5 metabolic system. Respiratory frequency (Rf, breaths/minute) and oxygen consumption (VO2, ml/minute)were assessed. Results of a repeated-measures ANOVA found a statistically significant difference in Rf values between the climatic conditions (F=5.05, p=0.017). Subsequent Tukey-Kramer multiple-comparison post-hoc test results indicate that participants exhibited significantly higher Rf values in the hot-dry condition (mean=17.498) compared to the room temperature (mean=15.859)and hot-humid (mean=15.764) conditions. In contrast, no significant differences for VO2 consumption between the three climatic conditions (F=2.33, p=0.123) were found. These results indicate that in the hot-dry climatic condition, participants breathe more frequently without increasing the total amount of air inspired (i.e., taking more frequent but shallower breaths). These results are largely consistent with findings of previous studies that have demonstrated similar physiological responses to heat stress. Furthermore, our study highlights the existence of differential respiratory responses in hot-dry vs. hot-humid conditions, suggesting that humidity may play an important role in mediating respiratory responses to heat stress. Additional research into the impacts of humidity on respiratory function is thus warranted.National Science Foundation #2020506 (Cowgill), #2020096 (Ocobock), #2203808 (Cho), #2020715 (Maddux
Short Peptides based on the conserved regions of MIEN1 protein exhibit anti-cancer activity by targeting the MIEN1 Signaling Pathway
No full textMigration and invasion enhancer 1 (MIEN1) overexpression characterizes several cancers and facilitates cancer cell migration and invasion. Leveraging conserved ITAM and prenylation motifs within MIEN1, we identified potent anti-cancer peptides. Among them, bioactive peptides LA3IK and RP-7 induced pronounced transcriptomic and protein expression changes at sub-IC50 concentrations. The peptides effectively inhibited genes and proteins driving cancer cell migration, invasion, and EMT pathways, concurrently suppressing EGF-induced NF-kappaB nuclear translocation in metastatic breast cancer cells. Specifically, peptides targeted the same signal transduction pathway initiated by MIEN1. Molecular docking and circular dichroism spectroscopy indicated the formation of MIEN1-peptide complexes. The third-positioned isoleucine in LA3IK and CVIL motif in RP-7 were crucial for inhibiting breast cancer cell migration. This is evident from the limited migration inhibition observed when MDA-MB-231 cells were treated with scrambled peptides LA3IK SCR and RP-7 SCR. Additionally, LA3IK and RP-7 effectively suppressed tumor growth in an orthotopic breast cancer model. Notably, mice tolerated high peptide doses of up to 90 mg/Kg well, surpassing significantly lower doses of 5 mg/Kg intravenously (iv) and 30 mg/Kg intraperitoneally (ip) used in both in vivo pharmacokinetic studies and orthotopic mouse model assays. D-isomers of LA3IK and RP-7 showed enhanced anti-cancer activity compared to their L-isomers. D-LA3IK remained stable in mouse plasma for 24 h with 75% remaining, exhibiting superior pharmacokinetic properties over D/L-RP-7. In summary, our findings mark the first report of short peptides based on MIEN1 protein sequence capable of inhibiting cancer signaling pathways, effectively impeding cancer progression both in vitro and in vivo
Early psychosis structural abnormalities in the midbrain correlate with positive and negative symptoms
No full textEarly psychosis (EP) is a critical period in developing psychotic disorders. During the EP period, timely intervention strategies can effectively mitigate symptoms of psychotic disorders. A primary target in current therapeutics for psychotic disorders is the dopaminergic system; however, current therapeutics are often inadequate in treating the advanced stages of psychotic disorders. Currently, there are hypotheses that the advent of psychotic disorders are alterations in the brain’s structure and functional connectivity leading to aberrant network organization. Given the prominence of the midbrain in synthesizing dopamine and being a hub in the circuitry of dopaminergic function in this study, we will quantify the structural properties of the midbrain using a publicly available dataset of EP subjects. The Human Connectome Project (HCP) is a global effort to determine human brain connectivity objectively. Specifically, there is a subset where the focus is on subjects within five years of their first psychotic episode, which is the focus of this study. In this project, we employ various computational tools (including FSL, ANTs, packages of Python and RStudio, etc.) to acquire relevant measures of brain structure in EP. Specifically, we performed gross anatomical analysis of brain volumetrics, regional microstructural analysis, and correlation analysis between brain and behavior indices. First, Deformation-based Morphometry (DBM) is a test performed on T1 MRI scans to determine brain volumes. DBM measures shape movements to align individuals with a registration template using the Jacobian determinant (JD), whereas a standard VBM focuses on voxel intensity differences between individuals and the template. In our results, DBM revealed mild changes around the midbrain between EP and healthy controls. Second, we analyzed Diffusion Tensor Imaging (DTI) data by obtaining indices such as Fractional Anisotropy (FA), Axial Diffusivity (AD), and Mean Diffusivity (MD). A midbrain mask was created based on Freesurfer atlas ROI labels, allowing a seed-based analysis centered around the midbrain. Group differences were estimated using the Welch two-group t-tests on ROI means of JD, FA, AD, MD, and midbrain volumes. Interestingly, group differences in JD and midbrain volumes were insignificant, but differences were more pronounced for FA, AD, and MD. Third, we employed Tract-Based Spatial Statistics (TBSS) to determine microstructural changes in white matter tracts. TBSS successfully captured structural variabilities within the midbrain, aligning with our study’s expectations, in addition to moderate changes in other main white matter tracts, such as corticospinal tract and cingulum, suggesting an initiation of altered brain connectivity emanating from alterations in the midbrain or a putative reorganization of dopaminergic circuitry. Fourth, correlations between these quantities in the EP group and behavioral scores (i.e., PANSS and CAINS tests) were explored. It is found that midbrain volume noticeably correlates with the Cognitive score of PANSS and JD, strongly correlates with AD and MD; FA correlates with the Negative score of PANSS, and MD correlates with the Positive score of PANSS. Overall, these findings contribute to understanding midbrain involvement in early psychosis and underscore the interest for further investigation in this research path
A Study on the Utility of Blood-Based Biomarkers for Alzheimer’s Disease in Predicting Cerebral Amyloid among Individuals with Down Syndrome
No full textResearch Appreciation Day Award Winner - Texas College of Osteopathic Medicine, 2024 Student Research Award - 1st PlacePurpose: Down Syndrome (DS) is one of the most common genetic disorders. Individuals with DS show Alzheimer’s Disease (AD)-related neuropathology at a younger age, placing them at an increased risk for developing dementia. Limited research has explored the relationship between blood-based biomarkers and cerebral amyloid positivity. Our study examines the association between blood-based biomarkers and the presence of cerebral amyloid detected by PET scans in participants with DS. Methods: Data were analyzed on a cohort of n=368 participants with DS aged 30 and above. Proteomic assays of amyloid beta 40 (Aꞵ40) and 42 (Aꞵ42), total tau, neurofilament light (NfL), and phosphorylated tau181 (pTau181) were performed on plasma samples using Single Molecule Array (Simoa). Cerebral amyloid levels were obtained through PET Amyloid imaging. Covariates included age, gender, and presence of at least one APOε4 allele. Correlations were run using R statistical software. Random Forest analyses were conducted to examine the link between the select biomarkers and cerebral amyloid SUVR levels. Logistic regressions were also used in examining the utility of AD biomarkers in detecting cerebral amyloid positivity. Significance was set at p<0.05. Results: The biomarkers that significantly correlated with cerebral amyloid SUVR levels were Aꞵ42 (p=0.020), total tau (p<0.001), NfL (p<0.001), and pTau181 (p<0.001). There was no significant correlation between Aꞵ40 (p=0.888) and levels of cerebral amyloid. Regression analysis demonstrated a high correlation (R2 = 0.956) between the biomarkers and cerebral amyloid positivity. Our profile was accurate in detecting the presence of cerebral amyloid, yielding an area under the curve (AUC) of 0.9984, a positive predictive value (PPV/Precision) of 0.9571, sensitivity of 0.9853, and specificity of 0.9404. Conclusion: Our findings demonstrate that our proteomic profile consisting of the biomarkers Aꞵ40, Aꞵ42, total tau, NfL, and pTau181, and select demographics was highly accurate in predicting the presence of cerebral amyloid in our cohort. Having a less invasive and less costly screening tool, such as a blood-based biomarker profile, will allow for earlier detection of dementia in individuals who are at risk. Future research should explore these findings in the context of a larger cohort for increased generalizability.NIH/NIA U19AG06805