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Twin Valley Behavioral Healthcare developed safety guidelines for injury-free inpatient management, which were implemented in 2004. The guidelines focus on best practices in the areas of verbal and physical interactions between patients and staff, administration of emergency medication, communication of critical information during precrisis and crisis periods, measurement of safety outcomes, and application of safety rules via policies and use of the agency logo, "Working Smart=Working Safe." Between 2004 and 2008 staff injuries decreased 90%--from 91 to nine injuries. Restraints and seclusions fell by 36%, patient complaints by 37%, and the need for codes for staff to assist in a psychiatric emergency by 25%. [ABSTRACT FROM AUTHOR]

Medical exome sequencing pipelines consist of various preprocessing steps to prioritize credible causal variants before a pathologist or variant curation scientist manually interprets potential findings that are then reported to patients. The variant allele frequency (VAF), reported as the fraction of sequencing reads supporting a variant call, can be used to screen for technical artifacts, yet a specific filtering threshold has yet to be established. A total of 13,122 manually curated variants, sequenced from 289 patients using the Agilent SureSelect Focused Exome enrichment kit at the University of Kentucky Clinical Genomics laboratory from October 2019 to May 2023, were evaluated. Totals of 278 single-nucleotide polymorphisms (SNPs) and 3340 SNPs as technical artifacts are clinically reported. All reported variants had a VAF between 0.33 and 0.63, and 82% (2725/3340) of sequencing artifacts had a VAF of <0.33. It is proposed that removing SNPs in which the VAF is less than approximately 0.30 reduces manual curation time by approximately 20% while capturing all medically relevant variants in medical exome sequencing data sets., Competing Interests: Disclosure Statement None declared., (Copyright © 2025 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Background: The "loss of control" over drug consumption, present in opioid use disorder (OUD) and known as escalation of intake, is well-established in preclinical rodent models. However, little is known about how antecedent behavioral characteristics, such as valuation of hedonic reinforcers prior to drug use, may impact the trajectory of fentanyl intake over time. Moreover, it is unclear if distinct escalation phenotypes may be driven by genetic markers predictive of OUD susceptibility., Methods: Male and female Sprague-Dawley rats (n=63) were trained in a sucrose reinforcement task using a progressive ratio schedule. Individual differences in responsivity to sucrose were hypothesized to predict escalation of fentanyl intake. Rats underwent daily 1-h acquisition sessions for i.v. fentanyl self-administration (2.5 μg/kg; FR1) for 7 days, followed by 21 6-h escalation sessions, then tissue from prefrontal cortex was collected for RNA sequencing and qPCR. Latent growth curve and group-based trajectory modeling were used, respectively, to evaluate the association between sucrose reinforcement and fentanyl self-administration and to identify whether distinct escalation phenotypes can be linked to gene expression patterns., Results: Sucrose breakpoints were not predictive of fentanyl acquisition nor change during escalation, but did predict fentanyl intake on the first day of extended access to fentanyl. Permutation analyses did not identify associations between behavior and single gene expression when evaluated overall, or between our ascertained phenotypes. However, weighted genome correlation network analysis (WGCNA) and gene set enrichment analysis (GSEA) determined several gene modules linked to escalated fentanyl intake, including genes coding for voltage-gated potassium channels, calcium channels, and genes involved in excitatory synaptic signaling. Transcription factor analyses identified EZH2 and JARID2 as potential transcriptional regulators associated with escalated fentanyl intake. Genome-wide association study (GWAS) term categories were also generated and positively associated with terms relating to substance use disorders., Discussion: Escalation of opioid intake is largely distinct from motivation for natural reward, such as sucrose. Further, the gene networks associated with fentanyl escalation suggest that engagement of select molecular pathways distinguish individuals with "addiction prone" behavioral endophenotypes, potentially representing druggable targets for opioid use disorder. Our extended in silico identification of SNPs and transcription factors associated with the "addiction prone" high escalating rats highlights the importance of integrating findings from translational preclinical models. Through a precision medicine approach, our results may aid in the development of patient-centered treatment options for those with OUD.

Objective: The objective of this study was to predict extubation readiness in preterm infants using machine learning analysis of bedside pulse oximeter and ventilator data., Study Design: This is an observational study with prospective recordings of oxygen saturation (SpO 2 ) and ventilator data from infants <30 weeks of gestation age. Research pulse oximeters collected SpO 2 (1 Hz sampling rate) to quantify intermittent hypoxemia (IH). Continuous ventilator metrics were collected (4-5-minute sampling) from bedside ventilators. Data modeling was completed using unbiased machine learning algorithms. Three model sets were created using the following data source combinations: (1) IH and ventilator (IH + SIMV), (2) IH, and (3) ventilator (SIMV). Infants were also analyzed separated by postnatal age (infants <2 or ≥2 weeks of age). Models were compared by area under the receiver operating characteristic curve (AUC)., Results: A total of 110 extubation events from 110 preterm infants were analyzed. Infants had a median gestation age and birth weight of 26 weeks and 825 g, respectively. Of the 3 models presented, the IH + SIMV model achieved the highest AUC of 0.77 for all infants. Separating infants by postnatal age increased accuracy further achieving AUC of 0.94 for <2 weeks of age group and AUC of 0.83 for ≥2 weeks group., Conclusions: Machine learning analysis has the potential to enhance prediction accuracy of extubation readiness in preterm infants while utilizing readily available data streams from bedside pulse oximeters and ventilators., Competing Interests: Declaration of Competing Interest None of the authors have financial ties to products in the study or potential conflicts of interests. This study is supported in part by the National Center for Advancing Translational Sciences (UL1TR001998 to E.G.A.J), NIHNICHD (K23HD109471 to E.G.A.J), and the University of Kentucky College of Medicine Dean's Office. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or University of Kentucky., (Copyright © 2024. Published by Elsevier Inc.)

Background: Adherence to self-administered biologic therapies is important to induce remission and prevent adverse clinical outcomes in Inflammatory bowel disease (IBD). This study aimed to use administrative claims data and machine learning methods to predict nonadherence in an academic medical center test population., Methods: A model-training dataset of beneficiaries with IBD and the first unique dispense of a self-administered biologic between June 30, 2016 and June 30, 2019 was extracted from the Commercial Claims and Encounters and Medicare Supplemental Administrative Claims Database. Known correlates of medication nonadherence were identified in the dataset. Nonadherence to biologic therapies was defined as a proportion of days covered ratio <80% at 1 year. A similar dataset was obtained from a tertiary academic medical center's electronic medical record data for use in model testing. A total of 48 machine learning models were trained and assessed utilizing the area under the receiver operating characteristic curve as the primary measure of predictive validity., Results: The training dataset included 6998 beneficiaries ( n  = 2680 nonadherent, 38.3%) while the testing dataset included 285 patients ( n  = 134 nonadherent, 47.0%). When applied to test data, the highest performing models had an area under the receiver operating characteristic curve of 0.55, indicating poor predictive performance. The majority of models trained had low sensitivity and high specificity., Conclusions: Administrative claims-trained models were unable to predict biologic medication nonadherence in patients with IBD. Future research may benefit from datasets with enriched demographic and clinical data in training predictive models., Competing Interests: The authors have no relevant competing or financial interests to declare., (© The Author(s) 2024. Published by Oxford University Press on behalf of Crohn's & Colitis Foundation.)

Background: Central venous access devices (CVAD) are associated with central line associated bloodstream infection (CLABSI) and venous thromboembolism (VTE). We identified trends in non-intensive care unit (ICU) CVAD utilization, described complication rates, and compared resources between low and high CVAD sites., Methods: We combined data from the Pediatric Health Information System (PHIS) database and surveys from included hospitals. We analyzed 10-year trends in CVAD encounters for non-ICU children between 01/2012-12/2021 and described variation and complication rates between 01/2017-12/2021. Using Fisher's exact test, we compared resources between low and high CVAD users., Results: CVAD use decreased from 6.3% to 3.8% of hospitalizations over 10 years. From 2017-2021, 67,830 encounters with CVAD were identified. Median age was 7 (IQR 2-13) years; 46% were female. Significant variation in CVAD utilization exists (range 1.4-16.9%). Rates of CLABSI and VTE were 4.0% and 3.4%, respectively. Survey responses from 33/41 (80%) hospitals showed 91% had vascular access teams, 30% used vascular access selection guides, and 70% used midline/long peripheral catheters. Low CVAD users were more likely to have a team guiding device selection (100% vs 43%, p = 0.026)., Conclusions: CVAD utilization decreased over time. Significant variation in CVAD use remains and may be associated with hospital resources., Impact: Central venous access device (CVAD) use outside of the ICU is trending down; however, significant variation exists between institutions. Children with CVADs hospitalized on the acute care units had a CLABSI rate of 4% and VTE rate of 3.4%. 91% of surveyed institutions have a vascular access team; however, the services provided vary between institutions. Even though 70% of the surveyed institutions have the ability to place midline/long peripheral catheters, the majority use these catheters less than a few times per month. Institutions with low CVAD use are more likely to have a vascular access team that guides device selection., (© 2024. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Soft tissue tumors (STTs) pose diagnostic and therapeutic challenges due to their rarity, complexity, and morphological overlap. Accurate differentiation between benign and malignant STTs is important to set treatment directions, however, this task can be difficult. The integration of machine learning and artificial intelligence (AI) models can potentially be helpful in classifying these tumors. The aim of this study was to investigate AI and machine learning tools in the classification of STT into benign and malignant categories. This study consisted of three components: (1) Evaluation of whole-slide images (WSIs) to classify STT into benign and malignant entities. Five specialized soft tissue pathologists from different medical centers independently reviewed 100 WSIs, representing 100 different cases, with limited clinical information and no additional workup. The results showed an overall concordance rate of 70.4% compared to the reference diagnosis. (2) Identification of cell-specific parameters that can distinguish benign and malignant STT. Using an image analysis software (QuPath) and a cohort of 95 cases, several cell-specific parameters were found to be statistically significant, most notably cell count, nucleus/cell area ratio, nucleus hematoxylin density mean, and cell max caliper. (3) Evaluation of machine learning library (Scikit-learn) in differentiating benign and malignant STTs. A total of 195 STT cases (156 cases in the training group and 39 cases in the validation group) achieved approximately 70% sensitivity and specificity, and an AUC of 0.68. Our limited study suggests that the use of WSI and AI in soft tissue pathology has the potential to enhance diagnostic accuracy and identify parameters that can differentiate between benign and malignant STTs. We envision the integration of AI as a supportive tool to augment the pathologists' diagnostic capabilities., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background: The focused assessment with sonography in trauma (FAST) is a widely used imaging modality to identify the location of life-threatening hemorrhage in a hemodynamically unstable trauma patient. This study evaluates the role of artificial intelligence in interpretation of the FAST examination abdominal views, as it pertains to adequacy of the view and accuracy of fluid survey positivity., Methods: Focused assessment with sonography for trauma examination images from 2015 to 2022, from trauma activations, were acquired from a quaternary care level 1 trauma center with more than 3,500 adult trauma evaluations, annually. Images pertaining to the right upper quadrant and left upper quadrant views were obtained and read by a surgeon or radiologist. Positivity was defined as fluid present in the hepatorenal or splenorenal fossa, while adequacy was defined by the presence of both the liver and kidney or the spleen and kidney for the right upper quadrant or left upper quadrant views, respectively. Four convolutional neural network architecture models (DenseNet121, InceptionV3, ResNet50, Vgg11bn) were evaluated., Results: A total of 6,608 images, representing 109 cases were included for analysis within the "adequate" and "positive" data sets. The models relayed 88.7% accuracy, 83.3% sensitivity, and 93.6% specificity for the adequate test cohort, while the positive cohort conferred 98.0% accuracy, 89.6% sensitivity, and 100.0% specificity against similar models. Augmentation improved the accuracy and sensitivity of the positive models to 95.1% accurate and 94.0% sensitive. DenseNet121 demonstrated the best accuracy across tasks., Conclusion: Artificial intelligence can detect positivity and adequacy of FAST examinations with 94% and 97% accuracy, aiding in the standardization of care delivery with minimal expert clinician input. Artificial intelligence is a feasible modality to improve patient care imaging interpretation accuracy and should be pursued as a point-of-care clinical decision-making tool., Level of Evidence: Diagnostic Test/Criteria; Level III., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

The superlative strength-to-weight ratio of carbon fibers (CFs) can substantially reduce vehicle weight and improve energy efficiency. However, most CFs are derived from costly polyacrylonitrile (PAN), which limits their widespread adoption in the automotive industry. Extensive efforts to produce CFs from low cost, alternative precursor materials have failed to yield a commercially viable product. Here, we revisit PAN to study its conversion chemistry and microstructure evolution, which might provide clues for the design of low-cost CFs. We demonstrate that a small amount of graphene can minimize porosity/defects and reinforce PAN-based CFs. Our experimental results show that 0.075 weight % graphene-reinforced PAN/graphene composite CFs exhibits 225% increase in strength and 184% enhancement in Young's modulus compared to PAN CFs. Atomistic ReaxFF and large-scale molecular dynamics simulations jointly elucidate the ability of graphene to modify the microstructure by promoting favorable edge chemistry and polymer chain alignment., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

As the demand for electric vehicles (EVs) and autonomous vehicles (AVs) rapidly grows, lower-cost, lighter, and stronger carbon fibers (CFs) are urgently needed to respond to consumers' call for greater EV traveling range and stronger safety structures for AVs. Converting polymeric precursors to CFs requires a complex set of thermochemical processes; a systematic understanding of each parameter in fiber conversion is still, to a large extent, lacking. Here, we demonstrate the effect of carbonization temperature on carbon ring structure formation by combining atomistic/microscale simulations and experimental validation. Experimental testing, as predicted by simulations, exhibited that the strength and ductility of PAN CFs decreased, whereas the Young's modulus increased with increasing carbonization temperature. Our simulations unveiled that high carbonization temperature accelerated the kinetics of graphitic phase nucleation and growth, leading to the decrease in strength and ductility but increase in modulus. The methodology presented herein using combined atomistic/microscale simulations and experimental validation lays a firm foundation for further innovation in CF manufacturing and low-cost alternative precursor development.

This study reports on a statewide survey of medical and behavioral health professionals to advance the knowledge base on the benefits and obstacles to delivering integrated pediatric health care. Surveys distributed in 3 statewide provider networks were completed by 110 behavioral health specialists (BHSs) and 111 primary care physicians (PCPs). Survey content documented their perceptions about key services, benefits, barriers, and needed opportunities related to integrated care. Factor analyses identified 8 factors, and other items were examined individually. We compared responses by specialty group (BHS vs PCP) and integrated care experience (no vs yes). The findings revealed differences across domains by specialty subgroup. In several cases, BHS (vs PCP) respondents, especially those with integrated care experience, reported lower benefits, higher barriers, and fewer resource requests. The implications of these results for enhancing care integration development, delivery, training, and research are discussed along with the study's limitations and empirical literature.

With rising energy concerns, efficient energy conversion and storage devices are required to provide a sustainable, green energy supply. Solar cells hold promise as energy conversion devices due to their utilization of readily accessible solar energy; however, the output of solar cells can be non-continuous and unstable. Therefore, it is necessary to combine solar cells with compatible energy storage devices to realize a stable power supply. To this end, supercapacitors, highly efficient energy storage devices, can be integrated with solar cells to mitigate the power fluctuations. Here, we report on the development of a solar cell-supercapacitor hybrid device as a solution to this energy requirement. A high-performance, cotton-textile-enabled asymmetric supercapacitor is integrated with a flexible solar cell via a scalable roll-to-roll manufacturing approach to fabricate a self-sustaining power pack, demonstrating its potential to continuously power future electronic devices.

The telementoring of surgical procedures is currently achieved via a wired infrastructure that usually requires sophisticated videoconference systems. This project represents the first step in assessing the potential for using handheld computers as a mobile alternative to current telementoring systems. Specifically, this project compares a handheld computer to a standard CRT monitor regarding their capability to accurately display video images from an endoscopic procedure. Video images from two previously recorded endoscopic procedures were transmitted from a standard VCR to: 1) a handheld computer (iPAQ 3670 running Pocket PC) via a wireless LAN and 2) a standard CRT monitor via a wired analog connection. The software-used on the handheld device was custom designed to allow 320 X 240 pixel video images to be broadcast in real time. Twenty-three surgical residents who had completed an endoscopy rotation were randomized to watch one of the two videotaped endoscopic procedures on the hand held computer or on the CRT monitor. After viewing the procedure, a ten-question quiz was used to assess the ability of each participant to recognize several anatomic landmarks. The result of each questionnaire was expressed as the percentage of correct responses. Using a crossover design, each participant then viewed the other videotaped procedure using the alternate device and completed a second quiz. The mean test score for each device was calculated, and these data was analyzed using a Student T test. The observed difference between the mean test score associated with the handheld device (77.93 +/- 11.26) and the CRT monitor (81.30 +/- 12.54) was not statistically significant (p<0.41). In addition, regardless of the device used, scores corresponding to video tape one were significantly higher than those recorded for video tape two (84.35 +/- 9.92 vs. 74.35 +/- 11.61; p < 0.01) All participants were able to recognize anatomic landmarks equally well when viewing broadcasted endoscopic procedures on a handheld display or a standard CRT monitor. Handheld computers may have a role in telementoring residents who are performing endoscopic procedures. Further research is needed to evaluate the integration of handheld devices into telementoring and robotic system to perform surgical procedures.

The glycoside of a new class of phytosteroids has been isolated from Solanum carolinense. The steroidal aglycone (carolinone) is alkylated at C-3 and is identified as C-[(2,4,5-trideoxy-3-keto-4,5-dehydro)-pentulopyranosyl]-(5----3)- (13,14- seco-14 beta,17 alpha-dihydroxy) estrogen. The hydrolytic labile glycosyl moiety is identified as O-(beta-D-glucopyranosyl) (1----1)-[L-(2,6-dideoxy-3-C-methyl)- arabinopyranose]. The linkage of this disaccharide in the steroidal glycoside (carolinoside) is shown to be O-(alpha-pentulopyranosyl)- (1----4)-O-(beta-L-arabinopyranosyl)-(1----1)-D-glucopyranose. Carolinoside occurs at concentrations of 10(-7)-10(-6) M in leaf tissue and was shown to be the host plant specific feeding induction factor for Manduca sexta.