Exploring the integration of artificial intelligence in the sports tourism industry

Artificial intelligence (AI) has advanced from a theoretical concept to a practical application thanks to the quick development of computer science and information technology. AI, a fundamental component of contemporary civilization, has a growing impact on all facets of daily life, including sports training. Artificial intelligence (AI) can be viewed as a supporting technology that specifically supports athletes' physical education training through methods like data analysis and simulation of training scenarios. Even though research on AI is still in its early stages, it is important to investigate how it may be used in sports training becausethis cutting-edge technology could in some ways make it easier for individuals to train physically. This study begins by reviewing the prior work on AI applications.In, this study investigates three specific situations of AI application in sports training and describes the key concepts based on the core idea and related research findings of AI. This study focuses on the close connection between artificial intelligence (AI) and physical education instruction and emphasises the benefits of AI, such as its use, ease, and innovation. This study creates the appropriate information data interface mode based on the integration of the sports tourist sector and the culture industry. (AU)

Validating core therapeutic targets for osteoporosis treatment based on integrating network pharmacology and informatics.

OBJECTIVE: Our goal was to find metabolism-related lncRNAs that were associated with osteoporosis (OP) and construct a model for predicting OP progression using these lncRNAs. METHODS: The GEO database was employed to obtain gene expression profiles. The WGCNA technique and differential expression analysis were used to identify hypoxia-related lncRNAs. A Lasso regression model was applied to select 25 hypoxia-related genes, from which a classification model was created. Its robust classification performance was confirmed with an area under the ROC curve close to 1, as verified on the validation set. Concurrently, we constructed a ceRNA network based on these genes to unveil potential regulatory processes. Biologically active compounds of STZYD were identified using the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP) database. BATMAN was used to identify its targets, and we obtained OP-related genes from Malacards and DisGeNET, followed by identifying intersection genes with metabolism-related genes. A pharmacological network was then constructed based on the intersecting genes. The pharmacological network was further integrated with the ceRNA network, resulting in the creation of a comprehensive network that encompasses herb-active components, pathways, lncRNAs, miRNAs, and targets. Expression levels of hypoxia-related lncRNAs in mononuclear cells isolated from peripheral blood of OP and normal patients were subsequently validated using quantitative real-time PCR (qRT-PCR). Protein levels of RUNX2 were determined through a western blot assay. RESULTS: CBFB, GLO1, NFKB2 and PIK3CA were identified as central therapeutic targets, and ADD3-AS1, DTX2P1-UPK3BP1-PMS2P11, TTTY1B, ZNNT1 and LINC00623 were identified as core lncRNAs. CONCLUSIONS: Our work uncovers a possible therapeutic mechanism for STZYD, providing a potential therapeutic target for OP. In addition, a prediction model of metabolism-related lncRNAs of OP progression was constructed to provide a reference for the diagnosis of OP patients.

Pan-genome mediated therapeutic target mining in Kingella kingae and inhibition assessment using traditional Chinese medicinal compounds: an informatics approach.

Kingella kingae causes bacteremia, endocarditis, osteomyelitis, septic arthritis, meningitis, spondylodiscitis, and lower respiratory tract infections in pediatric patients. Usually it demonstrates disease after inflammation of mouth, lips or infections of the upper respiratory tract. To date, therapeutic targets in this bacterium remain unexplored. We have utilized a battery of bioinformatics tools to mine these targets in this study. Core genes were initially inferred from 55 genomes of K. kingae and 39 therapeutic targets were mined using an in-house pipeline. We selected aroG product (KDPG aldolase) involved in chorismate pathway, for inhibition analysis of this bacterium using lead-like metabolites from traditional Chinese medicinal plants. Pharmacophore generation was done using control ZINC36444158 (1,16-bis[(dihydroxyphosphinyl)oxy]hexadecane), followed by molecular docking of top hits from a library of 36,000 compounds. Top prioritized compounds were ZINC95914016, ZINC33833283 and ZINC95914219. ADME profiling and simulation of compound dosing (100 mg tablet) was done to infer compartmental pharmacokinetics in a population of 300 individuals in fasting state. PkCSM based toxicity analysis revealed the compounds ZINC95914016 and ZINC95914219 as safe and with almost similar bioavailability. However, ZINC95914016 takes less time to reach maximum concentration in the plasma and shows several optimal parameters compared to other leads. In light of obtained data, we recommend this compound for further testing and induction in experimental drug design pipeline.Communicated by Ramaswamy H. Sarma.

The discovery of the natural compound Boeravinone-C as a potential antiobesity drug candidate targeting pancreatic lipase using chemo-informatics-based approaches.

Obesity is a metabolic disorder distinguished by excess fat deposition in fatty tissues. Pancreatic lipase is one of the promising drug targets for treating obesity due to its critical role in the hydrolysis of triglycerides into mono-glycerides and free fatty acids. Due to unsatisfactory results and severe side effects of the current drugs available for treating obesity, there is an urgent need to identify novel therapeutic options. Boerhaavia diffusa is one of the widely known species of flowering plant commonly known as Punamava. Extracts from Punamava plants have been widely used in treating countless ailments in traditional medicine. Recently, multiple reports demonstrated the potential antiobesity activity of B. diffusa plant extracts. In this scenario, we have evaluated numerous reported B. diffusa against pancreatic lipase drug targets to identify which reported phytochemicals to have the most promising potential to act as an inhibitor for pancreatic lipase using computational approaches. All the twenty-four phytochemicals from Boerhaavia diffusa were identified as significantly strong binders with a range of binding energies between -6.0 to -8.0 Kcal/mol inside the pancreatic lipase active binding site. On the other hand, we calculated 2D Quantitative Structure-Activity Relationship (QSAR) molecular descriptor properties adhered to Lipinski's rule of five. Between twenty-four phytochemicals evaluated, Boeravinone-C, with a range binding energy of -8.0 Kcal/mol, was discovered as the best lead-like molecule, compared to marketed Orlistat, which has shown -5.6 Kcal/mol of binding energy. Conclusively, Boeravinone-C from B. diffusa extract showed promising inhibitory potential against pancreatic lipase worth further evaluation.

Influence of Multimorbidity on New Treatment Initiation and Achieving Target Disease Activity Thresholds in Active Rheumatoid Arthritis: A Cohort Study Using the Rheumatology Informatics System for Effectiveness Registry.

OBJECTIVE: To determine whether multimorbidity is associated with treatment changes and achieving target disease activity thresholds in patients with active rheumatoid arthritis (RA). METHODS: We conducted a retrospective cohort study of adults with active RA within the Rheumatology Informatics System for Effectiveness (RISE) registry. Multimorbidity was measured using RxRisk, a medication-based index of chronic disease. We used multivariable logistic regression models to assess the associations of multimorbidity with the odds of initiating a new disease-modifying antirheumatic drug (DMARD) in active RA, and among those initiating a new DMARD, the odds of achieving low disease activity or remission. RESULTS: We identified 15,626 patients using the Routine Assessment of Patient Index Data 3 (RAPID3) cohort and 5,733 patients using the Clinical Disease Activity Index (CDAI) cohort. All patients had active RA, of which 1,558 (RAPID3) and 834 (CDAI) initiated a new DMARD and had follow-up disease activity measures. Patients were middle aged, female, and predominantly White, and on average received medications from 6 to 7 RxRisk categories. Multimorbidity was not associated with new DMARD initiation in active RA. However, a greater burden of multimorbidity was associated with lower odds of achieving treatment targets (per 1-unit RxRisk: RAPID3 cohort odds ratio [OR] 0.95 [95% confidence interval (95% CI) 0.91, 0.98]; CDAI cohort OR 0.94 [95% CI 0.90, 0.99]). Those with the highest burden of multimorbidity had the lowest odds of achieving target RA disease activity (RAPID3 cohort OR 0.54 [95% CI 0.34, 0.85]; CDAI cohort OR 0.65 [95% CI 0.37, 1.15]). CONCLUSION: These findings from a large, real-world registry illustrate the potential impact of multimorbidity on treatment response and indicate that a more holistic management approach targeting multimorbidity may be needed to optimize RA disease control in these patients.

Telemedicine informatics application for nutritional support surveillance of instutionalized persons in nursing homes from a hospital pharmacy service.

INTRODUCTION: Institutionalized patients who require nutrition support regularly visit the Unit of Nutrition Support of the Hospital Pharmacy  Service. During these visits, prior to establishing a nutrition regime and  followup scheme, an initial nutritional status assessment is performed.  Telemedicine and Telepharmacy have expanded in recent years for remote  monitoring of institutionalized persons. OBJECTIVE: To evaluate the implementation of a Telemedicine informatics application for nutritional support surveillance of instutionalized  persons in nursing homes from a hospital pharmacy service. Method: A multidisciplinary team led by the Hospital Pharmacy Service was  created. Data of institutionalized persons in nursing homes needing artificial  nutritional support was extracted from the SILICON prescription system and  the internal ecords of the hospital pharmacy service. Nursing homes were  selected on the basis of their previous experience using the Telemedicine  informatics application TELEA. The following nutritional  support variables were  assessed: score on Mini-Nutritional Assessment questionnaire; a 24-h  food record; pressure ulcer control; and laboratory parameters. The existing  information flow between nursing homes and hospital specialists was analyzed.  The functionalities available on TELEA were considered. RESULTS: In 2021, over 300 institutionalized persons from 28 nursing homes  were incluided for nutritional support surveillance program of the hospital  pharmacy service. The project was implemented in two nursing homes serving  38 patients, although only 13 were involved in the nutrition surveillance  program of the Nutrition Support Unit. Nutritional status assessment and  nutritional support surveillance reports were adapted to the Telemedicine  informatics application. Paper reports were replaced  with electronic data or  online questionnaires available on the informatics application. An information  flow protocol was established. An instantaneous messaging and alert system  was activated, which allowed continuous communication. Some Telepharmacy  requests were categorized as preferential when the clinical status of the patient  so required. All the information generated during the nutritional status  assessment and nutritional support surveillance process was integrated into  the electronic medical history of each patient. CONCLUSIONS: TELEA-based nutritional support surveillance facilitates the  continuum of care by enabling direct communication between nursing homes  and secondary care for institutionalized persons. This model makes it possible  to record nutrition-related data on the electronic medical history of patients  through a Telepharmacy process. This model also eliminates paper  prescriptions and medical reports, and unnecessary travels. A nutritional status  profile should also be made available to facilitate nutrition surveillance in institutionalized persons with chronic diseases. That  would be the first step for a new integrated healthcare informatics application  for frail/polymorbid elderly patients.

Introducción: Los pacientes institucionalizados que requieren soporte  nutricional artificial acuden de forma periódica a las consultas de la Unidad de  Soporte Nutricional del Servicio de Farmacia. En ellas se realiza una  valoración nutricional inicial, a partir de la cual se establece la pauta nutricional  y el plan de seguimiento. La Telemedicina y la Telefarmacia se han  expandido en los últimos años para la monitorización remota de personas  institucionalizadas. OBJETIVO: Evaluar la implementación de una aplicación informática de Telemedicina para la vigilancia del soporte nutricional de personas  nstitucionalizadas en residencias de ancianos desde un servicio de farmacia hospitalaria.Método: Se formó un equipo multidisciplinar liderado por el Servicio de Farmacia. Los datos de pacientes institucionalizados que requieren soporte nutricional artificial se obtuvieron del programa SILICON y de los  registros internos del Servicio de Farmacia. Se eligieron las primeras  residencias candidatas según la experiencia previa en el manejo de la  aplicación informática de asistencia domiciliaria. Se analizaron llas variables de  soporte nutricional necesarias para el seguimiento nutricional: Mini  Nutritional Assessment, recordatorio de ingestas de las últimas 24 horas,  control de úlceras por presión y parámetros analíticos. Se analizó el flujo de  información existente entre las residencias sociosanitarias y la atención  hospitalaria y se valoraron las opciones disponibles a través de la plataforma  tecnológica de asistencia domiciliaria. RESULTADOS: El Servicio de Farmacia realizó seguimiento nutricional a más de  300 pacientes institucionalizados en 28 residencias sociosanitarias en el año  2021. El proyecto se implantó en dos residencias sociosanitarias que cuentan  con 38 pacientes institucionalizados, aunque solo 13 pacientes estaban en  seguimiento por la Unidad de Soporte Nutricional. Todos los registros  generados en la valoración y seguimiento nutricional se adecuaron a la  aplicación informática de asistencia domiciliaria, se cambiaron los registros en  papel por información incluida en la plataforma o cuestionarios online  facilitados a través de la misma. Además, se protocolizó el flujo de información  generada y se activó un sistema de mensajería con alertas que  permite una comunicación continua. En caso de que la situación clínica  del  paciente lo requiera se puede programar una teleconsulta preferente.Toda la  información generada en el proceso de valoración y seguimientonutricional de  cada paciente se integró en la historia clínica electrónica. CONCLUSIONES: El seguimiento nutricional a través de la aplicación informática de asistencia domiciliaria facilita la continuidad asistencial por el establecimiento de una comunicación directa entre las residencias  sociosanitarias y la atención hospitalaria, permitiendo la integración de la  información nutricional de los pacientes en la historia clínica electrónica  mediante un proceso de Telefarmacia. Se han eliminado las prescripciones en  papel, informes clínicos impresos y los desplazamientos innecesarios. El  desarrollo de este perfil podría ser extensible al seguimiento nutricional de  pacientes con patologías crónicas, y ser el precedente de un nuevo programa  de cuidado integral del paciente anciano frágil o pluripatológico.

Rapid identification of chemical components in Zhizi Baipi decoction by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with a novel informatics UNIFI platform.

Zhizi Baipi decoction is a classic traditional Chinese medicine formula for the treatment of jaundice and various liver diseases. The chemical components of Zhizi baipi decoction were not clear resulting of the paucity of relevant studies, which hindered the elucidation of the pharmacological mechanism, and the comprehensive development and utilization of Zhizi baipi decoction in clinical. In this study, ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry combined with the UNIFI natural product information analysis platform was used to rapidly analyze and identify the chemical components in Zhizi baipi decoction. A total of 122 chemical components, including 53 flavonoids, 16 alkaloids, 25 terpenoids, five phenylpropanoids, 14 organic acids, and seven others, were identified from Zhizi baipi decoction. These compounds may be the active components of Zhizi baipi decoction. The method established in this study can systematically, rapidly, and accurately resolve the chemical components in Zhizi baipi decoction, which lays the foundation for further establishment of the pharmacodynamic substance basis and quality control of Zhizi baipi decoction.

Engaging the disability community in informatics research: rationales and practical steps.

As the informatics community grows in its ability to address health disparities, there is an opportunity to expand our impact by focusing on the disability community as a health disparity population. Although informaticians have primarily catered design efforts to one disability at a time, digital health technologies can be enhanced by approaching disability from a more holistic framework, simultaneously accounting for multiple forms of disability and the ways disability intersects with other forms of identity. The urgency of moving toward this more holistic approach is grounded in ethical, legal, and design-related rationales. Shaped by our research and advocacy with the disability community, we offer a set of guidelines for effective engagement. We argue that such engagement is critical to creating digital health technologies which more fully meet the needs of all disabled individuals.

Data-driven approaches to care delivery: Actionable informatics in the DoD's primary care behavioral health program.

INTRODUCTION: Transforming administrative health care data into meaningful metrics has been critical to the implementation of the Department of Defense's Primary Care Behavioral Health (PCBH) program. METHODS: Data from clinical encounters with PCBH providers are used to develop metrics of program performance collaboratively. Metrics focus on describing the PCBH program and patients, provider fidelity to the model, and provider performance. These metrics form two key deliverables: a monitoring dashboard for program managers and a training dashboard for expert trainers conducting site visits. RESULTS: Behavioral health consultants (BHCs) conducted nearly 200,000 encounters with more than 100,000 unique patients in fiscal year 2019 at more than 170 locations in 6 countries and 37 states. Administrative data derived from these encounters were used to create a variety of metrics that describe practice and performance at both the provider and program levels. These metrics are delivered through a variety of analytic products to stakeholders who use that information to make data-driven decisions about program direction and provider training. DISCUSSION: We discuss examples of program management decisions and expert trainer actions based on these dashboards, highlighting the benefits of continued collaboration between analysts and program managers. Specifically, excerpts from several dashboards illustrate how penetration and productivity metrics yield specific, tailored action plans to improve care delivery and provider performance. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Burnout trauma both? Identifying and addressing needs during COVID-19 through informatics.

In this brief article, the author notes that discussion of work/life integration have become increasingly com mon at her institution, as school-age children regularly make appearances in Zoom meetings, and team mem bers have to shift between dynamic roles in their work and family lives throughout the day. Talk of burnout abounds-and she often find herself wondering if in fact they are only experiencing burnout as an occupational phenomenon, or whether it is a compounded experi ence of burnout and the emotional exhaustion of collective trauma and grief. Even when concerns dissipate about COVID's relentless spread and severe disease, there is no doubt that we will have lingering mental health hangovers from the psychologi cal impacts of the past year; we must be pre pared to leverage informatics and technology to stem the tide. We will navigate through these uncharted waters through thoughtful and effective leadership that culti vates community and a work environment that is with aligned with our organizational and personal values; and as the past year has demonstrated, it is evi dent that technology and informatics will play a piv otal role in the future of work. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Pharmacoinformatics and molecular dynamics simulation-based phytochemical screening of neem plant (Azadiractha indica) against human cancer by targeting MCM7 protein.

Minichromosome maintenance complex component 7 (MCM7) belongs to the minichromosome maintenance family that is important for the initiation of eukaryotic DNA replication. Overexpression of the MCM7 protein is relative to cellular proliferation and responsible for aggressive malignancy in various cancers. Mechanistically, inhibition of MCM7 significantly reduces the cellular proliferation associated with cancer. To date, no effective small molecular candidate has been identified that can block the progression of cancer induced by the MCM7 protein. Therefore, the study has been designed to identify small molecular-like natural drug candidates against aggressive malignancy associated with various cancers by targeting MCM7 protein. To identify potential compounds against the targeted protein a comprehensive in silico drug design including molecular docking, ADME (Absorption, Distribution, Metabolism and Excretion), toxicity, and molecular dynamics (MD) simulation approaches has been applied. Seventy phytochemicals isolated from the neem tree (Azadiractha indica) were retrieved and screened against MCM7 protein by using the molecular docking simulation method, where the top four compounds have been chosen for further evaluation based on their binding affinities. Analysis of ADME and toxicity properties reveals the efficacy and safety of the selected four compounds. To validate the stability of the protein-ligand complex structure MD simulations approach has also been performed to the protein-ligand complex structure, which confirmed the stability of the selected three compounds including CAS ID:105377-74-0, CID:12308716 and CID:10505484 to the binding site of the protein. In the study, a comprehensive data screening process has performed based on the docking, ADMET properties, and MD simulation approaches, which found a good value of the selected four compounds against the targeted MCM7 protein and indicates as a promising and effective human anticancer agent.

Detection of camellia oil adulteration using chemometrics based on fatty acids GC fingerprints and phytosterols GC-MS fingerprints.

The fatty acid, squalene, and phytosterols, coupled to chemometrics were utilized to detect the adulteration of camellia oil (CAO) with palm superolein (PAO), refined olive oil (ROO), high oleic- sunflower oil (HO-SUO), sunflower oil (SUO), corn oil (COO), rice bran oil (RBO), rice oil (RIO), peanut oil (PEO), sesame oil (SEO), soybean oil (SOO), and rapeseed oil (RAO). CAO was characterized with higher triterpene alcohols, thus differentiated from other vegetable oils in principle component analysis (PCA). Using partial least squares-discriminant analysis (PLS-DA), CAO adulterated with PAO, ROO, HO-SUO, SUO, COO, RBO, RIO, PEO, SEO, SOO, RAO (5%-100%, w/w), could be classified, especially higher than 92.31% of the total discrimination accuracy, at an adulterated ratio above 30%. With less than 22 potential key markers selected by the variable importance in projection (VIP), the optimized PLS models were confirmed to be accurate for the adulterated level prediction in CAO.

Chemometrics-based aroma profiling for revealing origin, roasting indices, and brewing method in coffee seeds and its commercial blends in the Middle East.

Coffee is among the most consumed beverages worldwide. The present study reports on the aroma composition associated with coffee seeds brewing. Aroma of authentic coffee specimens of Coffea arabica and C. robusta alongside with typical products consumed in the Middle East were analyzed using HS-SPME coupled with GC-MS. In addition, multivariate data analysis (MVA) was employed. Results revealed for 102 volatiles with a distinct aroma profile between the different brewing methods. Infusion demonstrated higher esters level, while decoction and maceration were more abundant in sesquiterpenes and terpene alcohols, respectively. Besides, heat-induced products, i.e., 4-vinyl guaiacol was identified as potential roasting index in instant coffee and roasted C. robusta brews. Blending with cardamom further masked the smoky odor of such compounds by its fragrant terpinyl acetate. This study provides the first report on the chemical sensory attributes of Middle Eastern coffee blends and further reveal for the impact of brewing, roasting on its aroma composition.

HPLC-DAD fingerprints combined with chemometric techniques for the authentication of plucking seasons of Laoshan green tea.

Laoshan green teas plucked in summer and autumn were measured by high performance liquid chromatography-diode array detector (HPLC-DAD). After baseline correction, the fingerprints data were resolved by multivariate curve resolution-alternating least squares (MCR-ALS) and a total of 57 components were acquired. Relative concentrations of these components were afterwards applied to distinguish plucking seasons using principal component analysis (PCA), support vector machines (SVM) and partial least squares-discriminant analysis (PLS-DA). For both SVM and PLS-DA models, the total recognition rates of training set, cross-validation and testing set were 100%, 91.3% and 100%, respectively. Besides, three variable selection methods were employed to determine characteristic components for the authentication of summer and autumn teas. Results showed that PLS-DA model based on three characteristic components selected by VIP possesses identical predictive ability as the original model. This study demonstrated that our proposed strategy is competent for the authentication of plucking seasons of Laoshan green tea.

Weighted multiscale support vector regression for fast quantification of vegetable oils in edible blend oil by ultraviolet-visible spectroscopy.

Weighted multiscale support vector regression combined with ultraviolet-visible (UV-Vis) spectra for quantitative analysis of edible blend oil is proposed. In the approach, UV-Vis spectra of the training set are decomposed into a certain number of intrinsic mode functions (IMFs) and a residue by empirical mode decomposition (EMD) at first. Then support vector regression (SVR) sub-models are built on each IMF and residue. For prediction set, the spectra are decomposed as done on the training set and the final predictions are obtained by integrating SVR sub-model predictions by weighted average. The weight of the sub-model is the reciprocal of the fourth power of the root mean square error of cross-validation (RMSECV). For predicting peanut oil in binary blend oil and sesame oil in ternary blend oil, the proposed method has superiority in root mean square error of prediction (RMSEP) and correlation coefficient (R) compared with SVR and partial least squares (PLS).

Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury.

BACKGROUND: Efforts to minimize harms from opioid drug interactions may be hampered by limited evidence on which drugs, when taken concomitantly with opioids, result in adverse clinical outcomes. OBJECTIVE: To identify signals of opioid drug interactions by identifying concomitant medications (precipitant drugs) taken with individual opioids (object drugs) that are associated with unintentional traumatic injury DESIGN: We conducted pharmacoepidemiologic screening of Optum Clinformatics Data Mart, identifying drug interaction signals by performing confounder-adjusted self-controlled case series studies for opioid + precipitant pairs and injury. SETTING: Beneficiaries of a major United States-based commercial health insurer during 2000-2015 PATIENTS: Persons aged 16-90 years co-dispensed an opioid and ≥1 precipitant drug(s), with an unintentional traumatic injury event during opioid therapy, as dictated by the case-only design EXPOSURE: Precipitant-exposed (vs. precipitant-unexposed) person-days during opioid therapy. OUTCOME: Emergency department or inpatient International Classification of Diseases discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to generate confounder adjusted rate ratios. We accounted for multiple estimation via semi-Bayes shrinkage. RESULTS: We identified 25,019, 12,650, and 10,826 new users of hydrocodone, tramadol, and oxycodone who experienced an unintentional traumatic injury. Among 464, 376, and 389 hydrocodone-, tramadol-, and oxycodone-precipitant pairs examined, 20, 17, and 16 (i.e., 53 pairs, 34 unique precipitants) were positively associated with unintentional traumatic injury and deemed potential drug interaction signals. Adjusted rate ratios ranged from 1.23 (95 % confidence interval: 1.05-1.44) for hydrocodone + amoxicillin-clavulanate to 4.21 (1.88-9.42) for oxycodone + telmisartan. Twenty (37.7 %) of 53 signals are currently reported in a major drug interaction knowledgebase. LIMITATIONS: Potential for reverse causation, confounding by indication, and chance CONCLUSIONS: We identified previously undescribed and/or unappreciated signals of opioid drug interactions associated with unintentional traumatic injury. Subsequent etiologic studies should confirm (or refute) and elucidate these potential drug interactions.

Recommendations for the Nonpharmacological Treatment of Apathy in Brain Disorders.

Apathy is a common neuropsychiatric syndrome observed across many neurocognitive and psychiatric disorders. Although there are currently no definitive standard therapies for the treatment of apathy, nonpharmacological treatment (NPT) is often considered to be at the forefront of clinical management. However, guidelines on how to select, prescribe, and administer NPT in clinical practice are lacking. Furthermore, although new Information and Communication Technologies (ICT) are beginning to be employed in NPT, their role is still unclear. The objective of the present work is to provide recommendations for the use of NPT for apathy, and to discuss the role of ICT in this domain, based on opinions gathered from experts in the field. The expert panel included 20 researchers and healthcare professionals working on brain disorders and apathy. Following a standard Delphi methodology, experts answered questions via several rounds of web-surveys, and then discussed the results in a plenary meeting. The experts suggested that NPT are useful to consider as therapy for people presenting with different neurocognitive and psychiatric diseases at all stages, with evidence of apathy across domains. The presence of a therapist and/or a caregiver is important in delivering NPT effectively, but parts of the treatment may be performed by the patient alone. NPT can be delivered both in clinical settings and at home. However, while remote treatment delivery may be cost and time-effective, it should be considered with caution, and tailored based on the patient's cognitive and physical profile and living conditions.

Position of the Academy of Nutrition and Dietetics: Nutrition Informatics.

It is the position of the Academy of Nutrition and Dietetics that nutrition informatics is a rapidly evolving area of practice for registered dietitian nutritionists and nutrition and dietetic technicians, registered; and that the knowledge and skills inherent to nutrition informatics permeate all areas of the dietetics profession. Further, nutrition and dietetics practitioners must continually learn and update their informatics knowledge and skills to remain at the forefront of nutrition practice. Nutrition informatics is the intersection of information, nutrition, and technology. However, informatics is not just using technology to do work. The essence of nutrition informatics is to manage nutrition data in combination with standards, processes, and technology to improve knowledge and practice that ultimately lead to improved quality of health care and work efficiency. Registered dietitian nutritionists and nutrition and dietetic technicians, registered, are already experts in using evidence to practice in all areas of nutrition and dietetics. To remain at the forefront of technological innovation, the profession must actively participate in the development of standards, processes, and technologies for providing nutrition care.

A big picture view of precision nutrition: from reductionism to holism / 한국영양학회지

PURPOSE: This review describes the historical changes in nutrition philosophy from a reductionist to a holistic approach during the 20th century. Also, the role and efficient use of a holistic approach to precision nutrition are discussed. RESULTS: Over the past century, significant progress has been made in human nutrition research, unraveling fundamental mechanisms of single nutrients on single targets or pathways. This kind of a reductionist approach has helped to save populations from nutrient deficiency diseases and improve associated health outcomes in large parts of the world. However, a new set of nutrition problems, like obesity and diet-related chronic diseases, are growing each year worldwide, increasing the financial burden on the health care system. A linear cause-effect association between single nutrients and a single physiologic effect, is insufficient to solve the complex nutrition-health relationships. Research that involves a more holistic rather than reductionist approach is needed to tackle a new set of nutrition problems. Recent advances in technology, informatics, and statistical methods are enabling an understanding of the diversity of individuals and the complex interactions between foods and human bodies, leading to the concept of “precision nutrition.” CONCLUSION: The emerging goal of precision nutrition is to provide tailored dietary advice for maintaining health and preventing obesity and diet-related chronic diseases. The parts are already being installed. To grab the complexity, reductionism and holism must be used interdependently.

Mid infrared spectroscopy and chemometrics as tools for the classification of roasted coffees by cup quality.

Sensory (cup) analysis is a reliable methodology for green coffee quality evaluation, but faces barriers when applied to commercial roasted coffees due to lack of information on roasting conditions. The aim of this study was to examine the potential of mid-infrared spectroscopy for predicting cup quality of arabica coffees of different roasting degrees. PCA analysis showed separation of arabica and robusta. A two-level PLS-DA Hierarchical strategy was employed, with coffee being classified as high or low quality in the first level and then separated according to cup quality in the second level. Validation results showed that the second level models exhibited 100% sensitivity and specificity in the training sets. For the test set, sensitivity ranged from 67% (rio zona) to 100% (soft) while specificity ranged from 71% (rio) to 100% (rioysh, hard). Thus, the proposed method can be used for the quality evaluation of arabica coffees regardless of roasting conditions.