Elevating levels of the endocannabinoid 2-arachidonoylglycerol blunts opioid reward but not analgesia.

Converging findings have established that the endocannabinoid (eCB) system serves as a possible target for the development of new treatments for pain as a complement to opioid-based treatments. Here we show in male and female mice that enhancing levels of the eCB, 2-arachidonoylglycerol (2-AG), through pharmacological inhibition of its catabolic enzyme, monoacylglycerol lipase (MAGL), either systemically or in the ventral tegmental area (VTA) with JZL184, leads to a substantial attenuation of the rewarding effects of opioids in male and female mice using conditioned place preference and self-administration paradigms, without altering their analgesic properties. These effects are driven by CB1 receptors (CB1Rs) within the VTA as VTA CB1R conditional knockout, counteracts JZL184's effects. Conversely, pharmacologically enhancing the levels of the other eCB, anandamide (AEA), by inhibition of fatty acid amide hydrolase (FAAH) has no effect on opioid reward or analgesia. Using fiber photometry with fluorescent sensors for calcium and dopamine (DA), we find that enhancing 2-AG levels diminishes opioid reward-related nucleus accumbens (NAc) activity and DA neurotransmission. Together these findings reveal that 2-AG counteracts the rewarding properties of opioids and provides a potential adjunctive therapeutic strategy for opioid-related analgesic treatments.

Comparison of the Sensitivity and Specificity of Commercial Anti-Dengue Virus IgG Tests to Identify Persons Eligible for Dengue Vaccination.

The Advisory Committee on Immunization Practices (ACIP) recommended that dengue pre-vaccination screening tests for Dengvaxia administration have at least 98% specificity and 75% sensitivity. This study evaluates the performance of commercial anti-DENV IgG tests to identify tests that could be used for pre-vaccination screening. First, for 7 tests, we evaluated sensitivity and specificity in early convalescent dengue virus (DENV) infection, using 44 samples collected 7-30 days after symptom onset and confirmed by RT-PCR. Next, for the 5 best performing tests and two additional tests (with and without an external test reader) that became available later, we evaluated performance to detect past dengue infection among a panel of 44 specimens collected in 2018-2019 from healthy 9-16-year-old children from Puerto Rico. Finally, a full-scale evaluation was done with the 4 best performing tests using 400 specimens from the same population. We used virus focus reduction neutralization test and an in-house DENV IgG ELISA as reference standards. Of seven tests, five showed ≥75% sensitivity detecting anti-DENV IgG in early convalescent specimens with low cross-reactivity to Zika virus. For the detection of previous DENV infections the tests with the highest performance were the Euroimmun NS1 IgG ELISA (sensitivity 84.5%, specificity 97.1%) and CTK Dengue IgG rapid test R0065C with the test reader (sensitivity 76.2% specificity 98.1%). There are IgG tests available that can be used to accurately classify individuals with previous DENV infection as eligible for dengue vaccination to support safe vaccine implementation.

Analysis of variables to determine their influence on renewable energy forecasting using ensemble methods.

Forecasting is of great importance in the field of renewable energies because it allows us to know the quantity of energy that can be produced, and thus, to have an efficient management of energy sources. However, determining which prediction system is more adequate is very complex, as each energy infrastructure is different. This work studies the influence of some variables when making predictions using ensemble methods for different locations. In particular, the proposal analyzes the influence of the aspects: the variation of the sampling frequency of solar panel systems, the influence of the type of neural network architecture and the number of ensemble method blocks for each model. Following comprehensive experimentation across multiple locations, our study has identified the most effective solar energy prediction model tailored to the specific conditions of each energy infrastructure. The results offer a decisive framework for selecting the optimal system for accurate and efficient energy forecasting. The key point is the use of short time intervals, which is independent of type of prediction model and of their ensemble method.

Is it time to reduce the length of postgraduate training for physician-scientists in internal medicine?

Physician-scientists play a crucial role in advancing medical knowledge and patient care, yet the long periods of time required to complete training may impede expansion of this workforce. We examined the relationship between postgraduate training and time to receipt of NIH or Veterans Affairs career development awards (CDAs) for physician-scientists in internal medicine. Data from NIH RePORTER were analyzed for internal medicine residency graduates who received specific CDAs (K08, K23, K99, or IK2) in 2022. Additionally, information on degrees and training duration was collected. Internal medicine residency graduates constituted 19% of K awardees and 28% of IK2 awardees. Of MD-PhD internal medicine-trained graduates who received a K award, 92% received a K08 award; of MD-only graduates who received a K award, a majority received a K23 award. The median time from medical school graduation to CDA was 9.6 years for K awardees and 10.2 years for IK2 awardees. The time from medical school graduation to K or IK2 award was shorter for US MD-PhD graduates than US MD-only graduates. We propose that the time from medical school graduation to receipt of CDAs must be shortened to accelerate training and retention of physician-scientists.

Multivariate analysis applied to X-ray fluorescence to assess soil contamination pathways: case studies of mass magnetic susceptibility in soils near abandoned coal and W/Sn mines.

Determining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.

Validation of the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool: a new tool to assess the quality of health information provided by AI platforms.

BACKGROUND: The widespread diffusion of Artificial Intelligence (AI) platforms is revolutionizing how health-related information is disseminated, thereby highlighting the need for tools to evaluate the quality of such information. This study aimed to propose and validate the Quality Assessment of Medical Artificial Intelligence (QAMAI), a tool specifically designed to assess the quality of health information provided by AI platforms. METHODS: The QAMAI tool has been developed by a panel of experts following guidelines for the development of new questionnaires. A total of 30 responses from ChatGPT4, addressing patient queries, theoretical questions, and clinical head and neck surgery scenarios were assessed by 27 reviewers from 25 academic centers worldwide. Construct validity, internal consistency, inter-rater and test-retest reliability were assessed to validate the tool. RESULTS: The validation was conducted on the basis of 792 assessments for the 30 responses given by ChatGPT4. The results of the exploratory factor analysis revealed a unidimensional structure of the QAMAI with a single factor comprising all the items that explained 51.1% of the variance with factor loadings ranging from 0.449 to 0.856. Overall internal consistency was high (Cronbach's alpha = 0.837). The Interclass Correlation Coefficient was 0.983 (95% CI 0.973-0.991; F (29,542) = 68.3; p < 0.001), indicating excellent reliability. Test-retest reliability analysis revealed a moderate-to-strong correlation with a Pearson's coefficient of 0.876 (95% CI 0.859-0.891; p < 0.001). CONCLUSIONS: The QAMAI tool demonstrated significant reliability and validity in assessing the quality of health information provided by AI platforms. Such a tool might become particularly important/useful for physicians as patients increasingly seek medical information on AI platforms.

The combined effect of diffuse radiation and leaf wetness on functional traits and transpiration efficiency on a cloud forest species.

Cloud forests are unique biomes that thrive in foggy environments for a substantial part of the season. Fog in cloud forests plays two critical roles: it reduces incoming radiation and creates a humid environment, leading to the wetting of the canopy. This paper aims to investigate the combined effect of both radiation and wetness on Myrica faya -a cloud forest species present in subtropical regions- both directly in plants and through simulations. Experiments consisted of a controlled environment with two levels of radiation and leaf wetness: low radiation/wet conditions, and high radiation/no-wetness; and three treatments: continuous low radiation and wetness (CLR), continuous high radiation and no wetness (CHR), and alternate high low radiation and alternate wetness (AHLR). The results revealed that a combination of low radiation and leaf wetness significantly improves leaf stomata conductance and increases the specific leaf area (SLA). Changes in SLA were driven by leaf size changes. However, the minimum leaf conductance (gmin) did not respond to any of the treatments. The simulations focused on exploring the impact of radiation and canopy wetness on transpiration efficiency (TE), i.e. the ratio between photosynthesis (An) and transpiration (Tc), i.e. TE = An/Tc. The simulations demonstrated that TE increased exponentially as the canopy was gradually wetted, regardless of the radiation environment. This increase in TE results from Tc approaching zero while An maintains positive values. Overall, this study provides an integrated understanding of how fog alters M. faya functioning and, potentially, other cloud forest tree species.

The Role of Aryl Hydrocarbon Receptor in Bone Biology.

Aryl hydrocarbon receptor (AhR), a ligand-activated transcription factor, is crucial in maintaining the skeletal system. Our study focuses on encapsulating the role of AhR in bone biology and identifying novel signaling pathways in musculoskeletal pathologies using the GEO dataset. The GEO2R analysis identified 8 genes (CYP1C1, SULT6B1, CYB5A, EDN1, CXCR4B, CTGFA, TIPARP, and CXXC5A) involved in the AhR pathway, which play a pivotal role in bone remodeling. The AhR knockout in hematopoietic stem cells showed alteration in several novel bone-related transcriptomes (eg, Defb14, ZNF 51, and Chrm5). Gene Ontology Enrichment Analysis demonstrated 54 different biological processes associated with bone homeostasis. Mainly, these processes include bone morphogenesis, bone development, bone trabeculae formation, bone resorption, bone maturation, bone mineralization, and bone marrow development. Employing Functional Annotation and Clustering through DAVID, we further uncovered the involvement of the xenobiotic metabolic process, p450 pathway, oxidation-reduction, and nitric oxide biosynthesis process in the AhR signaling pathway. The conflicting evidence of current research of AhR signaling on bone (positive and negative effects) homeostasis may be due to variations in ligand binding affinity, binding sites, half-life, chemical structure, and other unknown factors. In summary, our study provides a comprehensive understanding of the underlying mechanisms of the AhR pathway in bone biology.

Severe Sinus Dysfunction in the Context of Chronic Lithium Intoxication and Poorly Controlled Hypothyroidism.

Cardiotoxicity associated with lithium is not a common event; however, it is potentially life-threatening, manifesting electrocardiographically with sinoatrial blocks, high-degree atrioventricular blocks, QT prolongation, and ventricular tachyarrhythmias. This case report presents a patient with severe sinus dysfunction in a clinically severe presentation secondary to cardiogenic shock. The patient sought medical attention for a one-week history of non-anginal chest pain, dizziness without syncope, generalized weakness, and somnolence progressing to bedridden status in the days preceding hospital admission. Laboratory findings revealed elevated blood levels of lithium and thyroid-stimulating hormone (TSH), along with concomitant Acute Kidney Injury Network (AKIN) II acute kidney injury. Subsequently, the patient was admitted to the intensive care unit, where persistent extreme sinus bradycardia of 30 bpm (beats per minute) with sinus pauses without ischemic changes was observed. The patient received supportive treatment, including renal replacement therapy, resulting in complete recovery of hemodynamic status without the need for long-term cardiac conduction devices.

Connecting Clinical Capacity and Intervention Sustainability in Resource-Variable Pediatric Oncology Centers in Latin America.

Clinical capacity for sustainability, or the clinical resources needed to sustain an evidence-based practice, represent proximal determinants that contribute to intervention sustainment. We examine the relationship between clinical capacity for sustainability and sustainment of PEWS, an evidence-based intervention to improve outcomes for pediatric oncology patients in resource-variable hospitals. We conducted a cross-sectional survey among Latin American pediatric oncology centers participating in Proyecto Escala de Valoración de Alerta Temprana (EVAT), an improvement collaborative to implement Pediatric Early Warning Systems (PEWS). Hospitals were eligible if they had completed PEWS implementation. Clinicians were eligible to participate if they were involved in PEWS implementation or used PEWS in clinical work. The Spanish language survey consisted of 56 close and open-ended questions about the respondent, hospital, participants' assessment of clinical capacity to sustain PEWS using the clinical sustainability assessment tool (CSAT), and perceptions about PEWS and its use as an intervention. Results were analyzed using a multi-level modeling approach to examine the relationship between individual, hospital, intervention, and clinical capacity determinants to PEWS sustainment. A total of 797 responses from 37 centers in 13 countries were included in the analysis. Eighty-seven percent of participants reported PEWS sustainment. After controlling for individual, hospital, and intervention factors, clinical capacity was significantly associated with PEWS sustainment (OR 3.27, p < .01). Marginal effects from the final model indicate that an increasing capacity score has a positive influence (11% for every additional CSAT point) of predicting PEWS sustainment. PEWS is a sustainable intervention and clinical capacity to sustain PEWS contributes meaningfully to PEWS sustainment.

Impact of electrophysiologists at daily multidisciplinary report in a paediatric cardiac care unit.

BACKGROUND: Paediatric cardiac electrophysiologists are essential in CHD inpatient care, but their involvement is typically limited to consultation with individual patients. In our integrated heart centre, an electrophysiologist reviews all cardiac inpatient telemetry over the preceding 24 hours and participates in daily multidisciplinary morning report. This study investigates the impact of the strategy of consistent, formalised electrophysiologist presence at multidisciplinary morning report. METHODS: This is a single-centre, prospective, observational study of electrophysiologist participation in patient encounters during heart centre multidisciplinary morning report from 10/20/2021 to 10/31/2022. Multidisciplinary morning report includes discussion of all intensive care and non-intensive care cardiac patients. An encounter was defined as reporting on one patient for one day. Electrophysiologists were initially blinded to observations. RESULTS: Two electrophysiologists were observed over 215 days encompassing 6413 patient encounters. Electrophysiologists made comments on 581(9.1%) encounters in 234 unique patients with diverse diagnoses, equating to a median of 3[interquartile range:1-4] encounters per day. These included identifications of arrhythmias and describing electrocardiographic findings. Recommendation to change management occurred in 282(48.5%) encounters, most commonly regarding medications (n = 142, 24.4%) or pacemaker management (n = 48, 8.3%). Of the 581 encounters, there were 61(10.5%) in which they corrected another physician's interpretation of rhythm or electrocardiogram. CONCLUSION: Routine electrophysiologist involvement in multidisciplinary morning report provides significant, frequent, and timely input in patient management by identifying precise rhythm-related diagnoses and allowing nuanced, patient-specific medication and pacemaker management of all cardiac patients, not just those consulted. Electrophysiologist presence at multidisciplinary morning report is a vital resource and this practice should be considered at integrated paediatric cardiac centres.

Brain and cognitive changes in patients with long COVID compared with infection-recovered control subjects.

Between 2.5 and 28% of people infected with SARS-CoV-2 suffer Long COVID or persistence of symptoms for months after acute illness. Many symptoms are neurological, but the brain changes underlying the neuropsychological impairments remain unclear. This study aimed to provide a detailed description of the cognitive profile, the pattern of brain alterations in Long COVID and the potential association between them. To address these objectives, 83 patients with persistent neurological symptoms after COVID-19 were recruited, and 22 now healthy controls chosen because they had suffered COVID-19 but did not experience persistent neurological symptoms. Patients and controls were matched for age, sex and educational level. All participants were assessed by clinical interview, comprehensive standardized neuropsychological tests and structural MRI. The mean global cognitive function of patients with Long COVID assessed by ACE III screening test (Overall Cognitive level - OCLz= -0.39± 0.12) was significantly below the infection recovered-controls (OCLz= +0.32± 0.16, p< 0.01). We observed that 48% of patients with Long COVID had episodic memory deficit, with 27% also impaired overall cognitive function, especially attention, working memory, processing speed and verbal fluency. The MRI examination included grey matter morphometry and whole brain structural connectivity analysis. Compared to infection recovered controls, patients had thinner cortex in a specific cluster centred on the left posterior superior temporal gyrus. In addition, lower fractional anisotropy (FA) and higher radial diffusivity (RD) were observed in widespread areas of the patients' cerebral white matter relative to these controls. Correlations between cognitive status and brain abnormalities revealed a relationship between altered connectivity of white matter regions and impairments of episodic memory, overall cognitive function, attention and verbal fluency. This study shows that patients with neurological Long COVID suffer brain changes, especially in several white matter areas, and these are associated with impairments of specific cognitive functions.

Performance and Consistency of ChatGPT-4 Versus Otolaryngologists: A Clinical Case Series.

OBJECTIVE: To study the performance of Chatbot Generative Pretrained Transformer-4 (ChatGPT-4) in the management of cases in otolaryngology-head and neck surgery. STUDY DESIGN: Prospective case series. SETTING: Multicenter University Hospitals. METHODS: History, clinical, physical, and additional examinations of adult outpatients consulting in otolaryngology departments of CHU Saint-Pierre and Dour Medical Center were presented to ChatGPT-4, which was interrogated for differential diagnoses, management, and treatment(s). According to specialty, the ChatGPT-4 responses were assessed by 2 distinct, blinded board-certified otolaryngologists with the Artificial Intelligence Performance Instrument. RESULTS: One hundred cases were presented to ChatGPT-4. ChaGPT-4 indicated a mean of 3.34 (95% confidence interval [CI]: 3.09, 3.59) additional examinations per patient versus 2.10 (95% CI: 1.76, 2.34; P = .001) for the practitioners. There was strong consistency (k > 0.600) between otolaryngologists and ChatGPT-4 for the indication of upper aerodigestive tract endoscopy, positron emission tomography and computed tomography, audiometry, tympanometry, and psychophysical evaluations. Primary diagnosis was correctly performed by ChatGPT-4 in 38% to 86% of cases depending on subspecialty. Additional examinations indicated by ChatGPT-4 were pertinent and necessary in 8% to 31% of cases, while the treatment regimen was pertinent in 12% to 44% of cases. The performance of ChatGPT-4 was not influenced by the human-reported level of difficulty of clinical cases. CONCLUSION: ChatGPT-4 may be a promising adjunctive tool in otolaryngology, providing extensive documentation about additional examinations, primary and differential diagnoses, and treatments. The ChatGPT-4 is more effective in providing a primary diagnosis, and less effective in the selection of additional examinations and treatments.

Sub-Doppler spectroscopy of the Cs atom 6S1/2-7P1/2 transition at 459 nm in a microfabricated vapor cell.

We report on the characterization of sub-Doppler resonances detected by probing the 6S1/2 - 7P1/2 transition of the Cs atom at 459 nm in a microfabricated vapor cell. The dependence of the sub-Doppler resonance (linewidth, amplitude) on some key experimental parameters, including the laser intensity and the cell temperature, is investigated. These narrow atomic resonances are of interest for high-resolution spectroscopy and instrumentation and may constitute the basis of a high-stability microcell optical standard.

Diabetic Ketoacidosis in Type 1 Diabetes Onset in Latin American Children.

OBJECTIVE: To describe the patterns of diabetic ketoacidosis (DKA) occurrence in children newly diagnosed with type 1 diabetes (T1DM) across several Latin American pediatric diabetes centers from 2018 to 2022. METHODS: A retrospective chart review included children under 18 with new-onset T1DM from 30 Latin American pediatric diabetes centers (Argentina, Chile, and Peru) between 30 December 2018 and 30 December 2022. Multiple logistic regression models examined the relationships between age, gender, medical insurance, BMI, and DKA at new-onset T1DM. As far as we know, there are no large studies in Latin American countries exploring the patterns of DKA in new-onset T1DM. RESULTS: A total of 2,026 (983 females) children, median age 9.12 (5.8 -11.7) years with new-onset-T1DM were included. Approximately 50% had no medical insurance. Mean glucose values were 467 mg/dL, pH 7.21, bicarbonate 13 mEq/L, HbA1c 11.3%, and BMI 18. The frequency of DKA was 1,229 (60.7%), out of which only 447 (36%) were severe. There was a significant decrease in the frequency of DKA as age increased: 373 (70.2%) in children under 6, 639 (61.6%) in those between 6 and 12, 217 and (47.5%) in those over 12. Children with medical insurance (58.8%) had a significantly lower frequency of DKA than those without (62.7%). The multiple logistic regression models showed that DKA was significantly and inversely associated with age [OR, 0.72 (95% CI 0.60-0.86)], BMI [OR, 0.95 (95% CI 0.92-0.99)], and medical insurance [OR, 0.75 (95% CI 0.60-0.94)] adjusted for sex. CONCLUSION: Latin American children with new-onset T1DM exhibited a substantial occurrence of DKA. Younger ages and the lack of medical insurance were significantly associated with DKA in new-onset T1DM.

Efficacy of wireless sensors in assessing occlusal and bite forces: A systematic review.

BACKGROUND: The noteworthy correlation between bite force and masticatory performance emphasizes its significance as a meaningful and objective method for assessing oral function. Furthermore, in the study of bruxism, the measurement of intraoral bite force assumes critical importance. Given the importance of assessing occlusal forces and bite force, this systematic review aims to assess the efficacy of wireless sensors in measuring these forces. METHODS: The search methodology employed in this systematic review adhered to the guidelines outlined by PRISMA. The strategy involved the exploration of various databases, including PubMed/MEDLINE, SCOPUS and SCIELO. An assessment tool was employed to evaluate the bias risk and study quality. RESULTS: This systematic review encompassed six prospective clinical studies involving a total of 89 participants. Wireless sensors for measuring occlusal forces and bite forces were predominantly employed in healthy adults or individuals with bruxism, along with children undergoing orthodontic treatment. All wireless sensors employed in the studies underwent validation and reproducibility assessments, affirming their reliability. The findings indicated that all wireless sensors exhibited efficacy in detecting occlusal forces and bite forces. CONCLUSION: Wireless sensors offer real-time monitoring of occlusal and bite forces, aiding in understanding force distribution and identifying bruxism patterns. Despite limited studies on their application, these sensors contribute to evolving insights. Integration into clinical practice requires careful consideration of factors like calibration and patient compliance. Ongoing research is crucial to address limitations and enhance the efficacy of wireless sensors in measuring occlusal and bite forces and managing bruxism.