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From the past decades, rodent models have played role in evaluating the use of several drugs for the treatment of brain diseases. Generally, these tests are performed by recoding a video and examine to carry out various annotation about the behavior and activities of the rodents. However, the video must be executed continuously to ensure proper annotation that causes time complexity and increases the human observation error. Conventional techniques for rodent behavioral analysis process are not affordable for the research purpose due to increase cost and poor interpretability. To tackle this issue, a new and effective deep learning (DL) technique is introduced to analyze the multiclass behaviors in rodents under real-time scenario. At first, the video captured from camera is preprocessed by performing frame conversion and noise removal process. For removing the noise, the Butterworth-amended unsharp mask filtering (B_UMF) technique is emphasized thereby improving the image quality. Finally, the Evolutionary Gravity Neocognitron Neural Network (EGravity-NCNN) model is proposed to classify multiple rodent behaviours using adaptive feature learning. The simulation process for the developed method is carried out via the Python platform and various performance like accuracy, precision and recall are scrutinized and compared with conventional schemes. The developed method achieved the overall accuracy of 97.33 %, precision of 96.29 %, and recall of 97.02 % for the classification of rodent behaviours accurately.

We identified a cluster of mpox exposures among key populations in Kenya through retrospective serologic screening. We identified strong seropositivity among sex workers and gay, bisexual, and other men who have sex with men. These findings demonstrate the need for increased mpox surveillance among mpox-endemic and mpox-endemic-adjacent regions in Africa.

ImportanceMost research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.ObjectiveTo identify the most common prolonged symptoms experienced by children (aged 6 to 17 years) after SARS-CoV-2 infection, how these symptoms differ by age (school-age [6-11 years] vs adolescents [12-17 years]), how they cluster into distinct phenotypes, and what symptoms in combination could be used as an empirically derived index to assist researchers to study the likely presence of PASC.Design, setting, and participantsMulticenter longitudinal observational cohort study with participants recruited from more than 60 US health care and community settings between March 2022 and December 2023, including school-age children and adolescents with and without SARS-CoV-2 infection history.ExposureSARS-CoV-2 infection.Main outcomes and measuresPASC and 89 prolonged symptoms across 9 symptom domains.ResultsA total of 898 school-age children (751 with previous SARS-CoV-2 infection [referred to as infected] and 147 without [referred to as uninfected]; mean age, 8.6 years; 49% female; 11% were Black or African American, 34% were Hispanic, Latino, or Spanish, and 60% were White) and 4469 adolescents (3109 infected and 1360 uninfected; mean age, 14.8 years; 48% female; 13% were Black or African American, 21% were Hispanic, Latino, or Spanish, and 73% were White) were included. Median time between first infection and symptom survey was 506 days for school-age children and 556 days for adolescents. In models adjusted for sex and race and ethnicity, 14 symptoms in both school-age children and adolescents were more common in those with SARS-CoV-2 infection history compared with those without infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. These symptoms affected almost every organ system. Combinations of symptoms most associated with infection history were identified to form a PASC research index for each age group; these indices correlated with poorer overall health and quality of life. The index emphasizes neurocognitive, pain, and gastrointestinal symptoms in school-age children but change or loss in smell or taste, pain, and fatigue/malaise-related symptoms in adolescents. Clustering analyses identified 4 PASC symptom phenotypes in school-age children and 3 in adolescents.Conclusions and relevanceThis study developed research indices for characterizing PASC in children and adolescents. Symptom patterns were similar but distinguishable between the 2 groups, highlighting the importance of characterizing PASC separately for these age ranges.

An algebraic model uses a set of algebraic equations to describe a situation. Constructing such models is a fundamental skill, but many students still lack the skill, even after taking several algebra courses in high school and college. For such students, we developed instruction that taught students to decompose the to-be-modelled situation into schema applications, where a schema represents a simple relationship such as distance-rate-time or part-whole. However, when a model consists of multiple schema applications, it needs some connection among them, usually represented by letting the same variable appear in the slots of two or more schemas. Students in our studies seemed to have more trouble identifying connections among schema applications than identifying the schema applications themselves. We developed several tutoring systems and evaluated them in university classes. One of them, a step-based tutoring system called OMRaaT (One Mathematical Relationship at a Time), was both reliably superior (p = 0.02, d = 0.67) to baseline and markedly superior (p < 0.001, d = 0.84) to an answer-based tutoring system using only commercially available software (MATLAB Grader).

We evaluate the relative impact of three sources of epistemic uncertainty on probabilistic seismic hazard analyses in California: source model uncertainty, ground motion model (GMM) uncertainty, and site parameter uncertainty. Seismic source model uncertainty is inherently contained in the source model framework applied by the USGS in the 2023 National Seismic Hazard Model (NSHM23); we have added tools to extract this uncertainty for California sites in the open-source seismic hazard software OpenSHA. GMM uncertainty is generally accounted for using alternative models in PSHA or a single backbone model with a defined uncertainty. Site parameter uncertainty refers to uncertainty in the shear wave velocity of the upper 30 meters of the site profile (VS30) and potentially other independent site parameters.We demonstrate the impacts of these major sources of epistemic uncertainty at the sites of two UC campuses, Berkeley, which is located near the active Hayward fault, and Davis, which is located in the relatively quiescent Central Valley. We investigate potential correlations between the different sources of uncertainty and find that source uncertainty is practically independent of GMM and VS30 uncertainty at Berkeley but dependent on GMM and VS30 at Davis. At both locations, GMM and site parameter uncertainty are correlated (i.e., inter-dependent). We represent epistemic uncertainty in ground motion with a period-dependent log-normal standard deviation term that is specific to a given site location, site condition, and exceedance frequency. We show that at Berkeley, the total epistemic uncertainty can be well approximated by the square root sum of squares (SRSS) of source uncertainty (i.e., uncertainty in ground motions related solely to the source model) and the combined GMM and site parameter uncertainty. We find that combined GMM and VS30 uncertainty is comparable to or greater than the source uncertainty at many oscillator periods at both sites. Combined uncertainties range from natural log standard deviations of about 0.2 at short periods to 0.6 at Berkeley and 0.3-0.7 at Davis at long periods.

Diamine-appended Mg2(dobpdc) (dobpdc4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) metal-organic frameworks are promising candidates for carbon capture that exhibit exceptional selectivities and high capacities for CO2. To date, CO2 uptake in these materials has been shown to occur predominantly via a chemisorption mechanism involving CO2 insertion at the amine-appended metal sites, a mechanism that limits the capacity of the material to ∼1 equiv of CO2 per diamine. Herein, we report a new framework, pip2-Mg2(dobpdc) (pip2 = 1-(2-aminoethyl)piperidine), that exhibits two-step CO2 uptake and achieves an unusually high CO2 capacity approaching 1.5 CO2 per diamine at saturation. Analysis of variable-pressure CO2 uptake in the material using solid-state nuclear magnetic resonance (NMR) spectroscopy and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) reveals that pip2-Mg2(dobpdc) captures CO2 via an unprecedented mechanism involving the initial insertion of CO2 to form ammonium carbamate chains at half of the sites in the material, followed by tandem cooperative chemisorption and physisorption. Powder X-ray diffraction analysis, supported by van der Waals-corrected density functional theory, reveals that physisorbed CO2 occupies a pocket formed by adjacent ammonium carbamate chains and the linker. Based on breakthrough and extended cycling experiments, pip2-Mg2(dobpdc) exhibits exceptional performance for CO2 capture under conditions relevant to the separation of CO2 from landfill gas. More broadly, these results highlight new opportunities for the fundamental design of diamine-Mg2(dobpdc) materials with even higher capacities than those predicted based on CO2 chemisorption alone.

OBJECTIVE: To compare the agreement and cost of two recall methods for estimating childrens minimum dietary diversity (MDD). DESIGN: We assessed childs dietary intake on two consecutive days: an observation on day one, followed by two recall methods (list-based recall and multiple-pass recall) administered in random order by different enumerators at two different times on day two. We compared the estimated MDD prevalence using survey-weighted linear probability models following a two one-sided test equivalence testing approach. We also estimated the cost-effectiveness of the two methods. SETTING: Cambodia (Kampong Thom, Siem Reap, Battambang, and Pursat provinces) and Zambia (Chipata, Katete, Lundazi, Nyimba, and Petauke districts). PARTICIPANTS: Children aged 6-23 months: 636 in Cambodia and 608 in Zambia. RESULTS: MDD estimations from both recall methods were equivalent to the observation in Cambodia but not in Zambia. Both methods were equivalent to the observation in capturing most food groups. Both methods were highly sensitive although the multiple-pass method accurately classified a higher proportion of children meeting MDD than the list-based method in both countries. Both methods were highly specific in Cambodia but moderately so in Zambia. Cost-effectiveness was better for the list-based recall method in both countries. CONCLUSION: The two recall methods estimated MDD and most other infant and young child feeding indicators equivalently in Cambodia but not in Zambia, compared to the observation. The list-based method produced slightly more accurate estimates of MDD at the population level, took less time to administer and was less costly to implement.

IMPORTANCE: The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or Long COVID) in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults. OBSERVATIONS: We describe the protocol for the Pediatric Observational Cohort Study of the NIHs REsearching COVID to Enhance Recovery (RECOVER) Initiative. RECOVER-Pediatrics is an observational meta-cohort study of caregiver-child pairs (birth through 17 years) and young adults (18 through 25 years), recruited from more than 100 sites across the US. This report focuses on two of four cohorts that comprise RECOVER-Pediatrics: 1) a de novo RECOVER prospective cohort of children and young adults with and without previous or current infection; and 2) an extant cohort derived from the Adolescent Brain Cognitive Development (ABCD) study (n = 10,000). The de novo cohort incorporates three tiers of data collection: 1) remote baseline assessments (Tier 1, n = 6000); 2) longitudinal follow-up for up to 4 years (Tier 2, n = 6000); and 3) a subset of participants, primarily the most severely affected by PASC, who will undergo deep phenotyping to explore PASC pathophysiology (Tier 3, n = 600). Youth enrolled in the ABCD study participate in Tier 1. The pediatric protocol was developed as a collaborative partnership of investigators, patients, researchers, clinicians, community partners, and federal partners, intentionally promoting inclusivity and diversity. The protocol is adaptive to facilitate responses to emerging science. CONCLUSIONS AND RELEVANCE: RECOVER-Pediatrics seeks to characterize the clinical course, underlying mechanisms, and long-term effects of PASC from birth through 25 years old. RECOVER-Pediatrics is designed to elucidate the epidemiology, four-year clinical course, and sociodemographic correlates of pediatric PASC. The data and biosamples will allow examination of mechanistic hypotheses and biomarkers, thus providing insights into potential therapeutic interventions. CLINICAL TRIALS.GOV IDENTIFIER: Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.

Management of intracoronary calcium (ICC) continues to be a challenge for interventional cardiologists. There have been significant advances in calcium treatment devices. However, there still exists a knowledge gap regarding which devices to choose for the treatment of ICC. The purpose of this manuscript is to review the principles of intravascular lithotripsy (IVL) and clinical data. The technique of IVL will then be compared to alternative calcium treatment devices. Clinical data will be reviewed concerning the treatment of coronary, peripheral artery and valvular calcifications. Controversies to be discussed include how to incorporate IVL into your practice, what is the best approach for treating calcium subtypes, how to approach under-expanded stents, what is the ideal technique for performing IVL, how safe is IVL, whether imaging adds value when performing IVL, and how IVL fits into a treatment program for peripheral arteries and calcified valves.

Tissue resident memory CD8+ T (TRM) cells offer rapid and long-term protection at sites of reinfection1. Tumour-infiltrating lymphocytes with characteristics of TRM cells maintain enhanced effector functions, predict responses to immunotherapy and accompany better prognoses2,3. Thus, an improved understanding of the metabolic strategies that enable tissue residency by T cells could inform new approaches to empower immune responses in tissues and solid tumours. Here, to systematically define the basis for the metabolic reprogramming supporting TRM cell differentiation, survival and function, we leveraged in vivo functional genomics, untargeted metabolomics and transcriptomics of virus-specific memory CD8+ T cell populations. We found that memory CD8+ T cells deployed a range of adaptations to tissue residency, including reliance on non-steroidal products of the mevalonate-cholesterol pathway, such as coenzyme Q, driven by increased activity of the transcription factor SREBP2. This metabolic adaptation was most pronounced in the small intestine, where TRM cells interface with dietary cholesterol and maintain a heightened state of activation4, and was shared by functional tumour-infiltrating lymphocytes in diverse tumour types in mice and humans. Enforcing synthesis of coenzyme Q through deletion of Fdft1 or overexpression of PDSS2 promoted mitochondrial respiration, memory T cell formation following viral infection and enhanced antitumour immunity. In sum, through a systematic exploration of TRM cell metabolism, we reveal how these programs can be leveraged to fuel memory CD8+ T cell formation in the context of acute infections and enhance antitumour immunity.

Diamine-appended Mg2(dobpdc) (dobpdc4- = 4,4-dioxidobiphenyl-3,3-dicarboxylate) metal-organic frameworks have emerged as promising candidates for carbon capture owing to their exceptional CO2 selectivities, high separation capacities, and step-shaped adsorption profiles, which arise from a unique cooperative adsorption mechanism resulting in the formation of ammonium carbamate chains. Materials appended with primary,secondary-diamines featuring bulky substituents, in particular, exhibit excellent stabilities and CO2 adsorption properties. However, these frameworks display double-step adsorption behavior arising from steric repulsion between ammonium carbamates, which ultimately results in increased regeneration energies. Herein, we report frameworks of the type diamine-Mg2(olz) (olz4- = (E)-5,5-(diazene-1,2-diyl)bis(2-oxidobenzoate)) that feature diverse diamines with bulky substituents and display desirable single-step CO2 adsorption across a wide range of pressures and temperatures. Analysis of CO2 adsorption data reveals that the basicity of the pore-dwelling amine─in addition to its steric bulk─is an important factor influencing adsorption step pressure; furthermore, the amine steric bulk is found to be inversely correlated with the degree of cooperativity in CO2 uptake. One material, ee-2-Mg2(olz) (ee-2 = N,N-diethylethylenediamine), adsorbs >90% of the CO2 from a simulated coal flue stream and exhibits exceptional thermal and oxidative stability over the course of extensive adsorption/desorption cycling, placing it among top-performing adsorbents to date for CO2 capture from a coal flue gas. Spectroscopic characterization and van der Waals-corrected density functional theory calculations indicate that diamine-Mg2(olz) materials capture CO2 via the formation of ammonium carbamate chains. These results point more broadly to the opportunity for fundamentally advancing materials in this class through judicious design.

A consistent set of measurement techniques must be applied to reliably and reproducibly evaluate the efficacy of treatments for cutaneous neurofibromas (cNFs) in people with neurofibromatosis type 1 (NF1). cNFs are neurocutaneous tumors that are the most common tumor in people with NF1 and represent an area of unmet clinical need. This review presents the available data regarding approaches in use or development to identify, measure, and track cNFs, including calipers, digital imaging, and high-frequency ultrasound sonography. We also describe emerging technologies such as spatial frequency domain imaging and the application of imaging modalities such as optical coherence tomography that may enable the detection of early cNFs and prevention of tumor-associated morbidity.