The impact of Benevolent Childhood Experiences on adult Flourishing: the mediating role of Light Triad traits.

The literature has well documented the relationship between Adverse Childhood Experiences, personality traits, and well-being. However, less is known about how Benevolent Childhood Experiences (BCEs) relate to "light" personality traits and Flourishing. The study analyzed the effects of BCEs on Flourishing, considering the mediator role of Light Triad traits (Kantianism, Humanism, and Faith in Humanity). The study used a quantitative methodology with a non-experimental, cross-sectional design; 410 Honduran adults responded to the survey, including questions regarding Light Triad personality traits, Flourishing, and BCEs. On average, respondents reported 7.34 BCEs. The number of reported BCEs did not vary significantly between men and women. However, specific BCEs were categorically associated with subjects' sex. A higher proportion of men reported having at least one teacher who cared about the respondent, having opportunities to have a good time, and liking/feeling comfortable with oneself. Flourishing was significantly higher for participants who reported the presence of BCEs. The largest effect size was achieved for the difference in Flourishing scores between those who reported liking school as a child and those who disliked it. The number of Benevolent Childhood Experiences had a significant total and direct effect on Flourishing scores. Significant indirect effects were also identified. Faith in Humanity and Humanism, not Kantianism, mediated the relationship between BCEs and Flourishing. BCEs significantly explained all Light Triad traits. In conclusion, BCEs have significant direct and indirect effects on adult Flourishing; Faith in Humanity and Humanism mediate this relationship.

Induced-charge electrophoresis of a tilted metal nanowire near an insulating wall.

Electric fields are commonly used to control the orientation and motion of microscopic metal particles in aqueous suspensions. For example, metallodielectric Janus spheres are propelled by the induced-charge electro-osmotic flow occurring on their metallic side, the most common case in electrokinetics of exploiting symmetry breaking of surface properties for achieving net particle motion. In this work, we demonstrate that a homogeneous metal rod can translate parallel to a dielectric wall as a result of the hydrodynamic wall-particle interaction arising from the induced-charge electro-osmosis on the rod surface. The applied electric field could be either dc or low-frequency ac. The only requirement for a nonvanishing particle velocity is that the axis of the rod be inclined with respect to the wall, i.e., it cannot be neither parallel nor perpendicular. We show numerical results of the rod velocity as a function of rod orientation and distance to the wall. The maximum particle velocity is found for an orientation of between ∼30^{∘} and ∼50^{∘}, depending on the position and aspect ratio of the cylinder. Particle velocities of up to tens of µm/s are predicted for typical conditions in electrokinetic experiments.

Concentration-polarization electroosmosis for particle fractionation.

Concentration-polarization electroosmosis (CPEO) refers to steady-state electroosmotic flows around charged dielectric micro-particles induced by low-frequency AC electric fields. Recently, these flows were shown to cause repulsion of colloidal particles from the wall of a microfluidic channel when an electric field is applied along the length of the channel. In this work, we exploit this mechanism to demonstrate fractionation of micron-sized polystyrene particles and bacteria in a flow-focusing device. The results are in agreement with predictions of the CPEO theory. The ease of implementation of CPEO-based fractionation in microfluidics makes it an ideal candidate for combining with current techniques commonly used to generate particle lift, such as inertial or viscoelastic focusing, requiring no extra fabrication steps other than inserting two electrodes.

Unraveling the Catalytic Mechanism of ß-Cyclodextrin in the Vitamin D Formation.

Previous experimental studies have shown that the isomerization reaction of previtamin D3 (PreD3) to vitamin D3 (VitD3) is accelerated 40-fold when it takes place within a ß-cyclodextrin dimer, in comparison to the reaction occurring in conventional isotropic solutions. In this study, we employ quantum mechanics-based molecular dynamics (MD) simulations and statistical multistructural variational transition state theory to unveil the origin of this acceleration. We find that the conformational landscape in the PreD3 isomerization is highly dependent on whether the system is encapsulated. In isotropic media, the triene moiety of the PreD3 exhibits a rich torsional flexibility. However, when encapsulated, such a flexibility is limited to a more confined conformational space. In both scenarios, our calculated rate constants are in close agreement with experimental results and allow us to identify the PreD3 flexibility restriction as the primary catalytic factor. These findings enhance our understanding of VitD3 isomerization and underscore the significance of MD and environmental factors in biochemical modeling.

HIV and AIDS in the state of Paraná, Brazil, 2007-2022: trends and spatiotemporal distribution.

OBJECTIVE: The aim of this study was to analyze the spatiotemporal evolution of the incidence rates of human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) in the state of Paraná, Brazil. METHODS: An ecological study with an analytical component of time series analysis was conducted in the state of Paraná from 2007 to 2022. The data source was the Notifiable Diseases Information System. To study the trend, the Prais-Winsten generalized linear regression model was used by decomposing the time series, and for spatial analysis, the Moran's index was applied. RESULTS: The total sample consisted of 50,676 HIV/AIDS records. The incidence rate showed an increasing trend, with an average growth of 2.14% [95% confidence interval - 95%CI 1.16-3.13] per month. From 2007 to 2014 and from 2015 to 2022, the average number of cases in the state was 105.64 and 159.20 per 100,000 inhabitants, respectively, with significant variation among municipalities. Spatial clusters of high risk persisted in the metropolitan region, the capital, and coastal areas, and a new cluster was observed in the northern region of the state. CONCLUSION: The incidence rates of HIV/AIDS showed an upward trend over time. The number of cases varied considerably in some municipalities, especially in the coastal region. Spatial analysis revealed geospatial patterns of high risk in the main metropolitan areas of Paraná: Curitiba (including the coastal area), Londrina, and Maringá, which share characteristics such as a high degree of urbanization and ongoing economic development.

On a Closer Look of a Doppler Tolerant Noise Radar Waveform in Surveillance Applications.

The prevalence of Low Probability of Interception (LPI) and Low Probability of Exploitation (LPE) radars in contemporary Electronic Warfare (EW) presents an ongoing challenge to defense mechanisms, compelling constant advances in protective strategies. Noise radars are examples of LPI and LPE systems that gained substantial prominence in the past decade despite exhibiting a common drawback of limited Doppler tolerance. The Advanced Pulse Compression Noise (APCN) waveform is a stochastic radar signal proposed to amalgamate the LPI and LPE attributes of a random waveform with the Doppler tolerance feature inherent to a linear frequency modulation. In the present work, we derive closed-form expressions describing the APCN signal's ambiguity function and spectral containment that allow for a proper analysis of its detection performance and ability to remove range ambiguities as a function of its stochastic parameters. This paper also presents a more detailed address of the LPI/LPE characteristic of APCN signals claimed in previous works. We show that sophisticated Electronic Intelligence (ELINT) systems that employ Time Frequency Analysis (TFA) and image processing methods may intercept APCN and estimate important parameters of APCN waveforms, such as bandwidth, operating frequency, time duration, and pulse repetition interval. We also present a method designed to intercept and exploit the unique characteristics of the APCN waveform. Its performance is evaluated based on the probability of such an ELINT system detecting an APCN radar signal as a function of the Signal-to-Noise Ratio (SNR) in the ELINT system. We evaluated the accuracy and precision of the random variables characterizing the proposed estimators as a function of the SNR. Results indicate a probability of detection close to 1 and show good performance, even for scenarios with a SNR slightly less than -10 dB. The contributions in this work offer enhancements to noise radar capabilities while facilitating improvements in ESM systems.

Unsuccessful tuberculosis treatment outcomes across Brazil's geographical landscape before and during the COVID-19 pandemic: are we truly advancing toward the sustainable development/end TB goal?

BACKGROUND: Tuberculosis is one of the most significant infectious diseases for global public health. The reallocation of healthcare resources and the restrictions imposed by the COVID-19 pandemic have hindered access to TB diagnosis and treatment. Increases in unfavorable outcomes of the disease have been observed in Brazil. The objective of this study was to analyze the spatial distribution of unfavorable TB treatment outcomes in Brazil before and during the pandemic. METHODS: An ecological study with spatial analysis was conducted with all 5569 municipalities in Brazil. All reported cases of tuberculosis between January 2010 and December 2021, as well as reported cases of COVID-19 from February 2020 to December 2021, were included. The outcomes studied encompass loss to follow-up, drug-resistant tuberculosis, and death. The Getis Ord GI* technique was employed to assess spatial association, and the Kernel density estimator was used to identify areas with concentrated increases or decreases in outcomes. Bivariate Local Moran's I was used to examine the spatial association between outcomes and COVID-19 incidence. The study was approved by the Research Ethics Committee of Ribeirão Preto Nursing School, University of São Paulo. RESULTS: There were 134,394 cases of loss to follow-up, 10,270 cases of drug resistance, and 37,863 deaths. Clusters of high and low values were identified for all three outcomes, indicating significant changes in the spatial distribution patterns. Increases in concentrations were observed for lost to follow-up cases in the Southeast, while reductions occurred in the Northeast, South, and Midwest. Drug-resistant tuberculosis experienced an increase in the Southern and Southeastern regions and a decrease in the Northeast and South. TB-related deaths showed notable concentrations in the Midwest, Northeast, South, and Southeast. There was an increase in high occurrence clusters for deaths after 2020 and 2021 in the Northeast. CONCLUSIONS: The pandemic has brought additional challenges, emphasizing the importance of enhancing efforts and disease control strategies, prioritizing early identification, treatment adherence, and follow-up. This commitment is vital for achieving the goal of tuberculosis elimination.

NIR-HSI as a tool to predict deoxynivalenol and fumonisins in maize kernels: a step forward in preventing mycotoxin contamination.

BACKGROUND: Maize is frequently contaminated with deoxynivalenol (DON) and fumonisins B1 (FB1 ) and B2 (FB2 ). In the European Union, these mycotoxins are regulated in maize and maize-derived products. To comply with these regulations, industries require a fast, economic, safe, non-destructive and environmentally friendly analysis method. RESULTS: In the present study, near-infrared hyperspectral imaging (NIR-HSI) was used to develop regression and classification models for DON, FB1 and FB2 in maize kernels. The best regression models presented the following root mean square error of cross validation and ratio of performance to deviation values: 0.848 mg kg-1 and 2.344 (DON), 3.714 mg kg-1 and 2.018 (FB1 ) and 2.104 mg kg-1 and 2.301 (FB2 ). Regarding classification, European Union legal limits for DON and FB1 + FB2 were selected as thresholds to classify maize kernels as acceptable or not. The sensitivity and specificity were 0.778 and 1 for the best DON classification model and 0.607 and 0.938 for the best FB1 + FB2 classification model. CONCLUSION: NIR-HSI can help reduce DON and fumonisins contamination in the maize food and feed chain. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Genome-wide association study identifies genetic variants underlying footrot in Portuguese Merino sheep.

BACKGROUND: Ovine footrot caused by Dichelobacter nodosus (D. nodosus) is a contagious disease with serious economic and welfare impacts in sheep production systems worldwide. A better understanding of the host genetic architecture regarding footrot resistance/susceptibility is crucial to develop disease control strategies that efficiently reduce infection and its severity. A genome-wide association study was performed using a customized SNP array (47,779 SNPs in total) to identify genetic variants associated to footrot resistance/susceptibility in two Portuguese native breeds, i.e. Merino Branco and Merino Preto, and a population of crossbred animals. A cohort of 1375 sheep sampled across 17 flocks, located in the Alentejo region (southern Portugal), was included in the analyses. RESULTS: Phenotypes were scored from 0 (healthy) to 5 (severe footrot) based on visual inspection of feet lesions, following the Modified Egerton System. Using a linear mixed model approach, three SNPs located on chromosome 24 reached genome-wide significance after a Bonferroni correction (p < 0.05). Additionally, six genome-wide suggestive SNPs were identified each on chromosomes 2, 4, 7, 8, 9 and 15. The annotation and KEGG pathway analyses showed that these SNPs are located within regions of candidate genes such as the nonsense mediated mRNA decay associated PI3K related kinase (SMG1) (chromosome 24) and the RALY RNA binding protein like (RALYL) (chromosome 9), both involved in immunity, and the heparan sulfate proteoglycan 2 (HSPG2) (chromosome 2) and the Thrombospodin 1 (THBS1) (chromosome 7) implicated in tissue repair and wound healing processes. CONCLUSION: This is the first attempt to identify molecular markers associated with footrot in Portuguese Merino sheep. These findings provide relevant information on a likely genetic association underlying footrot resistance/susceptibility and the potential candidate genes affecting this trait. Genetic selection strategies assisted on the information obtained from this study could enhance Merino sheep-breeding programs, in combination with farm management strategies, for a more effective and sustainable long-term solution for footrot control.

Social media addiction relationship with academic engagement in university students: The mediator role of self-esteem, depression, and anxiety.

This research analyzed how addiction to social media relates to academic engagement in university students, considering the mediating role of self-esteem, symptoms of depression, and anxiety. A quantitative methodology was used with a non-experimental-relational design. A set of questionnaires was applied to a non-probabilistic sample of 412 students enrolled at the National Autonomous University of Honduras. On average, participants use 4.83 different social media platforms at least once a week. Instagram and TikTok users report significantly higher levels of social media addiction, symptoms of depression, and anxiety compared to non-users. Directly, social media addiction does not significantly influence academic engagement scores. However, there are significant indirect inverse effects on academic engagement. Symptoms of depression and self-esteem mediate these effects. Social media addiction increases symptoms of depression, which in turn decreases academic engagement scores. Social media addiction decreases self-esteem, which serves as a variable that significantly increases academic engagement. Overall, findings suggest that social media addiction has a total inverse effect on academic engagement; symptoms of depression and self-esteem mediate this relationship. The implications of these findings are discussed.

Combined DFT and Kinetic Monte Carlo Study of UiO-66 Catalysts for γ-Valerolactone Production.

Zr-based metal-organic frameworks (MOFs) are excellent heterogeneous porous catalysts due to their thermal stability. Their tunability via node and linker modifications makes them amenable for theoretical studies on catalyst design. However, detailed benchmarks on MOF-based reaction mechanisms combined with kinetics analysis are still scarce. Thus, we here evaluate different computational models and density functional theory (DFT) methods followed by kinetic Monte Carlo studies for a case reaction relevant in biomass upgrading, i.e., the conversion of methyl levulinate to γ-valerolactone catalyzed by UiO-66. We show the impact of cluster versus periodic models, the importance of the DF of choice, and the direct comparison to experimental data via simulated kinetics data. Overall, we found that Perdew-Burke-Ernzerhof (PBE), a widely employed method in plane-wave periodic calculations, greatly overestimates reaction rates, while M06 with cluster models better fits the available experimental data and is recommended whenever possible.

Effect of temperature on the gas-phase reaction of CH3CN with OH radicals: experimental (T = 11.7-177.5 K) and computational (T = 10-400 K) kinetic study.

Acetonitrile (CH3CN) is present in the interstellar medium (ISM) in a variety of environments. However, at the ultracold temperatures of the ISM, radical-molecule reactions are not widely investigated because of the experimental handicap of getting organic molecules in the gas phase by conventional techniques. The CRESU (French acronym for Reaction Kinetics in a Uniform Supersonic Flow) technique solves this problem. For this reason, we present in this work the kinetic study of the gas-phase reaction of CH3CN with one of the most ubiquitous radicals, the hydroxyl (OH) radical, as a function of temperature (11.7-177.5 K). The kinetic technique employed to investigate the CH3CN + OH reaction was the pulsed laser photolysis-laser induced fluorescence. The rate coefficient for this reaction k(T) has been observed to drastically increase from 177.5 K to 107.0 K (about 2 orders of magnitude), while the increase in k(T) from 107.0 K to 11.7 K was milder (around 4 times). The temperature dependent expressions for k(T) are provided in the two distinct T-ranges, excluding the upper limit obtained for k(177.5 K): In addition, the rate coefficients estimated by the canonical competitive unified statistical (CCUS) theory show a similar behaviour to the experimental results, when evaluated within the high-pressure limit. This is consistent with the experimentally observed independence of k(T) with total gas density at selected temperatures. Astrochemical networks, such as the KIDA database or UMIST, do not include the CH3CN + OH reaction as a potential depletion process for acetonitrile in the ISM because the current studies predict very low rate coefficients at IS temperatures. According to the model (T = 10 K), the impact of the titled reaction on the abundances of CH3CN appears to be negligible in dark molecular clouds of the ISM (∼1% of the total depletion reactions included in UMIST network). With respect to the potential formation of the CH2CN radical in those environments, even in the most favourable scenario, where this radical could be formed in a 100% yield from the CH3CN + OH reaction, this route would only contribute around 2% to the current assumed formation routes by the UMIST network.

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.

BACKGROUND: The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19). METHODOLOGY: PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542. FINDINGS: In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias. INTERPRETATION: The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

Acute complications in open/miss primary and revision thoracolumbar spine surgery: a descriptive study of the most common complications and treatment of choice.

PURPOSE: Main question The aim of this study is to describe and analyze the frequency of acute perioperative (intraoperatively and 30 days after) complications of open/MISS thoracolumbar spine surgery. Secondary questions A) Describe the treatment of choice for every kind of complication mentioned. B) Perform a bibliographic search and compare the complications described and their frequency with those studied in the manuscript. METHODS: A retrospective cohort of 816 patients undergoing spinal surgery over a two year period was analyzed. Acute complications of 59 patients are described whether those with a greater number of levels required longer periods of hospitalization. RESULTS: The frequency of acute complications was 7.2%. The most common was infection (2.7%), followed by dural tear (1.7%), and screw malpositioning (1%), which is consistent with the current literature. No statistically significant results were observed when comparing the mean length of hospital stay among patients operated on a greater number of levels compared to the rest (P: 0.344; 95% CI: -3.88-10.93). CONCLUSIONS: The subsidiary patient of spinal surgery is getting older and has more comorbidities, and therefore, has a higher risk of complications. Although there are models predicting the risk of complications, they are not used in routine clinical practice. It would be necessary to unify the main criteria and establish guidelines for risk detection and therapeutic algorithms based on new high-quality studies.

Better individual-level risk models can improve the targeting and life-saving potential of early-mortality interventions.

Infant mortality remains high and uneven in much of sub-Saharan Africa. Even low-cost, highly effective therapies can only save lives in proportion to how successfully they can be targeted to those children who, absent the treatment, would have died. This places great value on maximizing the accuracy of any targeting or means-testing algorithm. Yet, the interventions that countries deploy in hopes of reducing mortality are often targeted based on simple models of wealth or income or a few additional variables. Examining 22 countries in sub-Saharan Africa, we illustrate the use of flexible (machine learning) risk models employing up to 25 generally available pre-birth variables from the Demographic and Health Surveys. Using these models, we construct risk scores such that the 10 percent of the population at highest risk account for 15-30 percent of infant mortality, depending on the country. Successful targeting in these models turned on several variables other than wealth, while models that employ only wealth data perform little or no better than chance. Consequently, employing such data and models to predict high-risk births in the countries studied flexibly could substantially improve the targeting and thus the life-saving potential of existing interventions.

The Influence of Sleep Disorders on Neurobiological Structures and Cognitive Processes in Pediatric Population with ASD and Epilepsy: A Systematic Review.

Autism Spectrum Disorder (ASD) and epilepsy are increasingly prevalent comorbidities in our society. These two disorders are often accompanied by other comorbidities, such as sleep disorders, significantly impacting the quality of life of individuals with ASD and epilepsy. To date, clinical approaches have primarily been descriptive in nature. Therefore, this study aimed to analyze the relationship between ASD, epilepsy, and sleep disorders, exploring neurobiological dysfunctions and cognitive alterations. A total of 22 scientific articles were selected using a systematic literature review following the criteria established using the PRISMA model. The selected articles were gathered from major databases: Medline, PubMed, PsycINFO, Google Scholar, and Web of Science. Inclusion criteria specified that study participants had an official diagnosis of ASD, the article precisely described the evaluation parameters used in the study participants, and individual characteristics of the sleep disorders of the study participants were specified. The results indicate, firstly, that the primary cause of sleep disorders in this population is directly linked to abnormal serotonin behaviors. Secondly, significant alterations in memory, attention, and hyperactivity were observed. In conclusion, sleep disorders negatively impact the quality of life and neurocognitive development of the pediatric population with ASD and epilepsy.

Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas.

The prognostic and predictive role of tumor-infiltrating lymphocytes (TILs) has been demonstrated in various neoplasms. The few publications that have addressed this topic in high-grade serous ovarian carcinoma (HGSOC) have approached TIL quantification from a semiquantitative standpoint. Clinical correlation studies, therefore, need to be conducted based on more accurate TIL quantification. We created a machine learning system based on H&E-stained sections using 76 molecularly and clinically well-characterized advanced HGSOC. This system enabled immune cell classification. These immune parameters were subsequently correlated with overall survival (OS) and progression-free survival (PFI). An intense colonization of the tumor cords by TILs was associated with a better prognosis. Moreover, the multivariate analysis showed that the intraephitelial (ie) TILs concentration was an independent and favorable prognostic factor both for OS (p = 0.02) and PFI (p = 0.001). A synergistic effect between complete surgical cytoreduction and high levels of ieTILs was evidenced, both in terms of OS (p = 0.0005) and PFI (p = 0.0008). We consider that digital analysis with machine learning provided a more accurate TIL quantification in HGSOC. It has been demonstrated that ieTILs quantification in H&E-stained slides is an independent prognostic parameter. It is possible that intraepithelial TIL quantification could help identify candidate patients for immunotherapy.

The Relevance of Life Cycle Assessment Tools in the Development of Emerging Decarbonization Technologies.

The development of emerging decarbonization technologies requires advanced tools for decision-making that incorporate the environmental perspective from the early design. Today, Life Cycle Assessment (LCA) is the preferred tool to promote sustainability in the technology development, identifying environmental challenges and opportunities and defining the final implementation pathways. So far, most environmental studies related to decarbonization emerging solutions are still limited to midpoint metrics, mainly the carbon footprint, with global sustainability implications being relatively unexplored. In this sense, the Planetary Boundaries (PBs) have been recently proposed to identify the distance to the ideal reference state. Hence, PB-LCA methodology can be currently applied to transform the resource use and emissions to changes in the values of PB control variables. This study shows a complete picture of the LCA's role in developing emerging technologies. For this purpose, a case study based on the electrochemical conversion of CO2 to formic acid is used to show the possibilities of LCA approaches highlighting the potential pitfalls when going beyond greenhouse gas emission reduction and obtaining the absolute sustainability level in terms of four PBs.

Case Report: Characterization of known (c.607G>C) and novel (c.416C>G) ELANE mutations in two Mexican families with congenital neutropenia.

The most common causes of congenital neutropenia are mutations in the ELANE (Elastase, Neutrophil Expressed) gene (19p13.3), mostly in exon 5 and the distal portion of exon 4, which result in different clinical phenotypes of neutropenia. Here, we report two pathogenic mutations in ELANE, namely, c.607G>C (p.Gly203Arg) and a novel variant c.416C>G (p.Pro139Arg), found in two Mexican families ascertained via patients with congenital neutropenia who responded positively to the granulocyte colony-stimulating factor (G-CSF) treatment. These findings highlight the usefulness of identifying variants in patients with inborn errors of immunity for early clinical management and the need to rule out mosaicism in noncarrier parents with more than one case in the family.