Early childhood development strategy for the world's children with disabilities.

Early childhood is foundational for optimal and inclusive lifelong learning, health and well-being. Young children with disabilities face substantial risks of sub-optimal early childhood development (ECD), requiring targeted support to ensure equitable access to lifelong learning opportunities, especially in low- and middle-income countries. Although the Sustainable Development Goals, 2015-2030 (SDGs) emphasise inclusive education for children under 5 years with disabilities, there is no global strategy for achieving this goal since the launch of the SDGs. This paper explores a global ECD framework for children with disabilities based on a review of national ECD programmes from different world regions and relevant global ECD reports published since 2015. Available evidence suggests that any ECD strategy for young children with disabilities should consists of a twin-track approach, strong legislative support, guidelines for early intervention, family involvement, designated coordinating agencies, performance indicators, workforce recruitment and training, as well as explicit funding mechanisms and monitoring systems. This approach reinforces parental rights and liberty to choose appropriate support pathway for their children. We conclude that without a global disability-focussed ECD strategy that incorporates these key features under a dedicated global leadership, the SDGs vision and commitment for the world's children with disabilities are unlikely to be realised.

Increased Incidence of Vestibular Disorders in Patients With SARS-CoV-2.

Objective: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population. Study Design: Retrospective. Setting: Clinical data in the National COVID Cohort Collaborative database (N3C). Methods: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period. Results: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29-2.50; P < 0.001), alpha (OR, 3.63; CI, 3.48-3.78; P < 0.001), delta (OR, 3.03; CI, 2.94-3.12; P < 0.001), omicron 21K variant (OR, 2.97; CI, 2.90-3.04; P < 0.001), and omicron 23A variant (OR, 8.80; CI, 8.35-9.27; P < 0.001). Conclusions: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings.

The N-terminal domain of Type IV-A1 CRISPR-associated DinG is vulnerable to proteolysis.

CasDinG is an ATP-dependent 5'-3' DNA helicase essential for bacterial Type IV-A1 CRISPR associated immunity. CasDinG contains an essential N-terminal domain predicted to bind DNA. To better understand the role of the N-terminal domain, we attempted to co-crystallize CasDinG with DNA substrates. We successfully crystallized CasDinG in a tightly packed, crystal conformation with previously unobserved unit cell dimensions. However, the structure lacked electron density for a bound DNA substrate and the CasDinG N-terminal domain. Additionally, the tight crystal packing disallowed space for the N-terminal domain, indicating that the N-terminal domain was proteolyzed before crystallization. Follow up experiments revealed that the N-terminal domain of CasDinG is proteolyzed after a few days at room temperature, but is protected from proteolysis at 4°C. These data provide a distinct x-ray crystal structure of CasDinG and indicate the essential N-terminal domain of CasDinG is prone to proteolysis.

Gut microbiota-mediated polyphenol metabolism is restrained by parasitic whipworm infection and associated with altered immune function in mice.

Polyphenols are phytochemicals commonly found in plant-based diets which have demonstrated immunomodulatory and anti-inflammatory properties. However, the interplay between polyphenols and pathogens at mucosal barrier surfaces has not yet been elucidated in detail. Here, we show that proanthocyanidin (PAC) polyphenols interact with gut parasites to influence immune function and gut microbial-derived metabolites in mice. PAC intake inhibited mastocytosis during infection with the small intestinal roundworm Heligmosomoides polygyrus, and altered the host tissue transcriptome at the site of infection with the large intestinal whipworm Trichuris muris, with a notable enhancement of type-1 inflammatory and interferon-driven gene pathways. In the absence of infection, PAC intake promoted the expansion of Turicibacter within the gut microbiota, increased fecal short chain fatty acids, and enriched phenolic metabolites such as phenyl-γ-valerolactones in the cecum. However, these putatively beneficial effects were reduced in PAC-fed mice infected with T. muris, suggesting concomitant parasite infection can attenuate gut microbial-mediated PAC catabolism. Collectively, our results suggest an inter-relationship between a phytonutrient and infection, whereby PAC may augment parasite-induced inflammation (most prominently with the cecum dwelling T. muris), and infection may abrogate the beneficial effects of health-promoting phytochemicals.

Social Determinants of Health and Limitation of Life-Sustaining Therapy in Neurocritical Care: A CHoRUS Pilot Project.

BACKGROUND: Social determinants of health (SDOH) have been linked to neurocritical care outcomes. We sought to examine the extent to which SDOH explain differences in decisions regarding life-sustaining therapy, a key outcome determinant. We specifically investigated the association of a patient's home geography, individual-level SDOH, and neighborhood-level SDOH with subsequent early limitation of life-sustaining therapy (eLLST) and early withdrawal of life-sustaining therapy (eWLST), adjusting for admission severity. METHODS: We developed unique methods within the Bridge to Artificial Intelligence for Clinical Care (Bridge2AI for Clinical Care) Collaborative Hospital Repository Uniting Standards for Equitable Artificial Intelligence (CHoRUS) program to extract individual-level SDOH from electronic health records and neighborhood-level SDOH from privacy-preserving geomapping. We piloted these methods to a 7 years retrospective cohort of consecutive neuroscience intensive care unit admissions (2016-2022) at two large academic medical centers within an eastern Massachusetts health care system, examining associations between home census tract and subsequent occurrence of eLLST and eWLST. We matched contextual neighborhood-level SDOH information to each census tract using public data sets, quantifying Social Vulnerability Index overall scores and subscores. We examined the association of individual-level SDOH and neighborhood-level SDOH with subsequent eLLST and eWLST through geographic, logistic, and machine learning models, adjusting for admission severity using admission Glasgow Coma Scale scores and disorders of consciousness grades. RESULTS: Among 20,660 neuroscience intensive care unit admissions (18,780 unique patients), eLLST and eWLST varied geographically and were independently associated with individual-level SDOH and neighborhood-level SDOH across diagnoses. Individual-level SDOH factors (age, marital status, and race) were strongly associated with eLLST, predicting eLLST more strongly than admission severity. Individual-level SDOH were more strongly predictive of eLLST than neighborhood-level SDOH. CONCLUSIONS: Across diagnoses, eLLST varied by home geography and was predicted by individual-level SDOH and neighborhood-level SDOH more so than by admission severity. Structured shared decision-making tools may therefore represent tools for health equity. Additionally, these findings provide a major warning: prognostic and artificial intelligence models seeking to predict outcomes such as mortality or emergence from disorders of consciousness may be encoded with self-fulfilling biases of geography and demographics.

Frequency of Persistent Opioid Use 6 Months After Exposure to IV Opioids in the Emergency Department: A Prospective Cohort Study.

BACKGROUND: As rates of opioid use disorder in the general population have increased, some have questioned whether IV opioids should be used routinely for treatment of acute severe pain in the emergency department (ED). OBJECTIVES: We determined the incidence of persistent opioid use among opioid-naïve patients exposed to IV opioids in the ED. METHODS: This was a prospective observational cohort study conducted in two EDs in the Bronx, NY. Opioid-naïve adults with severe pain who received IV opioids in the ED were followed-up 6 months later by telephone interview and review of the state opioid prescription database. We defined persistent opioid use as filling 6 or more prescriptions for opioids in the 6 months following the ED visit or an average of one prescription per month. RESULTS: We screened 1555 patients. Of these, 506 patients met entry criteria and provided analyzable data. Morphine was the IV opioid most frequently administered in the ED (478, 94%), followed by hydromorphone (20, 4%). Of the 506, 8 (2%) received both IV morphine and hydromorphone and 63 (12%) participants were prescribed an opioid for use after the ED visit. One patient/506 (0%) met our apriori criteria for persistent opioid use within 6 months. CONCLUSION: Among 506 opioid naïve ED patients administered IV opioids for acute severe pain, only one used opioids persistently during the subsequent 6 months.

Visualization strategies to aid interpretation of high-dimensional genotoxicity data.

This article describes a range of high-dimensional data visualization strategies that we have explored for their ability to complement machine learning algorithm predictions derived from MultiFlow® assay results. For this exercise, we focused on seven biomarker responses resulting from the exposure of TK6 cells to each of 126 diverse chemicals over a range of concentrations. Obviously, challenges associated with visualizing seven biomarker responses were further complicated whenever there was a desire to represent the entire 126 chemical data set as opposed to results from a single chemical. Scatter plots, spider plots, parallel coordinate plots, hierarchical clustering, principal component analysis, toxicological prioritization index, multidimensional scaling, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection are each considered in turn. Our report provides a comparative analysis of these techniques. In an era where multiplexed assays and machine learning algorithms are becoming the norm, stakeholders should find some of these visualization strategies useful for efficiently and effectively interpreting their high-dimensional data.

Effect of 20 mph speed limits on traffic injuries in Edinburgh, UK: a natural experiment and modelling study.

INTRODUCTION: There is limited research evaluating 20 mph speed limit interventions, and long-term assessments are seldom conducted either globally or within the UK. This study evaluated the impact of the phased 20 mph speed limit implementation on road traffic collisions and casualties in the City of Edinburgh, UK over approximately 3 years post implementation. METHODS: We used four sets of complementary analyses for collision and casualty rates. First, we compared rates for road segments changing to 20 mph against those at 30 mph. Second, we compared rates for the seven implementation zones in the city against paired control zones. Third, we investigated citywide casualty rate trends using generalised additive model. Finally, we used simulation modelling to predict casualty rate changes based on changes in observed speeds. RESULTS: We found a 10% (95% CI -19% to 0%) greater reduction in casualties (8% for collisions) for streets that changed to 20 mph compared with those staying at 30 mph. However, the reduction was similar, 8% (95% CI -22% to 5%) for casualties (10% collisions), in streets that were already at 20 mph. In the implementation zones, we found a 20% (95% CI -22% to -8%) citywide reduction in casualties (22% for collisions) compared with control zones; this compared with a predicted 10% (95% CI -18% to -2%) reduction in injuries based on the changes in speed and traffic volume. Citywide casualties dropped 17% (95% CI 13% to 22%) 3 years post implementation, accounting for trend. CONCLUSION: Our results indicate that the introduction of 20 mph limits resulted in a reduction in collisions and casualties 3 years post implementation. However, the effect exceeded expectations from changes in speed alone, possibly due to a wider network effect.

Synthetic phantoms enable calibration between abattoir based dual energy X-ray absorptiometers used for prediction of lamb carcass composition.

Dual energy x-ray absorptiometry (DXA) devices were installed at two Australian abattoirs to predict computed tomography (CT) determined fat % and lean % of lamb carcasses. This study tested three algorithms developed for these devices, termed ß1, ß2 and ß3, and assessed their accuracy and precision in predicting CT composition. Algorithm ß3 included the use of a plastic phantom calibration block scanned by both DXA devices to adjust prediction equations, resulting in superior accuracy to the algorithms without phantom calibration (ß1 and ß2). When compared to the gold-standard CT composition, the bias of the DXA predictions was lowest when using algorithm ß3 at the two sites (-1.17%, -0.49% for fat %, 0.11%, -0.37% for lean %). The difference of DXA composition predictions between sites was lowest when using algorithm ß3, which demonstrated between site differences of 0.59 CT fat %, and 0.46 CT lean%. In contrast, algorithm ß1 and ß2 produced differences of 23.7% and 30.8% for CT fat, and 17.3% and 21.9% for CT lean between the two DXA devices. There was a small difference of 0.78% between the fat predictions of the first DXA image compared to the second DXA image for each carcass. The precision of predictions improved slightly using algorithm ß3. This work demonstrates that the in-line DXA systems can produce comparable results across sites.

Impact of temperature on physical and cognitive performance in elite female football players during intermittent exercise.

There is limited research on female football players, especially related to their physical and cognitive performance under different climactic conditions. We analyzed the impact of a hot environmental temperature on physical performance and anticipation in elite female football players during a fatigue-inducing intermittent protocol. Elite female players (n = 21) performed the countermovement jump (CMJ) and responded to filmed sequences of offensive play under two distinct environmental temperatures (i.e., mild environment temperature- 20°C and 30% rh versus hot environment temperature- 38°C and 80% rh), interspersed by 1-week interval. Linear mixed models were used. CMJ performance declined following the intermittent protocol on both temperature conditions (p < 0.05). Moreover, there were significant main effects for protocol on CMJ speed (m/s) (p = 0.001; ηp 2 = 0.12), CMJ power (p = 0.002; ηp 2 = 0.11), and CMJ Heightmax (p = 0.002; ηp 2 = 0.12). After performing the intermittent protocol, exposure to a hot temperature caused a greater decline in anticipation accuracy (mild temperature = 64.41% vs. hot temperature = 53.44%; p < 0.001). Our study shows impaired performance in elite female football players following an intermittent protocol under hot compared with mild environmental conditions. We report decreased performance in both CMJ and anticipation performance under hotter conditions. The results reveal that exposure to hot temperatures had a negative effect on the accuracy of their anticipatory behaviors. We consider the implication of the work for research and training interventions.

Cardiac arrhythmia and epilepsy genetic variants in sudden unexpected death in epilepsy.

Introduction: Sudden Unexpected Death in Epilepsy (SUDEP) is the leading epilepsy-related cause of death, affecting approximately 1 per 1,000 individuals with epilepsy per year. Genetic variants that affect autonomic function, such as genes associated with cardiac arrhythmias, may predispose people with epilepsy to greater risk of both sudden cardiac death and SUDEP. Advances in next generation sequencing allow for the exploration of gene variants as potential biomarkers. Methods: Genetic testing for the presence of cardiac arrhythmia and epilepsy gene variants was performed via genetic panels in 39 cases of SUDEP identified via autopsy by the Ontario Forensic Pathology Service. Variants were summarized by in-silico evidence for pathogenicity from 4 algorithms (SIFT, PolyPhen-2, PROVEAN, Mutation Taster) and allele frequencies in the general population (GnomAD). A maximum credible population allele frequency of 0.00004 was calculated based on epilepsy prevalence and SUDEP incidence to assess whether a variant was compatible with a pathogenic interpretation. Results: Median age at the time of death was 33.3 years (range: 2, 60). Fifty-nine percent (n=23) were male. Gene panels detected 62 unique variants in 45 genes: 19 on the arrhythmia panel and 26 on the epilepsy panel. At least one variant was identified in 28 (72%) of decedents. Missense mutations comprised 57 (92%) of the observed variants. At least three in silico models predicted 12 (46%) cardiac arrhythmia panel missense variants and 20 (65%) epilepsy panel missense variants were pathogenic. Population allele frequencies were <0.00004 for 11 (42%) of the cardiac variants and 10 (32%) of the epilepsy variants. Together, these metrics identified 13 SUDEP variants of interest. Discussion: Nearly three-quarters of decedents in this SUDEP cohort carried variants in comprehensive epilepsy or cardiac arrhythmia gene panels, with more than a third having variants in both panels. The proportion of decedents with cardiac variants aligns with recent studies of the disproportionate cardiac burden the epilepsy community faces compared to the general population and suggests a possible cardiac contribution to epilepsy mortality. These results identified 13 priority targets for future functional studies of these genes potential role in sudden death and demonstrates the necessity for further exploration of potential genetic contributions to SUDEP.

A Systematic Genotoxicity Assessment of a Suite of Metal Oxide Nanoparticles Reveals Their DNA Damaging and Clastogenic Potential.

Metal oxide nanoparticles (MONP/s) induce DNA damage, which is influenced by their physicochemical properties. In this study, the high-throughput CometChip and micronucleus (MicroFlow) assays were used to investigate DNA and chromosomal damage in mouse lung epithelial cells induced by nano and bulk sizes of zinc oxide, copper oxide, manganese oxide, nickel oxide, aluminum oxide, cerium oxide, titanium dioxide, and iron oxide. Ionic forms of MONPs were also included. The study evaluated the impact of solubility, surface coating, and particle size on response. Correlation analysis showed that solubility in the cell culture medium was positively associated with response in both assays, with the nano form showing the same or higher response than larger particles. A subtle reduction in DNA damage response was observed post-exposure to some surface-coated MONPs. The observed difference in genotoxicity highlighted the mechanistic differences in the MONP-induced response, possibly influenced by both particle stability and chemical composition. The results highlight that combinations of properties influence response to MONPs and that solubility alone, while playing an important role, is not enough to explain the observed toxicity. The results have implications on the potential application of read-across strategies in support of human health risk assessment of MONPs.

A Web-Based Peer Support Network to Help Care Partners of People With Serious Illness: Co-Design Study.

BACKGROUND: Care partners of people with serious illness experience significant challenges and unmet needs during the patient's treatment period and after their death. Learning from others with shared experiences can be valuable, but opportunities are not consistently available. OBJECTIVE: This study aims to design and prototype a regional, facilitated, and web-based peer support network to help active and bereaved care partners of persons with serious illness be better prepared to cope with the surprises that arise during serious illness and in bereavement. METHODS: An 18-member co-design team included active care partners and those in bereavement, people who had experienced serious illness, regional health care and support partners, and clinicians. It was guided by facilitators and peer network subject-matter experts. We conducted design exercises to identify the functions and specifications of a peer support network. Co-design members independently prioritized network specifications, which were incorporated into an early iteration of the web-based network. RESULTS: The team prioritized two functions: (1) connecting care partners to information and (2) facilitating emotional support. The design process generated 24 potential network specifications to support these functions. The highest priorities included providing a supportive and respectful community; connecting people to trusted resources; reducing barriers to asking for help; and providing frequently asked questions and responses. The network platform had to be simple and intuitive, provide technical support for users, protect member privacy, provide publicly available information and a private discussion forum, and be easily accessible. It was feasible to enroll members in the ConnectShareCare web-based network over a 3-month period. CONCLUSIONS: A co-design process supported the identification of critical features of a peer support network for care partners of people with serious illnesses in a rural setting, as well as initial testing and use. Further testing is underway to assess the long-term viability and impact of the network.

A Strategy To Support Perinatal Mental Health By Collaborating With Tribal Communities In Montana.

Among Indigenous women and birthing people, reported rates of perinatal mental health complications are consistently higher than in the general US population. However, perinatal mental health programs and interventions tend to focus on the general population and do not account for the unique experiences and worldviews of Indigenous Peoples. We highlight a collaborative strategy employed by a Montana nonprofit to engage Tribal communities in completing a statewide online resource guide designed to help pregnant and parenting families find resources, including mental health and substance use treatment options, within and beyond their local communities. Based on this strategy, cultural resources relevant to Tribal communities were added to the resource guide. Agencies committed to addressing perinatal mental health disparities among Indigenous populations should consider similar strategies to share power with Tribal communities and collaboratively create culturally congruent programs and interventions.

Gestational Diabetes and Subsequent Metabolic Dysfunction: An National Health and Nutrition Examination Survey Analysis (2011-2018).

Background: Gestational diabetes mellitus (GDM) complicates ∼10% of pregnancies, with the highest rates among Asian women. Evidence suggests that GDM is associated with an increased risk for future chronic health conditions, yet data for Asian women are sparse. We explored the association between prior GDM and metabolic dysfunction with nationally representative data to obtain Asian-specific estimates. Methods: For this cross-sectional study, data were drawn from the National Health and Nutrition Examination Survey for 7195 women with a prior pregnancy. GDM (yes/no) was defined using the question "During pregnancy, were you ever told by a doctor or other health professional that you had diabetes, sugar diabetes, or gestational diabetes?." Current metabolic dysfunction (yes/no) was based on having at least one of four indicators: systolic blood pressure (SBP, ≥130 mmHg), waist circumference (≥88 cm), high-density lipoprotein (HDL) cholesterol (<50 mg/dL), and glycosylated hemoglobin (HbA1c) (≥6.5%). Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between prior GDM and metabolic outcomes, overall and by race. Models included sampling weights and demographic and behavioral factors. Results: Overall, women with prior GDM had 46% greater odds of high waist circumference (OR: 1.5; 95% CI: 1.1-2.0) and 200% greater odds (OR: 3.0; 95% CI: 2.1-4.2) of high HbA1c. Prior GDM was not associated with high blood pressure or low HDL cholesterol. In race-specific analyses, prior GDM was associated with increased risk of elevated HbA1c among Asian (OR: 6.6; 95% CI: 2.5-17.2), Mexican American (OR: 3.0; 95% CI: 1.5-5.8), Black (OR: 3.0; 95% CI: 1.7-5.5), and White (OR: 2.6; 95% CI: 1.5-4.6) women. Prior GDM was associated with elevated SBP among Mexican American women and low HDL among Black women. Discussion: Prior GDM is associated with elevated HbA1c among all women, yet is a stronger predictor of elevated HbA1c among Asian women than other women. Race-specific associations between prior GDM and metabolic dysfunction were observed among Mexican American and Black women. Further research is warranted to understand the observed race/ethnic-specific associations.

A 50-gene biomarker identifies estrogen receptor-modulating chemicals in a microarray compendium.

High throughput transcriptomics (HTTr) profiling has the potential to rapidly and comprehensively identify molecular targets of environmental chemicals that can be linked to adverse outcomes. We describe here the construction and characterization of a 50-gene expression biomarker designed to identify estrogen receptor (ER) active chemicals in HTTr datasets. Using microarray comparisons, the genes in the biomarker were identified as those that exhibited consistent directional changes when ER was activated (4 ER agonists; 4 ESR1 gene constitutively active mutants) and opposite directional changes when ER was suppressed (4 antagonist treatments; 4 ESR1 knockdown experiments). The biomarker was evaluated as a predictive tool using the Running Fisher algorithm by comparison to annotated gene expression microarray datasets including those evaluating the transcriptional effects of hormones and chemicals in MCF-7 cells. Depending on the reference dataset used, the biomarker had a predictive accuracy for activation of up to 96%. To demonstrate applicability for HTTr data analysis, the biomarker was used to identify ER activators in a set of 15 chemicals that are considered potential bisphenol A (BPA) alternatives examined at up to 10 concentrations in MCF-7 cells and analyzed by full-genome TempO-Seq. Using benchmark dose (BMD) modeling, the biomarker genes stratified the ER potency of BPA alternatives consistent with previous studies. These results demonstrate that the ER biomarker can be used to accurately identify ER activators in transcript profile data derived from MCF-7 cells.

Cystatin from the helminth Ascaris lumbricoides upregulates mevalonate and cholesterol biosynthesis pathways and immunomodulatory genes in human monocyte-derived dendritic cells.

Background: Ascaris lumbricoides cystatin (Al-CPI) prevents the development of allergic airway inflammation and dextran-induced colitis in mice models. It has been suggested that helminth-derived cystatins inhibit cathepsins in dendritic cells (DC), but their immunomodulatory mechanisms are unclear. We aimed to analyze the transcriptional profile of human monocyte-derived DC (moDC) upon stimulation with Al-CPI to elucidate target genes and pathways of parasite immunomodulation. Methods: moDC were generated from peripheral blood monocytes from six healthy human donors of Denmark, stimulated with 1 µM of Al-CPI, and cultured for 5 hours at 37°C. RNA was sequenced using TrueSeq RNA libraries and the NextSeq 550 v2.5 (75 cycles) sequencing kit (Illumina, Inc). After QC, reads were aligned to the human GRCh38 genome using Spliced Transcripts Alignment to a Reference (STAR) software. Differential expression was calculated by DESEq2 and expressed in fold changes (FC). Cell surface markers and cytokine production by moDC were evaluated by flow cytometry. Results: Compared to unstimulated cells, Al-CPI stimulated moDC showed differential expression of 444 transcripts (|FC| ≥1.3). The top significant differences were in Kruppel-like factor 10 (KLF10, FC 3.3, PBH = 3 x 10-136), palladin (FC 2, PBH = 3 x 10-41), and the low-density lipoprotein receptor (LDLR, FC 2.6, PBH = 5 x 10-41). Upregulated genes were enriched in regulation of cholesterol biosynthesis by sterol regulatory element-binding proteins (SREBP) signaling pathways and immune pathways. Several genes in the cholesterol biosynthetic pathway showed significantly increased expression upon Al-CPI stimulation, even in the presence of lipopolysaccharide (LPS). Regarding the pathway of negative regulation of immune response, we found a significant decrease in the cell surface expression of CD86, HLA-DR, and PD-L1 upon stimulation with 1 µM Al-CPI. Conclusion: Al-CPI modifies the transcriptome of moDC, increasing several transcripts encoding enzymes involved in cholesterol biosynthesis and SREBP signaling. Moreover, Al-CPI target several transcripts in the TNF-alpha signaling pathway influencing cytokine release by moDC. In addition, mRNA levels of genes encoding KLF10 and other members of the TGF beta and the IL-10 families were also modified by Al-CPI stimulation. The regulation of the mevalonate pathway and cholesterol biosynthesis suggests new mechanisms involved in DC responses to helminth immunomodulatory molecules.

Empirical Characterization of False Discovery Rates of Differentially Expressed Genes and Transcriptomic Benchmark Concentrations in Zebrafish Embryos.

High-throughput transcriptomics (HTTr) is increasingly applied to zebrafish embryos to survey the toxicological effects of environmental chemicals. Before the adoption of this approach in regulatory testing, it is essential to characterize background noise in order to guide experimental designs. We thus empirically quantified the HTTr false discovery rate (FDR) across different embryo pool sizes, sample sizes, and concentration groups for toxicology studies. We exposed zebrafish embryos to 0.1% dimethyl sulfoxide (DMSO) for 5 days. Pools of 1, 5, 10, and 20 embryos were created (n = 24 samples for each pool size). Samples were sequenced on the TempO-Seq platform and then randomly assigned to mock treatment groups before differentially expressed gene (DEG), pathway, and benchmark concentration (BMC) analyses. Given that all samples were treated with DMSO, any significant DEGs, pathways, or BMCs are false positives. As expected, we found decreasing FDRs for DEG and pathway analyses with increasing pool and sample sizes. Similarly, FDRs for BMC analyses decreased with increasing pool size and concentration groups, with more stringent BMC premodel filtering reducing BMC FDRs. Our study provides foundational data for determining appropriate experiment designs for regulatory toxicity testing with HTTr in zebrafish embryos.

Bacillus subtilis-597 induces changes in lung pathology and inflammation during influenza A virus infection in pigs.

In recent years, it has become apparent that imbalances in the gastrointestinal system can impact organs beyond the intestine such as the lungs. Given the established ability of probiotics to modulate the immune system by interacting with gastrointestinal cells, our research aimed to investigate whether administering the probiotic strain Bacillus subtilis-597 could mitigate the outcome of influenza virus infection in pigs. Pigs were fed a diet either with or without the probiotic strain B. subtilis-597 for 14 days before being intranasally inoculated with a swine influenza A H1N2 strain (1 C.2 lineage). Throughout the study, we collected fecal samples, blood samples, and nasal swabs to examine viral shedding and immune gene expression. After seven days of infection, the pigs were euthanized, and lung and ileum tissues were collected for gene expression analysis and pathological examination. Our findings indicate that the administration of B. subtilis-597 exhibit potential in reducing lung lesions, possibly attributable to a general suppression of the immune system as indicated by reduced C-reactive protein (CRP) levels in serum, decreased expression of interferon-stimulated genes (ISGs), and localized reduction of the inflammatory marker serum amyloid A (SAA) in ileum tissue. Notably, the immune-modulatory effects of B. subtilis-597 appeared to be unrelated to the gastrointestinal microbiota, as the composition remained unaltered by both the influenza infection and the administration of B. subtilis-597.