DPYD genetic polymorphisms in non-European patients with severe fluoropyrimidine-related toxicity: a systematic review.

BACKGROUND: Pre-treatment DPYD screening is mandated in the UK and EU to reduce the risk of severe and potentially fatal fluoropyrimidine-related toxicity. Four DPYD gene variants which are more prominently found in Europeans are tested. METHODS: Our systematic review in patients of non-European ancestry followed PRISMA guidelines to identify relevant articles up to April 2023. Published in silico functional predictions and in vitro functional data were also extracted. We also undertook in silico prediction for all DPYD variants identified. RESULTS: In 32 studies, published between 1998 and 2022, 53 DPYD variants were evaluated in patients from 12 countries encompassing 5 ethnic groups: African American, East Asian, Latin American, Middle Eastern, and South Asian. One of the 4 common European DPYD variants, c.1905+1G>A, is also present in South Asian, East Asian and Middle Eastern patients with severe fluoropyrimidine-related toxicity. There seems to be relatively strong evidence for the c.557A>G variant, which is found in individuals of African ancestry, but is not currently included in the UK genotyping panel. CONCLUSION: Extending UK pre-treatment DPYD screening to include variants that are present in some non-European ancestry groups will improve patient safety and reduce race and health inequalities in ethnically diverse societies.

Amivantamab plus lazertinib versus osimertinib in first-line EGFR-mutant advanced non-small-cell lung cancer with biomarkers of high-risk disease: a secondary analysis from MARIPOSA.

BACKGROUND: Amivantamab-lazertinib significantly prolonged progression-free survival (PFS) versus osimertinib in patients with epidermal growth factor receptor (EGFR)-mutant advanced non-small-cell lung cancer [NSCLC; hazard ratio (HR) 0.70; P < 0.001], including those with a history of brain metastases (HR 0.69). Patients with TP53 co-mutations, detectable circulating tumor DNA (ctDNA), baseline liver metastases, and those without ctDNA clearance on treatment have poor prognoses. We evaluated outcomes in these high-risk subgroups. PATIENTS AND METHODS: This analysis included patients with treatment-naive, EGFR-mutant advanced NSCLC randomized to amivantamab-lazertinib (n = 429) or osimertinib (n = 429) in MARIPOSA. Pathogenic alterations were identified by next-generation sequencing (NGS) of baseline blood ctDNA with Guardant360 CDx. Ex19del and L858R ctDNA in blood was analyzed at baseline and cycle 3 day 1 (C3D1) with Biodesix droplet digital polymerase chain reaction (ddPCR). RESULTS: Baseline ctDNA for NGS of pathogenic alterations was available for 636 patients (amivantamab-lazertinib, n = 320; osimertinib, n = 316). Amivantamab-lazertinib improved median PFS (mPFS) versus osimertinib for patients with TP53 co-mutations {18.2 versus 12.9 months; HR 0.65 [95% confidence interval (CI) 0.48-0.87]; P = 0.003} and for patients with wild-type TP53 [22.1 versus 19.9 months; HR 0.75 (95% CI 0.52-1.07)]. In patients with EGFR-mutant, ddPCR-detectable baseline ctDNA, amivantamab-lazertinib significantly prolonged mPFS versus osimertinib [20.3 versus 14.8 months; HR 0.68 (95% CI 0.53-0.86); P = 0.002]. Amivantamab-lazertinib significantly improved mPFS versus osimertinib in patients without ctDNA clearance at C3D1 [16.5 versus 9.1 months; HR 0.49 (95% CI 0.27-0.87); P = 0.015] and with clearance [24.0 versus 16.5 months; HR 0.64 (95% CI 0.48-0.87); P = 0.004]. Amivantamab-lazertinib significantly prolonged mPFS versus osimertinib among randomized patients with [18.2 versus 11.0 months; HR 0.58 (95% CI 0.37-0.91); P = 0.017] and without baseline liver metastases [24.0 versus 18.3 months; HR 0.74 (95% CI 0.60-0.91); P = 0.004]. CONCLUSIONS: Amivantamab-lazertinib effectively overcomes the effect of high-risk features and represents a promising new standard of care for patients with EGFR-mutant advanced NSCLC.

Being precise with anticoagulation to reduce adverse drug reactions: are we there yet?

Anticoagulants are potent therapeutics widely used in medical and surgical settings, and the amount spent on anticoagulation is rising. Although warfarin remains a widely prescribed oral anticoagulant, prescriptions of direct oral anticoagulants (DOACs) have increased rapidly. Heparin-based parenteral anticoagulants include both unfractionated and low molecular weight heparins (LMWHs). In clinical practice, anticoagulants are generally well tolerated, although interindividual variability in response is apparent. This variability in anticoagulant response can lead to serious incident thrombosis, haemorrhage and off-target adverse reactions such as heparin-induced thrombocytopaenia (HIT). This review seeks to highlight the genetic, environmental and clinical factors associated with variability in anticoagulant response, and review the current evidence base for tailoring the drug, dose, and/or monitoring decisions to identified patient subgroups to improve anticoagulant safety. Areas that would benefit from further research are also identified. Validated variants in VKORC1, CYP2C9 and CYP4F2 constitute biomarkers for differential warfarin response and genotype-informed warfarin dosing has been shown to reduce adverse clinical events. Polymorphisms in CES1 appear relevant to dabigatran exposure but the genetic studies focusing on clinical outcomes such as bleeding are sparse. The influence of body weight on LMWH response merits further attention, as does the relationship between anti-Xa levels and clinical outcomes. Ultimately, safe and effective anticoagulation requires both a deeper parsing of factors contributing to variable response, and further prospective studies to determine optimal therapeutic strategies in identified higher risk subgroups.

Ion Kinetics and Neutron Generation Associated with Electromagnetic Turbulence in Laboratory-Scale Counterstreaming Plasmas.

Electromagnetic turbulence and ion kinetics in counterstreaming plasmas hold great significance in laboratory astrophysics, such as turbulence field amplification and particle energization. Here, we quantitatively demonstrate for the first time how electromagnetic turbulence affects ion kinetics under achievable laboratory conditions (millimeter-scale interpenetrating plasmas with initial velocity of 2000 km/s, density of 4×10^{19} cm^{-3}, and temperature of 100 eV) utilizing a recently developed high-order implicit particle-in-cell code without scaling transformation. It is found that the electromagnetic turbulence is driven by ion two-stream and filamentation instabilities. For the magnetized scenarios where an applied magnetic field of tens of Tesla is perpendicular to plasma flows, the growth rates of instabilities increase with the strengthening of applied magnetic field, which therefore leads to a significant enhancement of turbulence fields. Under the competition between the stochastic acceleration due to electromagnetic turbulence and collisional thermalization, ion distribution function shows a distinct super-Gaussian shape, and the ion kinetics are manifested in neutron yields and spectra. Our results have well explained the recent unmagnetized experimental observations, and the findings of magnetized scenario can be verified by current astrophysical experiments.

Single-Atom Verification of the Optimal Trade-Off between Speed and Cost in Shortcuts to Adiabaticity.

The approach of shortcuts to adiabaticity enables the effective execution of adiabatic dynamics in quantum information processing with enhanced speed. Owing to the inherent trade-off between dynamical speed and the cost associated with the transitionless driving field, executing arbitrarily fast operations becomes impractical. To understand the accurate interplay between speed and energetic cost in this process, we propose theoretically and verify experimentally a new trade-off, which is characterized by a tightly optimized bound within s-parametrized phase spaces. Our experiment is carried out in a single ultracold ^{40}Ca^{+} ion trapped in a harmonic potential. By exactly operating the quantum states of the ion, we execute the Landau-Zener model as an example, where the quantum speed limit as well as the cost are governed by the spectral gap. We witness that our proposed trade-off is indeed tight in scenarios involving both initially eigenstates and initially thermal equilibrium states. Our work helps understanding the fundamental constraints in shortcuts to adiabaticity and illuminates the potential of underutilized phase spaces that have been traditionally overlooked.

Energy-Conversion Device Using a Quantum Engine with the Work Medium of Two-Atom Entanglement.

Although entanglement is considered as an essential resource for quantum information processing, whether entanglement helps for energy conversion or output in the quantum regime is still lack of experimental witness. Here, we report on an energy-conversion device operating as a quantum engine with the working medium acted by two entangled ions confined in a harmonic potential. The two ions are entangled by virtually coupling to one of the vibrational modes shared by the two ions, and the quantum engine couples to a quantum load, which is another shared vibrational mode. We explore the energy conversion efficiency of the quantum engine and investigate the useful energy (i.e., the maximum extractable work) stored in the quantum load by tuning the two ions in different degrees of entanglement as well as detecting the change of the phonons in the load. Our observation provides, for the first time, quantitative evidence that entanglement fuels the useful energy produced by the quantum engine, but not helpful for the energy conversion efficiency. We consider that our results may be useful to the study of quantum batteries for which one of the most indexes is the maximum extractable energy.

A novel role for endoplasmic reticulum protein ERp72 in the pathogenesis of autoantibody-induced arthritis.

OBJECTIVE: The family of protein disulphide isomerases (PDIs) is a group of oxidoreductases that catalyze the oxidation, reduction and isomerization of disulphide bonds. Recent studies have shown that overexpression of one of the family enzymes, ERp46, potentiates arthritis severity, suggesting that the PDI family participates in arthritis pathogenesis. This study investigated the role of another PDI member, ERp72, in autoantibody-induced arthritis. METHODS: Using the Cre-LoxP method, a mouse strain lacking ERp72 (ERp72-/- mice) was generated. Autoantibody-induced arthritis was induced in both ERp72-/- and ERp72+/+ control mice by injecting serum from K/BxN mice. The synovial inflammation severity was evaluated by joint diameter measurements and histological analysis. Proinflammatory cytokines expression in joint tissue and plasma was assessed by quantitative real-time PCR and ELISA. RESULTS: : The absence of ERp72 in the joints, white blood cells, spleen, thymus, and bone marrow of ERp72-/- mice was confirmed. In the K/BxN serum transfer-induced arthritis (STIA) model, ERp72-/- mice exhibited exacerbated arthritis compared to ERp72+/+ mice, with greater joint swelling, bone and cartilage erosion, and synovial inflammation. Furthermore, ERp72-/- mice exhibited increased expression of IL-1ß, IL-6 and TNF-α in inflamed joint tissues and higher IL-6 levels in plasma. Conversely, IL-10 levels were lower in ERp72-/- mice inflamed joints than in ERp72+/+ mice. Notably, the basal TNF-α level in the blood of ERp72-/- mice was significantly higher than in ERp72+/+ mice. CONCLUSION: ERp72 plays a key role in the negative regulation of autoantibody-induced arthritis.

Immediate application of frozen-thawed embryo transfer cycle in month following COVID-19 recovery does not impair ongoing pregnancy outcome.

OBJECTIVE: To investigate whether immediate frozen-thawed embryo transfer (FET) in the next month following coronavirus disease 2019 (COVID-19) recovery affects ongoing pregnancy outcome. METHODS: This was a retrospective cohort study carried out at a university-affiliated reproductive medicine center. The study group (post-COVID-19 group) comprised women who were affected by COVID-19 in December 2022 and immediately underwent FET in January 2023 after recovery, with transferred embryos not exposed to the infection. The control group comprised women treated during the pre-COVID-19 period (January 2019). Multivariable logistic regression analysis and a propensity score matching (PSM) approach were used to control potential confounders and selection bias. RESULTS: A total of 200 women were included in the post-COVID-19 group and 641 women were enrolled in the control group. The rate of ongoing pregnancy was comparable between the study cohorts in both the unadjusted and confounder-adjusted logistic regression models. Other reproductive outcomes, including the odds of a positive pregnancy test, implantation, clinical pregnancy and early pregnancy loss, were similar between the comparison groups. PSM models further confirmed the lack of significant differences in pregnancy outcome between the post-COVID-19 group and the control group. CONCLUSIONS: Among patients affected by COVID-19 for whom the transferred embryos were generated prior to infection, an immediate FET cycle in the next month after recovery does not seem to compromise ongoing pregnancy outcome. Thus, women who have frozen embryos from preinfection cycles should be counseled and encouraged to undergo FET as soon as possible after COVID-19 recovery. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Short term air pollution exposure during pregnancy and associations with maternal immune markers.

BACKGROUND: Air pollution exposure during pregnancy has been associated with numerous adverse pregnancy, birth, and child health outcomes. One proposed mechanism underlying these associations is maternal immune activation and dysregulation. We examined associations between PM2.5 and NO2 exposure during pregnancy and immune markers within immune function groups (TH1, TH2, TH17, Innate/Early Activation, Regulatory, Homeostatic, and Proinflammatory), and examined whether those associations changed across pregnancy. METHODS: In a pregnancy cohort study (n = 290) in Rochester, New York, we measured immune markers (using Luminex) in maternal plasma up to 3 times during pregnancy. We estimated ambient PM2.5 and NO2 concentrations at participants' home addresses using a spatial-temporal model. Using mixed effects models, we estimated changes in immune marker concentrations associated with interquartile range increases in PM2.5 (2.88 µg/m3) and NO2 (7.82 ppb) 0-6 days before blood collection, and assessed whether associations were different in early, mid, and late pregnancy. RESULTS: Increased NO2 concentrations were associated with higher maternal immune markers, with associations observed across TH1, TH2, TH17, Regulatory, and Homeostatic groups of immune markers. Furthermore, the largest increases in immune markers associated with each 7.82 ppb increase in NO2 concentration were in late pregnancy (e.g., IL-23 = 0.26 pg/ml, 95% CI = 0.07, 0.46) compared to early pregnancy (e.g., IL-23 = 0.08 pg/ml, 95% CI = -0.11, 0.26). CONCLUSIONS: Results were suggestive of NO2-related immune activation. Increases in effect sizes from early to mid to late pregnancy may be due to changes in immune function over the course of pregnancy. These findings provide a basis for immune activation as a mechanism for previously observed associations between air pollution exposure during pregnancy and reduced birthweight, fetal growth restriction, and pregnancy complications.

Relationship between fasting prior to contrast-enhanced CT and adverse reaction in patients with allergies history.

AIM: To examine the relationship between fasting prior to contrast-enhanced CT (CECT) and adverse reaction (AR) in patients with allergies history. MATERIALS AND METHODS: Patients with allergies history who underwent CECT from January 2014 to December 2020 (713 cases with iodinated contrast media (ICM)-related allergy history and 27045 cases with unrelated allergies history) were retrospectively analyzed. The occurrence of ICM-related AR and patient information were recorded. The relationship between fasting and AR and emetic complications was analyzed. RESULTS: There was no statistical difference in the overall incidence of AR and emetic complications between fasting group and non-fasting group (P>0.05) and fasting was not an influence factor for overall AR occurrence in patients with both ICM-related and unrelated allergies history. However, the incidence of severe AR in fasting group was higher than that in non-fasting group (P=0.01) in patients with unrelated allergies history. The AR incidence in fasting group was higher than that in non-fasting group (P=0.022) when receiving abdominal examinations in patients with unrelated allergies history. There was no statistical difference in the incidence of AR with different occurrence time between fasting group and non-fasting group (P>0.05) in patients with both ICM-related and unrelated allergies history. CONCLUSIONS: Fasting was associated with higher incidence of severe AR and was associated with higher AR incidence when receiving abdominal examinations in patients with unrelated allergies history. Fasting did not have effects on the occurrence time of AR in patients with allergies history. These provided new guidance for usage of ICM in patients with allergies history.

A novel perspective for exploring the relationship between cerebral small vessel disease and deep medullary veins with automatic segmentation.

BACKGROUND: This study aimed to establish an intelligent segmentation algorithm to count the number of deep medullary veins (DMVs) and analyze the relationship between DMVs and imaging markers of cerebral small vessel disease (CSVD). METHODS: DMVs on magnetic resonance imaging (MRI) of patients with CSVD were counted by intelligent segmentation and manual counting. The dice coefficient and intraclass correlation coefficient (ICC) were used to evaluate their consistency and correlation. Structural MR images were used to assess imaging markers and total burden of CSVD. A multivariate linear regression model was used to evaluate the correlation between the number of DMVs counted by intelligent segmentation and imaging markers of CSVD, including white matter hyperintensities of the presumed vascular origin, lacune, perivascular spaces, cerebral microbleeds, and total CSVD burden. RESULTS: A total of 305 patients with CSVD were enrolled. An intelligent segmentation algorithm was established to calculate the number of DMVs, and it was validated and tested. The number of DMVs counted intelligently significantly correlated with the manual counting method (r = 0.761, P< 0.001). The number of smart-counted DMVs negatively correlated with the imaging markers and total burden of CSVD (P< 0.001), and the correlation remained after adjusting for age and hypertension (P< 0.05). CONCLUSIONS: The proposed intelligent segmentation algorithm, which was established to count DMVs, can provide objective and quantitative imaging information for the follow-up of patients with CSVD. DMVs are involved in CSVD pathogenesis and a likely new imaging marker for CSVD.

Distinguishment between high-grade gliomas and solitary brain metastases in peritumoural oedema: quantitative analysis using synthetic MRI at 3 T.

AIM: To investigate the efficacy of synthetic magnetic resonance imaging (MRI) in distinguishing high-grade gliomas (HGGs) from solitary brain metastases (SBMs) in peritumoural oedema. MATERIALS AND METHODS: Thirty-five patients with HGGs and 25 patients with SBMs were recruited and scanned using synthetic MRI using a 3 T scanner. Two radiologists measured synthetic MRI-derived relaxation values independently (T1, T2, proton density [PD]) in the peritumoural oedema, which was used to generate quantitative metrics before (T1native, T2native, and PDnative) and after (T1post, T2post, and PDpost) contrast agent injection. Student's t-test or the Mann-Whitney U-test was performed to detect statistically significant differences in the aforementioned metrics in peritumoural oedema between HGGs and SBMs. The receiver operating characteristic (ROC) curves were plotted to evaluate the efficacy of each metric in distinguishing the two groups, and the areas under the curves (AUCs) were compared pairwise by performing the Delong test. RESULTS: The mean T1native, T2native, and T1post values in the peritumoural oedema of HGGs were significantly lower compared with SBMs (all p<0.05). The T1post value had a higher AUC (0.843) in differentiating HGGs and SBMs than all other individual metrics (all p<0.05). The combined T1native, T2native, and T1post model had the best distinguishing performance with an AUC, sensitivity, and specificity of 0.987, 94.3%, and 100%, respectively. CONCLUSIONS: Synthetic MRI may be a potential supplement to the preoperative diagnosis of HGGs and SBMs in clinical practice, as the synthetic MRI-derived tri-parametric model in the peritumoural oedema showed significantly improved diagnostic performance in distinguishing HGGs from SBMs.

Deep-learning features based on F18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) to predict preoperative colorectal cancer lymph node metastasis.

AIM: The objective of this study was to create and authenticate a prognostic model for lymph node metastasis (LNM) in colorectal cancer (CRC) that integrates clinical, radiomics, and deep transfer learning features. MATERIALS AND METHODS: In this study, we analyzed data from 119 CRC patients who underwent F18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) scanning. The patient cohort was divided into training and validation subsets in an 8:2 ratio, with an additional 33 external data points for testing. Initially, we conducted univariate analysis to screen clinical parameters. Radiomics features were extracted from manually drawn images using pyradiomics, and deep-learning features, radiomics features, and clinical features were selected using Least Absolute Shrinkage and Selection Operator (LASSO) regression and Spearman correlation coefficient. We then constructed a model by training a support vector machine (SVM), and evaluated the performance of the prediction model by comparing the area under the curve (AUC), sensitivity, and specificity. Finally, we developed nomograms combining clinical and radiological features for interpretation and analysis. RESULTS: The deep learning radiomics (DLR) nomogram model, which was developed by integrating deep learning, radiomics, and clinical features, exhibited excellent performance. The area under the curve was (AUC = 0.934, 95% confidence interval [CI]: 0.884-0.983) in the training cohort, (AUC = 0.902, 95% CI: 0.769-1.000) in the validation cohort, and (AUC = 0.836, 95% CI: 0.673-0.998) in the test cohort. CONCLUSION: We developed a preoperative predictive machine-learning model using deep transfer learning, radiomics, and clinical features to differentiate LNM status in CRC, aiding in treatment decision-making for patients.

QuTree: A tree tensor network package.

We present QuTree, a C++ library for tree tensor network approaches. QuTree provides class structures for tensors, tensor trees, and related linear algebra functions that facilitate the fast development of tree tensor network approaches such as the multilayer multiconfigurational time-dependent Hartree approach or the density matrix renormalization group approach and its various extensions. We investigate the efficiency of relevant tensor and tensor network operations and show that the overhead for managing the network structure is negligible, even in cases with a million leaves and small tensors. QuTree focuses on providing simple, high-level routines while retaining easy access to the backend to facilitate novel developments. We demonstrate the capabilities of the package by computing the eigenstates of coupled harmonic oscillator Hamiltonians and performing random circuit simulations on a virtual quantum computer.

Changes in Rumen Epithelial Morphology and Transcriptome, Rumen Metabolome, and Blood Biochemical Parameters in Lactating Dairy Cows with Subacute Rumen Acidosis Following Rumen Content Transplantation.

Interventions targeting the gut microbiota, such as fecal microbiota transplantation, prove effective in repairing the intestinal barrier and facilitating the recovery of its function and metabolism. However, the regulatory mechanisms governing the remodeling of rumen epithelial morphology and function, rumen metabolism, and host metabolism in cows of subacute ruminal acidosis (SARA) remain poorly understood. Here, we explored the changes in rumen epithelial morphology and transcriptome, rumen metabolome, and blood biochemical parameters in SARA cows following rumen content transplantation (RCT). The entire experiment consisted of 2 periods: the SARA induction period and the RCT period. During the SARA induction period, 12 ruminally cannulated lactating Holstein cows were randomly allocated into 2 groups, fed either a conventional diet [CON; n = 4; 40% concentrate, dry matter (DM) basis] or a high-grain diet (HG; n = 8; 60% concentrate, DM basis). Following the SARA induction period, the RCT period started. The HG cows were randomly assigned to 2 groups: the donor-recipient (DR) group and the self-recipient (SR) group. Rumen contents were entirely removed from both groups before RCT. For the DR group, cows were administered 70% rumen content from the CON cows, paired based on comparable body weight; for the SR group, each cow received 70% self-derived rumen content. The results revealed no significant differences in the thicknesses of the stratum corneum, granulosum, and spinosum/basale layers, as well as the total depth of the epithelium between the SR and DR groups. All these measurements exhibited a decreasing trend and fluctuations over time after the transfer. Notably, these fluctuations tended to stabilize at 13 or 16 d after RCT in the SR group, whereas they tended to stabilize after 8 or 13 d of transfer for the DR group. Transcriptome sequencing revealed that a total of 277 differentially expressed genes (DEGs) were identified between the 2 groups. Enrichment analysis showed that the DEGs were significantly enriched in 11 Gene Ontology biological processes and 14 KEGG pathways. The DEGs corresponding to almost any of these 11 biological process terms and 14 pathways showed mixed up- or downregulation following RCT. Metabolomics analysis indicated that a total of 33 differential metabolites were detected between the SR and DR groups, mainly enriched in 5 key metabolic pathways, including plant polysaccharides and starch degradation, lipid metabolism, amino sugar and nucleotide metabolism, purine metabolism, and Krebs cycle. Among them, the levels of differential metabolites associated with the degradation of plant polysaccharides and starches, metabolism of amino sugars and nucleotides, and purine metabolism pathways were significantly elevated in the DR cows. The results of blood biochemical parameters showed that the triglyceride concentration of the DR cows was increased than that of the SR cows, comparable to the level observed in the CON cows during the SARA induction period. Generally, our findings indicated that RCT facilitated the recovery of rumen epithelial morphological structure but did not promote its function recovery. Moreover, RCT enhanced rumen plant polysaccharide and starch degradation, amino sugar and nucleotide sugar metabolism, as well as purine metabolism. Additionally, it further promoted the recovery of plasma metabolites related to lipid metabolism.

Secondary infections of COVID-19 in schools and the effectiveness of school-based interventions: a systematic review and meta-analysis.

OBJECTIVES: This meta-analysis explored secondary infections of SARS-CoV-2 and the effectiveness of non-pharmaceutical interventions (NPIs) in school settings, with the aim of providing a reference to formulate scientific prevention and response strategies for similar major public health emergencies in specific settings. STUDY DESIGN: This was a systematic review and meta-analysis. METHODS: Systematic searches were conducted in PubMed, Web of Science and the Cochrane Library through to 1 August 2022 using the following key search terms: COVID-19, SARS-CoV-2, secondary attack rate, school, transmission, etc. The IVhet model was used for the meta-analysis, and the I2 index and Cochran's Q-test were used to assess heterogeneity. Publication bias was examined using Doi plot, Galbraith plots and Luis Furuya-Kanamori index. Prevalence Critical Appraisal Tool was used to assess the quality of the included articles, while Grading of Recommendations Assessment, Development, and Evaluation was used to rate the quality of the evidence. Subgroup analyses were conducted to explore the potential source of heterogeneity. RESULTS: Thirty-four studies involving 226,727 school contacts and 2216 secondary cases were included in this study. The pooled secondary attack rates (SARs) of close contacts, staff contacts and student contacts were 0.67% (95% confidence interval [CI]: 0.11, 1.56), 0.79% (95% CI: 0.00, 6.72) and 0.50% (95% CI: 0.00, 4.48), respectively. Subgroup analysis suggested that multiple or specific combinations (e.g. the combination of contact restriction and hygiene action) of NPIs appeared to be associated with lower SARs. CONCLUSIONS: The SAR of SARS-CoV-2 was low in schools. Multiple or specific combinations of prevention strategies appear to mitigate SARS-CoV-2 transmission in school settings. These findings provide a basis for continuous improvement of response strategies to major public health emergencies in the school environment.

Parent-child interaction, appetite self-regulation, and BMIz in Chinese preschoolers: a mediation analysis.

OBJECTIVES: Research on parent-child interaction (PCI) and its impact on children's weight status is a thriving study area. However, their potential pathways have not been established. This study investigated the association between PCI and children's body-mass index z score (BMIz) examining the role of appetite self-regulation (ASR) as a mediator. STUDY DESIGN: Mediation analysis. METHODS: We included children from 33 kindergartens in Wuhan with parents' consent, measuring children's height and weight, and calculating BMIz. To assess the PCI quality, we utilized the Brigance Parent-Child Interactions Scale. Additionally, children's ASR was tested by satiety responsiveness (SR) and food responsiveness (FR) using the Children's Eating Behavior Questionnaire. Quantile regression was employed to examine the PCI-BMIz association, while mediation analysis was conducted to explore ASR's mediating effect on the relationship between PCI and BMIz. RESULTS: Of 3973 children (53.88% boys) included in the analysis, the mean BMIz was 0.24 ± 1.13. The results revealed that children with poorer PCI quality have higher BMIz across all selected BMIz percentiles, except for the 5th percentile. Furthermore, these associations were significant across most percentiles, whether for boys or girls. Mediation analysis suggested that these associations were partially mediated by children's ASR (indFR = -0.026, PFR < 0.001; indSR = -0.058, PSR < 0.001), with stronger effects observed among boys. CONCLUSION: The variation in how strongly BMIz was linked to PCI across different percentiles suggests that children with poorer PCI have higher BMIz. The link is partially mediated through children's ASR. It's important to pay attention to the PCI quality in children with higher BMIz levels, especially in boys.

Association between non-alcoholic fatty liver disease and metabolic abnormalities in children with different weight statuses.

OBJECTIVES: Both obesity and non-alcoholic fatty liver disease (NAFLD) increase the risk of metabolic abnormalities. However, the metabolic status of children suffering from NAFLD and exhibiting various subtypes of obesity is currently unclear. We aimed to explore the association between NAFLD and metabolic abnormalities in children with different weight statuses. METHODS: We included 6086 participants aged 6-18 years from the China Child and Adolescent NAFLD Study (CCANS), all of whom had undergone ultrasonography or magnetic resonance imaging-proton density fat fraction (MRI-PDFF) to identify NAFLD and metabolic abnormalities, including hyperglycemia, high triglycerides (TG), low high-density lipoprotein cholesterol (HDL-C), high low-density lipoprotein cholesterol, high total cholesterol, and hyperuricemia. RESULTS: Among the participants, there were 2408 children with obesity and NAFLD, 174 with NAFLD, 2396 with obesity, and 1108 without obesity and NAFLD. The odds ratios (ORs) of suffering from individual metabolic abnormalities were significantly greater in children with obesity and NAFLD than in children without obesity and NAFLD, with ORs ranging from 6.23 (95% CI: 4.56, 8.53) to 1.77 (95% CI: 1.06, 2.94). The ORs of metabolic abnormalities, except for low HDL-C, were greater in children with NAFLD alone than in children without obesity or NAFLD, with ORs ranging from 4.36 (95% CI: 2.77, 6.84) to 2.08 (95% CI: 1.14, 3.78). Notably, obesity and NAFLD had a multiplicative effect on overall metabolic abnormalities, high TG levels, and low HDL-C levels. CONCLUSIONS: Children with obesity and NAFLD could be at a significantly increased risk of metabolic abnormalities. Even for children without obesity, NAFLD appears to be associated with an increased risk of experiencing a worsened metabolic status.

Elevated MIF identified by multiple cytokine analyses facilitates macrophage M2 polarization contributing to postoperative recurrence in chronic rhinosinusitis with nasal polyps.

BACKGROUND: Chronic rhinosinusitis with nasal polyps (CRSwNP) is characterized by tissue heterogeneity and high postoperative recurrence risk. This study aims to employ cytokine analyses to identify serum biomarkers associated with postoperative CRSwNP recurrence and elucidate underlying recurrent mechanisms. METHODS: A prospective cohort study was conducted on CRSwNP patients undergoing functional endoscopic sinus surgery. Serum and tissue samples were collected and analyzed for multiple cytokines. Participants were followed for 3 years and categorized into recurrent and non-recurrent groups. Cytokine profiles were compared, and potential markers for recurrence were further assessed. Macrophage migration inhibitory factor (MIF) expression in macrophages was modulated, and their polarization and cytokine secretion were assessed. RESULTS: In the discovery cohort (21 recurrent and 40 non-recurrent patients), circulating cytokine profiles differed significantly, with 8 cytokines showing differential expression between the two groups. Among them, serum eotaxin, MIF, RANTES, and TRAIL exhibited promise in predicting recurrence. In the validation cohort (24 recurrent and 44 non-recurrent patients), serum eotaxin, MIF, and TRAIL levels were higher in recurrent cases. Tissue MIF was elevated in recurrent cases and had a strong predictive value for recurrence. Moreover, tissue MIF was co-expressed with CD206 in recurrent cases. Mechanistically, MIF overexpression promoted macrophage M2 polarization and TGF-ß, CCL-24, and MIF secretion, and MIF recombinant protein facilitated M2 polarization, and TGF-ß1 and CCL-24 production, contributing to CRSwNP recurrence. CONCLUSIONS: Serum-specific cytokine signatures were associated with postoperative recurrence risk in CRSwNP. Elevated MIF enhanced macrophage M2 polarization and cytokine secretion, contributing to the recurrent mechanisms of CRSwNP.

Integrated Communication, Sensing, and Computation Framework for 6G Networks.

In the sixth generation (6G) era, intelligent machine network (IMN) applications, such as intelligent transportation, require collaborative machines with communication, sensing, and computation (CSC) capabilities. This article proposes an integrated communication, sensing, and computation (ICSAC) framework for 6G to achieve the reciprocity among CSC functions to enhance the reliability and latency of communication, accuracy and timeliness of sensing information acquisition, and privacy and security of computing to realize the IMN applications. Specifically, the sensing and communication functions can merge into unified platforms using the same transmit signals, and the acquired real-time sensing information can be exploited as prior information for intelligent algorithms to enhance the performance of communication networks. This is called the computing-empowered integrated sensing and communications (ISAC) reciprocity. Such reciprocity can further improve the performance of distributed computation with the assistance of networked sensing capability, which is named the sensing-empowered integrated communications and computation (ICAC) reciprocity. The above ISAC and ICAC reciprocities can enhance each other iteratively and finally lead to the ICSAC reciprocity. To achieve these reciprocities, we explore the potential enabling technologies for the ICSAC framework. Finally, we present the evaluation results of crucial enabling technologies to show the feasibility of the ICSAC framework.