Associations among neighborhood walkability, metal exposure, and sex steroid hormone levels: Results from Hangzhou Birth Cohort Study â ¡.

BACKGROUND: Neighborhood walkability may influence maternal-fetal exposure to environmental hazards and maternal-fetal health (e.g., fetal growth restriction, reproductive toxicity). However, few studies have explored the association between neighborhood walkability and hormones in pregnant women. METHODS: We included 533 pregnant women from the Hangzhou Birth Cohort Study II (HBCS-II) with testosterone (TTE) and estradiol (E2) measured for analysis. Neighborhood walkability was evaluated by calculating a walkability index based on geo-coded addresses. Placental metals were measured using inductively coupled plasma mass spectrometry (ICP-MS). TTE and E2 levels in umbilical cord blood were measured using chemiluminescence microparticle immunoassay (CMIA). Linear regression model was used to estimate the relationship between the walkability index, placental metals, and sex steroid hormones. Effect modification was also assessed to estimate the effect of placental metals on the associations of neighborhood walkability with TTE and E2. RESULTS: Neighborhood walkability was significantly linked to increased E2 levels (P trend=0.023). Compared with participants at the first quintile (Q1) of walkability index, those at the third quintiles (Q3) had lower chromium (Cr) levels (ß = -0.212, 95% CI = -0.421 to -0.003). Arsenic (As), cobalt (Co), manganese (Mn), molybdenum (Mo), nickel (Ni), lead (Pb), antimony (Sb), selenium (Se), tin (Sn), and vanadium (V) were linked to decreased TTE levels, and cadmium (Cd) was linked to increased TTE levels. No metal was significantly associated with E2 levels in trend analysis. In the analysis of effect modification, the associations of neighborhood walkability with TTE and E2 were significantly modified by Mn (P = 0.005) and Cu (P = 0.049) respectively. CONCLUSION: Neighborhood walkability could be a favorable factor for E2 production during pregnancy, which may be inhibited by maternal exposure to heavy metals.

Absence of PD-L1 signaling hinders macrophage defense against Mycobacterium tuberculosis via upregulating STAT3/IL-6 pathway.

The blockade of programmed death-ligand 1 (PD-L1) pathway has been clinically used in cancer immunotherapy, while its effects on infectious diseases remain elusive. Roles of PD-L1 signaling in the macrophage-mediated innate immune defense against M.tb is unclear. In this study, the outcomes of tuberculosis (TB) in wild-type (WT) mice treated with anti-PD-1/PD-L1 therapy and macrophage-specific Pdl1-knockout (Pdl1ΔΜΦ) mice were compared. Treatment with anti-PD-L1 or anti-PD-1 benefited protection against M.tb infection in WT mice, while Pdl1ΔΜΦ mice exhibited the increased susceptibility to M.tb infection. Mechanistically, the absence of PD-L1 signaling impaired M.tb killing by macrophages. Furthermore, elevated STAT3 activation was found in PD-L1-deficient macrophages, leading to increased interleukin (IL)-6 production and reduced inducible nitric oxide synthase (iNOS) expression. Inhibiting STAT3 phosphorylation partially impeded the increase in IL-6 production and restored iNOS expression in these PD-L1-deficient cells. These findings provide valuable insights into the complexity and mechanisms underlying anti-PD-L1 therapy in the context of tuberculosis.

Single-Atom-Based Nanoenzyme in Tissue Repair.

Since the discovery of ferromagnetic nanoparticles Fe3O4 that exhibit enzyme-like activity in 2007, the research on nanoenzymes has made significant progress. With the in-depth study of various nanoenzymes and the rapid development of related nanotechnology, nanoenzymes have emerged as a promising alternative to natural enzymes. Within nanozymes, there is a category of metal-based single-atom nanozymes that has been rapidly developed due to low cast, convenient preparation, long storage, less immunogenicity, and especially higher efficiency. More importantly, single-atom nanozymes possess the capacity to scavenge reactive oxygen species through various mechanisms, which is beneficial in the tissue repair process. Herein, this paper systemically highlights the types of metal single-atom nanozymes, their catalytic mechanisms, and their recent applications in tissue repair. The existing challenges are identified and the prospects of future research on nanozymes composed of metallic nanomaterials are proposed. We hope this review will illuminate the potential of single-atom nanozymes in tissue repair, encouraging their sequential clinical translation.

[Cannabinoid receptor 1 agonist arachidonyl-2'-chloroethylamide (ACEA) improves sepsis-associated encephalopathy by inhibiting inflammatory factors].

Objective To investigate the impact of the cannabinoid receptor agonist arachidonyl-2'-chloroethylamide (ACEA) on cognitive function in mice with sepsis-associated encephalopathy (SAE). Methods C57BL/6 mice were randomly divided into artificial cerebrospinal fluid (ACSF) and lipopolysaccharide (LPS) groups. The SAE model was established by intraventricular injection of LPS. The severity of sepsis in mice was assessed by sepsis severity score (MSS) and body mass changes. Behavioral paradigms were used to evaluate motor ability (open field test) and cognitive function (contextual fear conditioning test, Y-maze test). To evaluate the effects of ACEA intervention on SAE, mice were randomly assigned to ACSF group, ACEA intervention combined with ACSF group, LPS group, and ACEA intervention combined with LPS group. The dosage of ACEA intervention was 1.5 mg/kg. Real-time quantitative PCR was used to measure the mRNA expression levels of interleukin 1ß (IL-1ß), IL-6, and tumor necrosis factor α (TNF-α) in mouse hippocampal tissues. Western blot analysis was used to assess the protein levels of IL-6 and TNF-α in the hippocampus. Nissl staining was performed to examine neuronal damage in the CA1 region of the mouse hippocampus. Behavioral paradigms were again employed to evaluate motor ability and cognitive function. Results Three days after intraventricular LPS injection, mice exhibited significant cognitive dysfunction, confirming SAE modeling. Compared to the control group, the LPS group showed significant increases in mRNA of inflammatory factors such as IL-6, TNF-α, and IL-1ß, together with significant increases in IL-6 and TNF-α protein levels in the hippocampus, a decrease in Nissl bodies in the CA1 region, and significant cognitive dysfunction. Compared to the LPS group, the ACEA intervention group showed a significant decrease in the mRNA of IL-6, TNF-α, and IL-1ß, a significant reduction in IL-6 and TNF-α protein levels, an increase in Nissl bodies, and improved cognitive function. Conclusion ACEA improves cognitive function in SAE mice by inhibiting the expression levels of inflammatory factors IL-6 and TNF-α.

Landscape of the gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health.

OBJECTIVE: The remodelling of gut mycobiome (ie, fungi) during pregnancy and its potential influence on host metabolism and pregnancy health remains largely unexplored. Here, we aim to examine the characteristics of gut fungi in pregnant women, and reveal the associations between gut mycobiome, host metabolome and pregnancy health. DESIGN: Based on a prospective birth cohort in central China (2017 to 2020): Tongji-Huaxi-Shuangliu Birth Cohort, we included 4800 participants who had available ITS2 sequencing data, dietary information and clinical records during their pregnancy. Additionally, we established a subcohort of 1059 participants, which included 514 women who gave birth to preterm, low birthweight or macrosomia infants, as well as 545 randomly selected controls. In this subcohort, a total of 750, 748 and 709 participants had ITS2 sequencing data, 16S sequencing data and serum metabolome data available, respectively, across all trimesters. RESULTS: The composition of gut fungi changes dramatically from early to late pregnancy, exhibiting a greater degree of variability and individuality compared with changes observed in gut bacteria. The multiomics data provide a landscape of the networks among gut mycobiome, biological functionality, serum metabolites and pregnancy health, pinpointing the link between Mucor and adverse pregnancy outcomes. The prepregnancy overweight status is a key factor influencing both gut mycobiome compositional alteration and the pattern of metabolic remodelling during pregnancy. CONCLUSION: This study provides a landscape of gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health, which lays the foundation of the future gut mycobiome investigation for healthy pregnancy.

Transformation of dissolved organic matter during groundwater arsenite removal using air cathode iron electrocoagulation.

Dissolve organic matters (DOM) usually showed negative effect on the removal of inorganic arsenic (As) in groundwater by electrochemical approaches, yet which parts of sub-component within DOM played the role was lack of evidence. Herein, we investigated the effects of land-source humic-like acid (HA) on groundwater As(III) removal using air cathode iron electrocoagulation, based on the parallel factor analysis of three-dimensional excitation-emission matrix and statistical methods. Our results showed that the land-source HA contained five kinds of components and all components presented significantly negative correlations with the removal of both As(III) and As(V). However, the high aromatic fulvic-like acid and low aromatic humic-like acid components of land-source HA presented the opposite correlations with the concentration of As(III) during the reaction. The high aromaticity fulvic-like components of land-source HA (Sigma-Aldrich HA, SAHA) produced during the reaction facilitated the oxidation of As(III) due to its high electron transfer capacities and good solubility in wide pH range, but the low aromaticity humic-like ones worked against the oxidation of As(III). Our findings offered the novel insights for the flexible activities of DOM in electron Fenton system.

Promoting tissue repair using deferoxamine nanoparticles loaded biomimetic gelatin/HA composite hydrogel.

To effectively address underlying issues and enhance the healing process of hard-to-treat soft tissue defects, innovative therapeutic approaches are required. One promising strategy involves the incorporation of bioactive substances into biodegradable scaffolds to facilitate synergistic tissue regeneration, particularly in vascular regeneration. In this study, we introduce a composite hydrogel design that mimics the extracellular matrix (ECM) by covalently combining gelatin and hyaluronic acid (HA), with the encapsulation of deferoxamine nanoparticles (DFO NPs) for potential tissue regeneration applications. Crosslinked hydrogels were fabricated by controlling the ratio of HA in the gelatin-based hydrogels, resulting in improved mechanical properties, enhanced degradation ability, and optimised porosity, compared with hydrogel formed by gelatin alone. The DFO NPs, synthesized using a double emulsion method with PLGA, exhibited a sustained release of DFO over 12 days. Encapsulating the DFO NPs in the hydrogel enabled controlled release over 15 days. The DFO NPs, composite hydrogel, and the DFO NPs loaded hydrogel exhibited excellent cytocompatibility and promoted cell proliferation in vitro. Subcutaneous implantation of the composite hydrogel and the DFO NPs loaded hydrogel demonstrated biodegradability, tissue integration, and no obvious adverse effects, evidenced by histological analysis. Furthermore, the DFO NPs loaded composite hydrogel exhibited accelerated wound closure and promoted neovascularisation and granular formation when tested in an excisional skin wound model in mice. These findings highlight the potential of our composite hydrogel system for promoting the faster healing of diabetes-induced skin wounds and oral lesions through its ability to modulate tissue regeneration processes. .

ARDS in solid organ transplant recipients hospitalized for COVID-19 based on the 2023 new definition.

BACKGROUND: Solid organ transplant recipients (SOTRs) are more likely to suffer complications after being infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). OBJECTIVES: We aimed to describe the clinical features of SOTRs infected with SARS-CoV-2 and to assess independent risk factors associated with the development of acute respiratory distress syndrome (ARDS) following COVID-19 infection in SOTRs based on the new ARDS definition. METHODS: 358 SOTRs infected with SARS-CoV-2 were recruited and divided into two groups, patients with ARDS (n = 81) and patients without ARDS (n = 277). Demographic data, initial laboratory findings, therapeutic measures, and outcome indicators were compared between the two groups. The association between the onset of ARDS and related factors was analyzed using a logistic regression model. A nomogram was created to estimate the probability of developing ARDS. RESULTS: Approximately 22.6 % (81/358) of hospitalized SOTRs infected with SARS-CoV-2 developed ARDS. In comparison to patients without ARDS, those with ARDS presented with more underlying conditions, decreased lymphocyte counts and serum albumin levels, but increased levels of leukocytes, serum creatinine, nitrogen urea, uric acid, and inflammatory markers. Cerebrovascular disease, leukocyte counts, albumin levels, and IL-6 levels were independent risk factors for the development of ARDS in this population. Furthermore, a nomogram prediction model was created utilizing the aforementioned factors to facilitate early prediction of ARDS, exhibiting an AUC (area under curve) of 0.81. CONCLUSIONS: Cerebrovascular disease, leukocyte counts, albumin levels, and IL-6 levels were independent risk factors for the development of ARDS following COVID-19 infection in SOTRs.

Characterization of gene regulatory networks underlying key properties in human hematopoietic stem cell ontogeny.

Human hematopoiesis starts at early yolk sac and undergoes site- and stage-specific changes over development. The intrinsic mechanism underlying property changes in hematopoiesis ontogeny remains poorly understood. Here, we analyzed single-cell transcriptome of human primary hematopoietic stem/progenitor cells (HSPCs) at different developmental stages, including yolk-sac (YS), AGM, fetal liver (FL), umbilical cord blood (UCB) and adult peripheral blood (PB) mobilized HSPCs. These stage-specific HSPCs display differential intrinsic properties, such as metabolism, self-renewal, differentiating potentialities etc. We then generated highly co-related gene regulatory network (GRNs) modules underlying the differential HSC key properties. Particularly, we identified GRNs and key regulators controlling lymphoid potentiality, self-renewal as well as aerobic respiration in human HSCs. Introducing selected regulators promotes key HSC functions in HSPCs derived from human pluripotent stem cells. Therefore, GRNs underlying key intrinsic properties of human HSCs provide a valuable guide to generate fully functional HSCs in vitro.

Measurements of Spatial Angles Using Diamond Nitrogen-Vacancy Center Optical Detection Magnetic Resonance.

This article introduces a spatial angle measuring device based on ensemble diamond nitrogen-vacancy (NV) center optical detection magnetic resonance (ODMR). This device realizes solid-state all-optical wide-field vector magnetic field measurements for solving the angles of magnetic components in space. The system uses diamond NV center magnetic microscope imaging to obtain magnetic vector distribution and calculates the spatial angles of magnetic components based on the magnetic vector distribution. Utilizing magnetism for angle measuring enables non-contact measuring, reduces the impact on the object being measured, and ensures measurement precision and accuracy. Finally, the accuracy of the system is verified by comparing the measurement results with the set values of the angle displacement platform. The results show that the measurement error of the yaw angle of the system is 1°, and the pitch angle and roll angle are 1.5°. The experimental results are in good agreement with the expected results.

Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.

Purpose: To develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs). Material and methods: The study encompassed a cohort of 942 patients, involving examinations of 1076 vertebrae through X-ray, CT, and MRI across three distinct hospitals. The OVFs were categorized as class 0, 1, or 2 based on the Assessment System of Thoracolumbar Osteoporotic Fracture. The dataset was divided randomly into four distinct subsets: a training set comprising 712 samples, an internal validation set with 178 samples, an external validation set containing 111 samples, and a prospective validation set consisting of 75 samples. The ResNet-50 architectural model was used to implement deep transfer learning (DTL), undergoing -pre-training separately on the RadImageNet and ImageNet datasets. Features from DTL and radiomics were extracted and integrated using X-ray images. The optimal fusion feature model was identified through least absolute shrinkage and selection operator logistic regression. Evaluation of the predictive capabilities for OVFs classification involved eight machine learning models, assessed through receiver operating characteristic curves employing the "One-vs-Rest" strategy. The Delong test was applied to compare the predictive performance of the superior RadImageNet model against the ImageNet model. Results: Following pre-training separately on RadImageNet and ImageNet datasets, feature selection and fusion yielded 17 and 12 fusion features, respectively. Logistic regression emerged as the optimal machine learning algorithm for both DLR models. Across the training set, internal validation set, external validation set, and prospective validation set, the macro-average Area Under the Curve (AUC) based on the RadImageNet dataset surpassed those based on the ImageNet dataset, with statistically significant differences observed (P<0.05). Utilizing the binary "One-vs-Rest" strategy, the model based on the RadImageNet dataset demonstrated superior efficacy in predicting Class 0, achieving an AUC of 0.969 and accuracy of 0.863. Predicting Class 1 yielded an AUC of 0.945 and accuracy of 0.875, while for Class 2, the AUC and accuracy were 0.809 and 0.692, respectively. Conclusion: The DLR model, based on the RadImageNet dataset, outperformed the ImageNet model in predicting the classification of OVFs, with generalizability confirmed in the prospective validation set.

Longitudinal Associations Between Physical Activity and Depressive Symptoms in Chinese Children: Evidence from the Tongji Mental Health Cohort Study.

BACKGROUND: We aimed to examine the associations between depressive symptoms and physical activity parameters (e.g., intensity, frequency, and duration) among Chinese school-aged children. METHOD: Participants in this study were extracted from the Tongji Mental Health Cohort Study. The baseline survey was conducted in June 2020 involving 2588 school-aged children from two primary schools in Hubei Province, China. A total of 2435 children were followed up successfully in December 2020. The Children's Depression Inventory Short Form (CDI-S) was applied to evaluate depressive symptoms among school-aged children. The Physical Activity Rating Scale-3 (PARS-3) was adopted to estimate children's physical activity parameters including the intensity, frequency, and duration. Generalized estimation equation models were used to explore the longitudinal associations between physical activity and depressive symptoms among school-aged children. RESULTS: Engaging in moderate levels of physical activity (OR, 0.800; 95%CI, 0.692-0.924) or high levels of physical activity (OR, 0.808; 95%CI, 0.689-0.947) in the baseline survey was associated with a reduced risk of developing depressive symptoms in the follow-up survey compared with children engaging in low levels of physical activity. Stratified analyses revealed that the associations between physical activity and depressive symptoms exhibited a significant correlation among boys and children in the older age group (11-12 years). Our findings showed that engaging in physical activity more than once a week, with each session lasting 20 min or longer, was related to significant reductions in depressive symptoms by 43.8% and 22.3%, respectively. CONCLUSION: Self-reported physical activity is positively associated with improved mental health among Chinese school-aged children, especially when considering parameters such as frequency and duration. The association between vigorous-intensity physical activity and depressive symptoms in children should be cautiously interpreted. Future research should continue to explore the effects of vigorous-intensity physical activity on depressive symptoms in children.

Macrophage: A key player in neuropathic pain.

Research on the relationship between macrophages and neuropathic pain has flourished in the past two decades. It has long been believed that macrophages are strong immune effector cells that play well-established roles in tissue homeostasis and lesions, such as promoting the initiation and progression of tissue injury and improving wound healing and tissue remodeling in a variety of pathogenesis-related diseases. They are also heterogeneous and versatile cells that can switch phenotypically/functionally in response to the micro-environment signals. Apart from microglia (resident macrophages of both the spinal cord and brain), which are required for the neuropathic pain processing of the CNS, neuropathic pain signals in PNS are influenced by the interaction of tissue-resident macrophages and BM infiltrating macrophages with primary afferent neurons. And the current review looks at new evidence that suggests sexual dimorphism in neuropathic pain are caused by variations in the immune system, notably macrophages, rather than the neurological system.

Neuropathic pain is defined by the International Association for the Study of Pain as pain triggered or caused by primary damage to or dysfunction of the nervous system. Following intensive research into the mechanisms of neuropathic pain, macrophages have been revealed to play an important role in pathologic pain following nerve injury. Macrophages dynamically monitor the microenvironment to maintain tissue homeostasis. Once a macrophage is exposed to a pathologic stimulus, it in turn alters its functional phenotype and interacts with nociceptors, leading to neuropathic pain. This review wants to delve into the biology of macrophages in the central and peripheral nervous system, how they are related to play a role in neuropathic pain and whether there is sexual dimorphism in macrophages.

Does the Dose of Standard Adjuvant Chemotherapy Affect the Triple-negative Breast Cancer Benefit from Extended Capecitabine Metronomic Therapy? An Exploratory Analysis of the SYSUCC-001 Trial.

Purpose: Results from studies of extended capecitabine after the standard adjuvant chemotherapy in early stage triple-negative breast cancer (TNBC) were inconsistent, and only low-dose capecitabine from the SYSUCC-001 trial improved disease-free survival (DFS). Adjustment of the conventional adjuvant chemotherapy doses affect the prognosis and may affect the efficacy of subsequent treatments. This study investigated whether the survival benefit of the SYSUCC-001 trial was affected by dose adjustment of the standard adjuvant chemotherapy or not. Patients and Methods: We reviewed the adjuvant chemotherapy regimens before the extended capecitabine in the SYSUCC-001 trial. Patients were classified into "consistent" (standard acceptable dose) and "inconsistent" (doses lower than acceptable dose) dose based on the minimum acceptable dose range in the landmark clinical trials. Cox proportional hazards model was used to investigate the impact of dose on the survival outcomes. Results: All 434 patients in SYSUCC-001 trial were enrolled in this study. Most of patients administered the anthracycline-taxane regimen accounted for 88.94%. Among patients in the "inconsistent" dose, 60.8% and 47% received lower doses of anthracycline and taxane separately. In the observation group, the "inconsistent" dose of anthracycline and taxane did not affect DFS compared with the "consistent" dose. Moreover, in the capecitabine group, the "inconsistent" anthracycline dose did not affect DFS compared with the "consistent" dose. However, patients with "consistent" taxane doses benefited significantly from extended capecitabine (P=0.014). The sufficient dose of adjuvant taxane had a positive effect of extended capecitabine (hazard ratio [HR] 2.04; 95% confidence interval [CI] 1.02 to 4.06). Conclusion: This study found the dose reduction of adjuvant taxane might negatively impact the efficacy of capecitabine. Therefore, the reduction of anthracycline dose over paclitaxel should be given priority during conventional adjuvant chemotherapy, if patients need dose reduction and plan for extended capecitabine.

OsALKBH9-mediated m6A demethylation regulates tapetal PCD and pollen exine accumulation in rice.

The N6-methyladenosine (m6A) mRNA modification is crucial for plant development and stress responses. In rice, the male sterility resulting from the deficiency of OsFIP37, a core component of m6A methyltransferase complex, emphasizes the significant role of m6A in male fertility. m6A is reversible and can be removed by m6A demethylases. However, whether mRNA m6A demethylase regulates male fertility in rice has remained unknown. Here, we identify the mRNA m6A demethylase OsALKBH9 and demonstrate its involvement in male fertility regulation. Knockout of OsALKBH9 causes male sterility, dependent on its m6A demethylation activity. Cytological analysis reveals defective tapetal programmed cell death (PCD) and excessive accumulation of microspores exine in Osalkbh9-1. Transcriptome analysis of anthers shows up-regulation of genes involved in tapetum development, sporopollenin synthesis, and transport pathways in Osalkbh9-1. Additionally, we demonstrate that OsALKBH9 demethylates the m6A modification in TDR and GAMYB transcripts, which affects the stability of these mRNAs and ultimately leads to excessive accumulation of pollen exine. Our findings highlight the precise control of mRNA m6A modification and reveal the pivotal roles played by OsALKBH9-mediated m6A demethylation in tapetal PCD and pollen exine accumulation in rice.

Concentrations and influencing factors of 17 elements in placenta, cord blood, and maternal blood of women from an e-waste recycling area.

BACKGROUND: The effects of prenatal element exposure on mothers and fetuses have generated concern. Profiles of trace and toxic elements in biological material are urgently desired, especially for women who reside near e-waste recycling facilities. The aim of this study was to investigate elements concentrations in placenta, cord blood, and maternal blood of women and to evaluate the influencing factors. METHODS: A group of 48 women from an e-waste recycling site and a group of 31 women from a non-e-waste recycling site were recruited. Basic characteristics were collected by questionnaire and the concentrations of 17 elements in placenta, cord blood, and maternal blood samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). Finally, the generalized linear model regression analysis (GLM) was used to test the association between element concentrations and possible factors. RESULTS: Compared to the control group, the exposed group had significantly elevated cadmium (Cd), zinc (Zn), nickel (Ni), and antimony (Sb) in placenta, and higher lead (Pb) in maternal blood and cord blood (P<0.05). Sb concentration in maternal blood was significantly lower than in the control group (P<0.05). GLM analysis showed that element concentrations were mainly associated with maternal age [chromium (Cr), iron (Fe), selenium (Se), cobalt (Co), mercury (Hg) in placenta, copper (Cu) in maternal blood], education (Se, Sb in placenta), family income (Cu in maternal blood and Ni in placenta), passive smoking [Cu and Zn in placenta, Pb in maternal blood], and e-waste contact history (Hg in cord blood, Cu, Zn, and Cd in maternal blood). CONCLUSIONS: Women in the e-waste recycling area had higher toxic element levels in the placenta and blood samples. More preventive measures were needed to reduce the risk of element exposure for mothers and fetuses in these areas.

Sunlight-driven and gram-scale vanillin production via Mn-defected γ-MnO2 catalyst in aqueous environment.

The production of vanillin from biomass offers a sustainable route for synthesizing daily-use chemicals. However, achieving sunlight-driven vanillin synthesis through H2O activation in an aqueous environment poses challenges due to the high barrier of H2O dissociation. In this study, we have successfully developed an efficient approach for gram-scale vanillin synthesis in an aqueous reaction, employing Mn-defected γ-MnO2 as a photocatalyst at room temperature. Density functional theory calculations reveal that the presence of defective Mn species (Mn3+) significantly enhances the adsorption of vanillyl alcohol and H2O onto the surface of the γ-MnO2 catalyst. Hydroxyl radical (˙OH) species are formed through H2O activation with the assistance of sunlight, playing a pivotal role as oxygen-reactive species in the oxidation of vanillyl alcohol into vanillin. The Mn-defected γ-MnO2 catalyst exhibits exceptional performance, achieving up to 93.4% conversion of vanillyl alcohol and 95.7% selectivity of vanillin under sunlight. Notably, even in a laboratory setting during the daytime, the Mn-defected γ-MnO2 catalyst demonstrates significantly higher catalytic performance compared to the dark environment. This work presents a highly effective and promising strategy for low-cost and environmentally benign vanillin synthesis.

Imaging electromagnetic boundary of microdevice using a wide field quantum microscope.

Imaging of electronic device surface or sub-surface electromagnetic fields under operating conditions is important for device design and diagnosis. In this study, we proposed a method to characterize specific magnetic field properties of electromagnetic devices at micron-scale using a solid-state quantum sensor, namely diamond nitrogen-vacancy (NV) centers. By employing a wide-field magnetic field measurement technique based on NV centers, we rapidly obtain the first-order magnetic field distribution of anomalous regions. Furthermore, we approximate the second-order magnetic field (magnetic gradient tensor) using the differential gradient method. To visualize the electromagnetic anomalous regions boundary, we utilize the tensor invariants of the magnetic gradient tensor components, along with their nonlinear combinations. The identification error rate of the anomalous regions is within 12.5%. Additionally, the electromagnetic field of anomalous regions is simulated showing the measurement accuracy. Our study shows that the experimental results are very similar to the theoretical simulation of the electromagnetic field (error: 7%). This work is essential for advancing electromagnetic field characterization of electronic devices and the advancement of quantum magnetic sensor applications.

Sub-pixel marking and depth-based correction methods for the elimination of voxel drifting in integral imaging display.

Integral imaging is a kind of true three-dimensional (3D) display technology that uses a lens array to reconstruct vivid 3D images with full parallax and true color. In order to present a high-quality 3D image, it's vital to correct the axial position error caused by the misalignment and deformation of the lens array which makes the reconstructed lights deviate from the correct directions, resulting in severe voxel drifting and image blurring. We proposed a sub-pixel marking method to measure the axial position error of the lenses with great accuracy by addressing the sub-pixels under each lens and forming a homologous sub-pixel pair. The proposed measurement method relies on the geometric center alignment of image points, which is specifically expressed as the overlap between the test 3D voxel and the reference 3D voxel. Hence, measurement accuracy could be higher. Additionally, a depth-based sub-pixel correction method was proposed to eliminate the voxel drifting. The proposed correction method takes the voxel depth into consideration in the correction coefficient, and achieves accurate error correction for 3D images with different depths. The experimental results well confirmed that the proposed measuring and correction methods can greatly suppress the voxel drifting caused by the axial position error of the lenses, and greatly improve the 3D image quality.

MFNet: Meta-learning based on frequency-space mix for MRI segmentation in nasopharyngeal carcinoma.

Deep learning techniques have been applied to medical image segmentation and demonstrated expert-level performance. Due to the poor generalization abilities of the models in the deployment in different centres, common solutions, such as transfer learning and domain adaptation techniques, have been proposed to mitigate this issue. However, these solutions necessitate retraining the models with target domain data and annotations, which limits their deployment in clinical settings in unseen domains. We evaluated the performance of domain generalization methods on the task of MRI segmentation of nasopharyngeal carcinoma (NPC) by collecting a new dataset of 321 patients with manually annotated MRIs from two hospitals. We transformed the modalities of MRI, including T1WI, T2WI and CE-T1WI, from the spatial domain to the frequency domain using Fourier transform. To address the bottleneck of domain generalization in MRI segmentation of NPC, we propose a meta-learning approach based on frequency domain feature mixing. We evaluated the performance of MFNet against existing techniques for generalizing NPC segmentation in terms of Dice and MIoU. Our method evidently outperforms the baseline in handling the generalization of NPC segmentation. The MF-Net clearly demonstrates its effectiveness for generalizing NPC MRI segmentation to unseen domains (Dice = 67.59%, MIoU = 75.74% T1W1). MFNet enhances the model's generalization capabilities by incorporating mixed-feature meta-learning. Our approach offers a novel perspective to tackle the domain generalization problem in the field of medical imaging by effectively exploiting the unique characteristics of medical images.