The association between polychlorinated dibenzo-p-dioxin exposure and cancer mortality in the general population: a cohort study.

Introduction: Earlier research has indicated that being exposed to polychlorinated dibenzo-p-dioxins (PCDDs) in the workplace can heighten the likelihood of cancer-related deaths. Nevertheless, there is limited information available regarding the connection between PCDD exposure and the risk of cancer mortality in the general population (i.e., individuals not exposed to these substances through their occupation). Methods: The National Health and Nutrition Examination Survey (NHANES) detected PCDDs in the general population, and the death data were recently updated as of December 31, 2019. We conducted Cox regression analysis and controlled for covariates including age, gender, ethnicity, educational attainment, physical activity, alcohol intake, NHANES survey period, BMI category, cotinine concentration, and household earnings. Results: After accounting for confounding factors, the findings indicated that for each incremental rise of 1 log unit in 1,2,3,4,6,7,8,9-octachlorodibenzo-p-dioxin, there was a 76% rise in the likelihood of death from any cause, with a p value of 0.003. An increase of 1 log unit in the concentration of 1,2,3,4,6,7,8-heptachlorodibenzofuran could potentially lead to a 90% higher risk of cancer mortality, as indicated by a p value of 0.034 and a 95% confidence interval of 0.05-2.43. As the concentrations of 1,2,3,4,6,7,8-heptachlorodibenzofuran increased, the dose-response curve indicated a proportional rise in the risk of cancer mortality, accompanied by a linear p value of 0.044. The sensitivity analysis demonstrated that our findings were resilient. Discussion: In the general population, an elevated risk of cancer mortality was observed in PCDDs due to the presence of 1,2,3,4,6,7,8-heptachlorodibenzofuran. Mechanistic research is required to further confirm it.

Expert consensus on the diagnosis, treatment, and prevention of respiratory syncytial virus infections in children.

BACKGROUND: Respiratory syncytial virus (RSV) is the leading global cause of respiratory infections and is responsible for about 3 million hospitalizations and more than 100,000 deaths annually in children younger than 5 years, representing a major global healthcare burden. There is a great unmet need for new agents and universal strategies to prevent RSV infections in early life. A multidisciplinary consensus development group comprising experts in epidemiology, infectious diseases, respiratory medicine, and methodology aims to develop the current consensus to address clinical issues of RSV infections in children. DATA SOURCES: The evidence searches and reviews were conducted using electronic databases, including PubMed, Embase, Web of Science, and the Cochrane Library, using variations in terms for "respiratory syncytial virus", "RSV", "lower respiratory tract infection", "bronchiolitis", "acute", "viral pneumonia", "neonatal", "infant" "children", and "pediatric". RESULTS: Evidence-based recommendations regarding diagnosis, treatment, and prevention were proposed with a high degree of consensus. Although supportive care remains the cornerstone for the management of RSV infections, new monoclonal antibodies, vaccines, drug therapies, and viral surveillance techniques are being rolled out. CONCLUSIONS: This consensus, based on international and national scientific evidence, reinforces the current recommendations and integrates the recent advances for optimal care and prevention of RSV infections. Further improvements in the management of RSV infections will require generating the highest quality of evidence through rigorously designed studies that possess little bias and sufficient capacity to identify clinically meaningful end points.

Effect of transglutaminase on ovalbumin emulsion gels as carriers of encapsulated probiotic bacteria.

BACKGROUND: The use of emulsion gels to protect and deliver probiotics has become an important topic in the food industry. This study used transglutaminase (TGase) to regulate ovalbumin (OVA) to prepare a novel emulsion gel. The effects of OVA concentration and the addition of TGase on the microstructure, rheological properties, water-holding capacity, and stability of the emulsion gels were investigated. RESULTS: With the addition of TGase and the increasing OVA, the particle size of the emulsion gels decreased significantly (P < 0.05). The gels with TGase exhibited greater water holding, hardness, and chewiness to some extent by forming a more uniform and stable system. After simulated digestion, the survival rate of Bifidobacterium lactis embedded in OVA emulsion gels improved significantly in comparison with the oil-water mixture as a result of the protective effect of the emulsion gel encapsulation. CONCLUSION: By increasing the OVA content and adding TGase, the rheological characteristics, stability, and encapsulation capability of the OVA emulsion gel could be enhanced, providing a theoretical basis for the use of emulsion gels to construct probiotic delivery systems. © 2023 Society of Chemical Industry.

Association of organophosphate flame retardants with all-cause and cause-specific mortality among adults aged 40 years and older.

The longitudinal associations of urinary concentrations of diphenyl phosphate (DPHP), bis(2-chloroethyl) phosphate (BCEP), and bis(1,3-dichloro-2-propyl) phosphate (BDCPP) with all-cause, cardiovascular, and cancer mortality in a population of adults aged 40 years and older are still unclear. A total of 3238 participants were included in this cohort study. Urinary BCEP levels were positively associated with all-cause mortality and cardiovascular mortality. Specifically, a logarithmic increase in BCEP concentration was related to a 26 % higher risk of all-cause mortality and a 32 % higher risk of cardiovascular mortality. No significant associations were observed for DPHP and BDCPP in relation to mortality. Doseresponse analysis confirmed the linear associations of BCEP with all-cause and cardiovascular mortality and the nonlinear inverted U-shaped association between DPHP exposure and all-cause mortality. Notably, the economic burden associated with BCEP exposure was estimated, and it was shown that concentrations in the third tertile of BCEP exposure incurred approximately 507 billion dollars of financial burden for all-cause mortality and approximately 717 billion dollars for cardiovascular mortality. These results highlight the importance of addressing exposure to BCEP and its potential health impacts on the population. More research is warranted to explore the underlying mechanisms and develop strategies for reducing exposure to this harmful chemical.

Preparation and Application of Polyrotaxane Cross-Linking Agent Based on Cyclodextrin in Gel Materials Field.

The cross-linking point of a conventional chemical cross-linking agent is fixed. Therefore, gels that are prepared with a conventional cross-linking agent have poor deformability, strength, shear resistance, and further properties. Some researchers have prepared a new cross-linking agent using cyclodextrin (CD). In a polyrotaxane cross-linking agent, the cross-linking points can slide freely along the molecule chain. The special "slide ring" structure can provide better elongation, strength, and other properties to gels, which can effectively expand the application of the gel's materials. This paper summarizes the preparation methods and applications from different types of CD and compares the improvements of properties (swelling, viscoelastic properties, etc.). In addition, the current results of our group are presented, and some ideas are provided for the development of polyrotaxane cross-linking agents.

Preparation and Degradation Performance Study of P(AM/GG/PEGDA) Nanocomposite Self-Degradation Gel Plugging Material.

Lost circulation is a world-class problem, and the contradiction between plugging and unplugging in reservoirs is a problem that needs to be solved urgently. The traditional LCM is not suitable for reservoirs and the complex subsequent operations. Currently, a self-degrading plugging material is proposed. In this paper, a new self-degradation plugging material, CKS-DPPG, was prepared by AM, GG, nano silica, and PEGDA. The effects of reactant concentration, pH, mineralization, etc., on the swelling and degradation performance of CKS-DPPG were investigated. The plugging capacity was tested by fracture plugging equipment, and the mechanism of self-degradation was revealed. The results show that the CKS-DPPG reached a 50% degradation rate in 54 h and complete degradation in 106 h at 80 °C and pH = 8. Low temperatures, high mineralization, and weak alkaline conditions prolong the complete degradation time of CKS-DPPG, which facilitates subsequent operations. The simulation of the 3 mm opening fracture plugging experiment showed that the pressure-bearing capacity reached 6.85 MPa and that a 0.16 MPa pressure difference could unplug after degradation. The ester bond of PEGDA is hydrolyzed under high-temperature conditions, and the spatial three-dimensional structure of CKS-DPPG becomes linear. The CKS-DPPG can effectively reduce subsequent unplugging operations and lower production costs.

Mediation analysis of urinary metals and stroke risk by inflammatory markers.

BACKGROUND: The association between metals and stroke has been reported, but the mediating role of inflammation between metals and stroke remains unclear. METHODS: We included 9326 adults from the National Health and Nutrition Examination Survey in this study. Through least absolute selection and shrinkage operator (LASSO) regression, weighted quantile sum (WQS) regression, logistic regression, linear regression, restricted cubic spline analysis, and mediation analysis, we explored the association between metals and stroke, as well as the association between metals and inflammatory indicators, and further evaluated the mediating effect of inflammatory indicators on the association between selected metals and stroke risk. RESULTS: The results of the present study suggested positive associations between mixed metals, cadmium and uranium and stroke risk. There is a positive correlation and dose‒response relationship between cadmium and C-reactive protein (CRP). Moreover, CRP mediates 10.1% of the association between cadmium and stroke. CONCLUSIONS: At the epidemiological level, CRP mediates the association between cadmium and stroke risk, suggesting that inflammation may be a potential mechanism for metal-induced stroke.

Low-dimensional high entropy oxide (FeCoCrMnNi)3O4 for supercapacitor applications.

Previous studies have found that high entropy oxides can be used as electrode materials for supercapacitors. However, there is still the problem of their low energy density. We tried to increase the energy density while increasing the specific capacitance of high entropy oxides from the potential window. Transition metal elements Fe, Co, Cr, Mn and Ni were selected for their electrochemical activity, and high entropy oxides were prepared by a sol-gel method under different calcination temperatures. The calcination temperature affects the structural morphology and crystallinity of the high entropy oxides and thus also affects the electrochemical performance. The spinel-phase (FeCoCrMnNi)3O4 with a high specific surface area of 63.1 m2 g-1 was prepared at a low calcination temperature of 450 °C. The specific capacitance is 332.2 F g-1 at a current density of 0.3 A g-1 in 1 M KOH electrolyte with a wide potential window of (-1, 0.6). An improved energy density of 103.8 W h kg-1 is reached via the designed microstructure of the high entropy oxide electrode.

A Structure-Aware Hierarchical Graph-Based Multiple Instance Learning Framework for pT Staging in Histopathological Image.

Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to surrounding tissues, which relates to the prognosis and treatment choices. The pT staging relies on the field-of-views from multiple magnifications in the gigapixel images, which makes pixel-level annotation difficult. Therefore, this task is usually formulated as a weakly supervised whole slide image (WSI) classification task with the slide-level label. Existing weakly-supervised classification methods mainly follow the multiple instance learning paradigm, which takes the patches from single magnification as the instances and extracts their morphological features independently. However, they cannot progressively represent the contextual information from multiple magnifications, which is critical for pT staging. Therefore, we propose a structure-aware hierarchical graph-based multi-instance learning framework (SGMF) inspired by the diagnostic process of pathologists. Specifically, a novel graph-based instance organization method is proposed, namely structure-aware hierarchical graph (SAHG), to represent the WSI. Based on that, we design a novel hierarchical attention-based graph representation (HAGR) network to capture the critical patterns for pT staging by learning cross-scale spatial features. Finally, the top nodes of SAHG are aggregated by a global attention layer for bag-level representation. Extensive studies on three large-scale multi-center pT staging datasets with two different cancer types demonstrate the effectiveness of SGMF, which outperforms state-of-the-art up to 5.6% in the F1 score.

Childhood Leukemia Classification via Information Bottleneck Enhanced Hierarchical Multi-Instance Learning.

Leukemia classification relies on a detailed cytomorphological examination of Bone Marrow (BM) smear. However, applying existing deep-learning methods to it is facing two significant limitations. Firstly, these methods require large-scale datasets with expert annotations at the cell level for good results and typically suffer from poor generalization. Secondly, they simply treat the BM cytomorphological examination as a multi-class cell classification task, thus failing to exploit the correlation among leukemia subtypes over different hierarchies. Therefore, BM cytomorphological estimation as a time-consuming and repetitive process still needs to be done manually by experienced cytologists. Recently, Multi-Instance Learning (MIL) has achieved much progress in data-efficient medical image processing, which only requires patient-level labels (which can be extracted from the clinical reports). In this paper, we propose a hierarchical MIL framework and equip it with Information Bottleneck (IB) to tackle the above limitations. First, to handle the patient-level label, our hierarchical MIL framework uses attention-based learning to identify cells with high diagnostic values for leukemia classification in different hierarchies. Then, following the information bottleneck principle, we propose a hierarchical IB to constrain and refine the representations of different hierarchies for better accuracy and generalization. By applying our framework to a large-scale childhood acute leukemia dataset with corresponding BM smear images and clinical reports, we show that it can identify diagnostic-related cells without the need for cell-level annotations and outperforms other comparison methods. Furthermore, the evaluation conducted on an independent test cohort demonstrates the high generalizability of our framework.

EVA1A regulates hematopoietic stem cell regeneration via ER-mitochondria mediated apoptosis.

Excessive protein synthesis upon enhanced cell proliferation frequently results in an increase of unfolded or misfolded proteins. During hematopoietic regeneration, to replenish the hematopoietic system, hematopoietic stem cells (HSCs) are activated and undergo a rapid proliferation. But how the activated HSCs respond to the proliferation pressure is still ambiguous; The proper control of the functional reservoir in the activated HSCs remains poorly understood. Here, we show a significant upregulation of EVA1A protein associated with the increase of ER stress during hematopoietic regeneration. Deletion of Eva1a significantly enhances the regeneration capacity of HSCs by inhibiting the ER stress-induced apoptosis. Mechanistically, the expression of EVA1A protein was upregulated by CHOP, and thereby promoted the ER-mitochondria interlinking via MCL1, which resulted in mitochondria-mediated apoptosis. These findings reveal a pathway for ER stress responses of HSCs by the EVA1A mediated apoptosis, which play an important role in HSCs regeneration.

A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images.

Cancer region detection (CRD) and subtyping are two fundamental tasks in digital pathology image analysis. The development of data-driven models for CRD and subtyping on whole-slide images (WSIs) would mitigate the burden of pathologists and improve their accuracy in diagnosis. However, the existing models are facing two major limitations. Firstly, they typically require large-scale datasets with precise annotations, which contradicts with the original intention of reducing labor effort. Secondly, for the subtyping task, the non-cancerous regions are treated as the same as cancerous regions within a WSI, which confuses a subtyping model in its training process. To tackle the latter limitation, the previous research proposed to perform CRD first for ruling out the non-cancerous region, then train a subtyping model based on the remaining cancerous patches. However, separately training ignores the interaction of these two tasks, also leads to propagating the error of the CRD task to the subtyping task. To address these issues and concurrently improve the performance on both CRD and subtyping tasks, we propose a semi-supervised multi-task learning (MTL) framework for cancer classification. Our framework consists of a backbone feature extractor, two task-specific classifiers, and a weight control mechanism. The backbone feature extractor is shared by two task-specific classifiers, such that the interaction of CRD and subtyping tasks can be captured. The weight control mechanism preserves the sequential relationship of these two tasks and guarantees the error back-propagation from the subtyping task to the CRD task under the MTL framework. We train the overall framework in a semi-supervised setting, where datasets only involve small quantities of annotations produced by our minimal point-based (min-point) annotation strategy. Extensive experiments on four large datasets with different cancer types demonstrate the effectiveness of the proposed framework in both accuracy and generalization.

Structure of Amorphous Two-Dimensional Materials: Elemental Monolayer Amorphous Carbon versus Binary Monolayer Amorphous Boron Nitride.

The structure of amorphous materials has been debated since the 1930s as a binary question: amorphous materials are either Zachariasen continuous random networks (Z-CRNs) or Z-CRNs containing crystallites. It was recently demonstrated, however, that amorphous diamond can be synthesized in either form. Here we address the question of the structure of single-atom-thick amorphous monolayers. We reanalyze the results of prior simulations for amorphous graphene and report kinetic Monte Carlo simulations based on alternative algorithms. We find that crystallite-containing Z-CRN is the favored structure of elemental amorphous graphene, as recently fabricated, whereas the most likely structure of binary monolayer amorphous BN is altogether different than either of the two long-debated options: it is a compositionally disordered "pseudo-CRN" comprising a mix of B-N and noncanonical B-B and N-N bonds and containing "pseudocrystallites", namely, honeycomb regions made of noncanonical hexagons. Implications for other nonelemental 2D and bulk amorphous materials are discussed.

Unsupervised Representation Learning for Tissue Segmentation in Histopathological Images: From Global to Local Contrast.

Tissue segmentation is an essential task in computational pathology. However, relevant datasets for such a pixel-level classification task are hard to obtain due to the difficulty of annotation, bringing obstacles for training a deep learning-based segmentation model. Recently, contrastive learning has provided a feasible solution for mitigating the heavy reliance of deep learning models on annotation. Nevertheless, applying contrastive loss to the most abstract image representations, existing contrastive learning frameworks focus on global features, therefore, are less capable of encoding finer-grained features (e.g., pixel-level discrimination) for the tissue segmentation task. Enlightened by domain knowledge, we design three contrastive learning tasks with multi-granularity views (from global to local) for encoding necessary features into representations without accessing annotations. Specifically, we construct: (1) an image-level task to capture the difference between tissue components, i.e., encoding the component discrimination; (2) a superpixel-level task to learn discriminative representations of local regions with different tissue components, i.e., encoding the prototype discrimination; (3) a pixel-level task to encourage similar representations of different tissue components within a local region, i.e., encoding the spatial smoothness. Through our global-to-local pre-training strategy, the learned representations can reasonably capture the domain-specific and fine-grained patterns, making them easily transferable to various tissue segmentation tasks in histopathological images. We conduct extensive experiments on two tissue segmentation datasets, while considering two real-world scenarios with limited or sparse annotations. The experimental results demonstrate that our framework is superior to existing contrastive learning methods and can be easily combined with weakly supervised and semi-supervised segmentation methods.

A digital SIW-slot antenna array with FPGA implementation of beamforming.

The future satellite platform and 5G communication systems place high demands on antennas, in which the antenna should offer low-cost, lightweight, electronically steerable features. In this paper, the design of a digital slot antenna element based on substrate integrated waveguide (SIW) is proposed. SIW guides the microwave inside the substrate confined with planar metallic covers and through-hole synthetized side-walls in conventional applications, and can also radiate the microwave towards free space in antenna applications through opening slots in its metallic covers. The slot antenna element is realized by implementing PIN diodes across the gaps on both sides of the pad in the center of the slot antenna, to provide the switching freedom of the slot antenna element between radiating and non-radiating states. Besides, radial decoupling stubs are introduced into the bias line so as to reduce the leakage of the energy in the SIW structure. Applying a series of on/off states to the diodes produces various radiation patterns, thus wide range scanning is possible supposing that enough array elements are equipped. Finally, a digital SIW-slot array composed of 8 by 4 elements with tunable field programmable gate array circuits are fabricated and measured. The measured results validate the reconfigurable characteristics for the radiation pattern of the proposed digital SIW-slot antenna array without heavy engineering of phase shifter in conventional antenna arrays. The antenna is consisted by 4 by 8 elements and its dimension, simulated gain and radiation efficiency are 145 mm [Formula: see text] 127 mm [Formula: see text] 1.524 mm, 15 dBi and 53.5%, respectively. Our designed SIW antenna has the advantage of both size and weight. Furthermore, its digitalized control of beamforming allows a programming-friendly interface for smart antenna development.

A Study of the Mechanism and Separation of Structurally Similar Phenolic Acids by Commercial Polymeric Ultrafiltration Membranes.

This study examined the behavior and penetration mechanisms of typical phenolic (benzoic) acids, which determine their observed penetration rates during membrane separation, focusing on the influence of electrostatic and hydrophobic solute/membrane interactions. To understand the effects of hydrophobicity and electrostatic interaction on membrane filtration, the observed penetration of five structurally similar phenolic acids was compared with regenerated cellulose (RC) and polyamide (PA) membranes at different solute concentrations and solution pHs. Variation partitioning analysis (VPA) was performed to calculate the relative contributions of electrostatic and hydrophobic effects. The penetration of phenolic acids was mainly influenced by the electrostatic interaction, with salicylic acid having the highest penetration. Penetration of phenolic acids through the PA membrane decreased from 98% at pH 3.0 to 30-50% at pH 7.4, indicating the dominance of the electrostatic interaction. Moreover, based on its hydrophobicity and greater surface charge, the PA membrane could separate binary mixtures of protocatechuic/salicylic acid and 4-hydroxybenzoic/salicylic acid at pH 9.0, with separation factors of 1.81 and 1.78, respectively. These results provide a greater understanding of solute/membrane interactions and their effect on the penetration of phenolic acids through polymeric ultrafiltration membranes.

Membrane dynamics of ATG4B and LC3 in autophagosome formation.

The biogenesis of autophagosomes provides the basis for macroautophagy to capture and degrade intracellular cargoes. Binding of the autophagy-related protein ATG8/LC3 to autophagic membranes is essential to autophagosome formation, which involves the specific and dynamic processing of ATG8/LC3 by cysteine protease ATG4. However, to date, the mechanism whereby ATG4 is recruited to the membranes, the interaction of ATG4 and ATG8/LC3 on the membranes, and its role in the growth of phagophore are not completely understood. Here, we used fluorescence recovery after photobleaching to monitor the turnover of GFP-tagged ATG4B and LC3B in living animal cells. The data show that ATG4B localizes to early autophagic membranes in an LC3B-dependent manner. During autophagy, ATG4B and LC3B undergo rapid cytosol/isolation membrane exchange but not at the cytosol/completed autophagosome. In addition, ATG4B activity controls the efficiency of autophagosome formation by impacting the membrane binding/dissociation of LC3B. These data suggest that ATG4 and LC3 play interdependent roles in the formation of autophagosomes.

An Exploration of Mutagenesis in a Family with Cleidocranial Dysplasia without RUNX2 Mutation.

Cleidocranial dysplasia (CCD) is an autosomal dominant inheritable skeletal disorder characterized by cranial dysplasia, clavicle hypoplasia, and dental abnormalities. Mutations involving Runt-related transcription factor 2 (RUNX2) are currently the only known molecular etiology for CCD but are not identified in all CCD patients. No RUNX2 abnormality can be detected in about 20-30% of patients, and the molecular cause remains unknown. The present study includes a family case with typical features of CCD. RUNX2 mutation was first screened by sequencing analysis, and no mutation was detected. Copy number alterations of the RUNX2 gene were then measured by quantitative PCR and multiplex ligation-dependent probe amplification (MLPA). No copy number variation in RUNX2 could be detected. We performed whole-exome sequencing (WES) to identify the underlying genetic mutations. Unexpectedly, no abnormalities could be detected in genes related to the RUNX2 signaling pathway. Therefore, it was supposed that other new unknown gene variations might contribute to the CCD phenotype. We focused on Immunoglobulin superfamily member 10 (IGSF10), a gene related to bone development. An IGSF10 frameshift mutation (c.6001_6002delCT, p.Leu2001Valfs*24) was detected by WES. Sanger sequencing verified that this mutation was only detected in the patient and her affected mother but not in her unaffected father. Bioinformatics studies demonstrated that this mutation could change the 3D structure of the IGSF10 protein and severely damage its function. In addition, alkaline phosphatase (ALP) activity and the ability to form mineralized nodules were inhibited by IGSF10 knockdown compared with normal controls. The expression of bone sialoprotein (BSP) was significantly reduced by IGSF10 knockdown, but not that of other osteogenic markers. Our results provide new genetic evidence that IGSF10 mutation might contribute to CCD.

[Effect of Laptm4b Deletion on Hematopoietic Stem and Progenitor Cells Homeostasis in Mice].

OBJECTIVE: To investigate the effect of lysosomal-associated protein transmembrane-4 Beta(Laptm4b) deletion on hematopoietic stem/progenitor cells (HSPCs) homeostasis in mice. METHODS: The hematopoietic system specific Laptm4b-deficient mice were constructed. The number and proportion of HSPCs (LSK, LT, ST, MPP, etc) in Laptm4b-deficient mice were analyzed by flow cytometry. Single SLAM-HSC cell was sorted by flow sorter and cultured in vitro to measure the effect of Laptm4b deletion on the colony forming ability of hematopoietic stem cells (HSCs). The effect of Laptm4b-deficient on the reconstitution ability of HSCs in mice was detected by competitive transplantation experiment of SLAM-HSC cells. RESULTS: Laptm4b deficiency could moderately upregulate the proportion of T cells in the peripheral blood of the mice, but showed no significant effect on the proportion and number of HSPCs. Laptm4b deletion showed no effect on the reconstruction ability of HSCs after competitive transplantation, but it could inhibit the colony formation of HSCs in vitro. CONCLUSION: LAPTM4B may play a role in HSCs under the proliferation stress. Laptm4b-deficient in mice hematopoietic system showed no significant effect on the HSPCs homeostasis maintenance and reconstruction ability.