Efficient remediation of different concentrations of Cr-contaminated soils by nano zero-valent iron modified with carboxymethyl cellulose and biochar.

Nano zero-valent iron (nZVI) is widely used in soil remediation due to its high reactivity. However, the easy agglomeration, poor antioxidant ability and passivation layer of Fe-Cr coprecipitates of nZVI have limited its application scale in Cr-contaminated soil remediation, especially in high concentration of Cr-contaminated soil. Herein, we found that the carboxymethyl cellulose on nZVI particles could increase the zeta potential value of soil and change the phase of nZVI. Along with the presence of biochar, 97.0% and 96.6% Cr immobilization efficiency through CMC-nZVI/BC were respectively achieved in high and low concentrations of Cr-contaminated soils after 90-days remediation. In addition, the immobilization efficiency of Cr(VI) only decreased by 5.1% through CMC-nZVI/BC treatment after 10 weeks aging in air, attributing to the strong antioxidation ability. As for the surrounding Cr-contaminated groundwater, the Cr(VI) removal capacity of CMC-nZVI/BC was evaluated under different reaction conditions through column experiments and COMSOL Multiphysics. CMC-nZVI/BC could efficiently remove 85% of Cr(VI) in about 400 hr when the initial Cr(VI) concentration was 40 mg/L and the flow rate was 0.5 mL/min. This study demonstrates that uniformly dispersed CMC-nZVI/BC has an excellent remediation effect on different concentrations of Cr-contaminated soils.

Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region.

OBJECTIVES: To explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI). METHODS: A total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC). RESULTS: The XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80. CONCLUSION: Compared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted. CLINICAL RELEVANCE STATEMENT: The 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region. KEY POINTS: We investigated tumor and different peritumoral regions, as well as their fusion. MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region. The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.

PI4P-mediated solid-like Merlin condensates orchestrate Hippo pathway regulation.

Despite recent studies implicating liquid-like biomolecular condensates in diverse cellular processes, many biomolecular condensates exist in a solid-like state, and their function and regulation are less understood. We show that the tumor suppressor Merlin, an upstream regulator of the Hippo pathway, localizes to both cell junctions and medial apical cortex in Drosophila epithelia, with the latter forming solid-like condensates that activate Hippo signaling. Merlin condensation required phosphatidylinositol-4-phosphate (PI4P)-mediated plasma membrane targeting and was antagonistically controlled by Pez and cytoskeletal tension through plasma membrane PI4P regulation. The solid-like material properties of Merlin condensates are essential for physiological function and protect the condensates against external perturbations. Collectively, these findings uncover an essential role for solid-like condensates in normal physiology and reveal regulatory mechanisms for their formation and disassembly.

Achieving Remarkable Specific Mechanical Strength and Energy Absorption Capacity in SiC Nanowire Networks through Graded Structural Design.

Lightweight porous ceramics with a unique combination of superior mechanical strength and damage tolerance are in significant demand in many fields such as energy absorption, aerospace vehicles, and chemical engineering; however, it is difficult to meet these mechanical requirements with conventional porous ceramics. Here, we report a graded structure design strategy to fabricate porous ceramic nanowire networks that simultaneously possess excellent mechanical strength and energy absorption capacity. Our optimized graded nanowire networks show a compressive strength of up to 35.6 MPa at a low density of 540 mg·cm-3, giving rise to a high specific compressive strength of 65.7 kN·m·kg-1 and a high energy absorption capacity of 17.1 kJ·kg-1, owing to a homogeneous distribution of stress upon loading. These values are top performance compared to other porous ceramics, giving our materials significant potential in various engineering fields.

Review of cathodic electroactive bacteria: Species, properties, applications and electron transfer mechanisms.

Cathodic electroactive bacteria (C-EAB) which are capable of accepting electrons from solid electrodes provide fresh avenues for pollutant removal, biosensor design, and electrosynthesis. This review systematically summarized the burgeoning applications of the C-EAB over the past decade, including 1) removal of nitrate, aromatic derivatives, and metal ions; 2) biosensing based on biocathode; 3) electrosynthesis of CH4, H2, organic carbon, NH3, and protein. In addition, the mechanisms of electron transfer by the C-EAB are also classified and summarized. Extracellular electron transfer and interspecies electron transfer have been introduced, and the electron transport mechanism of typical C-EAB, such as Shewanella oneidensis MR-1, has been combed in detail. By bringing to light this cutting-edge area of the C-EAB, this review aims to stimulate more interest and research on not only exploring great potential applications of these electron-accepting bacteria, but also developing steady and scalable processes harnessing biocathodes.

Association between Personal Abiotic Airborne Exposures and Body Composition Changes among Healthy Adults (60-69 Years Old): A Combined Exposome-Wide and Lipidome Mediation Approach from the China BAPE Study.

BACKGROUND: Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults. OBJECTIVES: Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome. METHODS: From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators. RESULTS: The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate (FDRBH)<0.05]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi-α-cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% (p-value <0.05), of the observed increase in VFA. DISCUSSION: Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.

Tailoring Mechanical Properties of a Ceramic Nanowire Aerogel with Pyrolytic Carbon for In Situ Resilience at 1400 °C.

Resilient ceramic aerogels with a unique combination of lightweight, good high-temperature stability, high specific area, and thermal insulation properties are known for their promising applications in various fields. However, the mechanical properties of traditional ceramic aerogels are often constrained by insufficient interlocking of the building blocks. Here, we report a strategy to largely increase the interlocking degree of the building blocks by depositing a pyrolytic carbon (PyC) coating onto Si3N4 nanowires. The results show that the mechanical performances of the Si3N4 nanowire aerogels are intricately linked to the microstructure of the PyC nodes. The compression resilience of the Si3N4@PyC nanowire aerogels increases with an increase of the interlayer cross-linking in PyC. Additionally, benefiting from the excellent high-temperature stability of PyC, the Si3N4@PyC nanowire aerogels demonstrate significantly superior in situ resilience up to 1400 °C. The integrated mechanical and high-temperature properties of the Si3N4@PyC nanowire aerogels make them highly appealing for applications in harsh conditions. The facile method of manipulating the microstructure of the nodes may offer a perspective for tailoring the mechanical properties of ceramic aerogels.

Combination of RNA-seq and proteomics reveals the mechanism of DL0410 treatment in APP/PS1 transgenic mouse model of Alzheimer's disease.

There is a lack of a systematic understanding of the specific mechanism of action of DL0410 in AD treatment. In this study, the combination of RNA-seq and proteomics was firstly employed to uncover the mechanism of action of DL0410 in APP/PS1 transgenic mice. The results of behavioral tests showed that oral administration of DL0410 for 8 weeks improved memory and cognition of APP/PS1 mice. DL0410 significantly reduced ß-amyloid deposition and resulted in significant upregulation of synaptophysin, PSD95 and NMDAR/ CaMKⅡ signaling pathway in the hippocampus and cortex, indicating that DL0410 improved synaptic plasticity in APP/PS1 mice, which agrees with the results of RNA-seq and proteomics. Furthermore, the enrichment results of differentially expressed genes identified by RNA-seq and proteomics demonstrate the potential protective effects of DL0410 against oxidative stress and mitochondrial dysfunction. As expected, DL0410 dose-dependently ameliorated oxidative damage and markedly increased the expression of PGC-1α, TFAM, SOD1 and SOD2. Mitochondrial high-resolution respirometry results revealed that mitochondrial respiratory function was significantly improved in APP/PS1 mice administered with DL0410. In addition, DL0410 treatment reduced oxidative damage, strengthened antioxidant system and improved mitochondrial function in Aß-induced HT22 cells. Altogether, our findings suggest the potential of DL0410 as a novel candidate for AD treatment.

Personal exposure to airborne organic pollutants and lung function changes among healthy older adults.

Epidemiological evidence on the impact of airborne organic pollutants on lung function among the elderly is limited, and their underlying biological mechanisms remain largely unexplored. Herein, a longitudinal panel study was conducted in Jinan, Shandong Province, China, involving 76 healthy older adults monitored over a span of five months repetitively. We systematically evaluated personal exposure to a diverse range of airborne organic pollutants using a wearable passive sampler and their effects on lung function. Participants' pulmonary function indicators were assessed, complemented by comprehensive multi-omics analyses of blood and urine samples. Leveraging the power of interaction analysis, causal inference test (CIT), and integrative pathway analysis (IPA), we explored intricate relationships between specific organic pollutants, biomolecules, and lung function deterioration, elucidating the biological mechanisms underpinning the adverse impacts of these pollutants. We observed that bis (2-chloro-1-methylethyl) ether (BCIE) was significantly associated with negative changes in the forced vital capacity (FVC), with glycerolipids mitigating this adverse effect. Additionally, 31 canonical pathways [e.g., high mobility group box 1 (HMGB1) signaling, phosphatidylinositol 3-kinase (PI3K)/AKT pathway, epithelial mesenchymal transition, and heme and nicotinamide adenine dinucleotide (NAD) biosynthesis] were identified as potential mechanisms. These findings may hold significant implications for developing effective strategies to prevent and mitigate respiratory health risks arising from exposure to such airborne pollutants. However, due to certain limitations of the study, our results should be interpreted with caution.

KLSANet: Key local semantic alignment Network for few-shot image classification.

Few-shot image classification involves recognizing new classes with a limited number of labeled samples. Current local descriptor-based methods, while leveraging consistent low-level features across visible and invisible classes, face challenges including redundant adjacent information, irrelevant partial representation, and limited interpretability. This paper proposes KLSANet, a few-shot image classification approach based on key local semantic alignment network, which aligns key local semantics for accurate classification. Furthermore, we introduce a key local screening module to mitigate the influence of semantically irrelevant image parts on classification. KLSANet demonstrates superior performance on three benchmark datasets (CUB, Stanford Dogs, Stanford Cars), outperforming state-of-the-art methods in 1-shot and 5-shot settings with average improvements of 3.95% and 2.56% respectively. Visualization experiments demonstrate the interpretability of KLSANet predictions. Code is available at: https://github.com/ZitZhengWang/KLSANet.

On-Wire Design of Axial Periodic Halide Perovskite Superlattices for High-Performance Photodetection.

Precise synthesis of all-inorganic lead halide perovskite nanowire heterostructures and superlattices with designable modulation of chemical compositions is essential for tailoring their optoelectronic properties. Nevertheless, controllable synthesis of perovskite nanostructure heterostructures remains challenging and underexplored to date. Here, we report a rational strategy for wafer-scale synthesis of one-dimensional periodic CsPbCl3/CsPbI3 superlattices. We show that the highly parallel array of halide perovskite nanowires can be prepared roughly as horizontally guided growth on an M-plane sapphire. A periodic patterning of the sapphire substrate enables position-selective ion exchange to obtain highly periodic CsPbCl3/CsPbI3 nanowire superlattices. This patterning is further confirmed by micro-photoluminescence investigations, which show that two separate band-edge emission peaks appear at the interface of a CsPbCl3/CsPbI3 heterojunction. Additionally, compared with the pure CsPbCl3 nanowires, photodetectors fabricated using these periodic heterostructure nanowires exhibit superior photoelectric performance, namely, high ION/IOFF ratio (104), higher responsivity (49 A/W), and higher detectivity (1.51 × 1013 Jones). Moreover, a spatially resolved visible image sensor based on periodic nanowire superlattices is demonstrated with good imaging capability, suggesting promising application prospects in future photoelectronic imaging systems. All these results based on the periodic CsPbCl3/CsPbI3 nanowire superlattices provides an attractive material platform for integrated perovskite devices and circuits.

Biocompatible Perovskite Nanocrystals with Enhanced Stability for White Light-Emitting Diodes.

Recently emerged lead halide perovskite CsPbX3 (X = Cl, Br, and I) nanocrystals (PNCs) have attracted tremendous attention due to their excellent optical properties. However, the poor water stability, unsatisfactory luminescence efficiency, disappointing lead leakage, and toxicity have restricted their practical applications in photoelectronics and biomedical fields. Herein, a controllable encapsulated strategy is investigated to realize CsPbX3 PNCs/PVP @PMMA composites with superior luminescence properties and excellent biocompatibility. Additionally, the synthesized CsPbBr3 and CsPbBr0.6I2.4 PNCs/PVP@PMMA structures exhibit green and red emissions with a maximal photoluminescence quantum yield (PLQY) of about 70.24% and 98.26%, respectively. These CsPbX3 PNCs/PVP@PMMA structures show high emission efficiency, excellent stability after water storage for 18 months, and low cytotoxicity at the PNC concentration at 500 µg mL-1. Moreover, white light-emitting diode (WLED) devices based on mixtures of CsPbBr3 and CsPbBr0.6I2.4 PNCs/PVP@PMMA perovskite structures are investigated, which exhibit excellent warm-white light emissions at room temperature. A flexible manipulation method is used to fabricate the white light emitters based on these perovskite composites, providing a fantastic platform for fabricating solid-state white light sources and full-color displays.

TiO2 Electron Transport Layer with p-n Homojunctions for Efficient and Stable Perovskite Solar Cells.

Low-temperature processed electron transport layer (ETL) of TiO2 that is widely used in planar perovskite solar cells (PSCs) has inherent low carrier mobility, resulting in insufficient photogenerated electron transport and thus recombination loss at buried interface. Herein, we demonstrate an effective strategy of laser embedding of p-n homojunctions in the TiO2 ETL to accelerate electron transport in PSCs, through localized build-in electric fields that enables boosted electron mobility by two orders of magnitude. Such embedding is found significantly helpful for not only the enhanced crystallization quality of TiO2 ETL, but the fabrication of perovskite films with larger-grain and the less-trap-states. The embedded p-n homojunction enables also the modulation of interfacial energy level between perovskite layers and ETLs, favoring for the reduced voltage deficit of PSCs. Benefiting from these merits, the formamidinium lead iodide (FAPbI3) PSCs employing such ETLs deliver a champion efficiency of 25.50%, along with much-improved device stability under harsh conditions, i.e., maintain over 95% of their initial efficiency after operation at maximum power point under continuous heat and illumination for 500 h, as well as mixed-cation PSCs with a champion efficiency of 22.02% and over 3000 h of ambient storage under humidity stability of 40%. Present study offers new possibilities of regulating charge transport layers via p-n homojunction embedding for high performance optoelectronics.

A BEST classification system of large to giant congenital melanocytic nevi based on expert consensus and distribution characteristics.

BACKGROUND: Large to giant congenital melanocytic nevi (LGCMN) significantly decrease patients' quality of life, but the inaccuracy of current classification system makes their clinical management challenging. OBJECTIVES: To improve and extend the existing LGCMN 6B/7B classification systems by developing a novel LGCMN classification system based on a new phenotypic approach to clinical tool development. METHODS: Three hundred and sixty-one LGCMN cases were categorized into four subtypes based on anatomic site: bonce (25.48%), extremity (17.73%), shawl (19.67%) and trunks (37.12%) LGCMN. A 'BEST' classification system of LGCMN was established and validated by a support vector machine classifier combined with the 7B system. RESULTS: The most common LGCMN distributions were on bonce and trunks (bathing trunk), whereas breast/belly and body LGCMN were exceptionally rare. Sexual dimorphism characterized distribution, with females showing a wider range of lesions in the genital area. Nearly half of the patients with bathing trunk LGCMN exhibited a butterfly-like distribution. Approximately half of the LGCMN with chest involvement did not have nipple-areola complex involvement. Abdomen, back and buttock involvement was associated with the presence of satellite nevi (r = 0.558), and back and buttock involvement was associated with the presence of nodules (r = 0.364). CONCLUSIONS: The effective quantification of a standardized anatomical site provides data support for the accuracy of the 6B/7B classification systems. The simplified BEST classification system can help establish a LGCMN clinical database for exploration of LGCMN aetiology, disease management and prognosis prediction.

Modular Cascade of Flow Reactors: Continuous Flow Synthesis of Water-Insoluble Diazo Dyes in Aqueous System.

Continuous flow synthesis is pivotal in dye production to address batch-to-batch variations. However, synthesizing water-insoluble dyes in an aqueous system poses a challenge that can lead to clogging. This study successfully achieved the safe and efficient synthesis of azo dyes by selecting and optimizing flow reactor modules for different reaction types in the two-step reaction and implementing cascade cooperation. Integrating continuous flow microreactor with continuous stirred tank reactor (CSTR) enabled the continuous flow synthesis of Sudan Yellow 3G without introducing water-soluble functional groups or using organic solvents to enhance solubility. Optimizing conditions (acidity/alkalinity, temperature, residence time) within the initial modular continuous flow reactor resulted in a remarkable 99.5% isolated yield, 98.6 % purity, and a production rate of 2.90 g h-1. Scaling-up based on different reactor module characteristics further increased the production rate to 74.4 g h-1 while maintaining high yield and purity. The construction of this small 3D-printing modular cascaded reactor and process scaling-up provide technical support for continuous flow synthesis of water-insoluble dyes, particularly high-market-share azo dyes. Moreover, this versatile methodology proves applicable to continuous flow processes involving various homogeneous and heterogeneous reaction cascades.

Cu(II)-Loaded Polydopamine-Coated Urchin-like Titanate Microspheres as a High-Performance IMAC Adsorbent for Hemoglobin Separation.

Immobilized metal ion affinity chromatography (IMAC) adsorbents generally have excellent affinity for histidine-rich proteins. However, the leaching of metal ions from the adsorbent usually affects its adsorption performance, which greatly affects the reusable performance of the adsorbent, resulting in many limitations in practical applications. Herein, a novel IMAC adsorbent, i.e., Cu(II)-loaded polydopamine-coated urchin-like titanate microspheres (Cu-PDA-UTMS), was prepared via metal coordination to make Cu ions uniformly decorate polydopamine-coated titanate microspheres. The as-synthesized microspheres exhibit an urchin-like structure, providing more binding sites for hemoglobin. Cu-PDA-UTMS exhibit favorable selectivity for hemoglobin adsorption and have a desirable adsorption capacity towards hemoglobin up to 2704.6 mg g-1. Using 0.1% CTAB as eluent, the adsorbed hemoglobin was easily eluted with a recovery rate of 86.8%. In addition, Cu-PDA-UTMS shows good reusability up to six cycles. In the end, the adsorption properties by Cu-PDA-UTMS towards hemoglobin from human blood samples were analyzed by SDS-PAGE. The results showed that Cu-PDA-UTMS are a high-performance IMAC adsorbent for hemoglobin separation, which provides a new method for the effective separation and purification of hemoglobin from complex biological samples.

Exploring the relationship between Treg-mediated risk in COPD and lung cancer through Mendelian randomization analysis and scRNA-seq data integration.

BACKGROUND: Evidence from observational studies suggests an association between chronic obstructive pulmonary disease (COPD) and lung cancer. The potential interactions between the immune system and the lungs may play a causative role in COPD and lung cancer and offer therapeutic prospects. However, the causal association and the immune-mediated mechanisms between COPD and lung cancer remain to be determined. METHODS: We employed a two-sample Mendelian randomization (MR) approach to investigate the causal association between COPD and lung cancer. Additionally, we examined whether immune cell signals were causally related to lung cancer, as well as whether COPD was causally associated with immune cell signals. Furthermore, through two-step Mendelian randomization, we investigated the mediating effects of immune cell signals in the causal association between COPD and lung cancer. Leveraging publicly available genetic data, our analysis included 468,475 individuals of European ancestry with COPD, 492,803 individuals of European ancestry with lung cancer, and 731 immune cell signatures of European ancestry. Additionally, we conducted single-cell transcriptome sequencing analysis on COPD, lung cancer, and control samples to validate our findings. FINDINGS: We found a causal association between COPD and lung cancer (odds ratio [OR] = 1.63, 95% confidence interval [CI] = 1.31-2.02, P-value < 0.001). We also observed a causal association between COPD and regulatory T cells (odds ratio [OR] = 1.19, 95% confidence interval [CI] = 1.01-1.40, P-value < 0.05), as well as a causal association between regulatory T cells and lung cancer (odds ratio [OR] = 1.02, 95% confidence interval [CI] = 1.002-1.045, P-value < 0.05). Furthermore, our two-step Mendelian randomization analysis demonstrated that COPD is associated with lung cancer through the mediation of regulatory T cells. These findings were further validated through single-cell sequencing analysis, confirming the mediating role of regulatory T cells in the association between COPD and lung cancer. INTERPRETATION: As far as we are aware, we are the first to combine single-celled immune cell data with two-sample Mendelian randomization. Our analysis indicates a causal association between COPD and lung cancer, with regulatory T cells playing an intermediary role.

Effects of male hepatitis B virus infection and serostatus on sperm quality, pregnancy outcomes, and neonatal outcomes following intrauterine insemination.

OBJECTIVE: To evaluate the impact of male hepatitis B virus (HBV) infection and serostatus on sperm quality, pregnancy outcomes, and neonatal outcomes following intrauterine insemination for infertility. DESIGN AND METHODS: We retrospectively analyzed data from 962 infertile couples undergoing intrauterine insemination treatment at a single center. The case group comprised 212 infertile couples with male HBV infection, and the control group comprised 750 noninfected infertile couples. The couples were further divided into subgroups according to their hepatitis B e antigen (HBeAg)/anti-HBe status: hepatitis B surface antigen (HBsAg)+HBeAg- (group A), HBsAg+HBeAg+ (group B), and HBsAg-HBeAg- (control group). The main outcome parameters, including the seminal parameters, clinical pregnancy rate, miscarriage rate, live birth rate, preterm delivery rate, multiple pregnancy rate, delivery type, birth weight, and sex ratio, were compared. RESULTS: A lower sperm acrosin activity, higher cesarean rate, and newborn sex ratio were observed in the HBV-infected group and group A in comparison with the control group (P < 0.05). However, the standard sperm parameters, clinical pregnancy rate, miscarriage rate, live birth rate, preterm delivery, and birth weight showed no statistically significant differences among the groups. CONCLUSION: Male HBV infection does not adversely impact standard sperm parameters or pregnancy outcomes but can influence sperm acrosin activity and some neonatal outcomes. Moreover, the effect may vary among different HBV serostatuses.

MoViT: Memorizing Vision Transformers for Medical Image Analysis.

The synergy of long-range dependencies from transformers and local representations of image content from convolutional neural networks (CNNs) has led to advanced architectures and increased performance for various medical image analysis tasks due to their complementary benefits. However, compared with CNNs, transformers require considerably more training data, due to a larger number of parameters and an absence of inductive bias. The need for increasingly large datasets continues to be problematic, particularly in the context of medical imaging, where both annotation efforts and data protection result in limited data availability. In this work, inspired by the human decision-making process of correlating new "evidence" with previously memorized "experience", we propose a Memorizing Vision Transformer (MoViT) to alleviate the need for large-scale datasets to successfully train and deploy transformer-based architectures. MoViT leverages an external memory structure to cache history attention snapshots during the training stage. To prevent overfitting, we incorporate an innovative memory update scheme, attention temporal moving average, to update the stored external memories with the historical moving average. For inference speedup, we design a prototypical attention learning method to distill the external memory into smaller representative subsets. We evaluate our method on a public histology image dataset and an in-house MRI dataset, demonstrating that MoViT applied to varied medical image analysis tasks, can outperform vanilla transformer models across varied data regimes, especially in cases where only a small amount of annotated data is available. More importantly, MoViT can reach a competitive performance of ViT with only 3.0% of the training data. In conclusion, MoViT provides a simple plug-in for transformer architectures which may contribute to reducing the training data needed to achieve acceptable models for a broad range of medical image analysis tasks.