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Background: Hepatitis E virus (HEV) infection poses a significant health risk across diverse demographic groups, particularly among pregnant women, immunocompromised individuals, patients with chronic liver disease, and the elderly. The global epidemiology of HEV reveals distinct patterns of prevalence, transmission, and disease severity among these populations, necessitating targeted vaccination strategies. The licensing of the Hecolin (HEV 239) vaccine offers promise, but gaps in clinical trial data and varying immune responses in high-risk groups challenge its widespread applicability. Scope: This review synthesizes data on HEV’s epidemiology, discusses the susceptibility of vulnerable populations, evaluates the efficacy and safety of HEV 239, and highlights the urgent need for clinical research tailored to these groups. Key findings underscore the complexity of vaccine response influenced by immunological, physiological, and environmental factors. Additionally, potential advancements in vaccine technology, including the development of broad-spectrum vaccines and innovative delivery systems, are discussed as future directions. Strategies: Addressing regulatory, economic, and logistical barriers remains crucial for effective HEV vaccination programs. A multidisciplinary approach integrating public health policy, rigorous clinical evaluations, and collaborative frameworks is essential to ensure equitable access to HEV vaccination, ultimately improving health outcomes on a global scale.

The understanding of how the host immune response differs in T-cell phenotype and memory formation during SARS-CoV-2 infection in liver transplant recipients (LTRs) remains limited. LTRs who recovered from COVID-19 infection without prior vaccination represent a unique population for studying immune responses to SARS-CoV-2. Six LTRs with positive neutralizing antibodies (nAb+) and six LTRs with negative nAb (nAb-) were included at 6 months following COVID-19 infection. It was found that nAb+ LTRs had higher anti-RBD IgG titers and greater neutralizing percent inhibition compared to nAb- LTRs. Fifteen T-cell subsets were identified in COVID-19 convalescent LTRs, and it was shown that only terminal effector CD8+ - 3 decreased in the nAb+ group, while elevated IL-10 expression levels were found in the nAb- group. After stimulation with the SARS-CoV-2 XBB spike peptide pool in vitro , it was observed that the nAb+ group exhibited an increase in effector memory CD4+ cells with lower PD-1 expression, a reduction in effector memory CD4+ - 2 cells, and terminal effector CD8+ - 3 cells, while the nAb- group showed high expression of CTLA-4 and IL-10 in terminal effector CD8+ - 3 cells. Four SARS-CoV-2-specific T-cell subsets were identified, with high expression of TNF-α and IFN-γ in terminal effector CD8+ - 1 and terminal effector CD8+ - 2 cells in both groups. Perforin was mainly detected in terminal effector CD8+ - 2 cells in nAb+ LTRs. In addition to these proportional differences, stem cell memory CD4+ cells with higher IL-17A expression and stem cell memory CD8+ cells with higher CTLA-4 expression were also found in nAb- LTRs. These findings suggest that LTRs who developed nAb+ following SARS-CoV-2 infection exhibit stronger T-cell responses, with more robust immune activation and memory recall, compared to nAb- LTRs. This study underscores the importance of understanding T-cell responses during SARS-CoV-2 recovery for guiding vaccination strategies and managing immunity in LTRs.

Resistance to radiotherapy remains a major unmet clinical obstacle in the treatment of locally advanced rectal cancer. Cancer stem cells (CSCs) are considered to mediate tumor development and radioresistance. However, the role of CSCs in regulating resistance to radiotherapy in colorectal cancer (CRC) remains largely unknown. We established two radioresistant CRC cell lines, HCT116-R and RKO-R, using fractionated irradiation. Analysis using miRNA sequencing and quantitative real-time PCR confirmed lower levels of miR-7-5p in both of the radioresistant cells compared to their parental cells. Subsequently, we validated that miR-7-5p expression was decreased in cancerous tissues from radiotherapy-resistant rectal cancer patients. The Cancer Genome Atlas (TCGA) database analyses revealed that low miR-7-5p expression was significantly correlated with poor prognosis in CRC patients. Overexpression of miR-7-5p led to a rescue of radioresistance and an increase in radiation-induced apoptosis, and attenuated the stem cell-like properties in HCT116-R and RKO-R cells. Conversely, knocking down miR-7-5p in parental HCT116 and RKO cells suppressed the sensitivity to radiation treatment and enhance cancer cell stemness. Stemness-associated transcription factor KLF4 was demonstrated as a target of miR-7-5p. Rescue experiments revealed that miR-7-5p/KLF4 axis could induce radiosensitivity by regulating CSCs in colorectal cancer cells. Furthermore, we used CRC tumor tissues which exhibited resistance to neoadjuvant radiotherapy to establish a patient-derived xenograft (PDX) mouse model. Tail vein injection of magnetic nanoparticles carrying miR-7-5p mimics into the PDX mice significantly inhibited tumor growth with or without irradiation treatment in vivo. Our current studies not only demonstrate an anti-cancer function of miR-7-5p in regulating CSC properties and radiosensitivity in colorectal cancer, but also provide a novel potential strategy for delaying or reverse radiation resistance in preoperative radiotherapy of CRC patients.

Background Trueperella pyogenes is a commensal and a significant opportunistic pathogen in animals. A variety of identified or putative virulence factors are considered to significantly contribute to the occurrence of T. pyogenes infection in different species. However, these virulence factors are not fully understood. Results In the current study, the genes encoding putative fimbrial proteins, i.e. Fim A, Fim C, and Fim E, were cloned. Recombinant Fim A (rFim A), Fim C (rFim C), and Fim E (rFim E) were prepared and used to generate rabbit anti-rFim A, anti-rFim C, and anti-rFim E serum, respectively. Using these sera, we found that only Fim E was constitutively expressed in T. pyogenes . The expression level of Fim E in T. pyogenes peaked within 6–10 h of culture period in pH 7.5. Fim E protein expression was unaffected by anaerobic condition, but was inhibited by the microaerophilic condition. Tube agglutination tests indicated that Fim E was exhibited on the surface of T. pyogenes cells because anti-rFim E serum caused strong agglutination. Additionally, the blots for Fim A detection showed nonspecific reactions. Furthermore, the tube agglutination tests showed that anti-Fim A serum failed to cause agglutination of T. pyogenes cells, which indicated that Fim A was not, or poorly, expressed in cultured T. pyogenes . Anti-rFim C serum caused strong agglutination. However, the blots for Fim C detection showed a strong nonspecific reaction. Thus, the expression of Fim C was difficult to be determined using the current method. Conclusions Fim E was expressed in cultured T. pyogenes. However, Fim A was either not or poorly expressed in cultured T. pyogenes . Moreover, Fim C expression was not determined using the current strategy.

Ultraflexible microelectrode arrays (MEAs) that can stably record from a large number of neurons after their chronic implantation offer opportunities for understanding neural circuit mechanisms and developing next-generation brain–computer interfaces. The implementation of ultraflexible MEAs requires their reliable implantation into deep brain tissues in a minimally invasive manner, as well as their precise integration with optogenetic tools to enable the simultaneous recording of neural activity and neuromodulation. Here, we describe the process for the preparation of elastocapillary self-assembled ultraflexible MEAs, their use in combination with adeno-associated virus vectors carrying opsin genes and promoters to form an optrode probe and their in vivo experimental use in the brains of rodents, enabling electrophysiological recordings and optical modulation of neuronal activity over long periods of time (on the order of weeks to months). The procedures, including device fabrication, probe assembly and implantation, can be completed within 3 weeks. The protocol is intended to facilitate the applications of ultraflexible MEAs for long-term neuronal activity recording and combined electrophysiology and optogenetics. The protocol requires users with expertise in clean room facilities for the fabrication of ultraflexible MEAs. The authors describe the fabrication, assembly and long-term implantation of ultraflexible neural probes for the simultaneous recording of neural activity and neuromodulation in rodents.

Drought drastically restricts wheat production, so to dissect allelic variations of drought tolerant genes without imposing trade-offs between tolerance and yield is essential to cope with the circumstance. Here, we identify a drought tolerant WD40 protein encoding gene TaWD40-4B.1 of wheat via the genome-wide association study. The full-length allele TaWD40-4B.1 C but not the truncated allele TaWD40-4B.1 T possessing a nonsense nucleotide variation enhances drought tolerance and grain yield of wheat under drought. TaWD40-4B.1 C interacts with canonical catalases, promotes their oligomerization and activities, and reduces H 2 O 2 levels under drought. The knock-down of catalase genes erases the role of TaWD40-4B.1 C in drought tolerance. TaWD40-4B.1 C proportion in wheat accessions is negatively correlative with the annual rainfall, suggesting this allele may be selected during wheat breeding. The introgression of TaWD40-4B.1 C enhances drought tolerance of the cultivar harboring TaWD40-4B.1 T . Therefore, TaWD40-4B.1 C could be useful for molecular breeding of drought tolerant wheat. Drought stress limits wheat production around the world. Here, the authors report allelic variation of a WD40 encoding gene TaWD40-4B.1 contributes to wheat drought tolerance by interacting with canonical catalases as a chaperone to promote their activities to avoid ROS over accumulation.

Soft exoskeletons (exosuits) are expected to provide a comfortable wearing experience and compliant assistance compared with traditional rigid exoskeleton robots. In this paper, an exosuit with twisted string actuators (TSAs) is developed to provide high-strength and variable-stiffness actuation for hemiplegic patients. By formulating the analytic model of the TSA and decoding the human impedance characteristic, the human-exosuit coupled dynamic model is constructed. An adaptive impedance controller is designed to transfer the skills of the patient’s healthy limb (HL) to the bilateral impaired limb (IL) with a mirror training strategy, including the movement trajectory and stiffness profiles. A reinforcement learning (RL) algorithm is proposed to optimize the robotic assistance by adapting the impedance model parameters to the subject’s performance. Experiments are conducted to demonstrate the effectiveness and superiority of the proposed method.

Computer-aided automatic segmentation of retinal blood vessels plays an important role in the diagnosis of diseases such as diabetes, glaucoma, and macular degeneration. In this paper, we propose a multi-scale feature fusion retinal vessel segmentation model based on U-Net, named MSFFU-Net. The model introduces the inception structure into the multi-scale feature extraction encoder part, and the max-pooling index is applied during the upsampling process in the feature fusion decoder of an improved network. The skip layer connection is used to transfer each set of feature maps generated on the encoder path to the corresponding feature maps on the decoder path. Moreover, a cost-sensitive loss function based on the Dice coefficient and cross-entropy is designed. Four transformations—rotating, mirroring, shifting and cropping—are used as data augmentation strategies, and the CLAHE algorithm is applied to image preprocessing. The proposed framework is tested and trained on DRIVE and STARE, and sensitivity (Sen), specificity (Spe), accuracy (Acc), and area under curve (AUC) are adopted as the evaluation metrics. Detailed comparisons with U-Net model, at last, it verifies the effectiveness and robustness of the proposed model. The Sen of 0.7762 and 0.7721, Spe of 0.9835 and 0.9885, Acc of 0.9694 and 0.9537 and AUC value of 0.9790 and 0.9680 were achieved on DRIVE and STARE databases, respectively. Results are also compared to other state-of-the-art methods, demonstrating that the performance of the proposed method is superior to that of other methods and showing its competitive results.

Objectives YTHDF1 is known as a m6A reader protein, and many researches of YTHDF1 focused on the regulation of mRNA translation efficiency. However, YTHDF1 is also related to RNA degradation, but how YTHDF1 regulates mRNA degradation is indefinite. Liquid‐liquid phase separation (LLPS) underlies the formation of membraneless compartments in mammal cells, and there are few reports focused on the correlation of RNA degradation with LLPS. In this research, we focused on the mechanism of YTHDF1 degraded mRNA through LLPS. Materials and Methods The CRISPR/Cas9 knock out system was used to establish the YTHDF1 knock out (YTHDF1‐KO) cell lines (HEK293 and HeLa) and METTL14 knock out (METTL14‐KO) cell line (HEK293). 4SU‐TT‐seq was used to check the half‐life changes of mRNAs. Actinomycin D and qPCR were used to test the half‐life changes of individual mRNA. RNA was stained with SYTO RNA‐select dye in wild type (WT) and YTHDF1‐KO HeLa cell lines. Co‐localization of YTHDF1 and AGO2 was identified by immunofluorescence. The interaction domain of YTHDF1 and AGO2 was identified by western blot. Phase separation of YTHDF1 was performed in vitro and in vivo. Fluorescence recovery after photobleaching (FRAP) was performed on droplets as an assessment of their liquidity. Results In this research, we found that deletion of YTHDF1 led to massive RNA patches deposited in cytoplasm. The results of 4SU‐TT‐seq showed that deletion of YTHDF1 would prolong the half‐life of mRNAs. Immunofluorescence data showed that YTHDF1 and AGO2 could co‐localize in P‐body, and Co‐IP results showed that YTHDF1 could interact with AGO2 through YT521‐B homology (YTH) domain. We confirmed that YTHDF1 could undergo phase separation in vitro and in vivo, and compared with AGO2, YTHDF1 was more important in P‐body formation. The FRAP results showed that liquid AGO2 droplets would convert to gel/solid when YTHDF1 was deleted. As AGO2 plays important roles in miRISCs, we also found that miRNA‐mediate mRNA degradation is related to YTHDF1. Conclusions YTHDF1 recruits AGO2 through the YTH domain. YTHDF1 degrades targeting mRNAs by promoting P‐body formation through LLPS. The deletion of YTHDF1 causes the P‐body to change from liquid droplets to gel/solid droplets, and form AGO2/RNA patches, resulting in a degradation delay of mRNAs. These findings reveal a previously unrecognized crosstalk between YTHDF1 and AGO2, raising a new sight of mRNA post‐transcriptional regulation by YTHDF1. Working model: YTHDF1 interacts with AGO2 (AGO2 perhaps along with miRNA) through YTH domain, then undergoes LLPS to aggregate more components of miRISCs, and leading to P‐body formation for mRNA degradation. Deficiency of YTHDF1 disrupts the interaction between YTHDF1 and AGO2, leads to the conversion of AGO2 liquid droplets to gels/solids and substantially increases the mRNA stability.

In this article, an efficient sequential linear programming algorithm (SLP) for uncertainty analysis-based data-driven computational mechanics (UA-DDCM) is presented. By assuming that the uncertain constitutive relationship embedded behind the prescribed data set can be characterized through a convex combination of the local data points, the upper and lower bounds of structural responses pertaining to the given data set, which are more valuable for making decisions in engineering design, can be found by solving a sequential of linear programming problems very efficiently. Numerical examples demonstrate the effectiveness of the proposed approach on sparse data set and its robustness with respect to the existence of noise and outliers in the data set.