Targeted siRNA Therapy for Psoriasis: Translating Preclinical Potential into Clinical Treatments.

Psoriasis is a chronic inflammatory skin disease characterized by the excessive proliferation of keratinocytes and heightened immune activation. Targeting pathogenic genes through small interfering RNA (siRNA) therapy represents a promising strategy for the treatment of psoriasis. This mini-review provides a comprehensive summary of siRNA research targeting the pathogenesis of psoriasis, covering aspects such as keratinocyte function, inflammatory cell roles, preclinical animal studies, and siRNA delivery mechanisms. It details recent advancements in RNA interference that modulate key factors including keratinocyte proliferation (Fibroblast Growth Factor Receptor 2, FGFR2), apoptosis (Interferon Alpha Inducible Protein 6, G1P3), differentiation (Grainyhead Like Transcription Factor 2, GRHL2), and angiogenesis (Vascular Endothelial Growth Factor, VEGF); immune cell infiltration and inflammation (Tumor Necrosis Factor-Alpha, TNF-α; Interleukin-17, IL-17); and signaling pathways (JAK-STAT, Nuclear Factor Kappa B, NF-κB) that govern immunopathology. Despite significant advances in siRNA-targeted treatments for psoriasis, several challenges persist. Continued scientific developments promise the creation of more effective and safer siRNA medications, potentially enhancing the quality of life for psoriasis patients and revolutionizing treatments for other diseases. This article focuses on the most recent research advancements in targeting the pathogenesis of psoriasis with siRNA and explores its future therapeutic prospects.

MultiFuseYOLO: Redefining Wine Grape Variety Recognition through Multisource Information Fusion.

Based on the current research on the wine grape variety recognition task, it has been found that traditional deep learning models relying only on a single feature (e.g., fruit or leaf) for classification can face great challenges, especially when there is a high degree of similarity between varieties. In order to effectively distinguish these similar varieties, this study proposes a multisource information fusion method, which is centered on the SynthDiscrim algorithm, aiming to achieve a more comprehensive and accurate wine grape variety recognition. First, this study optimizes and improves the YOLOV7 model and proposes a novel target detection and recognition model called WineYOLO-RAFusion, which significantly improves the fruit localization precision and recognition compared with YOLOV5, YOLOX, and YOLOV7, which are traditional deep learning models. Secondly, building upon the WineYOLO-RAFusion model, this study incorporated the method of multisource information fusion into the model, ultimately forming the MultiFuseYOLO model. Experiments demonstrated that MultiFuseYOLO significantly outperformed other commonly used models in terms of precision, recall, and F1 score, reaching 0.854, 0.815, and 0.833, respectively. Moreover, the method improved the precision of the hard to distinguish Chardonnay and Sauvignon Blanc varieties, which increased the precision from 0.512 to 0.813 for Chardonnay and from 0.533 to 0.775 for Sauvignon Blanc. In conclusion, the MultiFuseYOLO model offers a reliable and comprehensive solution to the task of wine grape variety identification, especially in terms of distinguishing visually similar varieties and realizing high-precision identifications.

Application of Recombinant Human Superoxide Dismutase in Radical Concurrent Chemoradiotherapy for Cervical Cancer to Prevent and Treat Radiation-induced Acute Rectal Injury: A Multi-center, Randomized, Open-label, Prospective Trial.

PURPOSE: To evaluate the efficacy of recombinant human superoxide dismutase (rhSOD) enemas in radiation-induced acute rectal injury (RARI) in patients with locally advanced cervical cancer. METHODS: In this phase III, randomized, open-label trial (NCT04819685) conducted across 14 medical centers in China from June 2021 to August 2023, all patients received concurrent chemoradiotherapy (CCRT). The experimental group was treated with a rhSOD enema during chemoradiotherapy, and the control group had no enema. The Common Terminology Criteria for Adverse Events (version 5.0) was used to evaluate radiotherapy-induced side effects. Endoscopic appearance was assessed using the Vienna Rectoscopy Score. The primary endpoint in the acute phase was the occurrence rate and duration of grade ≥1 (≥G1) diarrhea during CCRT. Secondary endpoints included the occurrence rate and duration of ≥G2 and ≥G3 diarrhea; ≥G1 and ≥G2 diarrhea lasting at least 3 days; and damage to the rectal mucosa due to radiotherapy measured by endoscopy. RESULTS: Two-hundred-and-eighty-three patients were randomly divided into the experimental (n = 141) or control group (n = 140). The mean number of ≥G1 and ≥G2 diarrhea days were significantly lower in the experimental group than in the control group (3.5 and 0.8 days vs. 14.8 and 4.5 days, respectively; P<0.001). The incidence of ≥G2 diarrhea decreased from 53.6% to 24.1% when rhSOD enemas were used. Use of antidiarrheals was lower in the experimental group (36.2% vs. 55.7%, P<0.001). Three patients felt intolerable or abdominal pain following rhSOD enema. RARI grades in the experimental group tended to be lower than those in the control group (P=0.061). Logistic regression analysis revealed that rhSOD enema was associated with a lower occurrence rate of ≥G1/2 diarrhea for at least 3 days (P<0.001). CONCLUSION: The results of this study suggest that rhSOD enema is safe and significantly reduces the incidence, severity, and duration of RARI, protecting the rectal mucosa.

Targeting programmed cell death in inflammatory bowel disease through natural products: New insights from molecular mechanisms to targeted therapies.

Inflammatory bowel disease (IBD) is an autoimmune disorder primarily characterized by intestinal inflammation and recurrent ulceration, leading to a compromised intestinal barrier and inflammatory infiltration. This disorder's pathogenesis is mainly attributed to extensive damage or death of intestinal epithelial cells, along with abnormal activation or impaired death regulation of immune cells and the release of various inflammatory factors, which contribute to the inflammatory environment in the intestines. Thus, maintaining intestinal homeostasis hinges on balancing the survival and functionality of various cell types. Programmed cell death (PCD) pathways, including apoptosis, pyroptosis, autophagy, ferroptosis, necroptosis, and neutrophil extracellular traps, are integral in the pathogenesis of IBD by mediating the death of intestinal epithelial and immune cells. Natural products derived from plants, fruits, and vegetables have shown potential in regulating PCD, offering preventive and therapeutic avenues for IBD. This article reviews the role of natural products in IBD treatment by focusing on targeting PCD pathways, opening new avenues for clinical IBD management.

Interface engineering of hierarchical flower-like N, P, O-doped NixPy self-supported electrodes for highly efficient water-to-hydrogen fuel/oxygen conversion.

Rational construction of efficient bifunctional catalysts with robust catalytic activity and durability is significant for overall water splitting (conversion between water and hydrogen fuel/oxygen) using non-precious metal systems. In this work, the hierarchically porous N, P, O-doped transition metal phosphate in the Ni foam (NF) electrode (hollow flower-like NPO/NixPy@NF) was prepared through facile hydrothermal method coupled with phosphorization treatment. The hierarchical hollow flower-like NPO/NixPy@NF electrodes exhibited high bifunctional activity and stability for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline solutions. The optimized electrode showed low overpotentials of 76 and 240 mV for HER and OER to reach a current density of 10 mA cm-2, respectively. Notably, the NPO/NixPy@NF electrode only required a low voltage of 1.99 V to reach the current densities of 100 mA cm-2 with long-term stability for overall water splitting using the NPO/NixPy@NF|| NPO/NixPy@NF cell, surpassing that of the Pt/C-RuO2 (2.24 V@ 100 mA cm-2). The good catalytic and battery performance should be attributed to i) the open hierarchical structure that enhanced the mass transfer; ii) a highly conductive substrate that accelerated the electron transfer; iii) the rich heterojunction and strong synergy between Ni2P and Ni5P4 that improved the catalytic kinetic; iv) the proper-thickness amorphous phosphorus oxide nitride (PON) shell that realized the stability. This work demonstrates a promising methodology for designing bifunctional transition metal phosphides with high performance for efficient water splitting.

Utilizing Joukowsky transformation in the design of optical fiber for elliptical-to-circular mode conversion.

This study addresses the challenge of enhancing coupling efficiency between optical fibers and elliptical Gaussian beams emitted by semiconductor lasers, particularly in fiber communication systems. We introduce a method for fiber design utilizing the Joukowsky transformation to facilitate efficient mode transformation from elliptical to circular, thereby augmenting the coupling efficiency with both single-mode and multimode fibers. Theoretical analysis and numerical simulations demonstrate that the fiber with a structurally transitional core maintains high-efficiency mode transformation across various lengths, and its structure has been optimized accordingly. Additionally, our investigation reveals the designed fiber's ability to preserve polarization states, which could have significant implications in precision optical applications. The proposed design offers an approach to improving performance in optical communication systems, especially in wavelength-division multiplexing (WDM) transmission systems and fiber lasers.

Tunable non-polarizing optical bandpass filtering in prism pair coupled planar optical waveguide.

A tunable non-polarizing optical bandpass filter structure, comprising a prism pair coupled planar optical waveguide (POW), is demonstrated, by changing the incident angle of the filter. Experimental measurements show that pass bands for both TM and TE polarized waves are present in the filter simultaneously, and the two passbands overlap on each other. The overlapping of the two passbands can be sustainable for the peak wavelength from 623 to 852 nm as the incident angle of the light tuned within 2°. This POW based optical bandpass filter can be potentially applicable in various fields of optical and laser spectroscopies.

[Ecosystem Service Trade-off Synergy Strength and Spatial Pattern Optimization Based on Bayesian Network： A Case Study of the Fenhe River Basin].

Understanding the strength of trade-off and synergistic relationships among ecosystem services (ESs) is crucial for ecological management and restoration in the Fenhe River Basin. However, there is still a lack of sufficient research on the driving variables and spatial pattern optimization of the strength of ESs relationships in this area. Based on the quantitative assessment of six ESs in the Fenhe River Basin in 2000 and 2020, the ecosystem services trade-off synergy index (TSI) was introduced to quantitatively measure the strength of trade-off and synergistic relationships between each pair of ESs. A Bayesian network was constructed to identify the driving variables of trade-off and synergistic relationships, and sensitivity analysis was conducted to determine the degree of influence of key variables on the strength of these relationships. The optimization area of the strength of ESs trade-off and synergistic relationships was characterized in spatial patterns. The results showed that:① There were significant spatiotemporal differences in the six ESs in the Fenhe River Basin in 2000 and 2020. In terms of time scale, water yield, net primary productivity, crop productivity, soil conservation, and carbon storage all showed a trend of fluctuating increase. In terms of spatial scale, the spatial distribution changes in the six ESs were relatively small over the 20 years. ② The TSI of carbon storage was high in the surrounding area and low in the middle, showing a four-high and four-low pattern. The areas with the highest TSI between grain supply and other services were distributed from north to south. ③ Sensitivity analysis found that the strength of water yield, soil conservation, and habitat quality were significantly affected by precipitation, plant root depth restriction, and rainfall erosion. According to the conditional probability of different states of key variables, Wenshui County, Qingxu County, and Qi County in the central part of the Fenhe River Basin were identified as high-value areas for trade-off and synergistic relationships, which could be used as key areas for ecological restoration. These findings have important theoretical and practical significance for understanding the complex relationship between multiple ESs trade-off and synergistic relationships and their driving variables and for proposing sustainable ecological environment management policies.

Harnessing instability for work hardening in multi-principal element alloys.

The strength-ductility trade-off has long been a Gordian knot in conventional metallic structural materials and it is no exception in multi-principal element alloys. In particular, at ultrahigh yield strengths, plastic instability, that is, necking, happens prematurely, because of which ductility almost entirely disappears. This is due to the growing difficulty in the production and accumulation of dislocations from the very beginning of tensile deformation that renders the conventional dislocation hardening insufficient. Here we propose that premature necking can be harnessed for work hardening in a VCoNi multi-principal element alloy. Lüders banding as an initial tensile response induces the ongoing localized necking at the band front to produce both triaxial stress and strain gradient, which enables the rapid multiplication of dislocations. This leads to forest dislocation hardening, plus extra work hardening due to the interaction of dislocations with the local-chemical-order regions. The dual work hardening combines to restrain and stabilize the premature necking in reverse as well as to facilitate uniform deformation. Consequently, a superior strength-and-ductility synergy is achieved with a ductility of ~20% and yield strength of 2 GPa during room-temperature and cryogenic deformation. These findings offer an instability-control paradigm for synergistic work hardening to conquer the strength-ductility paradox at ultrahigh yield strengths.

Active fractions from Jingfang Baidu Powder alleviate Klebsiella-induced Pneumonia by inhibiting TLR4/Myd88-ERK signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Jingfang Baidu Powder (JFBDP) is a classic traditional Chinese medicine prescription. Although Jingfang Baidu powder obtained a general consensus on clinical efficacy in treating pneumonia, there were many Chinese herbal drugs in formula, complex components, and large oral dosage, which brings certain obstacles to clinical application. AIM OF THE STUDY: Therefore, screening of the active fraction that exerts anti-pneumonia helps improve the pharmaceutical preparation, improve the treatment compliance of patients, and further contribute to the clinical application, and the screening of the new active ingredients with anti-pneumonia. The histopathological observation, real-time quantitative PCR, western blotting, and immunofluorescence were applied to evaluate the anti-pneumonia efficacy of active fractions from JFBDP. RESULTS: Three fractions from JFBDP inhibit the gene expression of IL-1ß, IL-10, CCL3, CCL5, and CCL22 in lung tissue infected by Klebsiella at various degrees, and presented a good dose-response relationship. JF50 showed stronger anti-inflammatory effects among three fractions including JF30, JF50, and JF75. Besides, JF50 significantly reduced the protein expression of TLR4 and Myd88 in lung tissue infected with Klebsiella, and it also significantly inhibited p-ERK and p-NF-κB p65. JF50 significantly inhibits the protein expression of Caspase 3, Caspase 8, and Caspase 9 in lung tissue infected with Klebsiella at the dose of 25 mg/kg and 50 mg/kg. CONCLUSION: JF50 improves lung pathological damage in Klebsiella pneumonia mice by inhibiting the TLR4/Myd88/NF-κB-ERK signaling pathway, and inhibiting apoptosis of lung tissue cells. These findings provide a reference for further exploring the active substance basis of Jingfang Baidu Powder in treating bacterial pneumonia.

A deep learning-based 3D Prompt-nnUnet model for automatic segmentation in brachytherapy of postoperative endometrial carcinoma.

PURPOSE: To create and evaluate a three-dimensional (3D) Prompt-nnUnet module that utilizes the prompts-based model combined with 3D nnUnet for producing the rapid and consistent autosegmentation of high-risk clinical target volume (HR CTV) and organ at risk (OAR) in high-dose-rate brachytherapy (HDR BT) for patients with postoperative endometrial carcinoma (EC). METHODS AND MATERIALS: On two experimental batches, a total of 321 computed tomography (CT) scans were obtained for HR CTV segmentation from 321 patients with EC, and 125 CT scans for OARs segmentation from 125 patients. The numbers of training/validation/test were 257/32/32 and 87/13/25 for HR CTV and OARs respectively. A novel comparison of the deep learning neural network 3D Prompt-nnUnet and 3D nnUnet was applied for HR CTV and OARs segmentation. Three-fold cross validation and several quantitative metrics were employed, including Dice similarity coefficient (DSC), Hausdorff distance (HD), 95th percentile of Hausdorff distance (HD95%), and intersection over union (IoU). RESULTS: The Prompt-nnUnet included two forms of parameters Predict-Prompt (PP) and Label-Prompt (LP), with the LP performing most similarly to the experienced radiation oncologist and outperforming the less experienced ones. During the testing phase, the mean DSC values for the LP were 0.96 ± 0.02, 0.91 ± 0.02, and 0.83 ± 0.07 for HR CTV, rectum and urethra, respectively. The mean HD values (mm) were 2.73 ± 0.95, 8.18 ± 4.84, and 2.11 ± 0.50, respectively. The mean HD95% values (mm) were 1.66 ± 1.11, 3.07 ± 0.94, and 1.35 ± 0.55, respectively. The mean IoUs were 0.92 ± 0.04, 0.84 ± 0.03, and 0.71 ± 0.09, respectively. A delineation time < 2.35 s per structure in the new model was observed, which was available to save clinician time. CONCLUSION: The Prompt-nnUnet architecture, particularly the LP, was highly consistent with ground truth (GT) in HR CTV or OAR autosegmentation, reducing interobserver variability and shortening treatment time.

Mapping structural covariance networks of emotional withdrawal symptoms in males with methamphetamine use disorder during abstinence.

Individuals with methamphetamine use disorder (MUD) often experience anxiety and depressive symptoms during abstinence, which can worsen the likelihood of relapse. Thus, it is essential to understand the neuro-mechanism behind methamphetamine use and its associated emotional withdrawal symptoms in order to develop effective clinical strategies. This study aimed to evaluate associations between emotional withdrawal symptoms and structural covariance networks (SCNs) based on cortical thickness (CTh) across the brain. The CTh measures were obtained from Tl-weighted MRI data from a sample of 48 males with MUD during abstinence and 48 male healthy controls. The severity of anxiety and depressive symptoms was assessed by the Hamilton Anxiety Scale (HAMA) and depression (HAMD) scales. Two important nodes belonging to the brain reward system, the right rostral anterior cingulate cortex (rACC) and medial prefrontal cortex (medPFC), were selected as seeds to conduct SCNs and modulation analysis by emotional symptoms. MUDs showed higher structural covariance between the right rACC and regions in the dorsal attention, right frontoparietal, auditory, visual and limbic networks. They also displayed higher structural covariance between the right medPFC and regions in the limbic network. Moreover, the modulation analysis showed that higher scores on HAMA were associated with increased covariance between the right rACC and the left parahippocampal and isthmus cingulate cortex in the default mode network. These outcomes shed light on the complex neurobiological mechanisms underlying methamphetamine use and its associated emotional withdrawal symptoms and may provide new insights into the development of effective treatments for MUD.

Understanding the Transepithelial Transport and Transbilayer Diffusion of the Antihypertensive Peptide Asn-Cys-Trp: Insights from Caco-2 Cell Monolayers and the DPPC Model Membrane.

Understanding the transport mechanism of the peptide Asn-Cys-Trp (NCW) is crucial to improving its intestinal absorption and bioavailability. This study investigated the absorption of NCW through Caco-2 cell monolayers and its interaction with the DPPC bilayers. Results revealed that after a 3 h incubation, the Papp (AP-BL) and Papp (BL-AP) values of NCW at a concentration of 5 mmol/L were (22.24 ± 4.52) × 10-7 and (6.63 ± 2.31) × 10-7 cm/s, respectively, with the transport rates of 1.59 ± 0.32 and 0.62 ± 0.20%, indicating its moderate absorption. NCW was found to be transported via PepT1 and paracellular transport pathways, as evidenced by the significant impact of Gly-Pro and cytochalasin D on the Papp values. Moreover, NCW upregulated ZO-1 mRNA expression. Further investigation of the ZO-1-mediated interaction between NCW and tight junction proteins will contribute to a better understanding of the paracellular transport mechanism of NCW. The interaction between NCW and the DPPC bilayers was predominantly driven by entropy. NCW permeated the bilayers through electrostatic, hydrogen bonding, and hydrophobic interactions, resulting in increased fluidity, flexibility, and disorder as well as phase transition and phase separation of the bilayers.

Enhancing Aboveground Biomass Prediction through Integration of the SCDR Paradigm into the U-Like Hierarchical Residual Fusion Model.

Deep learning methodologies employed for biomass prediction often neglect the intricate relationships between labels and samples, resulting in suboptimal predictive performance. This paper introduces an advanced supervised contrastive learning technique, termed Improved Supervised Contrastive Deep Regression (SCDR), which is adept at effectively capturing the nuanced relationships between samples and labels in the feature space, thereby mitigating this limitation. Simultaneously, we propose the U-like Hierarchical Residual Fusion Network (BioUMixer), a bespoke biomass prediction network tailored for image data. BioUMixer enhances feature extraction from biomass image data, facilitating information exchange and fusion while considering both global and local features within the images. The efficacy of the proposed method is validated on the Pepper_Biomass dataset, which encompasses over 600 original images paired with corresponding biomass labels. The results demonstrate a noteworthy enhancement in deep regression tasks, as evidenced by performance metrics on the Pepper_Biomass dataset, including RMSE = 252.18, MAE = 201.98, and MAPE = 0.107. Additionally, assessment on the publicly accessible GrassClover dataset yields metrics of RMSE = 47.92, MAE = 31.74, and MAPE = 0.192. This study not only introduces a novel approach but also provides compelling empirical evidence supporting the digitization and precision improvement of agricultural technology. The research outcomes align closely with the identified problem and research statement, underscoring the significance of the proposed methodologies in advancing the field of biomass prediction through state-of-the-art deep learning techniques.

IL-33 regulates adipogenesis via Wnt/ß-catenin/PPAR-γ signaling pathway in preadipocytes.

Interleukin-33 (IL-33), an emerging cytokine within the IL-1 family, assumes a pivotal function in the control of obesity. However, the specific mechanism of its regulation of obesity formation remains unclear. In this study, we found that the expression level of IL-33 increased in visceral adipose tissue in mice fed with a high-fat diet (HFD) compared with that in mice fed with a normal diet (ND). In vitro, we also found the expression level of IL-33 was upregulated during the adipogenesis of 3T3-L1 cells. Functional test results showed that knockdown of IL-33 in 3T3-L1 cells differentiation could promote the accumulation of lipid droplets, the content of triglyceride and the expression of adipogenic-related genes (i.e. PPAR-γ, C/EBPα, FABP4, LPL, Adipoq and CD36). In contrast, overexpression of IL-33 inhibits adipogenic differentiation. Meanwhile, the above tests were repeated after over-differentiation of 3T3-L1 cells induced by oleic acid, and the results showed that IL-33 played a more significant role in the regulation of adipogenesis. To explore the mechanism, transcriptome sequencing was performed and results showed that IL-33 regulated the PPAR signaling pathway in 3T3-L1 cells. Further, Western blot and confocal microscopy showed that the inhibition of IL-33 could promote PPAR-γ expression by inhibiting the Wnt/ß-catenin signal in 3T3-L1 cells. This study demonstrated that IL-33 was an important regulator of preadipocyte differentiation and inhibited adipogenesis by regulating the Wnt/ß-catenin/PPAR-γ signaling pathway, which provided a new insight for further research on IL-33 as a new intervention target for metabolic disorders.

Comparative analysis of single-cell transcriptome reveals heterogeneity and commonality in the immune microenvironment of colorectal cancer and inflammatory bowel disease.

Background: During aging, chronic inflammation can promote tumor development and metastasis. Patients with chronic inflammatory bowel diseases (IBD) are at an increased risk of developing colorectal cancer (CRC). However, the molecular mechanism underlying is still unclear. Methods: We conducted a large-scale single-cell sequencing analysis comprising 432,314 single cells from 92 CRC and 24 IBD patients. The analysis focused on the heterogeneity and commonality of CRC and IBD with respect to immune cell landscape, cellular communication, aging and inflammatory response, and Meta programs. Results: The CRC and IBD had significantly different propensities in terms of cell proportions, differential genes and their functions, and cellular communication. The progression of CRC was mainly associated with epithelial cells, fibroblasts, and monocyte-macrophages, which displayed pronounced metabolic functions. In particular, monocyte-macrophages were enriched for the aging and inflammation-associated NF-κB pathway. And IBD was enriched in immune-related functions with B cells and T cells. Cellular communication analysis in CRC samples displayed an increase in MIF signaling from epithelial cells to T cells, and an increase in the efferent signal of senescence-associated SPP1 signaling from monocyte-macrophages. Notably, we also found some commonalities between CRC and IBD. The efferent and afferent signals showed that the pro-inflammatory cytokine played an important role. And the activity of aging and inflammatory response with AUCell analysis also showed a high degree of commonality. Furthermore, using the Meta programs (MPs) with the NMF algorithm, we found that the CRC non-malignant cells shared a substantial proportion of the MP genes with CRC malignant cells (68% overlap) and IBD epithelial cells (52% overlap), respectively. And it was extensively involved in functions of cell cycle and immune response, revealing its dual properties of inflammation and cancer. In addition, CRC malignant and non-malignant cells were enriched for the senescence-related cell cycle G2M phase transition and the p53 signaling pathway. Conclusion: Our study highlights the characteristics of aging, inflammation and tumor in CRC and IBD at the single-cell level, and the dual property of inflammation-cancer in CRC non-malignant cells may provide a more up-to-date understanding of disease transformation.

Identification of Three Novel Linear B-Cell Epitopes in Non-Structural Protein 3 of Porcine Epidemic Diarrhea Virus Using Monoclonal Antibodies.

Porcine epidemic diarrhea virus (PEDV) is a highly pathogenic swine coronavirus that causes diarrhea and high mortality in piglets, resulting in significant economic losses within the global swine industry. Nonstructural protein 3 (Nsp3) is the largest in coronavirus, playing critical roles in viral replication, such as the processing of polyproteins and the formation of replication-transcription complexes (RTCs). In this study, three monoclonal antibodies (mAbs), 7G4, 5A3, and 2D7, targeting PEDV Nsp3 were successfully generated, and three distinct linear B-cell epitopes were identified within these mAbs by using Western blotting analysis with 24 truncations of Nsp3. The epitope against 7G4 was located on amino acids 31-TISQDLLDVE-40, the epitope against 5A3 was found on amino acids 141-LGIVDDPAMG-150, and the epitope against 2D7 was situated on amino acids 282-FYDAAMAIDG-291. Intriguingly, the epitope 31-TISQDLLDVE-40 recognized by the mAb 7G4 appears to be a critical B-cell linear epitope due to its high antigenic index and exposed location on the surface of Nsp3 protein. In addition, bioinformatics analysis unveiled that these three epitopes were highly conserved in most genotypes of PEDV. These findings present the first characterization of three novel linear B-cell epitopes in the Nsp3 protein of PEDV and provide potential tools of mAbs for identifying host proteins that may facilitate viral infection.

Achieving Efficient Dark Blue Room-Temperature Phosphorescence with Ultra-Wide Range Tunable-Lifetime.

Tunable-lifetime room-temperature phosphorescence (RTP) materials have been widely studied due to their broad applications. However, only few reports have achieved wide-range lifetime modulation. In this work, ultra-wide range tunable-lifetime efficient dark blue RTP materials were realized by doping methyl benzoate derivatives into polyvinyl alcohol (PVA) matrix. The phosphorescence lifetimes of the doped films can be increased from 32.8 ms to 1925.8 ms. Such wide range of phosphorescence lifetime modulation is extremely rare in current reports. Moreover, the phosphorescence emission of the methyl 4-hydroxybenzoate-doped film is located in the dark blue region and the phosphorescence quantum yield reaches as high as 15.4 %, which broadens their applications in organic optoelectronic information. Further studies demonstrated that the reason for the tunable lifetime was that the magnitude of the electron-donating ability of the substituent group modulates the HOMO-LUMO and singlet-triplet energy gap of methyl benzoate derivatives, as well as the ability to non-covalent interactions with PVA. Moreover, the potential applications of luminescent displays and optical anti-counterfeiting of these high-performance dark blue RTP materials have been conducted.

ADAM22 acts as a novel predictive biomarker for unfavorable prognosis and facilitates metastasis via PI3K/AKT signaling pathway in nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a type of epithelial malignancy known for its high likelihood of metastasizing to distant organs, which remains the primary obstacle in the treatment of NPC. The present study aimed to identify potential intervention target for NPC metastasis. METHODS: The differentially expressed genes (DEGs) were firstly analyzed and intersected across various NPC related datasets in the Gene Expression Omnibus database. Subsequently, various techniques including quantitative polymerase chain reaction (qPCR), western blotting, immunohistochemistry, migration and invasion assays, in conjunction with bioinformatics and prognostic modeling, were utilized to elucidate the role of candidate genes in NPC metastasis. RESULTS: We discerned the gene a disintegrin and metalloprotease 22 (ADAM22) as a distinct and significant factor in the progression and metastasis of NPC through five datasets. The elevated expression of ADAM22 was observed in clinical tissue and plasma samples with advanced NPC, as well as in high metastatic cells. Furthermore, we highlighted its essential role in a prognostic model that demonstrated strong prediction performance for NPC. Notably, overexpression of ADAM22 was found to enhance the aggressiveness and epithelial-mesenchymal transition (EMT) of low metastatic NPC cells, whereas the downregulation of ADAM22 resulted in suppressed effect in high metastatic cells. Delving into the mechanism, ADAM22 activated the PI3K/Akt signaling pathway through the mediation of Rac Family Small GTPase 2 (RAC2), thereby facilitating EMT and metastasis in NPC. CONCLUSIONS: The study provided pioneering insights that ADAM22 had the potential to act as an oncogene by promoting EMT and metastasis of NPC through the RAC2-mediated PI3K/Akt signaling pathway. Thus, ADAM22 could serve as a novel prognostic indicator in NPC.

Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing.

OBJECTIVES: Rheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples. METHODS: The study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient. RESULTS: The study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64-0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63-0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61-0.96, a balanced accuracy range of 0.46-0.94, and an AUC range of 0.46-0.94. CONCLUSIONS: This study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.