Rapid discrimination of African swine fever virus nucleic acid and virions using BenzoNuclease.

African swine fever (ASF) is an acute and severe infectious disease caused by the African Swine Fever Virus (ASFV). ASFV exhibits significant resistance and stability in the environment, which, coupled with its double-stranded DNA and large genome, predisposes it to contaminate laboratory samples. This characteristic can lead to false-positive results in swine farm settings even days after disinfection, as detectable through polymerase chain reaction (PCR) or real-time fluorescent quantitative PCR (qPCR) assays. To meet the demand for efficient clinical methods capable of discriminating between ASFV nucleic acid and ASFV virions, this study aims to ascertain the efficacy of the nuclease "BenzoNuclease" in distinguishing ASFV nucleic acid (ASFV-DNA) from ASFV virions. BenzoNuclease is a versatile nucleic acid enzyme with the capacity to degrade nearly all forms of DNA and RNA. Initially, this research established a highly sensitive general PCR detection method for ASFV. Subsequently, a positive control was constructed using the M13 bacteriophage to substitute for active ASFV, facilitating the development of an improved qPCR method. It is important to note that common disinfectants have the potential to deactivate BenzoNuclease. However, in an environment simulating actual production applications, residual disinfectants do not interfere with the enzymatic efficacy of BenzoNuclease, thus not affecting the detection capabilities of this method. Positive clinical samples from pig farms, upon testing with the improved method, revealed that three samples were positive, indicating the presence of viral particles, while the remaining samples were negative, indicating the presence of nucleic acids. This provides an additional new option for sample testing in pig farms.

SERS biosensors based on catalytic hairpin self-assembly and hybridization chain reaction cascade signal amplification strategies for ultrasensitive microRNA-21 detection.

A highly sensitive surface-enhanced Raman scattering (SERS) biosensor has been developed for the detection of microRNA-21 (miR-21) using an isothermal enzyme-free cascade amplification method involving catalytic hairpin assembly (CHA) and hybridization chain reaction (HCR). The CHA reaction is triggered by the target miR-21, which causes hairpin DNA (C1 and C2) to self-assemble into CHA products. After AgNPs@Capture captures the resulting CHA product, the HCR reaction is started, forming long-stranded DNA on the surface of AgNPs. A strong SERS signal is generated due to the presence of a large amount of the Raman reporter methylene blue (MB) in the vicinity of the SERS "hot spot" on the surface of AgNPs. The monitoring of the SERS signal changes of MB allows for the highly sensitive and specific detection of miR-21. In optimal conditions, the biosensor exhibits a satisfactory linear range and a low detection limit for miR-21 of 42.3 fM. Additionally, this SERS biosensor shows outstanding selectivity and reproducibility. The application of this methodology to clinical blood samples allows for the differentiation of cancer patients from healthy controls. As a result, the CHA-HCR amplification strategy used in this SERS biosensor could be a useful tool for miRNA detection and early cancer screening.

[Value of calprotectin S100 A8/A9 in predicting the severity of Mycoplasma pneumoniae pneumonia in children]. / 钙卫蛋白S100 A8/A9å¯¹è‚ºç‚Žæ”¯åŽŸä½“è‚ºç‚Žæ‚£å„¿ç— æƒ ä¸¥é‡ç¨‹åº¦çš„é¢„æµ‹ä»·å€¼.

OBJECTIVES: To investigate the role of calprotectin S100 A8/A9 complex in evaluating the condition of children with severe Mycoplasma pneumoniae pneumonia (SMPP). METHODS: A prospective study was conducted among 136 children with Mycoplasma pneumoniae pneumonia (MPP) and 30 healthy controls. According to the severity of the condition, the children with MPP were divided into mild subgroup (40 children) and SMPP subgroup (96 children). The levels of S100 A8/A9 complex and related inflammatory factors were compared between the MPP group and the healthy control group, as well as between the two subgroups of MPP. The role of S100 A8/A9 in assessing the severity of MPP was explored. RESULTS: The MPP group had a significantly higher level of S100 A8/A9 than the healthy control group, with a significantly greater increase in the SMPP subgroup (P<0.05). The multivariate logistic regression analysis showed that the increases in serum C reactive protein (CRP) and S100A8/A9 were closely associated with SMPP (P<0.05). The receiver operating characteristic (ROC) curve analysis showed that the combined measurement of serum S100 A8/A9 and CRP had an area under the ROC curve of 0.904 in predicting SMPP, which was significantly higher than the AUC of S100 A8/A9 or CRP alone (P<0.05), with a specificity of 0.718 and a sensitivity of 0.952. CONCLUSIONS: S100 A8/A9 is closely associated with the severity of MPP, and the combination of S100 A8/A9 with CRP is more advantageous for assessing the severity of MPP in children.

Entropy drives the ligand recognition in G-protein-coupled receptor subtypes.

Achieving ligand subtype selectivity within highly homologous subtypes of G-protein-coupled receptor (GPCR) is critical yet challenging for GPCR drug discovery, primarily due to the unclear mechanism underlying ligand subtype selectivity, which hampers the rational design of subtype-selective ligands. Herein, we disclose an unusual molecular mechanism of entropy-driven ligand recognition in cannabinoid (CB) receptor subtypes, revealed through atomic-level molecular dynamics simulations, cryoelectron microscopy structure, and mutagenesis experiments. This mechanism is attributed to the distinct conformational dynamics of the receptor's orthosteric pocket, leading to variations in ligand binding entropy and consequently, differential binding affinities, which culminate in specific ligand recognition. We experimentally validated this mechanism and leveraged it to design ligands with enhanced or ablated subtype selectivity. One such ligand demonstrated favorable pharmacokinetic properties and significant efficacy in rodent inflammatory analgesic models. More importantly, it is precisely due to the high subtype selectivity obtained based on this mechanism that this ligand does not show addictive properties in animal models. Our findings elucidate the unconventional role of entropy in CB receptor subtype selectivity and suggest a strategy for rational design of ligands to achieve entropy-driven subtype selectivity for many pharmaceutically important GPCRs.

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma.

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

Parameter selection on a multi-exposure fusion method for measuring surfaces with varying reflectivity in microscope fringe projection profilometry.

As industrial and scientific advancements continue, the demand for precise measurement of three-dimensional (3D) shapes and surfaces is steadily increasing. However, accurate 3D measurement of certain surfaces, especially those with varying reflectivities, has always been a challenging issue. Multi-exposure fusion methods have shown stable, high-quality measurement results, but the selection of parameters for these methods has largely been based on experience. To address this issue, this paper has improved the multi-exposure fusion method and introduced a guided approach for parameter selection, significantly enhancing the completeness of measurement results. Additionally, a comparative model is developed to experimentally validate the specific impacts of Gaussian window variance, optimal grayscale range, and attenuation factor variance on the integrity of 3D reconstruction. The experimental results demonstrate that under the guidance of the parameter adjustment method proposed in this paper, the multi-exposure fusion for measuring the 3D topography of high-dynamic surfaces improves the restoration coverage from the original 86% (bright areas) and 50% (dark areas) to over 99%. This provides a selection strategy for parameter adjustment guidance in precise measurements based on the multi-exposure method.

Characterizing the aggregated encoding method utilizing bursts activated by a VCSEL-neuron with a feedback structure.

The rapid advancement of photonic technologies has facilitated the development of photonic neurons that emulate neuronal functionalities akin to those observed in the human brain. Neuronal bursts frequently occur in behaviors where information is encoded and transmitted. Here, we present the demonstration of the bursting response activated by an artificial photonic neuron. This neuron utilizes a single vertical-cavity surface-emitting laser (VCSEL) and encodes multiple stimuli effectively by varying the spike count during a burst based on the polarization competition in the VCSEL. By virtue of the modulated optical injection in the VCSEL employed to trigger the spiking response, we activate bursts output in the VCSEL with a feedback structure in this scheme. The bursting response activated by the VCSEL-neuron exhibits neural signal characteristics, promising an excitation threshold and the refractory period. Significantly, this marks the inaugural implementation of a controllable integrated encoding scheme predicated on bursts within photonic neurons. There are two remarkable merits; on the one hand, the interspike interval of bursts is distinctly diminished, amounting to merely one twenty-fourth compared to that observed in optoelectronic oscillators. Moreover, the interspike period of bursts is about 70.8% shorter than the period of spikes activated by a VCSEL neuron without optical feedback. Our results may shed light on the analogy between optical and biological neurons and open the door to fast burst encoding-based optical systems with a speed several orders of magnitude faster than their biological counterparts.

Enhanced extreme events in three cascade-coupled semiconductor lasers.

Extreme events (EEs) are rare and unpredictable, as have been observed in nature. Up to now, manipulating EEs has remained a challenge. Here, we experimentally observe the enhancement of EEs in a three cascade-coupled semiconductor laser system. Specifically, a continuous-wave optical injection semiconductor laser acts as the chaotic source with rare EEs, which is subsequently injected into a second laser for increasing the number of EEs. Interestingly, we find that the number and region size of EEs can be further enhanced by sequentially injecting into a third laser, i.e., a cascade-injection structure. Our experimental observations are in good agreement with the numerical results, which indicate that EEs can be significantly enhanced in wide injection parameter space due to the cascade-injection effect. Furthermore, our simulations show that the evoluation of the regions with enhanced EEs may be associated with the noise considered.

Structure-based identification of a G protein-biased allosteric modulator of cannabinoid receptor CB1.

Cannabis sativa is known for its therapeutic benefit in various diseases including pain relief by targeting cannabinoid receptors. The primary component of cannabis, Δ9-tetrahydrocannabinol (THC), and other agonists engage the orthosteric site of CB1, activating both Gi and ß-arrestin signaling pathways. The activation of diverse pathways could result in on-target side effects and cannabis addiction, which may hinder therapeutic potential. A significant challenge in pharmacology is the design of a ligand that can modulate specific signaling of CB1. By leveraging insights from the structure-function selectivity relationship (SFSR), we have identified Gi signaling-biased agonist-allosteric modulators (ago-BAMs). Further, two cryoelectron microscopy (cryo-EM) structures reveal the binding mode of ago-BAM at the extrahelical allosteric site of CB1. Combining mutagenesis and pharmacological studies, we elucidated the detailed mechanism of ago-BAM-mediated biased signaling. Notably, ago-BAM CB-05 demonstrated analgesic efficacy with fewer side effects, minimal drug toxicity and no cannabis addiction in mouse pain models. In summary, our finding not only suggests that ago-BAMs of CB1 provide a potential nonopioid strategy for pain management but also sheds light on BAM identification for GPCRs.

Conjoint analysis of physio-biochemical, transcriptomic, and metabolomic reveals the response characteristics of solanum nigrum L. to cadmium stress.

Cadmium (Cd) is a nonessential element in plants and has adverse effects on the growth and development of plants. However, the molecular mechanisms of Cd phytotoxicity, tolerance and accumulation in hyperaccumulators Solanum nigrum L. has not been well understood. Here, physiology, transcriptome, and metabolome analyses were conducted to investigate the influence on the S. nigrum under 0, 25, 50, 75 and 100 µM Cd concentrations for 7 days. Pot experiments demonstrated that compared with the control, Cd treatment significantly inhibited the biomass, promoted the Cd accumulation and translocation, and disturbed the balance of mineral nutrient metabolism in S. nigrum, particularly at 100 µM Cd level. Moreover, the photosynthetic pigments contents were severely decreased, while the content of total protein, proline, malondialdehyde (MDA), H2O2, and antioxidant enzyme activities generally increased first and then slightly declined with increasing Cd concentrations, in both leaves and roots. Furthermore, combined with the previous transcriptomic data, numerous crucial coding-genes related to mineral nutrients and Cd ion transport, and the antioxidant enzymes biosynthesis were identified, and their expression pattern was regulated under different Cd stress. Simultaneously, metabolomic analyses revealed that Cd treatment significantly changed the expression level of many metabolites related to amino acid, lipid, carbohydrate, and nucleotide metabolism. Metabolic pathway analysis also showed that S. nigrum roots activated some differentially expressed metabolites (DEMs) involved in energy metabolism, which may enhance the energy supply for detoxification. Importantly, central common metabolism pathways of DEGs and DEMs, including the "TCA cycle", "glutathione metabolic pathway" and "glyoxylate and dicarboxylate metabolism" were screened using conjoint transcriptomics and metabolomics analysis. Our results provide some novel evidences on the physiological and molecular mechanisms of Cd tolerance in hyperaccumulator S. nigrum plants.

IL-38 Aggravates Atopic Dermatitis via Facilitating Migration of Langerhans cells.

Atopic dermatitis (AD) is a common inflammation skin disease that involves dysregulated interplay between immune cells and keratinocytes. Interleukin-38 (IL-38), a poorly characterized IL-1 family cytokine, its role and mechanism in the pathogenesis of AD is elusive. Here, we show that IL-38 is mainly secreted by epidermal keratinocytes and highly expressed in the skin and downregulated in AD lesions. We generated IL-38 keratinocyte-specific knockout mice (K14Cre/+-IL-38f/f ) and induced AD models by 2,4-dinitrofluorobenzene (DNFB). Unexpectedly, after treatment with DNFB, K14Cre/+-IL-38f/f mice were less susceptible to cutaneous inflammation of AD. Moreover, keratinocyte-specific deletion of IL-38 suppressed the migration of Langerhans cells (LCs) into lymph nodes which results in disturbed differentiation of CD4+T cells and decreased the infiltration of immune cells into AD lesions. LCs are a type of dendritic cell that reside specifically in the epidermis and regulate immune responses. We developed LC-like cells in vitro from mouse bone marrow (BM) and treated with recombined IL-38. The results show that IL-38 depended on IL-36R, activated the phosphorylated expression of IRAK4 and NF-κB P65 and upregulated the expression of CCR7 to promoting the migration of LCs, nevertheless, the upregulation disappeared with the addition of IL-36 receptor antagonist (IL-36RA), IRAK4 or NF-κB P65 inhibitor. Furthermore, after treatment with IRAK4 inhibitors, the experimental AD phenotypes were alleviated and so IRAK4 is considered a promising target for the treatment of inflammatory diseases. Overall, our findings indicated a potential pathway that IL-38 depends on IL-36R, leading to LCs migration to promote AD by upregulating CCR7 via IRAK4/NF-κB and implied the prevention and treatment of AD, supporting potential clinical utilization of IRAK4 inhibitors in AD treatment.

African swine fever virus pB475L evades host antiviral innate immunity via targeting STAT2 to inhibit IFN-I signaling.

African swine fever virus (ASFV) causes severe disease in domestic pigs and wild boars, seriously threatening the development of the global pig industry. Type I interferon (IFN-I) is an important component of innate immunity, inducing the transcription and expression of antiviral cytokines by activating Janus-activated kinase-signal transducer and activator of transcription (STAT). However, the underlying molecular mechanisms by which ASFV antagonizes IFN-I signaling have not been fully elucidated. Therefore, using coimmunoprecipitation, confocal microscopy, and dual luciferase reporter assay methods, we investigated these mechanisms and identified a novel ASFV immunosuppressive protein, pB475L, which interacts with the C-terminal domain of STAT2. Consequently, pB475L inhibited IFN-I signaling by inhibiting STAT1 and STAT2 heterodimerization and nuclear translocation. Furthermore, we constructed an ASFV-B475L7PM mutant strain by homologous recombination, finding that ASFV-B475L7PM attenuated the inhibitory effects on IFN-I signaling compared to ASFV-WT. In summary, this study reveals a new mechanism by which ASFV impairs host innate immunity.

Monoclonal antibody development for early detection of ASFV I73R protein: Identification of a linear antigenic epitope.

African swine fever virus (ASFV), which was first identified in northern China in 2018, causes high mortality in pigs. Since the I73R protein in ASFV is abundantly expressed during the early phase of virus replication, it can be used as a target protein for early diagnosis. In this study, the I73R protein of ASFV was expressed, and we successfully prepared a novel monoclonal antibody (mAb), 8G11D7, that recognizes this protein. Through both indirect immunofluorescence and Western blotting assays, we demonstrated that 8G11D7 can detect ASFV strains. By evaluating the binding of the antibody to a series of I73R-truncated peptides, the definitive epitope recognized by the monoclonal antibody 8G11D7 was determined to be 58 DKTNTIYPP 66. Bioinformatic analysis revealed that the antigenic epitope had a high antigenic index and conservatism. This study contributes to a deeper understanding of ASFV protein structure and function, helping establish ASFV-specific detection method.

Case report: Multiple organ failure caused by Japanese spotted fever.

A 71-year-old male had disseminated multiple organ dysfunction syndrome (MODS). Following treatment with cefotaxime and piperacillin-tazobactam, his symptoms have worsened instead. Multiple organ failure caused by Japanese Spotted Fever (JSF) was diagnosed based on metagenomic next-generation sequencing (mNGS), we rapidly treated the patient with doxycycline. Thereafter, his symptoms gradually improved. In this report, we emphasized the importance of rapid microbial diagnostic tools and the early use of tetracyclines for the treatment of JSF.

IRG1/itaconate alleviates acute liver injury in septic mice by suppressing NLRP3 expression and its mediated macrophage pyroptosis via regulation of the Nrf2 pathway.

Sepsis, a systemic inflammatory response triggered by infection, has a considerably high mortality rate. However, effective prevention and intervention measures against sepsis remain insufficient. Therefore, this study aimed to investigate the mechanisms underlying the protective properties of immune response gene-1 (IRG1) and 4-Octyl itaconate (OI) during acute liver damage in mice with sepsis. A sepsis mouse model was established to compare wild-type and IRG1-/- groups. The impact of IRG1/Itaconate on pro- and anti-inflammatory cytokines was evaluated using J774A.1 cells. IRG1/Itaconate substantially reduced pro-inflammatory cytokines and increased the release of anti-inflammatory cytokines. It reduced pathological damage to liver tissues, preserved normal liver function, decreased the release of reactive oxygen species (ROS) and LDH, and enhanced the GSH/GSSG ratio. Moreover, IRG1 and itaconic acid activated the Nrf2 signaling pathway, regulating the expression of its downstream antioxidative stress-related proteins. Additionally, they inhibited the activity of NLRP3 inflammatory vesicles to suppress the expression of macrophage-associated pyroptosis signaling molecules. Our findings demonstrate that IRG1/OI inhibits NLRP3 inflammatory vesicle activation and macrophage pyroptosis by modulating the Nrf2 signaling pathway, thereby attenuating acute liver injury in mice with sepsis. These findings could facilitate the clinical application of IRG1/Itaconate to prevent sepsis-induced acute liver injury.

Wybutosine hypomodification of tRNAphe activates HERVK and impairs neuronal differentiation.

We previously reported that loss of function of TYW1 led to cerebral palsy with severe intellectual disability through reduced neural proliferation. However, whether TYW1 loss affects neural differentiation is unknown. In this study, we first demonstrated that TYW1 loss blocked the formation of OHyW in tRNAphe and therefore affected the translation efficiency of UUU codon. Using the brain organoid model, we showed impaired neuron differentiation when TYW1 was depleted. Interestingly, retrotransposons were differentially regulated in TYW1-/- hESCs (human embryonic stem cells). In particular, one kind of human-specific endogenous retrovirus-K (HERVK/HML2), whose reactivation impaired human neurodevelopment, was significantly up-regulated in TYW1-/- hESCs. Consistently, a UUU codon-enriched protein, SMARCAD1, which was a key factor in controlling endogenous retroviruses, was reduced. Taken together, TYW1 loss leads to up-regulation of HERVK in hESCs by down-regulated SMARCAD1, thus impairing neuron differentiation.

Improving prediction of tacrolimus concentration using a combination of population pharmacokinetic modeling and machine learning in chinese renal transplant recipients.

Aims: The population pharmacokinetic (PPK) model-based machine learning (ML) approach offers a novel perspective on individual concentration prediction. This study aimed to establish a PPK-based ML model for predicting tacrolimus (TAC) concentrations in Chinese renal transplant recipients. Methods: Conventional TAC monitoring data from 127 Chinese renal transplant patients were divided into training (80%) and testing (20%) datasets. A PPK model was developed using the training group data. ML models were then established based on individual pharmacokinetic data derived from the PPK basic model. The prediction performances of the PPK-based ML model and Bayesian forecasting approach were compared using data from the test group. Results: The final PPK model, incorporating hematocrit and CYP3A5 genotypes as covariates, was successfully established. Individual predictions of TAC using the PPK basic model, postoperative date, CYP3A5 genotype, and hematocrit showed improved rankings in ML model construction. XGBoost, based on the TAC PPK, exhibited the best prediction performance. Conclusion: The PPK-based machine learning approach emerges as a superior option for predicting TAC concentrations in Chinese renal transplant recipients.

DexDesign: an OSPREY-based algorithm for designing de novo D-peptide inhibitors.

With over 270 unique occurrences in the human genome, peptide-recognizing PDZ domains play a central role in modulating polarization, signaling, and trafficking pathways. Mutations in PDZ domains lead to diseases such as cancer and cystic fibrosis, making PDZ domains attractive targets for therapeutic intervention. D-peptide inhibitors offer unique advantages as therapeutics, including increased metabolic stability and low immunogenicity. Here, we introduce DexDesign, a novel OSPREY-based algorithm for computationally designing de novo D-peptide inhibitors. DexDesign leverages three novel techniques that are broadly applicable to computational protein design: the Minimum Flexible Set, K*-based Mutational Scan, and Inverse Alanine Scan. We apply these techniques and DexDesign to generate novel D-peptide inhibitors of two biomedically important PDZ domain targets: CAL and MAST2. We introduce a framework for analyzing de novo peptides-evaluation along a replication/restitution axis-and apply it to the DexDesign-generated D-peptides. Notably, the peptides we generated are predicted to bind their targets tighter than their targets' endogenous ligands, validating the peptides' potential as lead inhibitors. We also provide an implementation of DexDesign in the free and open source computational protein design software OSPREY.

Sevoflurane inhibits lung cancer development by promoting FUS1 transcription via downregulating IRF6.

Lung cancer is a major contributor to cancer deaths worldwide and is on the rise. Although surgical resection has been widely used as a standard of therapy for lung cancer patients, the relapse rate after surgery is high. It is still unclear whether there is a potential drug that can reduce the probability of post-surgical recurrence in lung cancer patients. We used five typical lung cancer cell lines as well as 41 lung cancer tissue samples and paracancer tissue samples to investigate the expression levels of IRF6 and FUS1. We also treated lung cancer cells (H322 and A549) with different concentrations of sevoflurane to study its influence on lung cancer cell tumorigenesis. Lentivirus-mediated gain-of-function studies of IRF6 and FUS1 were applied to validate the role of IRF6 and FUS1 in lung cancer. Next, we used short hairpin RNA-mediated loss of function of IRF6 and luciferase, ChIP assays to validate the regulatory role of IRF6 on FUS1. Our findings reported that IRF6 was up-regulated in lung cancer tissues, while FUS1 was down-regulated. Functional assays revealed that sevoflurane inhibits lung cancer development by downregulating IRF6 expression. Luciferase assay and ChIP-qPCR assay uncovered that IRF6 represses FUS1 transcriptional expression in lung cancer cells. We have shown that sevoflurane prevents lung cancer development by downregulating IRF6 to stimulate FUS1 transcription; indicating that sevoflurane can be used as the potential anesthetic drug in surgical resection to reduce post-operative tumor relapse in lung cancer patients.