Mutagenesis analysis of the zinc-finger antiviral protein

BACKGROUND: The zinc-finger antiviral protein (ZAP) specifically inhibits the replication of certain viruses, including murine leukemia virus (MLV), by preventing the accumulation of viral mRNA in the cytoplasm. ZAP directly binds to the viral mRNA through the zinc-finger motifs and recruits the RNA exosome to degrade the target RNA. RNA helicase p72 is required for the optimal function of ZAP. In an attempt to understand the structure-function relationship of ZAP, we performed alanine scanning analysis. RESULTS: A series of ZAP mutants was generated, in which three consecutive amino acids were replaced with three alanines. The mutants were analyzed for their antiviral activities against pseudotyped MLV vector. Out of the nineteen mutants analyzed, seven displayed significantly lower antiviral activities. Two mutations were in the very N-terminal domain, and five mutations were within or around the first and second zinc-finger motifs. These mutants were further analyzed for their abilities to bind to the target RNA, the exosome, and the RNA helicase p72. Mutants Nm3 and Nm63 lost the ability to bind to RNA. Mutants Nm 63 and Nm93 displayed compromised interaction with p72, while the binding of Nm133 to p72 was very modest. The interactions of all the mutants with the exosome were comparable to wild type ZAP. CONCLUSIONS: The integrity of the very N-terminal domain and the first and second zinc-finger motifs appear to be required for ZAP's antiviral activity. Analyses of the mutants for their abilities to interact with the target RNA and RNA helicase p72 confirmed our previous results. The mutants that bind normally to the target RNA, the exosome, and the RNA helicase p72 may be useful tools for further understanding the mechanism underlying ZAP's antiviral activity

Idiopathic desmoid-type fibromatosis of the pancreatic head: case report and literature review

Desmoid-type fibromatosis (DTF) is an uncommon nonmetastatic fibrous neoplasm. Sporadic intraperitoneal DTF is rarely described in current literature. We herein report a case of DTF of unknown cause involving the pancreatic head. A 41-year-old man presented with recurrent epigastric pain and weight loss. An abdominal computed tomography scan showed a well-delineated solid cystic mass inside the pancreatic head. Pylorus-preserving pancreaticoduodenectomy was performed due to the patient’s debilitating symptoms and suspected malignancy. The pathological examination revealed massive fibroblastic proliferation arising from the musculoaponeurotic tissues, consistent with a diagnosis of DTF. Immunohistochemical phenotyping determined positive immunoreactivity to vimentin and β-catenin, but negative immunoreactivity to smooth muscle actin, CD117, CD34, or S-100, confirming the diagnosis of DTF. No local recurrence or distant metastasis was found during a 24-month follow-up. Radical resection is recommended as first-line treatment for pancreatic DTF. Long-term follow-up studies are required to establish the prognosis of pancreatic DTF

GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks

Automatically evaluating vision-language tasks is challenging, especially when it comes to reflecting human judgments due to limitations in accounting for fine-grained details. Although GPT-4V has shown promising results in various multi-modal tasks, leveraging GPT-4V as a generalist evaluator for these tasks has not yet been systematically explored. We comprehensively validate GPT-4V's capabilities for evaluation purposes, addressing tasks ranging from foundational image-to-text and text-to-image synthesis to high-level image-to-image translations and multi-images to text alignment. We employ two evaluation methods, single-answer grading and pairwise comparison, using GPT-4V. Notably, GPT-4V shows promising agreement with humans across various tasks and evaluation methods, demonstrating immense potential for multi-modal LLMs as evaluators. Despite limitations like restricted visual clarity grading and real-world complex reasoning, its ability to provide human-aligned scores enriched with detailed explanations is promising for universal automatic evaluator

Adaptive Routing Forwarding Strategy Based on Neural Network Algorithm

With the profound changes in global digital media, the focus of Internet users has gradually shifted to how to quickly obtain information without paying attention to where the information is stored. However, the current TCP/IP network protocol architecture cannot adapt to the rapid development of today#39s content applications. In order to adapt to the changes in the Internet, information-centric networking (ICN)has received extensive attention. Besides, the optimization of the user service request scheduling problem is the core issue affecting the performance of the ICN , and it is one of the hot research topics in the ICN network. To solve this problem, this paper proposes an adaptive routing forwarding strategy based on neural network algorithm. Through the modeling of the classic architecture named data networking (NDN) network delay model of ICN network, a neural network algorithm is used to delay prediction, and a forwarding strategy mechanism based on predict delay is designed to innovate in the NDN. The interface information Stat is added to the forwarding information base (FIB) of the network component to implement the dynamic selection of the forwarding routing. In addition, routing dynamic self-adaptation adjustment mechanism and fault rerouting function are designed in consideration of the situation of route congestion and interruption. Simulation results show that this strategy effectively reduces network delay and improves network performance

Clinical, epidemiological, and drug resistance insights into HIV-positive patients in Meizhou, China

The acquired immunodeficiency syndrome (AIDS) epidemic, resulting from human immunodeficiency virus (HIV) infection, exhibits distinct regional characteristics. This study undertakes a retrospective analysis of the epidemiological and clinical features of 195 HIV-positive cases in Meizhou, China, from May 1, 2018 to December 31, 2019. Western blotting (WB) confirmed and assessed these cases. Notably, the majority of cases emanated from socio-economic groups with comparatively lower levels of education, with 80% being male. Strikingly, 90% of the cases were found to be in the middle to late stages of infection based on CD4+ T cell counts. Among the 30 different serum antibody profiles examined, reactivity with seven bands (p24, p31, gp41, p51, p66, gp120, and gp160) emerged as the most commonly observed WB pattern. The absence of specific bands, specifically p55 (17.44%), p39 (32.31%), and p17 (25.64%) were most frequent, with the detection frequency of p17 bands significantly reduced among cases in the AIDS and middle stages. An analysis of drug resistance genotypes indicated that, despite viral mutations conferring resistance to certain reverse transcriptase inhibitors, the first-line treatment regimen remained effective for patients in Meizhou. Notably, mutations resistant to protease inhibitors were infrequent (2.7%), suggesting that incorporating protease inhibitors into the treatment regimen may enhance therapeutic outcomes for local patients. These findings provide essential insights into the specific epidemiological patterns, serum antibody profiles, and drug resistance genotypes of HIV-infected patients in Meizhou. Significantly, this research contributes to the formulation of future treatment strategies tailored to the local context

An (E,E)-α-farnesene synthase gene of soybean has a role in defence against nematodes and is involved in synthesizing insect-induced volatiles

Plant terpene synthase genes (TPSs) have roles in diverse biological processes. Here, we report the functional characterization of one member of the soybean TPS gene family, which was designated GmAFS. Recombinant GmAFS produced in Escherichia coli catalysed the formation of a sesquiterpene (E,E)-a-farnesene. GmAFS is closely related to (E,E)-a-farnesene synthase gene from apple, both phylogenetically and structurally. GmAFS was further investigated for its biological role in defence against nematodes and insects. Soybean cyst nematode (SCN) is the most important pathogen of soybean. The expression of GmAFS in a SCN-resistant soybean was significantly induced by SCN infection compared with the control, whereas its expression in a SCN-susceptible soybean was not changed by SCN infection. Transgenic hairy roots overexpressing GmAFS under the control of the CaMV 35S promoter were generated in an SCN-susceptible soybean line. The transgenic lines showed significantly higher resistance to SCN, which indicates that GmAFS contributes to the resistance of soybean to SCN. In soybean leaves, the expression of GmAFS was found to be induced by Tetranychus urticate (two-spotted spider mites). Exogenous application of methyl jasmonate to soybean plants also induced the expression of GmAFS in leaves. Using headspace collection combined with gas chromatography–mass spectrometry analysis, soybean plants that were infested with T. urticae were shown to emit a mixture of volatiles with (E,E)-a-farnesene as one of the most abundant constituents. In summary, this study showed that GmAFS has defence roles in both below-ground and above-ground organs of soybean against nematodes and insects, respectively

Preliminary Study:Learning the Impact of Simulation Time on Reentry Location and Morphology Induced by Personalized Cardiac Modeling

Personalized cardiac modeling is widely used for studying the mechanisms of cardiac arrythmias. Due to the high demanding of computational resource of modeling, the arrhythmias induced in the models are usually simulated for just a few seconds. In clinic, it is common that arrhythmias last for more than several minutes and the morphologies of reentries are not always stable, so it is not clear that whether the simulation of arrythmias for just a few seconds is long enough to match the arrhythmias detected in patients. This study aimed to observe how long simulation of the induced arrhythmias in the personalized cardiac models is sufficient to match the arrhythmias detected in patients. A total of 5 contrast enhanced MRI datasets of patient hearts with myocardial infarction were used in this study. Then, a classification method based on Gaussian mixture model was used to detect the infarct tissue. For each reentry, 3 s and 10 s were simulated. The characteristics of each reentry simulated for different duration were studied. Reentries were induced in all 5 ventricular models and sustained reentries were induced at 39 stimulation sites in the model. By analyzing the simulation results, we found that 41% of the sustained reentries in the 3 s simulation group terminated in the longer simulation groups (10 s). The second finding in our simulation was that only 23.1% of the sustained reentries in the 3 s simulation did not change location and morphology in the extended 10 s simulation. The third finding was that 35.9% reentries were stable in the 3 s simulation and should be extended for the simulation time. The fourth finding was that the simulation results in 10 s simulation matched better with the clinical measurements than the 3 s simulation. It was shown that 10 s simulation was sufficient to make simulation results stable. The findings of this study not only improve the simulation accuracy, but also reduce the unnecessary simulation time to achieve the optimal use of computer resources to improve the simulation efficiency and shorten the simulation time to meet the time node requirements of clinical operation on patients

Determination of Advantages and Limitations of qPCR Duplexing in a Single Fluorescent Channel

Real-time (quantitative) polymerase chain reaction (qPCR) has been widely applied in molecular diagnostics due to its immense sensitivity and specificity. qPCR multiplexing, based either on fluorescent probes or intercalating dyes, greatly expanded PCR capability due to the concurrent amplification of several deoxyribonucleic acid sequences. However, probe-based multiplexing requires multiple fluorescent channels, while intercalating dye-based multiplexing needs primers to be designed for amplicons having different melting temperatures. Here, we report a single fluorescent channel-based qPCR duplexing method on a model containing the sequence of chromosomes 21 (Chr21) and 18 (Chr18). We combined nonspecific intercalating dye EvaGreen with a 6-carboxyfluorescein (FAM) probe specific to either Chr21 or Chr18. The copy number (cn) of the target linked to the FAM probe could be determined in the entire tested range from the denaturation curve, while the cn of the other one was determined from the difference between the denaturation and elongation curves. We recorded the amplitude of fluorescence at the end of denaturation and elongation steps, thus getting statistical data set to determine the limit of the proposed method in detail in terms of detectable concentration ratios of both targets. The proposed method eliminated the fluorescence overspilling that happened in probe-based qPCR multiplexing and determined the specificity of the PCR product via melting curve analysis. Additionally, we performed and verified our method using a commercial thermal cycler instead of a self-developed system, making it more generally applicable for researchers. This quantitative single-channel duplexing method is an economical substitute for a conventional rather expensive probe-based qPCR requiring different color probes and hardware capable of processing these fluorescent signals

The global mismatch between equitable carbon dioxide removal liability and capacity

Limiting climate change to 1.5°C and achieving net-zero emissions would entail substantial carbon dioxide removal (CDR) from the atmosphere by mid-century, but how much CDR is needed at country level over time is unclear. The purpose of this paper is to provide a detailed description of when and how much CDR is required at country level to take in order to achieve 1.5°C and how much CDR countries can carry out domestically. We allocate global CDR pathways among 170 countries according to six equity principles and assess these allocations with respect to countries' biophysical and geophysical capacity to deploy CDR. Allocating global CDR to countries based on these principles suggests that CDR will, on average, represent ∼4% of nations' total emissions in 2030, rising to ∼17% in 2040. Moreover, equitable allocations of CDR, in many cases, exceed implied land and carbon storage capacities. We estimate ∼15% of countries (25) would have insufficient land to contribute an equitable share of global CDR, and ∼40% of countries (71) would have insufficient geological storage capacity. Unless more diverse CDR technologies are developed, the mismatch between CDR liabilities and land-based CDR capacities will lead to global demand for 6 GtCO2 carbon credits from 2020 to 2050. This demonstrates an imperative demand for international carbon trading of CDR