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Background Acute myeloid leukemia (AML) is a disease characterized by the proliferation of abnormal cells originating from blood stem cells. Understanding the pathogenesis and progression of AML, as well as identifying molecular markers for early diagnosis and prognosis assessment, is of paramount importance.Methods The AML dataset was obtained from the Cancer Genome Atlas (TCGA), while the normal sample dataset was derived from the Genotype-Tissue Expression(GTEx) dataset. Furthermore, the association between SRSF12 expression and drug response was assessed using the Cancer Therapeutic Response Portal (CTRP) database to evaluate its potential therapeutic value. Finally, SRSF12 expression in AML cells was measured using quantitative real-time PCR (qRT-PCR).Result The difference in SRSF12 expression between 13 types of tumors and normal tissue samples was found to be statistically significant (P

IntroductionMelatonin, a tryptophan-derived indoleamine metabolite with important roles in plant growth and defense, has recently been regarded as a new plant hormone. Maize is one of the most important cereal crops in the world. Although the melatonin receptor gene, ZmPMTR1, has already been identified, the genetic basis of melatonin biosynthesis in maize has still not been elucidated. Serotonin N-acetyltransferase (SNAT) is the enzyme that converts serotonin to N-acetylserotonin (NAS) or 5-methoxytryptamine (5MT) to melatonin in Arabidopsis and rice, but no SNAT encoding gene has been identified yet in maize.MethodsThe bioinformatics analysis was used to identify maize SNAT genes and the enzyme activity of the recombinant proteins was determined through in vitro assay. The expression levels of ZmSNAT1 and ZmSNAT3 under drought and heat stresses were revealed by public RNA-seq datasets and qRT-PCR analysis.ResultsWe first identified three maize SNAT genes, ZmSNAT1, ZmSNAT2, and ZmSNAT3, through bioinformatics analysis, and demonstrated that ZmSNAT2 was present in only eight of the 26 cultivars analyzed. We then determined the enzyme activity of ZmSNAT1 and ZmSNAT3 using their recombinant proteins through in vitro assay. The results showed that both ZmSNAT1 and ZmSNAT3 could convert serotonin to NAS and 5-MT to melatonin. Recombinant ZmSNAT1 catalyzed serotonin into NAS with a higher catalytic activity (Km, 8.6 mM; Vmax, 4050 pmol/min/mg protein) than ZmSNAT3 (Km, 11.51 mM; Vmax, 142 pmol/min/mg protein). We further demonstrated that the 228th amino acid Tyr (Y228) was essential for the enzymatic activity of ZmSNAT1. Finally, we revealed that the expression of ZmSNAT1 and ZmSNAT3 varied among different maize cultivars and different tissues of a plant, and was responsive to drought and heat stresses.DiscussionIn summary, the present study identified and characterized the first two functional SNAT genes in maize, laying the foundation for further research on melatonin biosynthesis and its regulatory role in plant growth and response to abiotic stresses.

Abstract Background COVID-19-associated pulmonary fibrosis remains frequent. This study aimed to investigate pulmonary redox balance in COVID-19 ARDS patients and possible relationship with pulmonary fibrosis and long-term lung abnormalities. Methods Baseline data, chest CT fibrosis scores, N-terminal peptide of alveolar collagen III (NT-PCP-III), transforming growth factor (TGF)-β1, superoxide dismutase (SOD), reduced glutathione (GSH), oxidized glutathione (GSSG) and malondialdehyde (MDA) in bronchoalveolar lavage fluid (BALF) were first collected and compared between SARS-CoV-2 RNA positive patients with moderate to severe ARDS (n = 65, COVID-19 ARDS) and SARS-CoV-2 RNA negative non-ARDS patients requiring mechanical ventilation (n = 63, non-ARDS). Then, correlations between fibroproliferative (NT-PCP-III and TGF-β1) and redox markers were analyzed within COVID-19 ARDS group, and comparisons between survivor and non-survivor subgroups were performed. Finally, follow-up of COVID-19 ARDS survivors was performed to analyze the relationship between pulmonary abnormalities, fibroproliferative and redox markers 3 months after discharge. Results Compared with non-ARDS group, COVID-19 ARDS group had significantly elevated chest CT fibrosis scores (p

Abstract Effective forecasting of energy consumption structure is vital for China to reach its “dual carbon” objective. However, little attention has been paid to existing studies on the holistic nature and internal properties of energy consumption structure. Therefore, this paper incorporates the theory of compositional data into the study of energy consumption structure, which not only takes into account the specificity of the internal features of the structure, but also digs deeper into the relative information. Meanwhile, based on the minimization theory of squares of the Aitchison distance in the compositional data, a combined model based on the three single models, namely the metabolism grey model (MGM), back-propagation neural network (BPNN) model, and autoregressive integrated moving average (ARIMA) model, is structured in this paper. The forecast results of the energy consumption structure in 2023–2040 indicate that the future energy consumption structure of China will evolve towards a more diversified pattern, but the proportion of natural gas and non-fossil energy has yet to meet the policy goals set by the government. This paper not only suggests that compositional data from joint prediction models have a high applicability value in the energy sector, but also has some theoretical significance for adapting and improving the energy consumption structure in China.

Abstract China’s Belt and Road Initiative (BRI) aims to strengthen regional economic and policy cooperation and achieve the rapid development among the participating countries. While the impact on the financial development of the economic growth and energy environment of BRI participating countries has garnered close attention among scholars, few studies focus on the impact of financial development on the sustainable development goals (SDGs) of the BRI participating countries. To address this gap, we utilized panel regression models to quantitatively assess the impact of China’s financial development scale, structure, and efficiency on the SDGs of the BRI participating countries, and adopted Geographically and Temporally Weighted Regression (GTWR) model to explore the spatial-temporal effects of China’s financial development scale, structure, and efficiency on the SDGs of the BRI participating countries. Our findings indicate that China’s financial development has significantly promoted the SDGs of the BRI participating countries. This study further reveals that the scale and efficiency of China’s financial development have had a more pronounced impact on the SDGs of Asian countries, low- and middle-income countries, and the Land Silk Road participating countries, compared to those of European countries, high-income countries, and the Maritime Silk Road participating countries, respectively. In contrast, the structure of financial development primarily promotes the SDGs of European and high-income BRI participating countries in the land silk belt. The role of China’s financial development in promoting the SDGs of most BRI participating countries has gradually increased over time. This study provides valuable insights for decision-makers in China to facilitate the sustainable development of BRI participating countries and foster a shared community within the BRI framework.

Background:The COBLL1 gene has been implicated in human central obesity, fasting insulin levels, type 2 diabetes, and blood lipid profiles. However, its molecular mechanisms remain largely unexplored.Methods:In this study, we established cobll1a mutant lines using the CRISPR/Cas9-mediated gene knockout technique. To further dissect the molecular underpinnings of cobll1a during early development, transcriptome sequencing and bioinformatics analysis was employed.Results:Our study showed that compared to the control, cobll1a−/− zebrafish embryos exhibited impaired development of digestive organs, including the liver, intestine, and pancreas, at 4 days post-fertilization (dpf). Transcriptome sequencing and bioinformatics analysis results showed that in cobll1a knockout group, the expression level of genes in the Retinoic Acid (RA) signaling pathway was affected, and the expression level of lipid metabolism-related genes (fasn, scd, elovl2, elovl6, dgat1a, srebf1 and srebf2) were significantly changed (p < 0.01), leading to increased lipid synthesis and decreased lipid catabolism. The expression level of apolipoprotein genes (apoa1a, apoa1b, apoa2, apoa4a, apoa4b, and apoea) genes were downregulated.Conclusion:Our study suggest that the loss of cobll1a resulted in disrupted RA metabolism, reduced lipoprotein expression, and abnormal lipid transport, therefore contributing to lipid accumulation and deleterious effects on early liver development.

Abstract Background and Objectives Acute COVID-19 infection has been associated with neurological involvement. We report a case series of newly diagnosed patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) developed in a short period of time after acute COVID-19 infection. Methods New MS patients developing initial symptoms shortly after an acute COVID-19 infection were diagnosed based on the 2017 McDonald Criteria [Garcia-Ramos et al. in Cells, 2021]. The patients diagnosed with NMOSD met the 2015 International Panel criteria for the diagnosis of NMOSD (IPDN) [Thompson et al. in Lancet Neurol 17:162–173, 2018]. Results From the MS Patient Group Ten patients were included who had developed initial MS symptoms after COVID-19 infection. Gender distribution was equal (50% male). The mean age was 28 (range 17–39) years. Average time to neurological presentation was between 2 and 6 weeks following acute COVID-19 infection. Partial transverse myelitis was the initial presentation in 40% of the cases, and 60% of patients had spinal cord lesions present at the moment of diagnosis. All patients showed enhancing lesions on brain magnetic resonance imaging (MRI). The presence of cerebrospinal fluid (CSF) oligoclonal bands was found in all six tested cases. The majority of patients (80%) were unvaccinated for COVID-19. The two vaccinated patients had received two doses of the monovalent COVID-19 messenger ribonucleic acid (mRNA) (Pfizer Biotech) vaccine and no booster, a year prior to contracting COVID-19. Results From the NMOSD Group Two patients with NMOSD were included. Positive aquoporin-4 protein antibody (AQP-4 Ab) was detected in serum in both cases [one Enzyme Linked immunosorbent assay (ELISA) and one cell based]. Both patients had mild COVID-19 infection prior to presentation, initial neurologic symptoms presented between 3 and 6 weeks after COVID-19 infection. Neither patients were vaccinated. Both responded partially to steroids, one developed a relapse 40 days after diagnosis. Conclusion COVID-19 infection has been linked to several neurological and immune-driven conditions. This study suggests that in susceptible individuals, acute COVID-19 infection may act as a trigger for developing MS and NMOSD.

Summary: Transcriptional regulation of secondary cell wall (SCW) formation is strictly controlled by a complex network of transcription factors in vascular plants and has been shown to be mediated by a group of NAC master switches. In this study, we show that in a bHLH transcription factor, OsbHLH002/OsICE1, its loss-of-function mutant displays a lodging phenotype. Further results show that OsbHLH002 and Oryza sativa homeobox1 (OSH1) interact and share a set of common targets. In addition, the DELLA protein SLENDER RICE1, rice ortholog of KNOTTED ARABIDOPSIS THALIANA7, and OsNAC31 interact with OsbHLH002 and OSH1 and regulate their binding capacity on OsMYB61, a key regulatory factor in SCW development. Collectively, our results indicate OsbHLH002 and OSH1 as key regulators in SCW formation and shed light on molecular mechanisms of how active and repressive factors precisely orchestrate SCW synthesis in rice, which may provide a strategy for manipulating plant biomass production.

Fermented coffee beans are believed to have significantly different compositions of phenolic and volatile compounds and physicochemical properties compared to unfermented coffee beans. This study evaluated the effects of fermentation on coffee beans at a commercially roasted level by characterizing their phenolic compounds and semi-quantifying their volatile compounds using liquid chromatography–electrospray ionization quadrupole time-of-flight mass spectrometry (LC-ESI-QTOF-MS/MS) and headspace/gas chromatography–mass spectrometry (HS-SPME-GC-MS). Coffee beans from two varieties of Coffea arabica, Geisha (G) and Bourbon (B), both fermented beans had higher contents of total phenolic compounds (G: 33.52 mg/g; B: 29.95 mg/g), total flavonoid (G: 0.42 mg/g; B: 0.35 mg/g), total tannins (G: 3.49 mg/g; B: 3.18 mg/g), and higher antioxidant potential in all assays. In total, 131 phenolic compounds were tentatively characterized via LC-ESI-QTOF-MS/MS, where 73 and 65 phenolic compounds were characterized from fermented Geisha and Bourbon, respectively. Regarding GC-MS, the fermented coffee beans had higher levels of phenols, pyrazines, furan, and furanic compounds. These findings substantiated that fermented coffee beans exhibit elevated levels of phenolic and volatile compounds and greater antioxidant activity, which could contribute to relatively higher nutritional values and organoleptic properties.

Jobshop scheduling is a classic instance in the field of production scheduling. Solving and optimizing the scheduling problem of the jobshop can greatly reduce the production cost of the workshop and improve the processing efficiency, thereby improving the market competitiveness of the manufacturing enterprises. In order to make decisions on the complex dynamic scheduling process more accurately and simplify the solution process, the jobshop scheduling problem can be transformed into a reinforcement learning problem based on the Markov decision process. The performance of the adaptive scheduling algorithm in a dynamic manufacturing environment is improved based on the Deep Q Network (DQN). In the proposed scheduling algorithm, five state features of continuous value ranges are designed for input to a Deep Neural Network (DNN), as well as ten well-known heuristic dispatching rules are selected as the action set of the DQN. In the proposed scheduling algorithm, the target network and the prediction network are used to train the parameters. An action selection strategy based on the “softmax” function is designed in DQN. It selects dispatching rules with the largest action value as the execution action, thereby solving the problem that the suboptimal action value is greater than the optimal action Q value in the early learning stage. Furthermore, the non-optimal action is selected with a greater probability in the later learning stage. Ten benchmark jobshop test instances called “LA” used as simulation objects and operated in a simulation environment composed of Python. The simulation results confirm that the proposed scheduling algorithm based on DQN has better performance and universality than a single dispatching rule or traditional Q learning algorithm.

Reasonable automatic guided vehicle path planning can shorten the transportation time of materials and improve the production efficiency of the intelligent assembly workshop. Ant colony algorithm is a widely used path planning method, however, it suffers from the shortcomings that being easy to fall into local optimum and low search efficiency. To overcome these shortcomings, first, this paper proposes a step optimization method to improve the search efficiency of the ant colony algorithm, and a path simplification method to avoid getting blindly tortuous paths; Second, to overcome the problem that the ant colony algorithm is easy to fall into the local optimum, this paper proposes an adaptive pheromone volatilization coefficient strategy, which uses different pheromone volatilization coefficients at different stages of the search path; third, for the path conflict problem of multiple automatic guided vehicles, this paper proposes a load balancing strategy to avoid it, which is based on the consideration that, path conflicts are caused by excessive concentration of multiple automatic guided vehicles paths. Extensive simulation results demonstrate the feasibility and efficiency of the proposed methods.

Mutations in the Betaine aldehyde dehydrogenase 2 (OsBadh2) gene resulted in aroma, which is a highly preferred grain quality attribute in rice. However, research on naturally occurring aromatic rice has revealed ambiguity and controversy regarding aroma emission, stress tolerance, and response to salinity. In this study, mutant lines of two non-aromatic varieties, Huaidao#5 (WT_HD) and Jiahua#1 (WT_JH), were generated by targeted mutagenesis of OsBadh2 using CRISPR/Cas9 technology. The mutant lines of both varieties became aromatic; however, WT_HD mutants exhibited an improved tolerance, while those of WT_JH showed a reduced tolerance to salt stress. To gain insight into the molecular mechanism leading to the opposite effects, comparative analyses of the physiological activities and expressions of aroma- and salinity-related genes were investigated. The WT_HD mutants had a lower mean increment rate of malondialdehyde, superoxide dismutase, glutamate, and proline content, with a higher mean increment rate of γ-aminobutyric acid, hydrogen peroxide, and catalase than the WT_JH mutants. Fluctuations were also detected in the salinity-related gene expression. Thus, the response mechanism of OsBadh2 mutants is complicated where the genetic makeup of the rice variety and interactions of several genes are involved, which requires more in-depth research to explore the possibility of producing highly tolerant aromatic rice genotypes.

Stigma exsertion in male sterile lines of hybrid rice is important for seed yield. In the present study, ZS616 [Oryza sativa subsp. Xian (indica)], a male sterile line with a stigma exsertion rate (SER) as high as 94.5%, was crossed to DS552, a japonica line with almost no exserted stigmas. F3 plants with extremely low and high SER were sequenced to identify SER-associated quantitative trait loci (QTL). A major QTL for SER, qSER-3.1, was identified along with other QTL on chromosome 3 in a 3.9 Mb region. A total of 307 nonsynonymous single-nucleotide polymorphisms (SNPs) and 27 frame-shift insertion/deletions (InDels) differentiating ZS616 and DS552 were identified in the region containing qSER-3.1. Most SNPs (294) and InDels (25) were excluded after further analysis because they were shared by ZS616 and low (

The aim of this study was to summarize the research status and reveal the impact of mobile phone use on gait characteristics by reviewing the existing studies in terms of research status, participants, independent variables, dependent variables, main findings, etc. Twenty-nine studies which investigated the impact of using mobile phones on gait characteristics were identified through a literature search. The majority of these studies examined the effects of mobile phone use on gait characteristics in young people. The preliminary results showed that walking while using a mobile phone has significant impacts on gait. It can decrease gait velocity, cadence, step length and stride length, along with significantly increasing step width, step time and double support time. The results varied among different mobile phone usage, which resulted from the different motor and mental demands. Additionally, age and environment could affect the results as well. As well as the kinematic characteristics, we suggest that kinetic and EMG analysis are conducted in future studies.

In the present study, visual attention processes in complex, sport-related decision-making tasks were examined. Psychophysiological and performance data recorded from 15 advanced table tennis athletes and 15 intermediate level undergraduates were compared. A total of 240 three-dimensional pictures of stimuli composed of a white ball and hitting location (black shade point) were presented via a screen, in which 25% represented side-backspin serves, and the other 75% represented non-side-topspin serves. Participants were instructed to report the types of serves. The results indicated that table tennis athletes responded more quickly and accurately. C1 and P1components were induced in the occipital region, N1 in the central region, and P3 in all regions. For table tennis athletes, in the phase of early sensory processing for stimuli features (such as hitting location), the cerebral cortex was activated at a higher level in comparison with undergraduates. This may be caused by the long-term exercise training. Athletes have to be very sensitive to the physical features of relevant movement stimuli. In the phase of recognizing stimuli structures or patterns, advanced athletes’ cerebral cortexes were activated higher and faster. This may help them more effectively match visual information about serves to patterns stored in long-term memory.

Starch is the main food source for human beings and livestock all over the world, and it is also the raw material for production of industrial alcohol and biofuel. A considerable part of the world’s annual starch production comes from crops and their seeds. With the increasing demand for starch from food and non-food industries and the growing loss of arable land due to urbanization, understanding starch biosynthesis and its regulators is essential to produce the desirable traits as well as more and better polymers via biotechnological approaches in cereal crops. Because of the complexity and flexibility of carbon allocation in the formation of endosperm starch, cereal crops require a broad range of enzymes and one matching network of regulators to control the providential functioning of these starch biosynthetic enzymes. Here, we comprehensively summarize the current knowledge about regulatory factors of starch biosynthesis in cereal crops, with an emphasis on the transcription factors that directly regulate starch biosynthesis. This review will provide new insights for the manipulation of bioengineering and starch biosynthesis to improve starch yields or qualities in our diets and in industry.

The xantha trait of a yellow leaf rice mutant (HYB), controlled epigenetically by elevated CHG methylation of the genomes uncoupled 4 (OsGUN4) promoter, has reduced chlorophyll content, altered tetrapyrrole biosynthesis, and deregulated transcription of photosynthesis-associated nuclear genes (PhANGs) compared to its wild-type progenitor Longtefu B (LTB). In the present study, we identified a suppressor mutant (CYB) of HYB and characterized its genetic, molecular, and physiological basis of the mutant phenotype. We found that the light-green phenotype of CYB was caused by a suppressor mutation in an unknown gene other than OsGUN4. Compared to HYB, the CHG methylation in the OsGUN4 promoter was reduced, while OsGUN4 transcript and protein abundance levels were increased in CYB. The contents of total chlorophyll and its intermediate metabolites (except protoporphyrin IX) in CYB plants were intermediate between HYB and LTB. The expression levels of 30 genes involved in tetrapyrrole biosynthesis in CYB were all partially reverted to those of LTB, so were the PhANGs. In summary, a suppressor mutation caused the reversion of the xantha trait via reducing CHG methylation in OsGUN4 promoter.

OsIPK1 encodes inositol 1,3,4,5,6-pentakisphosphate 2-kinase, which catalyzes the conversion of myo-inositol-1,3,4,5,6-pentakisphosphate to myo-inositol-1,2,3,4,5,6-hexakisphosphate (IP6) in rice. By clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas9)-mediated mutagenesis in the 3rd exon of the gene, three OsIPK1 mutations, i.e., osipk1_1 (a 33-nt deletion), osipk1_2 (a 1-nt deletion), and osipk1_3 (a 2-nt deletion) were identified in T0 plants of the rice line Xidao #1 (wild type, WT). A transfer DNA free line with the homozygous osipk1_1 mutation was developed; however, no homozygous mutant lines could be developed for the other two mutations. The comparative assay showed that the osipk1_1 mutant line had a significantly lower level of phytic acid (PA, IP6; −19.5%) in rice grain and agronomic traits comparable to the WT. However, the osipk1_1 mutant was more tolerant to salt and drought stresses than the WT, with significantly lower levels of inositol triphosphate (IP3), reactive oxygen species (ROS) and induced IP6, and higher activities of antioxidant enzymes in seedlings subjected to these stresses. Further analyses showed that the transcription of stress response genes was significantly upregulated in the osipk1_1 mutant under stress. Thus, the low phytic acid mutant osipk1_1 should have potential applications in rice breeding and production.

This paper investigates the path following control problem of an unmanned surface vessel (USV) subject to input saturation and uncertainties including model parameters uncertainties and unknown time-varying external disturbances. A nonlinear robust adaptive control scheme is proposed to address the issue, more specifically, steering a USV to follow the desired path at a certain velocity assignment despite the involved disturbances, by utilizing the finite-time currents observer based line-of-sight (LOS) guidance and radial basis function neural networks (RBFNN). Backstepping and Lyapunov’s direct method are the main design frameworks. Based on the finite-time currents observer and adaptive control technique, an improved LOS guidance law is proposed to obtain the desired approaching angle to the desired path, making compensations for the effects of unknown time-varying ocean currents. Then, a kinetic controller with the capability of uncertainties estimation and disturbances rejection is proposed based on the RBFNNs, where the adaptive laws including leakage terms estimate the approximation error and the unknown time-varying disturbances. Subsequently, sophisticated auxiliary control systems are employed to handle input saturation constraints of actuators. All error signals of the closed-loop system are proved to be locally uniformly ultimately bounded (UUB). Numerical simulations demonstrated the effectiveness and robustness of the proposed path following control method.

Inositol 1,3,4-trisphosphate 5/6-kinase (ITPK) is encoded by six genes in rice (OsITPK1-6). A previous study had shown that nucleotide substitutions of OsITPK6 could significantly lower the phytic acid content in rice grains. In the present study, the possibility of establishing a genome editing-based method for breeding low-phytic acid cultivars in rice was explored, in conjunction with the functional determination of OsITPK6. Four OsITPK6 mutant lines were generated by targeted mutagenesis of the gene’s first exon using the CRISPR/Cas9 method, one (ositpk6_1) with a 6-bp in-frame deletion, and other three with frameshift mutations (ositpk6_2, _3, and _4). The frameshift mutations severely impaired plant growth and reproduction, while the effect of ositpk6_1 was relatively limited. The mutant lines ositpk6_1 and _2 had significantly lower levels (−10.1% and −32.1%) of phytic acid and higher levels (4.12- and 5.18-fold) of inorganic phosphorus compared with the wild-type (WT) line. The line ositpk6_1 also showed less tolerance to osmotic stresses. Our research demonstrates that mutations of OsITPK6, while effectively reducing phytic acid biosynthesis in rice grain, could significantly impair plant growth and reproduction.

H9N2 influenza viruses have been circulating worldwide in multiple avian species and have repeatedly infected humans to cause typical disease. The continued avian-to-human interspecies transmission of H9N2 viruses raises concerns about the possibility of viral adaption with increased virulence for humans. To investigate the genetic basis of H9N2 influenza virus host range and pathogenicity in mammals, we generated a mouse-adapted H9N2 virus (SD16-MA) that possessed significantly higher virulence than wide-type virus (SD16). Increased virulence was detectable after 8 sequential lung passages in mice. Five amino acid substitutions were found in the genome of SD16-MA compared with SD16 virus: PB2 (M147L, V250G and E627K), HA (L226Q) and M1 (R210K). Assessments of replication in mice showed that all of the SD16-MA PB2, HA and M1 genome segments increased virus replication; however, only the mouse-adapted PB2 significantly increased virulence. Although the PB2 E627K amino acid substitution enhanced viral polymerase activity and replication, none of the single mutations of mouse adapted PB2 could confer increased virulence on the SD16 backbone. The combination of M147L and E627K significantly enhanced viral replication ability and virulence in mice. Thus, our results show that the combination of PB2 amino acids at position 147 and 627 is critical for the increased pathogenicity of H9N2 influenza virus in mammalian host.

BACKGROUND: The influenza viruses circulating in animals sporadically transmit to humans and pose pandemic threats. Animal models to evaluate the potential public health risk potential of these viruses are needed. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the guinea pig as a mammalian model for the study of the replication and transmission characteristics of selected swine H1N1, H1N2, H3N2 and avian H9N2 influenza viruses, compared to those of pandemic (H1N1) 2009 and seasonal human H1N1, H3N2 influenza viruses. The swine and avian influenza viruses investigated were restricted to the respiratory system of guinea pigs and shed at high titers in nasal tracts without prior adaptation, similar to human strains. None of the swine and avian influenza viruses showed transmissibility among guinea pigs; in contrast, pandemic (H1N1) 2009 virus transmitted from infected guinea pigs to all animals and seasonal human influenza viruses could also horizontally transmit in guinea pigs. The analysis of the receptor distribution in the guinea pig respiratory tissues by lectin histochemistry indicated that both SAα2,3-Gal and SAα2,6-Gal receptors widely presented in the nasal tract and the trachea, while SAα2,3-Gal receptor was the main receptor in the lung. CONCLUSIONS/SIGNIFICANCE: We propose that the guinea pig could serve as a useful mammalian model to evaluate the potential public health threat of swine and avian influenza viruses.

Abstract The purpose of this study is to investigate the relationship between chronic pain and the mortality rate of cerebrovascular disease (CVD) in cancer patients. Thus, we performed a case-control investigation was conducted by utilizing data from the Surveillance, Epidemiology, and End Results (SEER) database between 1975 and 2019. Multiple demographics, pain rating and other clinical characteristics were extracted to assess predictors for the death from CVD in cancer patients. Different machine learning algorithms were applied to construct pain-related prediction model. The analysis involved 16,850 case patients and 710,729 controls. Among cancer patients, approximately 2.3% succumbed to subsequent CVD. Cancer pain (Pain rating II) was associated with a decreased risk of CVD. Univariate and multivariate COX analyses indicated that older age at cancer diagnosis, male gender, single marital status, Black or Other race, and lack of systemic therapy correlated with a higher risk of CVD-related death. Propensity score matching revealed a significantly lower proportion of Pain rating II in the case group. The logistic regression algorithm demonstrated superior predictive ability for 5-year and 10-year CVD risk in cancer patients. Notably, survival time, age, and pain rating emerged as the top three crucial variables. This study firstly investigated pain and various risk factors for CVD in cancer patients, highlighting pain as a novel and possible protective factor for CVD. The development of a risk model based on pain could aid in identifying individuals at high risk for CVD and may inspire innovative strategies for preventing CVD in cancer patients.