Production of biliverdin by biotransformation of exogenous heme using recombinant Pichia pastoris cells.

Biliverdin, a bile pigment hydrolyzed from heme by heme oxygenase (HO), serves multiple functions in the human body, including antioxidant, anti-inflammatory, and immune response inhibitory activities. Biliverdin has great potential as a clinical drug; however, no economic and efficient production method is available currently. Therefore, the production of biliverdin by the biotransformation of exogenous heme using recombinant HO-expressing yeast cells was studied in this research. First, the heme oxygenase-1 gene (HO1) encoding the inducible plastidic isozyme from Arabidopsis thaliana, with the plastid transport peptide sequence removed, was recombined into Pichia pastoris GS115 cells. This resulted in the construction of a recombinant P. pastoris GS115-HO1 strain that expressed active HO1 in the cytoplasm. After that, the concentration of the inducer methanol, the induction culture time, the pH of the medium, and the concentration of sorbitol supplied in the medium were optimized, resulting in a significant improvement in the yield of HO1. Subsequently, the whole cells of GS115-HO1 were employed as catalysts to convert heme chloride (hemin) into biliverdin. The results showed that the yield of biliverdin was 132 mg/L when hemin was added to the culture of GS115-HO1 and incubated for 4 h at 30 °C. The findings of this study have laid a good foundation for future applications of this method for the economical production of biliverdin.

Heritable microbiome variation is correlated with source environment in locally adapted maize varieties.

Beneficial interactions with microorganisms are pivotal for crop performance and resilience. However, it remains unclear how heritable the microbiome is with respect to the host plant genotype and to what extent host genetic mechanisms can modulate plant-microbiota interactions in the face of environmental stresses. Here we surveyed 3,168 root and rhizosphere microbiome samples from 129 accessions of locally adapted Zea, sourced from diverse habitats and grown under control and different stress conditions. We quantified stress treatment and host genotype effects on the microbiome. Plant genotype and source environment were predictive of microbiome abundance. Genome-wide association analysis identified host genetic variants linked to both rhizosphere microbiome abundance and source environment. We identified transposon insertions in a candidate gene linked to both the abundance of a keystone bacterium Massilia in our controlled experiments and total soil nitrogen in the source environment. Isolation and controlled inoculation of Massilia alone can contribute to root development, whole-plant biomass production and adaptation to low nitrogen availability. We conclude that locally adapted maize varieties exert patterns of genetic control on their root and rhizosphere microbiomes that follow variation in their home environments, consistent with a role in tolerance to prevailing stress.

Mortality in patients admitted to hospital with heart failure in China: a nationwide Cardiovascular Association Database-Heart Failure Centre Registry cohort study.

BACKGROUND: China has the largest burden of heart failure worldwide. However, large-scale studies on heart failure mortality are scarce. We aimed to investigate mortality and identify risk factors for mortality among patients with heart failure in China. METHODS: This prospective cohort study used data from the China Cardiovascular Association (CCA) Database-Heart Failure Centre Registry, which were linked to the National Mortality Registration Information Management System by the Chinese Centre for Disease Control and Prevention. We included patients enrolled from Jan 1, 2017, to Dec 31, 2021, across 572 CCA Database-Heart Failure Centre certified hospitals in 31 provinces of mainland China. Eligible patients were aged 18 years or older (younger than 100 years) with a principal discharge diagnosis of heart failure based on Chinese heart failure guidelines. All-cause mortality at 30 days, 1 year, and 3 years for patients with heart failure were calculated and the causes of death were recorded. Multivariable analysis was used to analyse factors associated with all-cause mortality and cardiovascular mortality. This study was registered with the Chinese Clinical Trial Registry, ChiCTR2200066305. FINDINGS: Of the 327 477 patients in the registry, 230 637 eligible adults with heart failure were included in our analyses. Participant mean age was 69·3 years (SD 13·2), 94 693 (41·1%) participants were female, and 135 944 (58·9%) were male. The median follow-up time was 531 days (IQR 251-883). Post-discharge all-cause mortality of patients with heart failure at 30 days was 2·4% (95% CI 2·3-2·5), at 1 year was 13·7% (13·5-13·9), and at 3 years was 28·2% (27·7-28·6). Cardiovascular death accounted for 32 906 (71·5%) of 46 006 all-cause deaths. Patients with heart failure with reduced ejection fraction had the highest all-cause mortality. A lower guideline adherence score was independently associated with the increase of all-cause and cardiovascular mortality. INTERPRETATION: In China, mortality for patients with heart failure is still high, especially in patients with reduced ejection fraction. Our findings suggest that guideline-directed medical therapy needs to be improved. FUNDING: National High Level Hospital Clinical Research Funding, the Capital's Funds for Health Improvement and Research, and the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Oral vitamin D supplementation on the prevention of peritoneal dialysis-related peritonitis: A pilot randomised controlled trial.

OBJECTIVE: Peritoneal dialysis (PD)-related peritonitis is independently associated with low serum 25-hydroxy vitamin D [25(OH)D] levels. Our objective is to examine the feasibility of conducting a large, randomised controlled trial to determine the effects of vitamin D supplementation on the risk of PD-related peritonitis. DESIGN: Pilot, prospective, open-label randomised controlled trial. SETTING: Peking University First Hospital, China. PARTICIPANTS: Patients receiving PD who had recovered from a recent episode of peritonitis between 30 September 2017 and 28 May 2020. INTERVENTIONS: Oral natural vitamin D supplementation (2000 IU per day) versus no vitamin D supplementation for 12 months. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcomes were feasibility (recruitment success, retention, adherence, safety) and fidelity (change in serum 25(OH)D level during follow-up) for a large, randomised controlled trial in the future to determine the effects of vitamin D on PD-related peritonitis. Secondary outcomes were time to peritonitis occurrence and outcome of subsequent peritonitis. RESULTS: Overall, 60 among 151 patients were recruited (recruitment rate was 39.7%, 95% CI 31.9-47.5%, recruitment rate among eligible patients was 61.9%, 95% CI 52.2-71.5%). Retention and adherence rates were 100.0% (95% CI 100.0-100.0%) and 81.5% (95% CI 66.8-96.1%), respectively. During follow-up, serum 25(OH)D levels increased in the vitamin D (VD) group (from 19.25 ± 10.11 nmol/L to 60.27 ± 23.29 nmol/L after 6 months, p < 0.001, n = 31), and remained higher (p < 0.001) than those in the control group (n = 29). No differences were observed between the two groups with respect to time to subsequent peritonitis (hazard ratio 0.85, 95% CI 0.33-2.17) or any of the peritonitis outcomes. Adverse events were uncommon. CONCLUSIONS: A randomised controlled trial of the effect of vitamin D supplementation on peritonitis occurrence in patients receiving PD is feasible, safe and results in adequate serum 25(OH)D levels.

Cut-off values of haemoglobin and clinical outcomes in incident peritoneal dialysis: the PDTAP study.

BACKGROUND: To explore the cut-off values of haemoglobin (Hb) on adverse clinical outcomes in incident peritoneal dialysis (PD) patients based on a national-level database. METHODS: The observational cohort study was from the Peritoneal Dialysis Telemedicine-assisted Platform (PDTAP) dataset. The primary outcomes were all-cause mortality, major adverse cardiovascular events (MACE) and modified MACE (MACE+). The secondary outcomes were the occurrences of hospitalization, first-episode peritonitis and permanent transfer to haemodialysis (HD). RESULTS: A total of 2591 PD patients were enrolled between June 2016 and April 2019 and followed up until December 2020. Baseline and time-averaged Hb <100 g/l were associated with all-cause mortality, MACE, MACE+ and hospitalizations. After multivariable adjustments, only time-averaged Hb <100 g/l significantly predicted a higher risk for all-cause mortality {hazard ratio [HR] 1.83 [95% confidence interval (CI) 1.19-281], P = .006}, MACE [HR 1.99 (95% CI 1.16-3.40), P = .012] and MACE+ [HR 1.77 (95% CI 1.15-2.73), P = .010] in the total cohort. No associations between Hb and hospitalizations, transfer to HD and first-episode peritonitis were observed. Among patients with Hb ≥100 g/l at baseline, younger age, female, use of iron supplementation, lower values of serum albumin and renal Kt/V independently predicted the incidence of Hb <100 g/l during the follow-up. CONCLUSION: This study provided real-world evidence on the cut-off value of Hb for predicting poorer outcomes through a nation-level prospective PD cohort.

Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize.

Root-associated microbiomes in the rhizosphere (rhizobiomes) are increasingly known to play an important role in nutrient acquisition, stress tolerance, and disease resistance of plants. However, it remains largely unclear to what extent these rhizobiomes contribute to trait variation for different genotypes and if their inclusion in the genomic selection protocol can enhance prediction accuracy. To address these questions, we developed a microbiome-enabled genomic selection method that incorporated host SNPs and amplicon sequence variants from plant rhizobiomes in a maize diversity panel under high and low nitrogen (N) field conditions. Our cross-validation results showed that the microbiome-enabled genomic selection model significantly outperformed the conventional genomic selection model for nearly all time-series traits related to plant growth and N responses, with an average relative improvement of 3.7%. The improvement was more pronounced under low N conditions (8.4-40.2% of relative improvement), consistent with the view that some beneficial microbes can enhance N nutrient uptake, particularly in low N fields. However, our study could not definitively rule out the possibility that the observed improvement is partially due to the amplicon sequence variants being influenced by microenvironments. Using a high-dimensional mediation analysis method, our study has also identified microbial mediators that establish a link between plant genotype and phenotype. Some of the detected mediator microbes were previously reported to promote plant growth. The enhanced prediction accuracy of the microbiome-enabled genomic selection models, demonstrated in a single environment, serves as a proof-of-concept for the potential application of microbiome-enabled plant breeding for sustainable agriculture.

Identification of mitophagy-related genes with potential clinical utility in myocardial infarction at transcriptional level.

Background: Myocardial infarction (MI) ranks among the most prevalent cardiovascular diseases. Insufficient blood flow to the coronary arteries always leads to ischemic necrosis of the cardiac muscle. However, the mechanism of myocardial injury after MI remains unclear. This article aims to explore the potential common genes between mitophagy and MI and to construct a suitable prediction model. Methods: Two Gene Expression Omnibus (GEO) datasets (GSE62646 and GSE59867) were used to screen the differential expression genes in peripheral blood. SVM, RF, and LASSO algorithm were employed to find MI and mitophagy-related genes. Moreover, DT, KNN, RF, SVM and LR were conducted to build the binary models, and screened the best model to further external validation (GSE61144) and internal validation (10-fold cross validation and Bootstrap), respectively. The performance of various machine learning models was compared. In addition, immune cell infiltration correlation analysis was conducted with MCP-Counter and CIBERSORT. Results: We finally identified ATG5, TOMM20, MFN2 transcriptionally differed between MI and stable coronary artery diseases. Both internal and external validation supported that these three genes could accurately predict MI withAUC = 0.914 and 0.930 by logistic regression, respectively. Additionally, functional analysis suggested that monocytes and neutrophils might be involved in mitochondrial autophagy after myocardial infarction. Conclusion: The data showed that the transcritional levels of ATG5, TOMM20 and MFN2 in patients with MI were significantly different from the control group, which might be helpful to further accurately diagnose diseases and have potential application value in clinical practice.

Point-of-care ultrasound diagnosis of skull fracture in Chinese children 0-6 years old with scalp hematoma from minor head trauma: A preliminary prospective observational study.

Background: Previous studies have suggested that point-of-care ultrasound could help to evaluate and diagnose pediatric skull fracture for the closed scalp hematoma from blunt trauma. However, relevant data in Chinese children are missing, especially in children 0-6 years old. Objectives: Our study aimed to evaluate the efficacy of point-of-care ultrasound to diagnose skull fracture in children 0-6 years old with scalp hematoma in China. Methods: We performed a prospective observational study and screened children 0-6 years old with closed scalp hematoma and a Glasgow coma scale of 14-15 at Hospital in China. Enrolled children (N = 152) were first evaluated for skull fracture with point-of-care ultrasound by the emergency physician and then received a head computed tomography scan. Results: The point-of-care ultrasound examination and computed tomography scan revealed skull fracture in 13 (8.6%) and 12 (7.9%) children, respectively. The kappa test showed a satisfactory agreement between two examinations (P < 0.0001), with kappa = 0.87 (95% confidence interval, i.e., 95% CI, [0.69, 1.00]) and area under the curve = 0.95 (95% CI [0.86, 1], P < 0.0001). The point-of-care ultrasound examination had the sensitivity of 91.7% (95% CI [62.5%, 100%]), specificity of 98.6% (95% CI [94.6%, 100%]), positive predictive value of 84.6% (95% CI [56.5%, 96.9%]), negative predictive value of 99.2% (95% CI [95.6%, 100%]), and accuracy of 98.0% (95% CI [94.1%, 99.6%]). Conclusions: While our study is preliminary in nature, our findings may guide future larger studies in assessing the utility of point-of-care ultrasound examination in diagnosing skull fractures in children with scalp hematoma from minor head trauma.

Integrating the flow regime and water quality effects into a niche-based metacommunity dynamics model for river ecosystems.

Aquatic community dynamics are closely dominated by flow regime and water quality conditions, which are increasingly threatened by dam regulation, water diversion, and nutrition pollution. However, further understanding of the ecological impacts of flow regime and water quality conditions on aquatic multi-population dynamics has rarely been integrated into existing ecological models. To address this issue, a new niche-based metacommunity dynamics model (MDM) is proposed. The MDM aims to simulate the coevolution processes of multiple populations under changing abiotic environments, pioneeringly applied to the mid-lower Han River, China. The quantile regression method was used for the first time to derive ecological niches and competition coefficients of the MDM, which are demonstrated to be reasonable by comparing them with the empirical evidence. Simulation results show that the Nash efficiency coefficients for fish, zooplankton, zoobenthos, and macrophytes are more than 0.64, while the Pearson correlation coefficients for them are no less than 0.71. Overall, the MDM performs effectively in simulating metacommunity dynamics. For all river stations, the average contributions of biological interaction, flow regime effects, and water quality effects to multi-population dynamics are 64%, 21%, and 15%, respectively, suggesting that the population dynamics are dominated by biological interaction. For upstream stations, the fish population is 8%-22% more responsive to flow regime alteration than other populations, while other populations are 9%-26% more responsive to changes in water quality conditions than fish. For downstream stations, flow regime effects on each population account for less than 1% due to more stable hydrological conditions. The innovative contribution of this study lies in proposing a multi-population model to quantify the effects of flow regime and water quality on aquatic community dynamics by incorporating multiple indicators of water quantity, water quality, and biomass. This work has potential for the ecological restoration of rivers at the ecosystem level. This study also highlights the importance of considering threshold and tipping point issues when analyzing the "water quantity-water quality-aquatic ecology" nexus in future works.

Cardiac arrest as initial presentation of pheochromocytoma in a young.

We reported a case of pheochromocytoma with initial presentation of cardiac arrest. The patient underwent implantable cardioverter defibrillator for primary prevention but subsequently experienced repeated implantable cardioverter defibrillator shocks and syncopal episodes. A mass was found in the adrenal gland by CT, which was confirmed by anatomopathological analysis of the surgical specimen.

HomeMonitor: An Enhanced Device Event Detection Method for Smart Home Environment.

As more and more smart devices are deployed in homes, the communication between these smart home devices and elastic computing services may face some risks of privacy disclosure. Different device events (such as the camera on, video on, etc.) will generate different data traffic during communication. However, the current smart home system lacks monitoring of these device events, which may cause the disclosure of private data collected by these devices. In this paper, we present our device event monitor system, HomeMonitor. HomeMonitor runs in the OpenWRT system and supports complete event monitoring for smart home devices. HomeMoitor solves the problem that machine learning models for detecting device events do not scale flexibly. It uses the network packet size and the direction of the device event for unique identification during training. When detecting, it only needs to get the packet size and timestamp and then query the policy table for signature matching to control the device events. We evaluated the effectiveness of HomeMonitor, and the experiments show that the match rate of our method is 98.8%, the false positive rate is 1.8%, and the detection time is only 16.67% for PINBALL. The results mean that our method achieves the balance of applicable protocol scope, detection performance, and detection accuracy.

Estimation of Left Ventricular Ejection Fraction Using Cardiovascular Hemodynamic Parameters and Pulse Morphological Characteristics with Machine Learning Algorithms.

It is estimated that 360,000 patients have suffered from heart failure (HF) in Taiwan, mostly those over the age of 65 years, who need long-term medication and daily healthcare to reduce the risk of mortality. The left ventricular ejection fraction (LVEF) is an important index to diagnose the HF. The goal of this study is to estimate the LVEF using the cardiovascular hemodynamic parameters, morphological characteristics of pulse, and bodily information with two machine learning algorithms. Twenty patients with HF who have been treated for at least six to nine months participated in this study. The self-constructing neural fuzzy inference network (SoNFIN) and XGBoost regression models were used to estimate their LVEF. A total of 193 training samples and 118 test samples were obtained. The recursive feature elimination algorithm is used to choose the optimal parameter set. The results show that the estimating root-mean-square errors (ERMS) of SoNFIN and XGBoost are 6.9 ± 2.3% and 6.4 ± 2.4%, by comparing with echocardiography as the ground truth, respectively. The benefit of this study is that the LVEF could be measured by the non-medical image method conveniently. Thus, the proposed method may arrive at an application level for clinical practice in the future.

Transcriptome analysis reveals gene expression changes of the basidiomycetous yeast Apiotrichum mycotoxinivorans in response to ochratoxin A exposure.

Ochratoxin A (OTA) is one of the most common and deleterious mycotoxins found in food and feedstuffs worldwide; however, Apiotrichum mycotoxinivorans can detoxify OTA. Our results show that A. mycotoxinivorans GUM1709 efficiently degraded OTA, but it caused the accumulation of intracellular reactive oxygen species. The main aim of this study was to identify potential OTA-detoxifying enzymes and to explore the effects of OTA on A. mycotoxinivorans GMU1709. RNA-seq data revealed that 1643 and 1980 genes were significantly upregulated and downregulated, respectively, after OTA exposure. Functional enrichment analyses indicated that OTA exposure enhanced defense capability, protein transport, endocytosis, and energy metabolism; caused ribosomal stress; suppressed DNA replication and transcription; inhibited cell growth and division; and promoted cell death. The integration of secretome, gene expression, and molecular docking analyses revealed that two carboxypeptidase homologues (members of the metallocarboxypeptidase family) were most likely responsible for the detoxification of both extracellular and intracellular OTA. Superoxide dismutase and catalase were the main genes activated in response to oxidative stress. In addition, analysis of key genes associated with cell division and apoptosis showed that OTA exposure inhibited mitosis and promoted cell death. This study revealed the possible OTA response and detoxification mechanisms in A. mycotoxinivorans.

Spine Segmentation with Multi-view GCN and Boundary Constraint.

Multi-class segmentation of vertebrae and inter-vertebral discs (IVDs) is crucial for the diagnosis and treatment of spinal diseases. However, it is still a challenge due to similarities between neighboring vertebrae of a subject and differences among the IVDs from different subjects. In this paper, we propose a novel spine segmentation framework to achieve automatic segmentation of vertebrae and IVDs in MR images. The core component of the new framework is a Multi-View GCN (MVGCN), which utilizes multi-view features and graph convolutional network (GCN) to reason about the relations of vertebrae and IVDs. We additionally use a boundary constraint for better segmentation of the boundary between vertebrae and IVDs. We test our method on a public spine dataset of 172 MR volumetric images for the vertebrae and IVDs segmentation. The experimental results demonstrate the efficacy of our method. Code and models of our method will be available in the future.

Transcriptomic responses of the zearalenone (ZEN)-detoxifying yeast Apiotrichum mycotoxinivorans to ZEN exposure.

Zearalenone (ZEN) is a potent oestrogenic mycotoxin that is mainly produced by Fusarium species and is a serious environmental pollutant in animal feeds. Apiotrichum mycotoxinivorans has been widely used as a feed additive to detoxify ZEN. However, the effects of ZEN on A. mycotoxinivorans and its detoxification mechanisms remain unclear. In this study, transcriptomic and bioinformatic analyses were used to investigate the molecular responses of A. mycotoxinivorans to ZEN exposure and the genetic basis of ZEN detoxification. We detected 1424 significantly differentially expressed genes (DEGs), of which 446 were upregulated and 978 were downregulated. Functional and enrichment analyses showed that ZEN-induced genes were significantly associated with xenobiotic metabolism, oxidative stress response, and active transport systems. However, ZEN-inhibited genes were mainly related to cell division, cell cycle, and fungal development. Subsequently, bioinformatic analysis identified candidate ZEN-detoxification enzymes. The Baeyer-Villiger monooxygenases and carboxylesterases, which are responsible for the formation and subsequent hydrolysis of a new ZEN lactone, respectively, were significantly upregulated. In addition, the expression levels of genes related to conjugation and transport involved in the xenobiotic detoxification pathway were significantly upregulated. Moreover, the expression levels of genes encoding enzymatic antioxidants and those related to growth and apoptosis were significantly upregulated and downregulated, respectively, which made it possible for A. mycotoxinivorans to survive in a highly toxic environment and efficiently detoxify ZEN. This is the first systematic report of ZEN tolerance and detoxification in A. mycotoxinivorans. We identified the metabolic enzymes that were potentially involved in detoxifying ZEN in the GMU1709 strain and found that ZEN-induced transcriptional regulation of genes is key to withstanding highly toxic environments. Hence, our results provide valuable information for developing enzymatic detoxification systems or engineering this detoxification pathway in other species.

Genome-wide mediation analysis: an empirical study to connect phenotype with genotype via intermediate transcriptomic data in maize.

Mapping genotype to phenotype is an essential topic in genetics and genomics research. As the Omics data become increasingly available, 2-variable methods have been widely applied to associate genotype with the phenotype (genome-wide association study), gene expression with the phenotype (transcriptome-wide association study), and genotype with gene expression. However, signals detected by these 2-variable association methods suffer from low mapping resolution or inexplicit causality between genotype and phenotype, making it challenging to interpret and validate the molecular mechanisms of the underlying genomic variations and the candidate genes. Under the context of genetics research, we hypothesized a causal chain from genotype to phenotype partially mediated by intermediate molecular processes, i.e. gene expression. To test this hypothesis, we applied the high-dimensional mediation analysis, a class of causal inference method with an assumed causal chain from the exposure to the mediator to the outcome, and implemented it with a maize association panel (N = 280 lines). Using 40 publicly available agronomy traits, 66 newly generated metabolite traits, and published RNA-seq data from 7 different tissues, our empirical study detected 736 unique mediating genes. Noticeably, 83/736 (11%) genes were identified in mediating more than 1 trait, suggesting the prevalence of pleiotropic mediating effects. We demonstrated that several identified mediating genes are consistent with their known functions. In addition, our results provided explicit hypotheses for functional validation and suggested that the mediation analysis is a powerful tool to integrate Omics data to connect genotype to phenotype.