The GWAS SNP rs80207740 modulates erythrocyte traits via allele-specific binding of IKZF1 and targeting XPO7 gene.

Genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with erythrocyte traits. However, the functional variants and their working mechanisms remain largely unknown. Here, we reported that the SNP of rs80207740, which was associated with red blood cell (RBC) volume and hemoglobin content across populations, conferred enhancer activity to XPO7 gene via allele-differentially binding to Ikaros family zinc finger 1 (IKZF1). We showed that the region around rs80207740 was an erythroid-specific enhancer using reporter assays, and that the G-allele further enhanced activity. 3D genome evidence showed that the enhancer interacted with the XPO7 promoter, and eQTL analysis suggested that the G-allele upregulated expression of XPO7. We further showed that the rs80207740-G allele facilitated the binding of transcription factor IKZF1 in EMSA and ChIP analyses. Knockdown of IKZF1 and GATA1 resulted in decreased expression of Xpo7 in both human and mouse erythroid cells. Finally, we constructed Xpo7 knockout mouse by CRISPR/Cas9 and observed anemic phenotype with reduced volume and hemoglobin content of RBC, consistent to the effect of rs80207740 on erythrocyte traits. Overall, our study demonstrated that rs80207740 modulated erythroid indices by regulating IKZF1 binding and Xpo7 expression.

Recent advances in the potential role of RNA N4-acetylcytidine in cancer progression.

N4-acetylcytidine (ac4C) is a highly conserved chemical modification widely found in eukaryotic and prokaryotic RNA, such as tRNA, rRNA, and mRNA. This modification is significantly associated with various human diseases, especially cancer, and its formation depends on the catalytic activity of N-acetyltransferase 10 (NAT10), the only known protein that produces ac4C. This review discusses the detection techniques and regulatory mechanisms of ac4C and summarizes ac4C correlation with tumor occurrence, development, prognosis, and drug therapy. It also comments on a new biomarker for early tumor diagnosis and prognosis prediction and a new target for tumor therapy. Video Abstract.

Research progress of N1-methyladenosine RNA modification in cancer.

N1-methyladenosine (m1A) is a post-transcriptionally modified RNA molecule that plays a pivotal role in the regulation of various biological functions and activities. Especially in cancer cell invasion, proliferation and cell cycle regulation. Over recent years, there has been a burgeoning interest in investigating the m1A modification of RNA. Most studies have focused on the regulation of m1A in cancer enrichment areas and different regions. This review provides a comprehensive overview of the methodologies employed for the detection of m1A modification. Furthermore, this review delves into the key players in m1A modification, known as the "writers," "erasers," and "readers." m1A modification is modified by the m1A methyltransferases, or writers, such as TRMT6, TRMT61A, TRMT61B, TRMT10C, NML, and, removed by the demethylases, or erasers, including FTO and ALKBH1, ALKBH3. It is recognized by m1A-binding proteins YTHDF1, TYHDF2, TYHDF3, and TYHDC1, also known as "readers". Additionally, we explore the intricate relationship between m1A modification and its regulators and their implications for the development and progression of specific types of cancer, we discuss how m1A modification can potentially facilitate the discovery of novel approaches for cancer diagnosis, treatment, and prognosis. Our summary of m1A methylated adenosine modification detection methods and regulatory mechanisms in various cancers provides useful insights for cancer diagnosis, treatment, and prognosis. Video Abstract.

Detection of wheat saccharification power and protein content using stacked models integrated with hyperspectral imaging.

BACKGROUND: Wheat is one of the key ingredients used to make Chinese liquor, and its saccharification power and protein content directly affect the quality of the liquor. In pursuit of a non-destructive assessment of wheat components and the optimization of raw material proportions in liquor, this study introduces a precise predictive model that integrates hyperspectral imaging (HSI) with stacked ensemble learning (SEL). RESULTS: This study extracted hyperspectral information from 14 different varieties of wheat and employed various algorithms for preprocessing. It was observed that multiplicative scatter correction (MSC) emerged as the most effective spectral preprocessing method. The feature wavelengths were extracted from the preprocessed spectral data using three different feature extraction methods. Then, single models (support vector machine (SVM), backpropagation neural network (BPNN), random forest (RF), and gradient boosting tree (XGBoost)) and a SEL model were developed to compare the prediction accuracies of the SEL model and the single models based on the full-band spectral data and the characteristic wavelengths. The findings indicate that the MSC-competitive adaptive reweighted sampling-SEL model demonstrated the highest prediction accuracy, with Rp 2 (test set-determined coefficient) values of 0.9308 and 0.9939 for predicting the saccharification power and protein content and root mean square error of the test set values of 0.0081 U and 0.0116 g kg-1, respectively. CONCLUSION: The predictive model established in this study, integrating HSI and SEL models, accurately detected wheat saccharification power and protein content. This validation underscores the practical potential of the SEL model and holds significant importance for non-destructive component analysis of raw materials used in liquor. © 2024 Society of Chemical Industry.

First principles study of structural and electron properties in scorodite: the bulk and surface.

Scorodite (FeAsO4·2H2O) is an ideal material for the fixation of arsenic that has attracted considerable research interest in recent decades. However, the position of the H atom in the scorodite crystal structure, water molecular configuration, surface morphology, and chemical state of the surface atoms have not been reported. In this work, density functional theory (DFT) is used to optimize the scorodite crystal structure, and the atomic bonding is analyzed. At the same time, a surface model is constructed to calculate the configuration and electronic structure of the surface atoms for different coordination groups. The results show that the tetrahedral [AsO4] and octahedral [FeO4(2H2O)] groups in the scorodite crystal structure have good stability(geometry configuration), and the covalent bond strength between the As atom and the bridged oxygen atom (Ob) is greater than that between the Ob atom and the Fe atom. The water molecules in the crystal structure do not seriously deform and ionize. The configuration of the water molecules remains stable through electrostatic interactions (Ow-Fe) and hydrogen bonding (H-Ob). The Fe atoms on the surface of scorodite can coordinate with OH and H2O, while the As atoms can only form a stable coordination with OH. When an Fe atom on the surface coordinates with two H2O atoms, the Fe atom will shrink to the inside of the bulk. With the increase in the hydroxylation number of the Fe atom, the bonding strength between the Fe atom and the Ob atom decreases. Different surface configurations do not affect the stability(geometry configuration) of the [AsO4] structure. In addition, the surface water molecular layer has a very weak effect on the surface coordination configuration. By contrast, in the surface configuration of the (W + OH) structure, the change in the surface atomic layer spacing is the smallest.

Atomic reconstruction and oxygen adsorption behavior of the pyrite (100) surface: a DFT study.

The analysis of the surface chemical behavior of pyrite is highly crucial in the fields of environmental conservation, metal extraction, and flotation separation. In this paper, the mechanism of atomic reconstruction on the pyrite surface and the adsorption behavior of O2 on a reconstructed surface are calculated by density functional theory (DFT). Different reconstruction surfaces were constructed by deleting S and Fe atoms on the (100) surface of pyrite. In addition, the geometric configuration, formation energy, binding energy, cohesion energy, and surface electronic properties of the reconstruction surface were calculated. The adsorption energies and geometric configurations of O2 on different reconstructed surfaces were also determined. The results show that under Fe-poor conditions, the charge of Fe atoms increases, and S atoms form Sn on the reconstructed surface. The binding energy between the Sn and the substrate (ideal surface) is lower, which is similar to the Sn adsorption on the substrate surface with the Fe atom as the site. Sn has high cohesive energy and is resistant to being attacked by oxidants, which leads to structural collapse, and a low affinity for O2. Under S-poor conditions, the -[Fe-S]n- plane structure formed on the reconstructed surface. The -[Fe-S]n- structure stably bonds to the substrate by an Fe-S bond, and exhibits strong binding energy. However, the -[Fe-S]n- structure has low cohesive energy and exhibits thermodynamic instability. In contrast, O2 shows a strong affinity for the -[Fe-S]n- structure, indicating that the deficiency of the S atom promotes the surface oxidation reaction. The mechanism of atomic reconstruction on the surface of pyrite is of utmost importance for understanding its surface chemical behavior.

Rapid nondestructive detecting of sorghum varieties based on hyperspectral imaging and convolutional neural network.

BACKGROUND: The purity of sorghum varieties is an important indicator of the quality of raw materials used in the distillation of liquors. Different varieties of sorghum may be mixed during the acquisition process, which will affect the flavor and quality of liquor. To facilitate the rapid identification of sorghum varieties, this study proposes a sorghum variety identification model using hyperspectral imaging (HSI) technology combined with convolutional neural network (AlexNet). RESULTS: First, the watershed algorithm, which was modified with the extended-maxim transform, was used to segment the hyperspectral images of a single sorghum grain. The isolated forest algorithm was used to eliminate abnormal spectral data from the complete spectral data. Secondly, the AlexNet model of sorghum variety identification was established based on the two-dimensional gray image data of sorghum grain in group 1. The effects of different preprocessing methods and different convolution kernel sizes on the performance of the AlexNet model were discussed. The eigenvalues of the last layer of the AlexNet model were visualized using the t-distributed random neighborhood embedding method, which is used to evaluate the separability of features extracted by the AlexNet model. The performance differences between the optimal AlexNet model and traditional machine learning models for sorghum variety identification were compared. Finally, the varieties of sorghum grains in groups 2 and 3 were identified based on the optimal AlexNet model, and the average accuracy values of the test set reached 95.62% and 95.91% respectively. CONCLUSION: The results in this study demonstrated that HSI combined with the AlexNet model could provide a feasible technical approach for the detection of sorghum varieties. © 2022 Society of Chemical Industry.

Risk factors for multidrug resistance in tuberculosis patients with diabetes mellitus.

OBJECTIVE: To study the risk factors and prediction models of multidrug resistance in patients with tuberculosis and diabetes and those with a history of tuberculosis treatment. METHODS: A total of 256 tuberculosis patients with diabetes who were registered in Luoyang city, Henan Province, from January 2018 to December 2021. Logistic regression analysis was performed to analyse the risk factors for multidrug resistance. ROC curves were used to analyse the predictive model for multidrug resistance. RESULTS: Age < 65 years old, HbA1c, and a history of tuberculosis treatment were independent risk factors for multidrug resistance in patients with tuberculosis and diabetes (P < 0.05). The area under the ROC curve of predictive model for MDR was 0.878 (95% CI (0.824, 0.932)). Age < 65 years old and HbA1c were independent risk factors for MDR in patients with TB and diabetes with a history of TB treatment. The area under the ROC curve of predictive model for MDR was 0.920 [95% CI (0.831, 0.999)]. CONCLUSION: The predictive model had certain prediction value for the risk of multidrug resistance in patients with tuberculosis and diabetes.

A Salivary Odorant-Binding Protein Mediates Nilaparvata lugens Feeding and Host Plant Phytohormone Suppression.

Odorant-binding proteins (OBPs) typically act as transporters of odor molecules and play an important role in insect host location. Here, we identified an OBP in brown planthopper (BPH) Nilaparvata lugens salivary glands via transcriptome sequencing. Real-time quantitative PCR and Western blotting analysis results showed that NlugOBP11 was highly expressed in salivary glands and secreted into rice plant during feeding, suggesting that it assists in BPH feeding on rice. Functional analysis in N. lugens saliva revealed that silencing this gene by RNA interference decreased the BPH stylet performance in the phloem of rice plants, reduced sap sucking, and ultimately led to insect death. Moreover, overexpression of NlugOBP11 in rice protoplasts or Nicotiana benthamiana leaves inhibited the production of defense-related signaling molecule salicylic acid in rice plant. The results demonstrate that NlugOBP11 is not only essential for BPH feeding, but also acts as an effector that inhibits plant defense.

Alterations of the human gut microbiome in liver cirrhosis.

Liver cirrhosis occurs as a consequence of many chronic liver diseases that are prevalent worldwide. Here we characterize the gut microbiome in liver cirrhosis by comparing 98 patients and 83 healthy control individuals. We build a reference gene set for the cohort containing 2.69 million genes, 36.1% of which are novel. Quantitative metagenomics reveals 75,245 genes that differ in abundance between the patients and healthy individuals (false discovery rate < 0.0001) and can be grouped into 66 clusters representing cognate bacterial species; 28 are enriched in patients and 38 in control individuals. Most (54%) of the patient-enriched, taxonomically assigned species are of buccal origin, suggesting an invasion of the gut from the mouth in liver cirrhosis. Biomarkers specific to liver cirrhosis at gene and function levels are revealed by a comparison with those for type 2 diabetes and inflammatory bowel disease. On the basis of only 15 biomarkers, a highly accurate patient discrimination index is created and validated on an independent cohort. Thus microbiota-targeted biomarkers may be a powerful tool for diagnosis of different diseases.

Rice defense responses are induced upon leaf rolling by an insect herbivore.

BACKGROUND: Plant defense against herbivores begins with perception. The earlier plant detects the harm, the greater plant will benefit in its arm race with the herbivore. Before feeding, the larvae of the rice pest Cnaphalocrocis medinalis, initially spin silk and fold up a leaf. Rice can detect and protect itself against C. medinalis feeding. However, whether rice could perceive C. medinalis leaf rolling behavior is currently unknown. Here, we evaluated the role of leaf rolling by C. medinalis and artificial leaf rolling in rice plant defense and its indirect effect on two important C. medinalis parasitoids (Itoplectis naranyae and Apanteles sp.) through a combination of volatile profiling, gene-transcriptional and phytohormonal profiling. RESULTS: Natural leaf rolling by C. medinalis resulted in an increased attraction of I. naranyae when compared to the undamaged plant after 12 h. Volatile analysis revealed that six out of a total 22 components significantly increased in the headspace of C. medinalis rolled plant when compared to undamaged plant. Principal component analysis of these components revealed similarities in the headspace of undamaged plant and artificially rolled plant while the headspace volatiles of C. medinalis rolled plant deferred significantly. Leaf rolling and feeding by C. medinalis up-regulated the plant transcriptome and a series of jasmonic acid (JA) and salicylic acid (SA) related genes. While feeding significantly increased JA level after 12 to 36 h, rolling significantly increased SA level after 2 to 12 h. Compared to artificial rolling, natural rolling significantly increased JA level after 36 h and SA level after 2 and 12 h. CONCLUSIONS: Our findings suggest that natural leaf rolling by C. medinalis can be perceived by rice plant. The detection of this behavior may serve as an early warning signal in favor of the rice plant defenses against C. medinalis.

Use of selective serotonin reuptake inhibitors and risk of upper gastrointestinal bleeding: a systematic review and meta-analysis.

BACKGROUND & AIMS: Selective serotonin reuptake inhibitors (SSRIs) are used to treat various psychiatric disorders. However, there are concerns that SSRIs increase the risk for upper gastrointestinal bleeding (UGIB). METHODS: We performed a systematic review and meta-analysis of controlled observational studies to determine whether SSRI use affects the risk for UGIB. Our analysis included all observational studies that compared UGIB development among patients receiving SSRIs vs no treatment. We calculated pooled odds ratios using random- and fixed-effects models. RESULTS: A total of 22 studies (6 cohort and 16 case-control studies) involving more than 1,073,000 individuals were included in our meta-analysis. In comparing SSRI users with patients who had not taken SSRIs, the odds for developing UGIB were 1.55-fold higher (odds ratio, 1.55; 95% confidence interval, 1.35-1.78). In subgroup analyses, the association was greatest for patients who received concurrent therapy with nonsteroidal anti-inflammatory or antiplatelet drugs; we found no significant increase in the risk of developing UGIB among patients receiving concurrent acid-suppressing drugs. CONCLUSIONS: SSRI use was associated with an almost 2-fold increase in the risk of developing UGIB, especially among patients at high risk for GI bleeding (concurrent use of nonsteroidal anti-inflammatory or antiplatelet drugs). This risk might be reduced significantly by concomitant use of acid-suppressing drugs.

An analysis of microbiota-targeted therapies in patients with avian influenza virus subtype H7N9 infection.

BACKGROUND: Selective prophylactic decontamination of the digestive tract is a strategy for the prevention of secondary nosocomial infection in patients with avian influenza virus subtype H7N9 infection. Our aim was to summarize the effectiveness of these therapies in re-establishing a stable and diverse microbial community, and reducing secondary infections. METHODS: Comprehensive therapies were dependent on the individual clinical situation of subjects, and were divided into antiviral treatment, microbiota-targeted therapies, including pro- or pre-biotics and antibiotic usage, and immunotherapy. Quantitative polymerase chain reaction and denaturing gradient gel electrophoresis (DGGE) were used for real-time monitoring of the predominant intestinal microbiome during treatment. Clinical information about secondary infection was confirmed by analyzing pathogens isolated from clinical specimens. RESULTS: Different antibiotics had similar effects on the gut microbiome, with a marked decrease and slow recovery of the Bifidobacterium population. Interestingly, most fecal microbial DGGE profiles showed the relative stability of communities under the continual suppression of the same antibiotics, and significant changes when new antibiotics were introduced. Moreover, we found no marked increase in C-reactive protein, and no cases of bacteremia or pneumonia, caused by probiotic use in the patients, which confirmed that the probiotics used in this study were safe for use in patients with H7N9 infection. Approximately 72% of those who subsequently suffered exogenous respiratory infection by Candida species or multidrug-resistant Acinetobacter baumannii and Klebsiella pneumoniae were older than 60 years. The combination of probiotics and prebiotics with antibiotics seemed to fail in these patients. CONCLUSIONS: Elderly patients infected with the influenza A (H7N9) virus are considered a high-risk group for developing secondary bacterial infection. Microbiota restoration treatment reduced the incidence of enterogenous secondary infection, but not exogenous respiratory infection. The prophylactic effects of microbiota restoration strategies for secondary infection were unsatisfactory in elderly and critically ill patients.

Administration of Lactobacillus salivarius LI01 or Pediococcus pentosaceus LI05 improves acute liver injury induced by D-galactosamine in rats.

This work investigated the effect of the intragastric administration of five lactic acid bacteria from healthy people on acute liver failure in rats. Sprague-Dawley rats were given intragastric supplements of Lactobacillus salivarius LI01, Lactobacillus salivarius LI02, Lactobacillus paracasei LI03, Lactobacillus plantarum LI04, or Pediococcus pentosaceus LI05 for 8 days. Acute liver injury was induced on the eighth day by intraperitoneal injection of 1.1 g/kg body weight D-galactosamine (D-GalN). After 24 h, samples were collected to determine the level of liver enzymes, liver function, histology of the terminal ileum and liver, serum levels of inflammatory cytokines, bacterial translocation, and composition of the gut microbiome. The results indicated that pretreatment with L. salivarius LI01 or P. pentosaceus LI05 significantly reduced elevated alanine aminotransferase and aspartate aminotransferase levels, prevented the increase in total bilirubin, reduced the histological abnormalities of both the liver and the terminal ileum, decreased bacterial translocation, increased the serum level of interleukin 10 and/or interferon-γ, and resulted in a cecal microbiome that differed from that of the liver injury control. Pretreatment with L. plantarum LI04 or L. salivarius LI02 demonstrated no significant effects during this process, and pretreatment with L. paracasei LI03 aggravated liver injury. To the best of our knowledge, the effects of the three species-L. paracasei, L. salivarius, and P. pentosaceus-on D-GalN-induced liver injury have not been previously studied. The excellent characteristics of L. salivarius LI01 and P. pentosaceus LI05 enable them to serve as potential probiotics in the prevention or treatment of acute liver failure.

Mechanistic studies of adsorption and ion exchange of Si(OH)4 molecules on the surface of scorodites.

Scorodites are commonly used for arsenic immobilization, and it is also the main component of arsenic bearing tailings. Alkali-activated geopolymers are commonly used to landfill arsenic-bearing minerals. However, there no previous studies have explored the interaction between geopolymer molecules and the surface of scorodite. In this paper, Si(OH)4 as a monomer molecule of geopolymer, the mechanism of adsorption and 'ion exchange' between Si(OH)4 molecule and the surface of scorodite during alkali-activation is studied. Results show that the Fe-terminated scorodite (010) surface has high stability. Si(OH)4 are more easily adsorbed on the hollow site of an Fe-terminated scorodite (010) surface, which is described as chemisorption. Compared with Si(OH)4, NaOH is easier to adsorb on an Fe-terminated scorodite (010) surface. The co-adsorption of NaOH and Si(OH)4 on the Fe-terminated scorodite (010) surface was studied, and also belongs to chemical adsorption. When the hydroxyl binds to the As atom, the adsorbed Si(OH)4 is more likely to undergo an 'ion exchange' reaction with the surface, and the reaction is barrierless. The intermediate As(OH)4 produced by the 'ion exchange' reaction can be deprotonated to form an arsenate molecule, which can occur spontaneously. This work reveals that the interaction mechanism of geopolymer molecules on surface of scorodite.

RNA 5-methylcytosine writer NSUN5 promotes hepatocellular carcinoma cell proliferation via a ZBED3-dependent mechanism.

Hepatocellular carcinoma (HCC) is one of the leading contributors to cancer-related mortality worldwide. Nop2/Sun domain family member 5 (NSUN5), a conserved RNA 5-methylcytosine methyltransferase, is conventionally recognized as oncogenic. However, its role in HCC development remains unknown. In this study, we observed a remarkable upregulation of NSUN5 expression in both tumor tissues from patients with HCC, establishing a correlation with unfavorable clinical outcomes. NSUN5 knockdown and overexpression significantly inhibited and promoted HCC cell proliferation, respectively. Additionally, employing a combination of methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RIP-seq techniques, we identified zinc finger BED domain-containing protein 3 (ZBED3) as a novel downstream target of NSUN5. Additionally, we found that the overexpression of ZBED3 counteracted the tumor-suppressing effect of NSUN5 knockdown and simultaneously reversed the inhibition of the Wnt/ß-catenin signaling pathway. In summary, we elucidated the oncogenic role of NSUN5 in HCC development and identified the ZBED3/Wnt/ß-catenin signaling pathway as its downstream target. This study provides a novel therapeutic target for further development in HCC treatment.

Rapid determination of starch and alcohol contents in fermented grains by hyperspectral imaging combined with data fusion techniques.

Starch and alcohol serve as pivotal indicators in assessing the quality of lees fermentation. In this paper, two hyperspectral imaging (HSI) techniques (visible-near-infrared (Vis-NIR) and NIR) were utilized to acquire separate HSI data, which were then fused and analyzed toforecast the starch and alcohol contents during the fermentation of lees. Five preprocessing methods were first used to preprocess the Vis-NIR, NIR, and the fused Vis-NIR and NIR data, after which partial least squares regression models were established to determine the best preprocessing method. Following, competitive adaptive reweighted sampling, successive projection algorithm, and principal component analysis algorithms were used to extract the characteristic wavelengths to accurately predict the starch and alcohol levels. Finally, support vector machine (SVM)-AdaBoost and XGBoost models were built based on the low-level fusion (LLF) and intermediate-level fusion (ILF) of single Vis-NIR and NIR as well as the fused data. The results showed that the SVM-AdaBoost model built using the LLF data afterpreprocessing by standard normalized variable was most accurate for predicting the starch content, with an R P 2 $\ R_P^2$ of 0.9976 and a root mean square error of prediction (RMSEP) of 0.0992. The XGBoost model built using ILF data was most accurate for predicting the alcohol content, with an R P 2 $R_P^2$ of 0.9969 and an RMSEP of 0.0605. In conclusion, the analysis of fused data from distinct HSI technologies facilitates rapid and precise determination of the starch and alcohol contents in fermented grains.

Genomic epidemiology and transmission characteristics of mcr1-positive colistin-resistant Escherichia coli strains circulating at natural environment.

MCR-positive Escherichia coli (MCRPEC) have been reported in humans worldwide. The high prevalence of mcr-1 poses clinical and environmental risks due to its diverse genetic mechanisms. Given the vital role of animals and the environment in the spread of antibiotic resistance, a "One Health" perspective should be taken when addressing antimicrobial resistance issues. This study conducted a prospective study in six farms (located in Jiaxing City, Zhejiang province, China) in 2019. MCRPEC strains were screened from samples of different sources. The molecular epidemiological surveys and transmission potential were investigated by whole-genome sequencing and phylogenetic analysis. MCRPEC were detected in different farms with various sources. Sequence type complex 10 was dominant and distributed widely in multiple sources. Core-genome multilocus sequence type (cgMLST) analysis indicated that clonal transmission could occur within and between farms. In addition, mcr-1 genes with different locations showed different transmission tendencies. The study indicated that interspecies and cross-regional transmission of MCRPEC could occur between different sectors in farms. Further surveillance and research of non-clinical MCRPEC strains are necessary to reduce the threat of MCRPEC.

Multicomponent hyperspectral grade evaluation of ilmenite using spectral-spatial joint features.

Obtaining a comprehensive understanding of ore grade information is of significant importance for evaluating the value of ore. However, the real-time detection of multicomponent grade needs more effective online methods. This study proposes a novel approach utilizing hyperspectral imaging (HSI) to evaluate the grade information of nine major ilmenite components by integrating spectral and spatial data. Four multivariate input-output models were developed to mitigate variable interference to predict each component's grade. The results demonstrated that the backpropagation neural network (BPNN) model built from iPLS-VCPA-IRIV feature selection spectral data worked best (RP2 = 0.9935, RMSEP = 0.1364, RPD = 12.8986, and RPIQ = 21.4871, with a computational time of approximately 0.8 s). Furthermore, applying the best optimal combination algorithm for multicomponent grade inversion yielded highly accurate results, in which 97% of the component inversion residuals were less than 1. This investigation affirms that HSI enables rapid and accurate prediction and inversion of the multicomponent grade of ilmenite, thereby presenting a promising alternative to online analysis in the mineral field.

Emergence of mcr-8.2-harboring hypervirulent ST412 Klebsiella pneumoniae strain from pediatric sepsis: A comparative genomic survey.

Emerging mobile colistin resistance (mcr) genes pose a significant threat to public health for colistin was used as the last resort to treat multidrug-resistant (MDR) pathogenic bacterial infections. Hypervirulent Klebsiella pneumoniae (hvKP) is a clinically significant pathogen resulting in highly invasive infections, often complicated by devastating dissemination. Worryingly, the untreatable and severe infections caused by mcr-harbouring hvKP leave the selection of antibiotics for clinical anti-infective treatment in a dilemma. Herein, we screened 3,461 isolates from a tertiary teaching hospital from November 2018 to March 2021, and an mcr-8.2-harbouring hvKP FAHZZU2591 with a conjugative plasmid was identified from paediatric sepsis. This is the first report of MCR-8-producing hvKP from paediatric sepsis to our best knowledge. The susceptibility, genetic features, and plasmid profiles of the isolate were investigated. Further, we assessed the virulence potential of FAHZZU2591 and verified its pathogenicity and invasive capacity using a mouse model. The phylogenetic analysis of mcr-8-bearing K. pneumoniae revealed that China is the predominant reservoir of the mcr-8 gene, and the clinic is the primary source. Our work highlights the risk for the spread of mcr-positive hvKP in clinical, especially in paediatric sepsis, and the persistent surveillance of colistin-resistance hvKP is urgent.