Control compounds for preclinical drug-induced liver injury assessment: Consensus-driven systematic review by the ProEuroDILI network.

BACKGROUND & AIMS: Idiosyncratic drug-induced liver injury (DILI) is a complex and unpredictable event caused by drugs, and herbal or dietary supplements. Early identification of human hepatotoxicity at preclinical stages remains a major challenge, in which the selection of validated in vitro systems and test drugs has a significant impact. In this systematic review, we analyzed the compounds used in hepatotoxicity assays and established a list of DILI-positive and -negative control drugs for validation of in vitro models of DILI, supported by literature and clinical evidence and endorsed by an expert committee from the COST Action ProEuroDILI Network (CA17112). METHODS: Following 2020 PRISMA guidelines, original research articles focusing on DILI which used in vitro human models and performed at least one hepatotoxicity assay with positive and negative control compounds, were included. Bias of the studies was assessed by a modified 'Toxicological Data Reliability Assessment Tool'. RESULTS: A total of 51 studies (out of 2,936) met the inclusion criteria, with 30 categorized as reliable without restrictions. Although there was a broad consensus on positive compounds, the selection of negative compounds lacked clarity. 2D monoculture, short exposure times and cytotoxicity endpoints were the most tested, although there was no consensus on drug concentrations. CONCLUSIONS: Extensive analysis highlighted the lack of agreement on control compounds for in vitro DILI assessment. Following comprehensive in vitro and clinical data analysis together with input from the expert committee, an evidence-based consensus-driven list of 10 positive and negative control drugs for validation of in vitro models of DILI is proposed. IMPACT AND IMPLICATIONS: Prediction of human toxicity early in the drug development process remains a major challenge, necessitating the development of more physiologically relevant liver models and careful selection of drug-induced liver injury (DILI)-positive and -negative control drugs to better predict the risk of DILI associated with new drug candidates. Thus, this systematic study has crucial implications for standardizing the validation of new in vitro models of DILI. By establishing a consensus-driven list of positive and negative control drugs, the study provides a scientifically justified framework for enhancing the consistency of preclinical testing, thereby addressing a significant challenge in early hepatotoxicity identification. Practically, these findings can guide researchers in evaluating safety profiles of new drugs, refining in vitro models, and informing regulatory agencies on potential improvements to regulatory guidelines, ensuring a more systematic and efficient approach to drug safety assessment.

PTI-ETI synergistic signal mechanisms in plant immunity.

Plants face a relentless onslaught from a diverse array of pathogens in their natural environment, to which they have evolved a myriad of strategies that unfold across various temporal scales. Cell surface pattern recognition receptors (PRRs) detect conserved elicitors from pathogens or endogenous molecules released during pathogen invasion, initiating the first line of defence in plants, known as pattern-triggered immunity (PTI), which imparts a baseline level of disease resistance. Inside host cells, pathogen effectors are sensed by the nucleotide-binding/leucine-rich repeat (NLR) receptors, which then activate the second line of defence: effector-triggered immunity (ETI), offering a more potent and enduring defence mechanism. Moreover, PTI and ETI collaborate synergistically to bolster disease resistance and collectively trigger a cascade of downstream defence responses. This article provides a comprehensive review of plant defence responses, offering an overview of the stepwise activation of plant immunity and the interactions between PTI-ETI synergistic signal transduction.

Prior drug allergies are associated with worse outcome in patients with idiosyncratic drug-induced liver injury: A machine learning approach for risk stratification.

The impact of prior drug allergies (PDA) on the clinical features and outcomes of patients who develop idiosyncratic drug-induced liver injury (DILI) is largely unknown. We aimed to assess the clinical presentation and outcomes of DILI patients based on the presence or absence of PDA and explore the association between culprit drugs responsible for DILI and allergy. We analysed a well-vetted cohort of DILI cases enrolled from the Spanish DILI Registry. Bootstrap-enhanced least absolute shrinkage operator procedure was used in variable selection, and a multivariable logistic model was fitted to predict poor outcomes in DILI. Of 912 cases with a first episode of DILI, 61 (6.7%) had documented PDA. Patients with PDA were older (p = 0.009), had higher aspartate aminotransferase (AST) levels (p = 0.047), lower platelet count (p = 0.011) and higher liver-related mortality than those without a history of drug allergies (11% vs. 1.6%, p < 0.001). Penicillin was the most common drug associated with PDA in DILI patients (32%). A model including PDA, nR-based type of liver injury, female sex, AST, total bilirubin, and platelet count showed an excellent performance in predicting poor outcome in patients from the Spanish DILI Registry (area under the ROC curve [AUC] 0.887; 95% confidence interval [CI] 0.794 - 0.981) and the LATINDILI Network (AUC 0.932; 95% CI 0.884 - 0.981). Patients with suspected DILI should be screened for PDA as they would require a close monitoring for early detection of worsening clinical course.

Characterization of drug-induced liver injury associated with drug reaction with eosinophilia and systemic symptoms in two prospective DILI registries.

Idiosyncratic drug-induced liver injury (DILI) associated with drug reactions with eosinophilia and systemic symptoms (DRESS) is poorly characterized among patients of Western countries. We aimed to comprehensively assess the clinical characteristics, outcomes, and causative agents in a prospective, well-vetted cohort of DILI patients with DRESS (DILI-DRESS). We identified 53 DILI-DRESS cases from the Spanish DILI Registry and the Latin American DILI Network. For comparison purposes, we defined a group of DILI patients (n = 881). DILI-DRESS cases were younger (47 vs. 53 years, respectively; p = 0.042) and presented more frequently with cholestatic/mixed damage (p = 0.018). Most DILI-DRESS patients showed moderate liver injury, 13% developed severe damage, and only one patient (with hepatocellular injury due to anti-tuberculosis drugs) progressed to acute liver failure and died. DILI-DRESS cases showed a distinctive causative drug pattern compared to DILI cases. The most frequent drugs were carbamazepine (13%), anti-tuberculosis drugs (13%), amoxicillin-clavulanate (11%), and allopurinol and lamotrigine (7.6% each). Among all cases of DILI due to allopurinol and lamotrigine, 67% presented with a DILI-DRESS phenotype, respectively. Higher total bilirubin (TBL) levels at DILI recognition (odds ratio [OR] 1.23; 95% confidence interval [CI] 1.04-1.45) and absence of eosinophilia (OR 8.77; 95% CI 1.11-69.20) increased the risk for developing a severe-fatal injury in DILI-DRESS patients. DILI-DRESS patients have a more frequent cholestasis/mixed pattern of injury at presentation, with antiepileptics as distinctive causative drug class. Most of the lamotrigine and allopurinol cases present with this phenotype. Higher TBL levels and absence of eosinophilia at DILI recognition are markers of poor outcomes.

Probe-Type Multi-Core Fiber Optic Sensor for Simultaneous Measurement of Seawater Salinity, Pressure, and Temperature.

In this article, we propose and demonstrate a probe-type multi-core fiber (MCF) sensor for the multi-parameter measurement of seawater. The sensor comprises an MCF and two capillary optical fibers (COFs) with distinct inner diameters, in which a 45° symmetric core reflection (SCR) structure and a step-like inner diameter capillary (SIDC) structure filled with polydimethylsiloxane (PDMS) are fabricated at the fiber end. The sensor is equipped with three channels for different measurements. The surface plasmon resonance (SPR) channel (CHSPR) based on the side-polished MCF is utilized for salinity measurement. The fiber end air cavity, forming the Fabry-Pérot interference (FPI) channel (CHFPI), is utilized for pressure and temperature measurement. Additionally, the fiber Bragg grating (FBG) channel (CHFBG), which is inscribed in the central core, serves as temperature compensation for the measurement results. By combining three sensing principles with space division multiplexing (SDM) technology, the sensor overcomes the common challenges faced by multi-parameter sensors, such as channel crosstalk and signal demodulation difficulties. The experimental results indicate that the sensor has sensitivities of 0.36 nm/‱, -10.62 nm/MPa, and -0.19 nm/°C for salinity, pressure, and temperature, respectively. As a highly integrated and easily demodulated probe-type optical fiber sensor, it can serve as a valuable reference for the development of multi-parameter fiber optic sensors.

An individual patient data meta-analysis to determine cut-offs for and confounders of NAFLD-fibrosis staging with magnetic resonance elastography.

BACKGROUND & AIMS: We conducted an individual patient data meta-analysis to establish stiffness cut-off values for magnetic resonance elastography (MRE) in staging liver fibrosis and to assess potential confounding factors. METHODS: A systematic review of the literature identified studies reporting MRE data in patients with NAFLD. Data were obtained from the corresponding authors. The pooled diagnostic cut-off value for the various fibrosis stages was determined in a two-stage meta-analysis. Multilevel modelling methods were used to analyse potential confounding factors influencing the diagnostic accuracy of MRE in staging liver fibrosis. RESULTS: Eight independent cohorts comprising 798 patients were included in the meta-analysis. The area under the receiver operating characteristic curve (AUROC) for MRE in detecting significant fibrosis was 0.92 (sensitivity, 79%; specificity, 89%). For advanced fibrosis, the AUROC was 0.92 (sensitivity, 87%; specificity, 88%). For cirrhosis, the AUROC was 0.94 (sensitivity, 88%, specificity, 89%). Cut-offs were defined to explore concordance between MRE and histopathology: ≥F2, 3.14 kPa (pretest probability, 39.4%); ≥F3, 3.53 kPa (pretest probability, 24.1%); and F4, 4.45 kPa (pretest probability, 8.7%). In generalized linear mixed model analysis, histological steatohepatitis with higher inflammatory activity (odds ratio 2.448, 95% CI 1.180-5.079, p <0.05) and high gamma-glutamyl transferase (GGT) concentration (>120U/L) (odds ratio 3.388, 95% CI 1.577-7.278, p <0.01] were significantly associated with elevated liver stiffness, and thus affecting accuracy in staging early fibrosis (F0-F1). Steatosis, as measured by magnetic resonance imaging proton density fat fraction, and body mass index(BMI) were not confounders. CONCLUSIONS: MRE has excellent diagnostic performance for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Elevated inflammatory activity and GGT level may lead to overestimation of early liver fibrosis, but anthropometric measures such as BMI or the degree of steatosis do not. IMPACT AND IMPLICATIONS: This individual patient data meta-analysis of eight international cohorts, including 798 patients, demonstrated that MRE achieves excellent diagnostic accuracy for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Cut-off values (significant fibrosis, 3.14 kPa; advanced fibrosis, 3.53 kPa; and cirrhosis, 4.45 kPa) were established. Elevated inflammatory activity and gamma-glutamyltransferase level may affect the diagnostic accuracy of MRE, leading to overestimation of liver fibrosis in early stages. We observed no impact of diabetes, obesity, or any other metabolic disorder on the diagnostic accuracy of MRE.

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60.

BACKGROUND: Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield. RESULTS: Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29-9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41-6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation. CONCLUSIONS: A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

Identification of WUSCHEL-related homeobox gene and truncated small peptides in transformation efficiency improvement in Eucalyptus.

BACKGROUND: The WUSCHEL-related Homeobox (WOX) genes, which encode plant-specific homeobox (HB) transcription factors, play crucial roles in regulating plant growth and development. However, the functions of WOX genes are little known in Eucalyptus, one of the fastest-growing tree resources with considerable widespread cultivation worldwide. RESULTS: A total of nine WOX genes named EgWOX1-EgWOX9 were retrieved and designated from Eucalyptus grandis. From the three divided clades marked as Modern/WUS, Intermediate and Ancient, the largest group Modern/WUS (6 EgWOXs) contains a specific domain with 8 amino acids: TLQLFPLR. The collinearity, cis-regulatory elements, protein-protein interaction network and gene expression analysis reveal that the WUS proteins in E. grandis involve in regulating meristems development and regeneration. Furthermore, by externally adding of truncated peptides isolated from WUS specific domain, the transformation efficiency in E. urophylla × E. grandis DH32-29 was significant enhanced. The transcriptomics data further reveals that the use of small peptides activates metabolism pathways such as starch and sucrose metabolism, phenylpropanoid biosynthesis and flavonoid biosynthesis. CONCLUSIONS: Peptides isolated from WUS protein can be utilized to enhance the transformation efficiency in Eucalyptus, thereby contributing to the high-efficiency breeding of Eucalyptus.

Photoelectric characteristics of hydrogen-terminated polycrystalline diamond MESFETs.

In the field of diamond MESFETs, this work is what we believe to be the first to investigate the optoelectronic properties of hydrogen-terminated polycrystalline diamond MESFETs under visible and near-UV light irradiation. It is shown that the diamond MESFETs are well suited for weak light detection in the near-ultraviolet region around the wavelength of 368 nm, with a responsivity of 6.14 × 106 A/W and an external quantum efficiency of 2.1 × 107 when the incident light power at 368.7 nm is only 0.75 µW/cm2. For incident light at 275.1 nm, the device's sensitivity and EQE increase as the incident light power increases; at an incident light power of 175.32 µW/cm2 and a VGS of -1 V, the device's sensitivity is 2.9 × 105 A/W and the EQE is 1.3 × 106. For incident light in the wavelength range of 660 nm to 404 nm with an optical power of 70 µW/cm2, the device achieves an average responsivity of 1.21 × 105 A/W. This indicates that hydrogen-terminated polycrystalline diamond MESFETs are suitable for visible and near-UV light detection, especially for weak near-UV light detection. However, the transient response test of the device shows a long relaxation time of about 0.2 s, so it is not yet suitable for high-speed UV communication or detection.

Inflow Angle Impacts Morphology, Hemodynamics, and Inflammation of Side-wall Intracranial Aneurysms.

BACKGROUND: Aneurysm inflow angle has been shown to be associated with hemodynamic changes by computational fluid dynamics. However, these studies were based on single aneurysm model and were limited to side-wall aneurysms. PURPOSE: To investigate the association between inflow angle and morphology, hemodynamic, and inflammation of intracranial side-wall and bifurcation aneurysms. STUDY TYPE: Prospective. POPULATION: A total of 62 patients (aged 58.34 ± 12.39, 44 female) with 59 unruptured side-wall aneurysms and 17 unruptured bifurcation aneurysms were included. FIELD STRENGTH/SEQUENCE: A 3.0 T; 3D fast field echo sequence (TOF-MRA); free-breathing, 3D radio-frequency-spoiled, multi-shot turbo field echo sequence (4D-flow MRI); 3D black-blood T1-weighted volumetric turbo spin echo acquisition sequence (T1 -VISTA) ASSESSMENT: Two neuroradiologists assessed the inflow angle and size for intracranial aneurysms in 3D space with TOF-MRA images. The average and maximum inflow velocity (Vavg-IA , Vmax-IA ), blood flow (Flowavg-IA , Flowmax-IA ), and average wall shear stress (WSSavg-IA ) for aneurysms were assessed from 4D-flow MRI in regions of interest drawn by two neuroradiologists. The aneurysmal wall enhancement (AWE) grades between precontrast and postcontrast T1 -VISTA images were evaluated by three neuroradiologists. STATISTICAL TESTS: Kruskal-Wallis H test, χ2 test, Pearson's correlation coefficient, scatter plots and regression lines, multivariate logistic regression analysis (partial correlation r) were performed. A P < 0.05 was considered statistically significant. RESULTS: The WSSavg-IA (0.52 ± 0.34 vs. 0.27 ± 0.22) and AWE grades (1.38 ± 1.04 vs. 2.02 ± 0.68) between the two inflow angle subgroups of side-wall aneurysms were significantly different. The aneurysm size (rs  = 0.31), WSSavg-IA (rs  = -0.45), and AWE grades (rs  = 0.45) were significantly correlated with inflow angle in side-wall aneurysms. While in bifurcation aneurysms, there were no significant associations between inflow angle and size (P = 0.901), Vavg-IA (P = 0.699), Vmax-IA (P = 0.482), Flowavg-IA (P = 0.550), Flowmax-IA (P = 0.689), WSSavg-IA (P = 0.573), and AWE grades (P = 0.872). DATA CONCLUSION: A larger aneurysm size, a lower WSS and a higher AWE grade were correlated with a larger inflow angle in side-wall aneurysms. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

A deep learning framework for intracranial aneurysms automatic segmentation and detection on magnetic resonance T1 images.

OBJECTIVES: To design a deep learning-based framework for automatic segmentation and detection of intracranial aneurysms (IAs) on magnetic resonance T1 images and test the robustness and performance of framework. METHODS: A retrospective diagnostic study was conducted based on 159 IAs from 136 patients who underwent the T1 images. Among them, 127 cases were randomly selected for training and validation, and 32 cases were used to assess the accuracy and consistency of our algorithm. We developed and assembled three convolutional neural networks for the segmentation and detection of IAs. The segmentation and detection performance of the model were compared with the ground truth, and various metrics were calculated at the voxel level, IAs level, and patient level to show the performance of our framework. RESULTS: Our assembled model achieved overall Dice, voxel-level sensitivity, specificity, balanced accuracy, and F1 score of 0.802, 0.874, 0.9998, 0.937, and 0.802, respectively. A coincidence greater than 0.7 between the aneurysms predicted by the model and the ground truth was considered as a true positive. For IAs detection, the sensitivity reached 90.63% with 0.58 false positives per case. The volume of IAs segmented by our model showed a high agreement and consistency with the volume of IAs labeled by experts. CONCLUSION: The deep learning framework is achievable and robust for IAs segmentation and detection. Our model offers more clinical application opportunities compared to digital subtraction angiography (DSA)-based, CTA-based, and MRA-based methods. CLINICAL RELEVANCE STATEMENT: Our deep learning framework effectively detects and segments intracranial aneurysms using clinical routine T1 sequences, showing remarkable effectiveness and offering great potential for improving the detection of latent intracranial aneurysms and enabling early identification. KEY POINTS: •There is no segmentation method based on clinical routine T1 images. Our study shows that the proper deep learning framework can effectively localize the intracranial aneurysms. •The T1-based segmentation and detection method is more universal than other angiography-based detection methods, which can potentially reduce missed diagnoses caused by the absence of angiography images. •The deep learning framework is robust and has the potential to be applied in a clinical setting.

Aneurysm wall enhancement, atherosclerotic proteins, and aneurysm size may be related in unruptured intracranial fusiform aneurysms.

OBJECTIVE: This cross-sectional study aimed to investigate the associations between aneurysm wall enhancement (AWE), atherosclerotic protein levels, and aneurysm size in unruptured intracranial fusiform aneurysms (IFAs). METHODS: Patients with IFAs underwent high-resolution magnetic resonance imaging (HR-MRI) and atherosclerotic protein examinations from May 2015 to December 2021 were collected. A CRstalk (signal intensity [SI] of IFA wall/SI of pituitary stalk) > 0.60 was considered to indicate AWE. Atherosclerotic protein data was obtained from the peripheral blood. Aneurysmal characteristics included the maximal diameter of the cross-section (Dmax), location, type of IFA, presence of mural thrombus, and mural clots. Statistical analyses were performed with univariate analysis, logistic regression analysis, and Spearman's correlation coefficient. RESULTS: Seventy-one IFAs from 71 patients were included in the study. Multivariate analysis revealed statin use (OR = 0.189, p = 0.026) and apolipoprotein B (Apo-B) level (OR = 6.019, p = 0.026) were the independent predictors of AWE in IFAs. In addition, statin use (OR = 0.813, p = 0.036) and Apo-B level (OR = 1.610, p = 0.003) were also the independent predictors of CRstalk. Additionally, we found that CRstalk and AWE were significantly positively associated with Dmax (rs = 0.409 and 0.349, respectively; p < 0.001 and p = 0.003, respectively). CONCLUSIONS: There may be correlations between AWE, atherosclerotic protein levels, and aneurysm size in patients with IFAs. Apo-B and statin use were independent predictors of AWE in IFAs, which have the potential to be new therapeutic targets for IFAs. KEY POINTS: • There may be correlations between aneurysm wall enhancement, atherosclerotic protein levels in the peripheral blood, and aneurysm size in patients with intracranial fusiform aneurysms. • Apolipoprotein B and statin use were independent predictors of aneurysm wall enhancement in intracranial fusiform aneurysms.

Evaluation of diagnostic and prognostic candidate biomarkers in drug-induced liver injury vs. other forms of acute liver damage.

AIMS: Detection and characterization of idiosyncratic drug-induced liver injury (DILI) currently rely on standard liver tests, which are suboptimal in terms of specificity, sensitivity and prognosis. Therefore, DILI diagnosis can be delayed, with important consequences for the patient. In this study, we aimed to evaluate the potential of osteopontin, cytokeratin-18 (caspase-cleaved: ccK18 and total: K18), α-glutathione-S-transferase and microRNA-122 as new DILI biomarkers. METHODS: Serial blood samples were collected from 32 DILI and 34 non-DILI acute liver injury (ALI) cases and a single sample from 43 population controls without liver injury (HLC) and analysed using enzyme-linked immunosorbent assay (ELISA) or single-molecule arrays. RESULTS: All biomarkers differentiated DILI and ALI from HLC with an area under receiver operator characteristic curve (AUC) value of >0.75 but were less efficient in distinguishing DILI from ALI, with ccK18 (0.79) and K18 (0.76) demonstrating highest potential. However, the AUC improved considerably (0.98) for ccK18 when comparing DILI and a subgroup of autoimmune hepatitis cases. Cytokeratin-18, microRNA-122 and α-glutathione-S-transferase correlated well with traditional transaminases, while osteopontin correlated most strongly with the international normalized ratio (INR). CONCLUSIONS: ccK18 appears promising in distinguishing DILI from autoimmune hepatitis but less so from other forms of acute liver injury. Osteopontin demonstrates prognostic potential with higher levels detected in more severe cases regardless of aetiology.

Synthesis of isobutanol using acetate as sole carbon source in Escherichia coli.

BACKGROUND: With concerns about depletion of fossil fuel and environmental pollution, synthesis of biofuels such as isobutanol from low-cost substrate by microbial cell factories has attracted more and more attention. As one of the most promising carbon sources instead of food resources, acetate can be utilized by versatile microbes and converted into numerous valuable chemicals. RESULTS: An isobutanol synthetic pathway using acetate as sole carbon source was constructed in E. coli. Pyruvate was designed to be generated via acetyl-CoA by pyruvate-ferredoxin oxidoreductase YdbK or anaplerotic pathway. Overexpression of transhydrogenase and NAD kinase increased the isobutanol titer of recombinant E. coli from 121.21 mg/L to 131.5 mg/L under batch cultivation. Further optimization of acetate supplement concentration achieved 157.05 mg/L isobutanol accumulation in WY002, representing the highest isobutanol titer by using acetate as sole carbon source. CONCLUSIONS: The utilization of acetate as carbon source for microbial production of valuable chemicals such as isobutanol could reduce the consumption of food-based substrates and save production cost. Engineering strategies applied in this study will provide a useful reference for microbial production of pyruvate derived chemical compounds from acetate.

Rupture discrimination of multiple small (< 7 mm) intracranial aneurysms based on machine learning-based cluster analysis.

BACKGROUND: Small multiple intracranial aneurysms (SMIAs) are known to be more prone to rupture than are single aneurysms. However, specific recommendations for patients with small MIAs are not included in the guidelines of the American Heart Association and American Stroke Association. In this study, we aimed to evaluate the feasibility of machine learning-based cluster analysis for discriminating the risk of rupture of SMIAs. METHODS: This multi-institutional cross-sectional study included 1,427 SMIAs from 660 patients. Hierarchical cluster analysis guided patient classification based on patient-level characteristics. Based on the clusters and morphological features, machine learning models were constructed and compared to screen the optimal model for discriminating aneurysm rupture. RESULTS: Three clusters with markedly different features were identified. Cluster 1 (n = 45) had the highest risk of subarachnoid hemorrhage (SAH) (75.6%) and was characterized by a higher prevalence of familiar IAs. Cluster 2 (n = 110) had a moderate risk of SAH (38.2%) and was characterized by the highest rate of SAH history and highest number of vascular risk factors. Cluster 3 (n = 505) had a relatively mild risk of SAH (17.6%) and was characterized by a lower prevalence of SAH history and lower number of vascular risk factors. Lasso regression analysis showed that compared with cluster 3, clusters 1 (odds ratio [OR], 7.391; 95% confidence interval [CI], 4.074-13.150) and 2 (OR, 3.014; 95% CI, 1.827-4.970) were at a higher risk of aneurysm rupture. In terms of performance, the area under the curve of the model was 0.828 (95% CI, 0.770-0.833). CONCLUSIONS: An unsupervised machine learning-based algorithm successfully identified three distinct clusters with different SAH risk in patients with SMIAs. Based on the morphological factors and identified clusters, our proposed model has good discrimination ability for SMIA ruptures.

Nitrofurantoin-induced liver injury: long-term follow-up in two prospective DILI registries.

Nitrofurantoin is a synthetic antibiotic that is recommended as first-choice treatment for uncomplicated urinary tract infections. The prescription of this drug has increased dramatically, especially in Latin American countries. We described the demographics, clinical characteristics, biochemical features, and outcome of nitrofurantoin-induced liver injury. We analyzed 23 cases from the Latin American DILI Network (LATINDILI) and the Spanish DILI Registry. Causality was assessed with the RUCAM and RECAM scale. Of the 23 DILI cases included in our series, 96% patients were women, and the mean age of the whole cohort was 61 years. The median time of drug exposure was 175 days (interquartile range [IQR] 96-760), with 11 patients who were prescribed nitrofurantoin for more than six months. Hepatocellular damage was the most frequent pattern of liver injury (83%), and nearly half of the patients had an asymptomatic presentation (52%). Neither death nor liver transplantation was documented in this series. Overall, 65% of the patients (n = 15) presented with positive autoantibody titres. The median time to resolution was 81 days (IQR 57-141), and 15 patients (83%) recovered within six months. Five patients (22%) developed nitrofurantoin-induced autoimmune-like hepatitis (NI-AILH), of whom two were characterized by a persistent increase in transaminases that required immunosuppressive treatment to achieve normalization of liver enzymes. Clinicians who prescribe nitrofurantoin should be aware that patients who had taken nitrofurantoin for a long term may be at risk of developing nitrofurantoin-induced autoimmune-like hepatitis.

Classification of Fluorescently Labelled Maize Kernels Using Convolutional Neural Networks.

Accurate real-time classification of fluorescently labelled maize kernels is important for the industrial application of its advanced breeding techniques. Therefore, it is necessary to develop a real-time classification device and recognition algorithm for fluorescently labelled maize kernels. In this study, a machine vision (MV) system capable of identifying fluorescent maize kernels in real time was designed using a fluorescent protein excitation light source and a filter to achieve optimal detection. A high-precision method for identifying fluorescent maize kernels based on a YOLOv5s convolutional neural network (CNN) was developed. The kernel sorting effects of the improved YOLOv5s model, as well as other YOLO models, were analysed and compared. The results show that using a yellow LED light as an excitation light source combined with an industrial camera filter with a central wavelength of 645 nm achieves the best recognition effect for fluorescent maize kernels. Using the improved YOLOv5s algorithm can increase the recognition accuracy of fluorescent maize kernels to 96%. This study provides a feasible technical solution for the high-precision, real-time classification of fluorescent maize kernels and has universal technical value for the efficient identification and classification of various fluorescently labelled plant seeds.

Herbal and Dietary Supplements-Induced Liver Injury in Latin America: Experience From the LATINDILI Network.

BACKGROUND: Herbal and dietary supplements (HDS) consumption, a growing cause of hepatotoxicity, is a common practice among Latin-American populations. OBJECTIVES: To evaluate clinical, laboratory features and outcome in HDS-hepatotoxicity included in the Latin America-Drug Induced Liver Injury (LATINDILI) Network. METHODS: A total of 29 adjudicated cases of HDS hepatotoxicity reported to the LATINDILI Network from October 2011 through December 2019 were compared with 322 DILI cases due to conventional drugs and 16 due to anabolic steroids as well as with other series of HDS-hepatotoxicity. RESULTS: From 367 DILI cases, 8% were attributed to HDS. An increasing trend in HDS-hepatotoxicity was noted over time (p = .04). Camellia sinensis, Herbalife® products, and Garcinia cambogia, mostly used for weight loss, were the most frequently adjudicated causative agents. Mean age was 45 years (66% female). Median time to onset was 31 days. Patients presented typically with hepatocellular injury (83%) and jaundice (66%). Five cases (17%) developed acute liver failure. Compared to conventional medications and anabolic steroids, HDS hepatotoxicity cases had the highest levels of aspartate and alanine transaminase (p = .008 and p = .021, respectively), had more re-exposure events to the culprit HDS (14% vs 3% vs 0%; p = .026), and had more severe and fatal/liver transplantation outcomes (21% vs 12% vs 13%; p = .005). Compared to other DILI cohorts, less HDS hepatotoxicity cases in Latin America were hospitalized (41%). CONCLUSIONS: HDS-hepatotoxicity in Latin-America affects mainly young women, manifests mostly with hepatocellular injury and is associated with higher frequency of accidental re-exposure. HDS hepatotoxicity is more serious with a higher chance of death/liver transplantation than DILI related to conventional drugs.

Additive Effect of Coexisting Aneurysms Increases Subarachnoid Hemorrhage Risk in Patients With Multiple Aneurysms.

BACKGROUND AND PURPOSE: It remains unclear whether the additive effect of coexisting intracranial aneurysms increases the risk of subarachnoid hemorrhage (SAH) in patients with multiple intracranial aneurysms. We have performed a tentative analysis for the additive effect of coexisting aneurysms. METHODS: This multi-institutional cross-sectional study included 1781 aneurysms from 746 patients with multiple intracranial aneurysms. Using the generalized linear mixed model, we analyzed risk factors associated with individual aneurysm rupture and assessed the additive risk of SAH for each patient. RESULTS: The coexisting aneurysms number was not significantly associated with individual intracranial aneurysm rupture, both in unadjusted and adjusted analyses. Patient-level analysis found that an increased number of coexisting aneurysms was significantly associated with a greater estimated additive risk (P<0.001). Estimated additive risks of patients with 2, 3, and 4 or more coexisting intracranial aneurysms were 25.9%, 31.8%, and 38.1%, respectively, which are comparable to the actual incidence of SAH in those patients (26.6%, 29.5%, and 36.5%, respectively), with a Spearman correlation coefficient of 1.000 (P<0.001). Compared with aneurysm-related factors, the estimated additive effect had better discrimination power for SAH risk, with areas under the receiver operating characteristic curve of 0.821. CONCLUSIONS: We found that a greater number of coexisting aneurysms did not increase rupture risk of individual aneurysms, but the potential additive effect might increase SAH risk in patients with multiple intracranial aneurysms.

Serum lnc34a is a potential prediction biomarker for bone metastasis in hepatocellular carcinoma patients.

BACKGROUND: Early screening and intervention therapies are crucial to improve the prognosis of hepatocellular carcinoma (HCC) patients with bone metastasis. We aimed to identify serum lncRNA as a prediction biomarker in HCC bone metastasis. METHODS: The expression levels of lnc34a in serum samples from 157 HCC patients were detected by quantitative real-time polymerase chain reaction (PCR). Univariate analysis and multivariate analysis were performed to determine statistically significant variables. RESULTS: Expression levels of lnc34a in serum from HCC patients with bone metastasis were significantly higher than those without bone metastasis. The high expressions of lnc34a, vascular invasion and Barcelona Clinic Liver Cancer (BCLC) stage were associated with bone metastasis by analysis. Moreover, lnc34a expression was specifically associated with bone metastasis rather than lung or lymph node metastasis in HCC. CONCLUSIONS: High serum lnc34a expression was a independent risk factor for developing bone metastasis in HCC.