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PubMed2002

Role of endothelin-converting enzyme, chymase and neutral endopeptidase in the processing of big ET-1, ET-1(1-21) and ET-1(1-31) in the trachea of allergic mice.

The present study examined the roles of endothelin-converting enzyme (ECE), neutral endopeptidase (NEP) and mast cell chymase as processors of the endothelin (ET) analogues ET-1(1-21), ET-1(1-31) and big ET-1 in the trachea of allergic mice. Male CBA/CaH mice were sensitized with ovalbumin (10 microg) delivered intraperitoneal on days 1 and 14, and exposed to aerosolized ovalbumin on days 14, 25, 26 and 27 (OVA mice). Mice were killed and the trachea excised for histological analysis and contraction studies on day 28. Tracheae from OVA mice had 40% more mast cells than vehicle-sensitized mice (sham mice). Ovalbumin (10 microg/ml) induced transient contractions (15+/-3% of the C(max)) in tracheae from OVA mice. The ECE inhibitor CGS35066 (10 microM) inhibited contractions induced by big ET-1 (4.8-fold rightward shift of dose-response curve; P<0.05), but not those induced by either ET-1(1-21) or ET-1(1-31). The chymase inhibitors chymostatin (10 microM) and Bowman-Birk inhibitor (10 microM) had no effect on contractions induced by any of the ET analogues used. The NEP inhibitor CGS24592 (10 microM) inhibited contractions induced by ET-1(1-31) (6.2-fold rightward shift; P<0.05) but not ET-1(1-21) or big ET-1. These data suggest that big ET-1 is processed predominantly by a CGS35066-sensitive ECE within allergic airways rather than by mast cell-derived proteases such as chymase. If endogenous ET-1(1-31) is formed within allergic airways, it is likely to undergo further conversion by NEP to more active products.

Animals↗
PubMed2004

Genetic variability in the coat protein genes of lettuce big-vein associated virus and Mirafiori lettuce big-vein virus.

Available data suggests that lettuce big-vein disease is caused by the ophiovirus Mirafiori lettuce big-vein virus (MLBVV) but not by the varicosavirus Lettuce big-vein-associated virus (LBVaV), although the latter is frequently associated with the disease. Since the disease occurs worldwide, the putative coat protein (CP) open reading frames of geographically distinct isolates of MLBVV and LBVaV were sequenced. Comparison of both nucleotide and amino acid sequences showed a high level of sequence similarity among LBVaV isolates. Phylogenetic analysis of LBVaV CP nucleotide sequences showed that most of the Spanish isolates clustered in a phylogenetic group whereas English isolates were more similar to the USA isolate. An Australian isolate was closely related to the Dutch isolate. Genetic diversity among MLBVV CP nucleotide sequences was higher ranging from 0.2% to 12%. Phylogenetic analysis of MLBVV CP nucleotide sequences revealed two distinct subgroups. However, this grouping was not correlated with symptom development on lettuce or the geographic origin of the MLBVV isolates. Finally, a quick method based on RFLP analysis of RT-PCR amplicons was developed for assigning MLBVV isolates to the two subgroups.

Amino Acid Sequence↗
PubMed1996

Evaluation of the in vivo genotoxic potential of three carcinogenic aromatic amines using the Big Blue transgenic mouse mutation assay.

Three genotoxic mouse carcinogens, 4-chloro-o-phenylenediamine (4-C-o-PDA), 2-nitro-p-phenylenediamine (2-N-p-PDA), and 2,4-diaminotoluene (2,4-DAT), were tested in the Big Blue transgenic mouse mutation assay. Each experiment consisted of a vehicle control group with ten Big Blue C57BL/6 mice, five of either sex, and an equally sized group treated with a high dose of the test chemical. In addition, four animals were treated with the vehicle and six animals with the test compound for the measurement of bromodeoxyuridine (BrdU) incorporation to determine cellular proliferation. Prior to the mutagenicity experiments, the maximally tolerated dose of each compound was determined using nontransgenic C57BL/6 mice. Based on these results the doses used in the main study were 200 mg/kg/day for 4-C-o-PDA, 150 mg/kg/ day for 2-N-p-PDA, and 80 mg/kg/day for 2,4-DAT. Animals were treated for 10 days over a 2 week period and were killed 10 days after the ast treatment. In an additional experiment with 2,4-DAT, animals were killed 28 days after treatment. Since all three chemicals are liver carcinogens in the mouse, the DNA of the liver was analyzed using the standard procedures for the Big Blue assay. Hepatocyte proliferation was assessed by immunohistochemical detection of proliferating cell nuclear antigen (PCNA) and, in some studies, by measuring BrdU incorporation. 4-C-o-PDA and 2-N-p-PDA did not induce an increase in PCNA expression when measured 10 days after the last treatment. There was no increase in BrdU incorporation immediately after treatment with 4-C-o-PDA or with 2,4-DAT. However, 10 days after the last treatment with 2,4-DAT, a strong mitogenic effect was found with both techniques, i.e., in the PCNA and BrdU assays. 4-C-o-PDA, a liver carcinogen in both genders of mice, induced a small, statistically significant increase of the mutant frequencies in females. No increase was found in males. 2-N-p-PDA, which has been reported to induce liver tumors only in females, was found positive in males and was clearly negative in females. 2,4-DAT, a liver carcinogen in female mice, was positive in females and negative in males when the animals were killed 10 days after the last treatment. After an expression time of 28 days, 2,4-DAT induced a statistically significant increase in both sexes. The effect in females was marginally stronger than after 10 days' expression time and almost identical to the effect observed in males under these test conditions. In conclusion, the experiments showed that the Big Blue assay detects the genotoxicity of the three carcinogenic monocyclic aromatic amines tested. However, it seems that the sex specificity of the carcinogenic effects of these compounds is not reflected by the mutagenicity data in Big Blue mice.

Animals↗
PubMed2026

AI-integrated digital breeding for crop improvement.

Crop breeding increasingly depends on the effective integration and interpretation of large, heterogeneous datasets spanning genomic, phenotypic, multi-omics, and environmental layers. Conventional breeding approaches are often insufficient to capture the complex relationships among these data or to support timely selection decisions. Digital breeding can help address this limitation by complementing field experimentation, mixed models, and genomic prediction with the integration of biological data and computational prediction throughout the breeding process. In particular, the rapid advancement of artificial intelligence (AI) has improved the analysis of high-dimensional datasets and broadened its application to trait prediction, selection, and breeding design. Here, we review recent developments in AI-enabled digital breeding, encompassing genomic, phenomic, and multi-omics data generation and analysis, predictive modeling, explainable and generative AI, and data-driven breeding decision support. We further discuss emerging AI applications, their current contributions to crop research and breeding, and the major considerations affecting their reliable and practical implementation. Collectively, this review provides a structured understanding of the roles of AI across the digital breeding process and offers guidance for future methodological development and practical application in crop improvement.

artificial intelligence↗
PubMed2026

Machine learning for population-level risk prediction of future cholangiocarcinoma.

BACKGROUND: The poor prognosis of cholangiocarcinoma (CCA) is largely driven by rapid, asymptomatic disease progression, which usually results in a late diagnosis in the absence of established screening strategies. An early, cost-effective, and universally applicable risk assessment strategy would therefore be valuable. METHODS: We developed machine learning (ML) models on prospective, multimodal data from 487,495 UK Biobank (UKB) participants, of whom 649 developed CCA during follow-up. Data from England (80%) were utilised for ML development via five-fold cross-validation, and then all models were tested on withheld data from Scotland, Wales, and Newcastle (20%). Iterative ablation studies reduced inputs from >150 features across demographic data, lifestyle, health records, blood parameters, genomics, and metabolomics to models built on five and ten routinely available clinical parameters. These were externally validated in the Penn Medicine Biobank (PMBB; n = 2638; 28 CCA), All of Us Research Program (AOU; n = 330,433; 362 CCA), Japan Medical Data Centre Claims Database (JMDC; n = 8,425,522; 723 CCA) and TriNetX (n = 728,886; 1592 CCA). FINDINGS: We show that ML models integrating biliary-disease associated health records and Gamma glutamyltransferase can stratify risk of future CCA. Evaluation on the UKB test set as well as three independent cohorts revealed robust performance and generalisability across ethnicities. We achieved AUROCs of 0.71 [95% CI: 0.703-0.711], 0.77 [95% CI: 0.764-0.778 ], 0.796 [95% CI: 0.795-0.798] and 0.8 [95% CI: 0.794-0.805] for UKB, PMBB, AOU, and JMDC respectively, with respective AUPRCs of 0.014 [95% CI: 0.009-0.018], 0.042 [95% CI: 0.037-0.048], 0.038 [95% CI: 0.033-0.042] and 0.001 [95% CI: 0.001-0.001]. In AOU, application of the Youden J-optimised threshold yielded a number needed to screen of 79. Separate models for intra- and extrahepatic CCA did not improve performance. In line with the pathophysiology, performance declined for longer intervals between assessment and event. A group-level analysis in the TriNetX cohort revealed hazard ratios of up to 82.5 [95% CI: 26.4-257.96]. We provide extensive interpretability results and release all source codes used to develop the presented models. INTERPRETATION: We provide a comprehensive framework for early CCA risk stratification in the general population, identifying key predictors, and demonstrating the potential of data-driven models in personalised screening for hepatobiliary cancer. FUNDING: German Cancer Aid (grant #70115730), Junior Principal Investigator Fellowship programme of RWTH Aachen Excellence strategy.

Humans↗
PubMed2025

Evolution and applications of genome-scale metabolic models in yeast systems biology studies.

Genome-scale metabolic models (GEMs) can be used to simulate the metabolic network of an organism in a systematic and holistic way. Different yeast species, including Saccharomyces cerevisiae, have emerged as powerful cell factories for bioproduction. Recently, with the dedicated efforts from the scientific community, significant progress has been made in the development of yeast GEMs. Numerous versions of yeast GEMs and the derived multiscale models have been released, facilitating integrative omics analysis and rational strain design for different types of yeast cell factories. These advancements reflected the evolution and maturation of yeast GEMs together with a model ecosystem around them. This review will summarize the development and expansion of yeast GEMs and discuss their applications in yeast systems biology studies. It is anticipated that yeast GEMs will continue to play an increasingly important role in pioneering yeast physiological and metabolic studies in coming years.

Systems Biology↗
PubMed2025

Through the lens of bioenergy crops: advances, bottlenecks, and promises of plant engineering.

Advances in engineering of bioenergy crops were driven over the past years by adapting technological breakthroughs and accelerating conventional applications but also exposed intriguing challenges. New tools revealed rich interconnectivity in the exponentially growing and dynamic 'big' omics data' of metabolomes, transcriptomes, and genomes at previously inaccessible magnitude (global, cross-species, meta-) and resolution (single cell). Insights enabled fresh hypotheses and stimulated disciplines such as functional genomics with discovery of broad regulatory networks and their determinants, that is, DNA parts, including promoters, regulatory elements, and transcription factors. Their rational design, assembly into increasingly complex blueprints, and installation into diverse chassis is an existing frontier that may benefit from emerging technologies to address bottlenecks. Interweaving nature-inspired to fully synthetic parts has already allowed building of fine-tuned regulatory circuits, or new-to-nature metabolic routes insulated from the biological context of the chassis species. Similarly, developments and the evolving need for unifying principles in plant transformation and species-agnostic technologies highlight future opportunities for engineering the next generation of bioenergy plants.

Crops, Agricultural↗
PubMed2001

[Prenatal effects of acetylsalicylic acid].

Acetylsalicylic acid is frequently ingested over-the-counter (OTC) drug, either as single or in combination with other drugs. It has been used in various diseases including that complicated pregnancy, such as preeclampsia and fetal grow retardation. Analgesic, antipyretic, especially anti-inflammatory activity occurs in high therapeutic doses. In low-dose acetylsalicylic acid is used to block production of thromboxane A2. Big epidemiological data suggest that low-dose of acetylsalicylic acid, even taken chronically, is safe for mother and fetus. However, animal and various human data have shown that high doses of the drug could produce different congenital malformations. The current literature suggests that acetylsalicylic acid should be given in pregnancy only if the potential benefit justifies the potential risk to the fetus. Anti-inflammatory doses should be stopped in the third trimester of gestation or given if the drug is needed in life-threatening situation or for serious disease for which safer drugs can not be used or are ineffective.

Abnormalities, Drug-Induced↗
PubMed1975

Biochemical properties of big renin extracted from human plasma.

The properties of big renin, a relatively inactive form of renin isolated from human plasma, were examined following partial purification by gel filtration. Exposure of big renin to pH 3.0-3.6, or brief incubation with trypsin or pepsin, resulted in a ten-fold increase in enzymatic activity. Activation was not effected by 4M NaCl, 6M urea, or incubation with neuraminidase. Both before and after inactivation, big renin eluted from Sephadex gel more rapidly than normal plasma renin. During polyacrylamide gel disc electrophoresis, inactive big renin migrated more slowly than either normal renin or big renin previously activated. Using sheep substrate, the enzyme kinetics of normal renin and previously activated big renin were identical, while inactive big renin possessed a higher Michaelis constant. These data indicate that big renin is closely related biochemically to normal plasma renin. As the activation of big renin results in the formation of the substance even more similar to normal renin, the possibility exists that big renin may prove to be a precursor form of normal renin.

Chromatography, Gel↗
PubMed1984

Discrepancy between immunoactivity and bioactivity of big-big and big human growth hormones in acromegaly.

The heterogeneity of hGH in the sera, culture media of tumor cells and tumor extract from acromegalic patients was studied employing gel chromatography, RIA and lymphoma cell bioassay. The chromatographic profile of the sera on Sephadex G-100 (superfine) column showed three peaks: the major peak eluted with 125I-hGH (little hGH), the less retarded small peak (big hGH) and the peak at void volume (big-big hGH). Bioassay to radioimmunoassay ratio of big-big, big and little hGH were 1.07-5.75, 0.25-0.70 and 0.70-1.56, respectively. These ratios were not significantly different among the acromegalic sera obtained before and after TRH test. The longer duration sera were kept for, the higher percent of big-big hGH and the lower percent of little hGH the sera contained by RIA. The percentage of big-big hGH was less in the culture media of tumor cells than that in acromegalic sera, and the least in tumor extract by RIA. Rechromatography of big-big hGH fraction of tumor extract showed the conversion of big-big hGH to big and little hGHs. These data suggest that big-big hGH was artificially made from little and big hGH during storage. Rechromatography of fractions between big-big hGH and big hGH produced another peak (medium-big hGH) with approximately 80 K-90 K daltons of molecular weight. This peak was converted to almost a little hGH peak after mercaptoethanol treatment and was supposed to be a tetramer of little hGH.

Acromegaly↗
PubMed2005

Trajectories of Marijuana Use During the Transition to Adulthood: The Big Picture Based on National Panel Data.

The purposes of this study were to: a) identify trajectory groups of frequent marijuana use during emerging adulthood, b) distinguish among trajectory groups according to demographic and lifestyle characteristics, and c) examine how the trajectory groups relate to behavioral, attitudinal, and social-emotional correlates over time. National panel data from the Monitoring the Future study were used: 18 cohorts of high school seniors (classes of 1977-94) were followed biennially through age 24. Frequent marijuana use was defined as 3+ occasions of use in past month and/or 20 to 40+ occasions in past year. Based on four waves of complete longitudinal data (N=19,952), six frequent marijuana use trajectory groups were identified: chronic, decreased, increased, fling, rare, and abstain. Categorical analyses revealed trajectory group differences in demographic and lifestyle characteristics at senior year and age 24. The trajectory groups varied significantly in longitudinal patterns of other substance use, problem behaviors, and well-being.

Journal Article↗