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At least 865 records · Page 48Linked to original sources

PubMed2004

Estimation of the non-isothermal inactivation patterns of Bacillus sporothermodurans IC4 spores in soups from their isothermal survival data.

The isothermal survival curves of the heat resistant spores of Bacillus sporothermodurans IC4, in the range of 117-125 degrees C, were determined in chicken, mushroom and pea soups by the capillary method. They were all non-linear with a noticeable upper concavity and could be described by the equation log(10) [N(t)/N(0)]=-b(T)t(n) with a fixed power, n, of the order of 0.7-0.8. The temperature dependence of b(T) could be described by the equation b(T)=log(e)[1+exp[k(T-T(c))]], where T(c) is the temperature where intensive inactivation starts and k is the slope of b(T) at temperatures well above T(c). They were 121-123 degrees C and 0.2-0.4 degrees C(-1), respectively, depending on the soup. These parameters were used to estimate the survival curves of the spores in two non-isothermal heat treatments using the procedure originally proposed by Peleg and Penchina [Crit. Rev. Food Sci. Nutr. 40 (2000) 159]. The results were compared with experimental survival curves, determined by the direct injection method, in another laboratory. There was a general agreement, although not perfect, between the predicted and experimentally observed survival ratios. Also, the isothermal survival parameters, estimated directly from the non-isothermal inactivation data using the model, were in general agreement with those calculated from the isothermal data. This suggests that the heat inactivation patterns of B. sporothermodurans IC4 spores in soups can be at least roughly estimated using the same general survival model, which has until now only been experimentally validated for vegetative bacterial cells.

Agaricales↗

PubMed2004

Shear distribution and variability in the USP Apparatus 2 under turbulent conditions.

Computational analysis is used to examine the hydrodynamic environment within the USP Apparatus II at common operating conditions. Experimental validation of the computational model shows that the simulations of fluid motion match the dispersion of dye observed in experiments. The computations are then used to obtain data that cannot be easily measured with experiments, specifically the distribution of shear forces within the media and along the wall. Results show that the shear environment is highly non-uniform. Increasing the paddle speed from 50 to 100 rpm does not improve shear homogeneity within the apparatus. Experiments show that this uneven distribution of hydrodynamic forces is a direct cause of dissolution testing variability. This variability is large enough to cause for type II dissolution test failures, i.e., failures are a result of a vulnerability of the testing method rather than a problem with a dosage form. Future development of new dissolution tests should include evaluations of the hydrodynamic environments to eliminate this potential source of failure that is unrelated to product quality.

Chemistry, Pharmaceutical↗

PubMed2005

(144)Ce as a potential candidate for interstitial and intravascular brachytherapy.

PURPOSE: To investigate the suitability of (144)Ce for both interstitial and intravascular brachytherapy applications. METHODS AND MATERIALS: Monte Carlo calculations of radial dose rate distributions in water were performed for (144)Ce in a spring-shaped source and compared with two commonly used interstitial and intravascular sources, (192)Ir and (32)P. The numeric simulations were checked experimentally with a calibrated ionization chamber in a water phantom. Other source characteristics, such as half-life and specific activity, were also compared. RESULTS: For interstitial brachytherapy, (144)Ce presents dosimetric advantages over (192)Ir in terms of higher dose rate at shorter distances and lower irradiation of organs outside the tumor. The source size and shape reduce the anisotropy and the number of dwell positions necessary. The longer half-life of (144)Ce might also be advantageous over (192)Ir. For intravascular brachytherapy, (144)Ce permits the treatment of larger arteries as compared with (32)P, compensates centering errors more effectively, and has a more suitable half-life. The experimental validation showed good agreement (within 10%) with the Monte Carlo simulated dose rate distributions. CONCLUSIONS: There are certain potential advantages of using (144)Ce as a source for both interstitial and intravascular brachytherapy. The basis for this finding is provided by the Monte Carlo radial dose rate comparisons with (192)Ir and (32)P, as well as by such characteristics as half-life and specific activity.

Brachytherapy↗

PubMed2025

Redistribution of super-enhancers promotes malignancy in human hepatocellular carcinoma.

INTRODUCTION: Super-enhancers (SEs) are defined as the regulatory region where intensive transcriptional cofactors bind. Dysregulation of SEs is related to multiple diseases, however, its role in hepatocellular carcinoma (HCC) remains elusive. OBJECTIVES: This work aimed to reveal the dysregulation of SEs in HCC and the therapeutic potential for HCC treatment. METHODS: Fifteen HCC and twelve paracancerous samples underwent chromatin immunoprecipitation (ChIP) sequencing targeting H3K27ac, and subsequently the SEs were identified by the Rank Ordering of Super-Enhancers algorithm. Differential SEs featured by tumor or paracancerous tissues were identified, and cross-referenced with the differential expression genes and prognosis-related genes in 2 independent public or in-house HCC cohorts. The SE region of HSPA4 was deleted in the genome of HCCLM3 cell by CRISPR-Cas9, named HSPA4-SE-KO cells. The potential druggable transcriptional factors were identified by CRCmapper, GeneMANIA and Drug Gene Interaction Database (DGID). RESULTS: Five targets, including CDKN2C, HSPA4, GGH, PDGFA, and CAP2, were identified as HCC-gain SEs with oncogenic potential, which were further validated experimentally by SE inhibitors and ChIP targeting H3K27ac and BRD4. Cell proliferation and migration assays further confirmed that silencing of these HCC-gain SEs significantly suppressed the malignant phenotype of HCC cell lines. HSPA4 appeared strongest oncogenic functions among these targets, which was further verified by HCC mouse xenograft models and clinical sample investigation. Moreover, HSPA4-SE-KO cells obtained significantly suppressed HSPA4 expression and retarded tumorigenic capability. Finally, dysregulation of transcriptional factors engaged in the oncogenic role of SEs, and Danthron that targeting RXRA were identified from DGID for HCC treatment. CONCLUSION: The dysregulated SE landscape of HCC promoted the malignancy phenotype by the upregulation of oncogenes, and SE-regulatory network might be potential drug targets for HCC treatment. Our study deepened the insight of epigenetic dysregulation in HCC, offering the groundwork for SEs as potential therapeutic targets of HCC treatment.

Humans↗

PubMed2026

Functional screening of ZIP8 naturally occurring variants identifies pathogenic mutations and trafficking defects.

The rapid expansion of human genomic data has revealed a large number of naturally occurring variants, creating a major challenge for functional annotation. The human metal transporter SLC39A8 (ZIP8) is a clinically important divalent metal transporter, yet most of its documented variants remain uncharacterized. Here, we developed a workflow to functionally evaluate ZIP8 variants by integrating laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) with scaled-up cell-based transport assays. Using this method, we systematically analyzed 33 naturally occurring missense variants located in the extracellular domain (ECD) of ZIP8. The assay enables direct quantification of intracellular metal accumulation with substantially improved throughput (∼150 samples per hour). Functional screening identified 14 potential pathogenic variants with significantly reduced transport activity. Comparison with computational predictions revealed a moderate correlation between activity and AlphaMissense pathogenicity scores (R2 = 0.423), while an error rate of ∼20% for AlphaMissense underscores the need for experimental validation. Flow cytometry analysis showed that most loss-of-function variants exhibit impaired trafficking of the protein to the cell surface possibly due to mutation-caused protein misfolding or instability. Structural mapping of activity-compromised variants, together with functional assessment of the ZIP8-ECD, highlights the importance of this domain in ZIP8 expression and intracellular protein trafficking. Together, this work establishes a scalable approach for functional screening of metal transporter variants and provides new insights into the structure-function relationships of ZIP8.

Journal Article↗

PubMed2006

Beyond the data deluge: data integration and bio-ontologies.

Biomedical research is increasingly a data-driven science. New technologies support the generation of genome-scale data sets of sequences, sequence variants, transcripts, and proteins; genetic elements underpinning understanding of biomedicine and disease. Information systems designed to manage these data, and the functional insights (biological knowledge) that come from the analysis of these data, are critical to mining large, heterogeneous data sets for new biologically relevant patterns, to generating hypotheses for experimental validation, and ultimately, to building models of how biological systems work. Bio-ontologies have an essential role in supporting two key approaches to effective interpretation of genome-scale data sets: data integration and comparative genomics. To date, bio-ontologies such as the Gene Ontology have been used primarily in community genome databases as structured controlled terminologies and as data aggregators. In this paper we use the Gene Ontology (GO) and the Mouse Genome Informatics (MGI) database as use cases to illustrate the impact of bio-ontologies on data integration and for comparative genomics. Despite the profound impact ontologies are having on the digital categorization of biological knowledge, new biomedical research and the expanding and changing nature of biological information have limited the development of bio-ontologies to support dynamic reasoning for knowledge discovery.

Animals↗

PubMed2004

Load transfer across the scapula during humeral abduction.

Stress analysis in the individual parts of the scapula under normal physiological conditions is necessary to understand the load transfer mechanism, its relation with morphology of bone and to analyse the deviations in stress patterns due to implantation of the glenoid. The purpose of this study was to obtain stress distribution in the scapula during abduction of the arm and to obtain a qualitative estimate of the function of coracoacromial ligament. An accurate three-dimensional (3D) finite element (FE) model of the natural scapula has been developed for this purpose, using computed tomography data and shell-solid modelling approach. The model was experimentally validated. A musculoskeletal shoulder model of forces that calculates all muscle, ligament and joint reaction forces, in six load cases (30-180 degrees) during unloaded humeral abduction was used as applied loading conditions for the 3D FE model. High tensile and compressive stresses (15-60 MPa) were generated in the thick bony ridges of the scapula, like the scapular spine, lateral border, glenoid and acromion. High compressive stresses (45-58 MPa) were evoked in the glenoid and at the connection of glenoid-scapular spine-infraspinous fossa. The stresses in the infraspinous fossa and supraspinous fossa were low (0.05-15 MPa). These results indicated that the transfer of major muscle and joint reaction take place predominantly through the thick bony ridges, whereas the fossa area act more as attachment sites of large muscles. During humeral abduction, coracoacromial ligament was stretched, and presumably will be under tension.

Biomechanical Phenomena↗

PubMed2005

Computational analysis of type II endoleaks in a stented abdominal aortic aneurysm model.

Insertion of a stent-graft into an aneurysm to form a new (synthetic) blood vessel and prevent the weakened artery wall from rupture is an attractive surgical intervention when compared to traditional open surgery. However, focusing on a stented abdominal aortic aneurysm (AAA), post-operative complications such as endoleaks may occur. An endoleak is the net influx of blood during the cardiac cycle into the cavity (or sac) formed by the stent-graft and the AAA wall. A natural endoleak source may stem from one or two secondary branches leading to and from the aneurysm, labeled types IIa and IIb endoleaks. Employing experimentally validated fluid-structure interaction solvers, the transient 3-D lumen and cavity blood flows, wall movements, pressure variations, maximum wall stresses and migration forces were computed for types IIa and IIb endoleaks. Simulation results indicate that the sac pressure caused by these endoleaks depends largely on the inlet branch pressure, where the branch inlet pressure increases, the sac pressure may reach the systemic level and AAA-rupture is possible. The maximum wall stress is typically located near the anterior-distal side in this model, while the maximum stent-graft stress occurs near the bifurcating point, in both cases, due to local stress concentrations. The time-varying leakage rate depends on the pressure difference between AAA sac and inlet branch. In contrast, the stent-graft migration force is reduced by type II endoleaks because it greatly depends on the pressure difference between the stent-graft and the aneurysm cavity.

Algorithms↗

PubMed2006

Open-loop control of the biomass concentration within the growth phase of recombinant protein production processes.

Recombinant protein production processes are typically divided into two phases. In the first one, pure cell propagation takes place, while in the second one product formation is switched on within the cells by adding an inducer. In the initial biomass formation phase, the cell density is rather low and, hence, the measurement quantities that could be used to determine the process' state depict small values and are rather severely distorted by measurement noise. Because of these measurement problems, the fermentation cannot be reliably controlled by feedback control during this first production phase; instead, the process must be controlled in an open-loop fashion. The consequence, worked out in this paper, is to design substrate feed rate profiles for the growth phase in such a way that they are robust with respect to the main disturbances observed in practice. The robustness of the biomass formation is shown to be primarily dependent on the specific growth rate adjusted in the first hours. High batch-to-batch reproducibility can be obtained with exponential feeding profiles F(t) corresponding to specific growth rates micro(set) well below the maximal specific growth rate micro(max) of the organism. The reduction in the growth rate needed to obtain a robust process behavior depends on the inaccuracies in the initial biomass concentrations. Quantitative feed rate profiles were obtained by numerical simulation and these results were validated experimentally by means of a series of cultivation runs, where a recombinant pharmaceutical protein was produced. All experimental data confirmed the assumptions made in the robust process design study.

Bacteria↗

PubMed2026

pKAKA: a protein language model for prioritizing kinase-disrupting variants in diseases.

Protein kinases are pivotal regulators of cellular signaling, and their genetic variations are frequently implicated in diseases. Although numerous kinase mutations have been identified as drivers of altered activity, with a few successfully targeted therapeutically, the functional impact of most variants remains uncharacterized. To bridge this gap, we curate a comprehensive dataset that contains 2553 experimentally validated kinase activity-related key alterations (KAKAs) from the literature. While many mutations outside canonical functional regions are known to affect kinase activity, systematic methods to predict their functional consequences are lacking. Consequently, we develop a computational method to predict potential KAKAs, leveraging transfer learning on the pre-trained protein language model ProtBert. Our model, termed pKAKA, achieves an impressive AUC score of 0.9593 and outperforms the AlphaMissense benchmark in comparative testing. Systematic analysis of kinase missense mutations underscores the critical role of KAKAs in pathogenesis, with highlights including JAK2 V617F in atherosclerotic cardiovascular disease, LRRK2 G2385R in Parkinson's disease, EGFR L858R in lung adenocarcinoma, and EGFR G598V in glioma. Overall, this study significantly advances our understanding of how mutations that influence kinase activity contribute to disease mechanisms.

Humans↗

PubMed2026

Probiotic potential of Parabacteroides johnsonii in mitigating age-related ovarian functional decline.

The gut microbiota is increasingly recognized as a regulator of reproductive health, yet its role in ovarian aging remains unclear. Here, we combine Mendelian randomization (MR) analysis with experimental validation to investigate the causal relationship between gut microbiota and ovarian aging. MR analysis identifies four microbial taxa significantly associated with age at natural menopause. In mouse models, germ-free mice exhibit accelerated ovarian functional decline, including reduced ovarian reserve and impaired folliculogenesis. Fecal microbiota transplantation (FMT) from young donors alleviates ovarian aging phenotypes, whereas FMT from aged donors exacerbates functional decline. Metagenomic analysis reveals species-level differences between young and ovarian-aging mice, with Parabacteroides johnsonii (P. johnsonii) enriched in young mice. Administration of P. johnsonii to middle-aged mice improves ovarian reserve, reduces follicular atresia, enhances granulosa cell proliferation, and decreases systemic inflammation. These findings highlight a causal role of the gut microbiota in ovarian aging and support microbiota-targeted interventions as a potential strategy to preserve ovarian function.

Female↗

PubMed2003

Parameterization and classification of the protein universe via geometric techniques.

We present a scheme for the classification of 3487 non-redundant protein structures into 1207 non-hierarchical clusters by using recurring structural patterns of three to six amino acids as keys of classification. This results in several signature patterns, which seem to decide membership of a protein in a functional category. The patterns provide clues to the key residues involved in functional sites as well as in protein-protein interaction. The discovered patterns include a "glutamate double bridge" of superoxide dismutase, the functional interface of the serine protease and inhibitor, interface of homo/hetero dimers, and functional sites of several enzyme families. We use geometric invariants to decide superimposability of structural patterns. This allows the parameterization of patterns and discovery of recurring patterns via clustering. The geometric invariant-based approach eliminates the computationally explosive step of pair-wise comparison of structures. The results provide a vast resource for the biologists for experimental validation of the proposed functional sites, and for the design of synthetic enzymes, inhibitors and drugs.

Algorithms↗

PubMed2004

Insight into molecular interactions between two PB1 domains.

Specific protein-protein interactions play crucial roles in the regulation of any biological process. Recently, a new protein-protein interaction domain termed PB1 (Phox and Bem1) was identified, which is conserved throughout evolution and present in diverse proteins functioning in signal transduction, cell polarity and survival. Here, we investigated the structure and molecular interactions of the PB1 heterodimer complex composed of the PB1 domains of the yeast proteins Bem1 and Cdc24. A structural model of the Cdc24 PB1 was built by homology modeling and molecular dynamics simulations, and experimentally validated by 15N nuclear Overhauser effect spectroscopy (NOESY)-heteronuclear single quantum coherence (HSQC) analysis. Residues at the interface of the complex for both proteins were identified by NMR titration experiments. A model of the heterodimer was obtained by docking of the two PB1 domains with HADDOCK, which applies ambiguous interaction restraints on residues at the interface to drive the docking procedure. The refined model was validated by site-directed mutagenesis on both Bem1 and Cdc24. Finally, the docking was repeated from the newly published NMR structure of Cdc24, allowing us to assess the performance of homology-based docking. Our results provide insight into the molecular structure of the Bem1-Cdc24 PB1-mediated heterodimer, which allowed identification of critical residues at the binding interface.

Adaptor Proteins, Signal Transducing↗

PubMed2006

Integrated prediction of the helical membrane protein interactome in yeast.

At least a quarter of all genes in most genomes contain putative transmembrane (TM) helices, and helical membrane protein interactions are a major component of the overall cellular interactome. However, current experimental techniques for large-scale detection of protein-protein interactions are biased against membrane proteins. Here, we define protein-protein interaction broadly as co-complexation, and develop a weighted-voting procedure to predict interactions among yeast helical membrane proteins by optimally combining evidence based on diverse genome-wide information such as sequence, function, localization, abundance, regulation, and phenotype. We use logistic regression to simultaneously optimize the weights of all evidence sources for best discrimination based on a set of known helical membrane protein interactions. The resulting integrated classifier not only significantly outperforms classifiers based on any single genomic feature, but also does better than a benchmark Naïve Bayes classifier (using a simplifying assumption of conditional independence among features). Finally, we apply the optimized classifier genome-wide, and construct a comprehensive map of predicted helical membrane protein interactome in yeast. This can serve as a guide for prioritizing further experimental validation efforts.

Membrane Proteins↗

PubMed2004

A simple method to measure 13CH2 heteronuclear dipolar cross-correlation spectral densities.

Here, we report a method to simultaneously determine CH2 cross-correlation spectral densities and T1 relaxation times in the laboratory and rotating frames. To accomplish this, we have employed an indirect approach that is based on measurement of differences in relaxation rates acquired with and without cross-correlation terms. The new method, which can be employed using multidimensional NMR and standard relaxation pulse sequences, is validated experimentally by investigation of a selectively 13C-enriched hexadecapeptide and the uniformly 13C-enriched immunoglobulin-binding domain of streptococcal protein G (GB1). Use of this approach makes determination of CH2 cross-correlation spectral densities in uniformly 13C-enriched proteins now routine and provides novel information concerning their internal motions.

Bacterial Proteins↗

PubMed2005

Spatially encoded NMR and the acquisition of 2D magnetic resonance images within a single scan.

An approach that enables the acquisition of multidimensional NMR spectra within a single scan has been recently proposed and demonstrated. The present paper explores the applicability of such ultrafast acquisition schemes toward the collection of two-dimensional magnetic resonance imaging (2D MRI) data. It is shown that ideas enabling the application of these spatially encoded schemes within a spectroscopic setting, can be extended in a straightforward manner to pure imaging. Furthermore, the reliance of the original scheme on a spatial encoding and subsequent decoding of the evolution frequencies endows imaging applications with a greater simplicity and flexibility than their spectroscopic counterparts. The new methodology also offers the possibility of implementing the single-scan acquisition of 2D MRI images using sinusoidal gradients, without having to resort to subsequent interpolation procedures or non-linear sampling of the data. Theoretical derivations on the operational principles and imaging characteristics of a number of sequences based on these ideas are derived, and experimentally validated with a series of 2D MRI results collected on a variety of model phantom samples.

Algorithms↗

PubMed2006

Dynamics of paramagnetic agents by off-resonance rotating frame technique in the presence of magnetization transfer effect.

The simple method for measuring the rotational correlation time of paramagnetic ion chelates via off-resonance rotating frame technique is challenged in vivo by the magnetization transfer effect. A theoretical model for the spin relaxation of water protons in the presence of paramagnetic ion chelates and magnetization transfer effect is described. This model considers the competitive relaxations of water protons by the paramagnetic relaxation pathway and the magnetization transfer pathway. The influence of magnetization transfer on the total residual z-magnetization has been quantitatively evaluated in the context of the magnetization map and various difference magnetization profiles for the macromolecule conjugated Gd-DTPA in cross-linked protein gels. The numerical simulations and experimental validations confirm that the rotational correlation time for the paramagnetic ion chelates can be measured even in the presence of strong magnetization transfer. This spin relaxation model also provides novel approaches to enhance the detection sensitivity for paramagnetic labeling by suppressing the spin relaxations caused by the magnetization transfer. The inclusion of the magnetization transfer effect allows us to use the magnetization map as a simulation tool to design efficient paramagnetic labeling targeting at specific tissues, to design experiments running at low RF power depositions, and to optimize the sensitivity for detecting paramagnetic labeling. Thus, the presented method will be a very useful tool for the in vivo applications such as molecular imaging via paramagnetic labeling.

Algorithms↗

PubMed2006

A novel tracing algorithm for high throughput imaging Screening of neuron-based assays.

High throughput neuron image processing is an important method for drug screening and quantitative neurobiological studies. The method usually includes detection of neurite structures, feature extraction, quantification, and statistical analysis. In this paper, we present a new algorithm for fast and automatic extraction of neurite structures in microscopy neuron images. The algorithm is based on novel methods for soma segmentation, seed point detection, recursive center-line detection, and 2D curve smoothing. The algorithm is fully automatic without any human interaction, and robust enough for usage on images with poor quality, such as those with low contrast or low signal-to-noise ratio. It is able to completely and accurately extract neurite segments in neuron images with highly complicated neurite structures. Robustness comes from the use of 2D smoothening techniques and the idea of center-line extraction by estimating the surrounding edges. Efficiency is achieved by processing only pixels that are close enough to the line structures, and by carefully chosen stopping conditions. These make the proposed approach suitable for demanding image processing tasks in high throughput screening of neuron-based assays. Detailed results on experimental validation of the proposed method and on its comparative performance with other proposed schemes are included.

Algorithms↗