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In recent years, artificial intelligence (AI) has shown promising applications in various scientific domains, including biochemical analysis research. However, the effectiveness of AI in modeling small-scale, imbalanced datasets remains an open question in such fields. This study explores the capabilities of eight basic AI algorithms, including ridge regression, logistic regression, random forest regression, and others, in modeling a small, imbalanced clinical dataset (total n = 387, class 0 = 27, class 1 = 360) related to the records of the biochemical blood tests from the patients with multiple wasp stings (MWS). Through rigorous evaluation using k-fold cross-validation and comprehensive scoring, we found that none of the models could effectively model the data. Even after fine-tuning the hyperparameters of the best-performing models, the results remained below acceptable thresholds. The study highlights the challenges of applying AI to small-scale datasets with imbalanced groups in biochemical or clinical research and emphasizes the need for novel algorithms tailored to small-scale data. The findings also call for further exploration into techniques such as transfer learning and data augmentation, and they underline the importance of understanding the minimum dataset scale required for effective AI modeling in biochemical contexts. [ABSTRACT FROM AUTHOR]

Interstitial cystitis/painful bladder syndrome (IC/PBS) is a chronic disease for which no effective treatment is available. Transforming growth factor-β (TGF-β) is thought to be involved in the pathogenesis of IC/PBS, and previous studies have suggested that administrations of a TGF-β inhibitor significantly ameliorated IC/PBS in a mouse model. However, the molecular mechanisms underlying the therapeutic effect of a TGF-b inhibitor on IC/PBS has not been comprehensively analyzed. TGF-β has a variety of actions, such as regulation of immune cells and fibrosis. In our study, we induced IC/PBS-like disease in mice by an intravesical administration of hydrogen peroxide (H₂O₂) and examined the effects of three TGF-β inhibitors, Repsox, SB431542, and SB505124, on the urinary functions as well as histological and gene expression profiles in the bladder. TGF-β inhibitor treatment improved urinary function and histological changes in the IC/PBS mouse model, and SB431542 was most effective among the TGF-β inhibitors. In our present study, TGF-β inhibitor treatment improved abnormal enhancement of nociceptive mechanisms, immunity and inflammation, fibrosis, and dysfunction of bladder urothelium. These results show that multiple mechanisms are involved in the improvement of urinary function by TGF-β inhibitor. [ABSTRACT FROM AUTHOR]

Two well-established numerical representations of the coagulation cascade either initiated by the intrinsic system (Chatterjee et al., PLOS Computational Biology 2010) or the extrinsic system (Butenas et al., Journal of Biological Chemistry, 2004) were compared with thrombin generation assays under realistic pathological conditions. Biochemical modifications such as the omission of reactions not relevant to the case studied, the modification of reactions related to factor XI activation and auto-activation, the adaptation of initial conditions to the thrombin assay system, and the adjustment of some of the model parameters were necessary to align in vitro and in silico data. The modified models are able to reproduce thrombin generation for a range of factor XII, XI, and VIII deficiencies, with the coagulation cascade initiated either extrinsically or intrinsically. The results emphasize that when existing models are extrapolated to experimental parameters for which they have not been calibrated, careful adjustments are required. [ABSTRACT FROM AUTHOR]

The evolution of biochemical models is difficult to track. At present, it is not possible to inspect the differences between model versions at the network level. Biochemical models are often constructed in a distributed, non-linear process: collaborators create model versions on different branches from novel information, model extensions, during curation and adaption. To discuss and align the versions, it is helpful to abstract the changes to the network level. The differences between two model versions can be detected by the software tool BiVeS. However, it cannot show the structural changes resulting from the differences. Here, we present a method to visualise the differences between model versions effectively. We developed a JSON schema to communicate the differences at the network level and extended BiVeS accordingly. Additionally, we developed DiVil, a web-based tool to represent the model and the differences as a standardised network using D3. It combines an automatic layout with an interactive user interface to improve the visualisation and to inspect the model. The network can be exported in standardised formats as images or markup language. Our method communicates the structural differences between model versions. It facilitates the discussion of changes and thus supports the collaborative and non-linear nature of model development. Availability and implementation: DiVil prototype: https://divil.bio.informatik.uni-rostock.de, Code on GitHub: https://github.com/Gebbi8/DiVil, licensed under Apache License 2.0. Contact: url="tom.gebhardt@uni-rostock.de. [ABSTRACT FROM AUTHOR]

To infer the parameters of mechanistic models with intractable likelihoods, techniques such as approximate Bayesian computation (ABC) are increasingly being adopted. One of the main disadvantages of ABC in practical situations, however, is that parameter inference must generally rely on summary statistics of the data. This is particularly the case for problems involving high-dimensional data, such as biological imaging experiments. However, some summary statistics contain more information about parameters of interest than others, and it is not always clear how to weight their contributions within the ABC framework. We address this problem by developing an automatic, adaptive algorithm that chooses weights for each summary statistic. Our algorithm aims to maximize the distance between the prior and the approximate posterior by automatically adapting the weights within the ABC distance function. Computationally, we use a nearest neighbour estimator of the distance between distributions. We justify the algorithm theoretically based on properties of the nearest neighbour distance estimator. To demonstrate the effectiveness of our algorithm, we apply it to a variety of test problems, including several stochastic models of biochemical reaction networks, and a spatial model of diffusion, and compare our results with existing algorithms. [ABSTRACT FROM AUTHOR]

Protein structure alignment is an important tool for studying evolutionary biology and protein modeling. A tool which intensively searches for the globally optimal non-sequential alignments is rarely found. We propose ALIGN-CSA which shows improvement in scores, such as DALI-score, SP-score, SO-score and TM-score over the benchmark set including 286 cases. We performed benchmarking of existing popular alignment scoring functions, where the dependence of the search algorithm was effectively eliminated by using ALIGN-CSA. For the benchmarking, we set the minimum block size to 4 to prevent much fragmented alignments where the biological relevance of small alignment blocks is hard to interpret. With this condition, globally optimal alignments were searched by ALIGN-CSA using the four scoring functions listed above, and TM-score is found to be the most effective in generating alignments with longer match lengths and smaller RMSD values. However, DALI-score is the most effective in generating alignments similar to the manually curated reference alignments, which implies that DALI-score is more biologically relevant score. Due to the high demand on computational resources of ALIGN-CSA, we also propose a relatively fast local refinement method, which can control the minimum block size and whether to allow the reverse alignment. ALIGN-CSA can be used to obtain much improved alignment at the cost of relatively more extensive computation. For faster alignment, we propose a refinement protocol that improves the score of a given alignment obtained by various external tools. All programs are available from . [ABSTRACT FROM AUTHOR]

Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex systems. [ABSTRACT FROM AUTHOR]

Background: Although erythropoietin has been used for decades in the treatment of anemia, data regarding endogenous levels in the general population are scarce. Therefore, we determined erythropoietin reference ranges and its clinical, biochemical and genetic associations in the general population. Methods: We used data from 6,777 subjects enrolled in the Prevention of REnal and Vascular ENd-stage Disease (PREVEND) study. Fasting venous blood samples were obtained in the morning from all participants from 2001–2003. Serum erythropoietin concentrations were measured using a fully automated chemiluminescent enzyme-labeled immunometric assay. A genome-wide association study was performed to identify genetic determinants. Results: Mean age (± SD) was 53 ± 12 years and 50% were female. Median (IQR) erythropoietin concentrations were 7.6 (5.8–9.9) IU/L in men and 7.9 (6.0–10.6) IU/L in women. A strong positive correlation was found between erythropoietin and waist circumference, glucose and systolic blood pressure (all P < 0.05). In subjects with normal renal function there was a strong exponential relation between hemoglobin and erythropoietin, whereas in renal impairment (eGFR < 60 mL/min/1.73m²) this relation was linear (men) or absent (women) (P < 0.001 for interaction). Single-nucleotide polymorphisms at the HBS1L-MYB locus were shown to be related to erythropoietin levels (P < 9x10-21), more significantly than other erythrocyte parameters. Conclusion: We provide age-specific reference ranges for endogenous serum erythropoietin. Erythropoietin levels are positively associated with the components of the metabolic syndrome, except cholesterol. We show that even mild renal failure blunts erythropoietin production and propose the HBS1L-MYB locus as a regulator of erythropoietin. [ABSTRACT FROM AUTHOR]

Cheese ripening is a complex biochemical process driven by microbial communities composed of both eukaryotes and prokaryotes. Surface-ripened cheeses are widely consumed all over the world and are appreciated for their characteristic flavor. Microbial community composition has been studied for a long time on surface-ripened cheeses, but only limited knowledge has been acquired about its in situ metabolic activities. We applied metagenomic, metatranscriptomic and biochemical analyses to an experimental surface-ripened cheese composed of nine microbial species during four weeks of ripening. By combining all of the data, we were able to obtain an overview of the cheese maturation process and to better understand the metabolic activities of the different community members and their possible interactions. Furthermore, differential expression analysis was used to select a set of biomarker genes, providing a valuable tool that can be used to monitor the cheese-making process. [ABSTRACT FROM AUTHOR]

Malignant transformation results in abnormal cell cycle regulation and uncontrolled growth in head and neck squamous cell carcinoma (HNSCC) and other cancers. S100A8/A9 (calprotectin) is a calcium-binding heterodimeric protein complex implicated in cell cycle regulation, but the specific mechanism and role in cell cycle control and carcinoma growth are not well understood. In HNSCC, S100A8/A9 is downregulated at both mRNA and protein levels. We now report that downregulation of S100A8/A9 correlates strongly with a loss of cell cycle control and increased growth of carcinoma cells. To show its role in carcinogenesis in an in vitro model, S100A8/A9 was stably expressed in an S100A8/A9-negative human carcinoma cell line (KB cells, HeLa-like). S100A8/A9 expression increases PP2A phosphatase activity and p-Chk1 (Ser345) phosphorylation, which appears to signal inhibitory phosphorylation of mitotic p-Cdc25C (Ser216) and p-Cdc2 (Thr14/Tyr15) to inactivate the G2/M Cdc2/cyclin B1 complex. Cyclin B1 expression then downregulates and the cell cycle arrests at the G2/M checkpoint, reducing cell division. As expected, S100A8/A9-expressing cells show both decreased anchorage-dependent and -independent growth and mitotic progression. Using shRNA, silencing of S100A8/A9 expression in the TR146 human HNSCC cell line increases growth and survival and reduces Cdc2 inhibitory phosphorylation at Thr14/Tyr15. The level of S100A8/A9 endogenous expression correlates strongly with the reduced p-Cdc2 (Thr14/Tyr14) level in HNSCC cell lines, SCC-58, OSCC-3 and UMSCC-17B. S100A8/A9-mediated control of the G2/M cell cycle checkpoint is, therefore, a likely suppressive mechanism in human squamous cell carcinomas and may suggest new therapeutic approaches. [ABSTRACT FROM AUTHOR]

Prion diseases are classically characterized by the accumulation of pathological prion protein (PrPSc) with the protease resistant C-terminal fragment (PrPres) of 27–30 kDa. However, in both humans and animals, prion diseases with atypical biochemical features, characterized by PK-resistant PrP internal fragments (PrPres) cleaved at both the N and C termini, have been described. In this study we performed a detailed comparison of the biochemical features of PrPSc from atypical prion diseases including human Gerstmann-Sträussler-Scheinker disease (GSS) and variably protease-sensitive prionopathy (VPSPr) and in small ruminant Nor98 or atypical scrapie. The kinetics of PrPres production and its cleavage sites after PK digestion were analyzed, along with the PrPSc conformational stability, using a new method able to characterize both protease-resistant and protease-sensitive PrPSc components. All these PrPSc types shared common and distinctive biochemical features compared to PrPSc from classical prion diseases such as sporadic Creutzfeldt-Jakob disease and scrapie. Notwithstanding, distinct biochemical signatures based on PrPres cleavage sites and PrPSc conformational stability were identified in GSS A117V, GSS F198S, GSS P102L and VPSPr, which allowed their specific identification. Importantly, the biochemical properties of PrPSc from Nor98 and GSS P102L largely overlapped, but were distinct from the other human prions investigated. Finally, our study paves the way towards more refined comparative approaches to the characterization of prions at the animal–human interface. [ABSTRACT FROM AUTHOR]

Natural environments represent an incredible source of microbial genetic diversity. Discovery of novel biomolecules involves biotechnological methods that often require the design and implementation of biochemical assays to screen clone libraries. However, when an assay is applied to thousands of clones, one may eventually end up with very few positive clones which, in most of the cases, have to be "domesticated" for downstream characterization and application, and this makes screening both laborious and expensive. The negative clones, which are not considered by the selected assay, may also have biotechnological potential; however, unfortunately they would remain unexplored. Knowledge of the clone sequences provides important clues about potential biotechnological application of the clones in the library; however, the sequencing of clones one-by-one would be very time-consuming and expensive. In this study, we characterized the first metagenomic clone library from the feces of a healthy human volunteer, using a method based on 454 pyrosequencing coupled with a clone-by-clone Sanger end-sequencing. Instead of whole individual clone sequencing, we sequenced 358 clones in a pool. The medium-large insert (7-15 kb) cloning strategy allowed us to assemble these clones correctly, and to assign the clone ends to maintain the link between the position of a living clone in the library and the annotated contig from the 454 assembly. Finally, we found several open reading frames (ORFs) with previously described potential medical application. The proposed approach allows planning ad-hoc biochemical assays for the clones of interest, and the appropriate sub-cloning strategy for gene expression in suitable vectors/hosts. [ABSTRACT FROM AUTHOR]

A novel procedure is presented which, by balancing elements and electric charge of biochemical reactions which occur at constant pH and pMg, allows assessing the thermodynamics properties of reaction ΔrG'0, ΔrH'0, ΔrS'0 and the change in binding of hydrogen and magnesium ions of these reactions. This procedure of general applicability avoids the complex calculations required by the use of the Legendre transformed thermodynamic properties of formation ΔfG'0, ΔfH'0 and ΔfS'0 hitherto considered an obligatory prerequisite to deal with the thermodynamics of biochemical reactions. As a consequence, the term ''conditional'' is proposed in substitution of ''Legendre transformed'' to indicate these thermodynamics properties. It is also shown that the thermodynamic potential G is fully adequate to give a criterion of spontaneous chemical change for all biochemical reactions and then that the use of the Legendre transformed G' is unnecessary. The procedure proposed can be applied to any biochemical reaction, making possible to re-unify the two worlds of chemical and biochemical thermodynamics, which so far have been treated separately. [ABSTRACT FROM AUTHOR]

Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems. [ABSTRACT FROM AUTHOR]

Background: We have showed that secretory Apolipoprotein J/Clusterin (sCLU) is down-regulated in senescent, stressed or diseased red blood cells (RBCs). It was hypothesized that sCLU loss relates to RBCs vesiculation, a mechanism that removes erythrocyte membrane patches containing defective or potentially harmful components. Methodology/Principal Findings: To investigate this issue we employed a combination of biochemical and microscopical approaches in freshly prepared RBCs or RBCs stored under standard blood bank conditions, an in vitro model system of cellular aging. We found that sCLU is effectively exocytosed in vivo during membrane vesiculation of freshly prepared RBCs. In support, the RBCs' sCLU content was progressively reduced during RBCs ex vivo maturation and senescence under cold storage due to its selective exocytosis in membrane vesicles. A range of typical vesicular components, also involved in RBCs senescence, like Band 3, CD59, hemoglobin and carbonylated membrane proteins were found to physically interact with sCLU. Conclusions/Significance: The maturation of RBCs is associated with a progressive loss of sCLU. We propose that sCLU is functionally involved in the disposal of oxidized/defected material through RBCs vesiculation. This process most probably takes place through sCLU interaction with RBCs membrane proteins that are implicit vesicular components. Therefore, sCLU represents a pro-survival factor acting for the postponement of the untimely clearance of RBCs. [ABSTRACT FROM AUTHOR]

Background: Secretory Apolipoprotein J/Clusterin (sCLU) is a ubiquitously expressed chaperone that has been functionally implicated in several pathological conditions of increased oxidative injury, including aging. Nevertheless, the biological role of sCLU in red blood cells (RBCs) remained largely unknown. In the current study we identified sCLU as a component of human RBCs and we undertook a detailed analysis of its cellular topology. Moreover, we studied the erythrocytic membrane sCLU content during organismal aging, in conditions of increased organismal stress and accelerated RBCs senescence, as well as during physiological in vivo cellular senescence. Methodology/Principal Findings: By using a combination of molecular, biochemical and high resolution microscopical methods we found that sCLU is a novel structural component of RBCs extra- and intracellular plasma membrane and cytosol. We observed that the RBCs membrane-associated sCLU decreases during organismal aging or exposure to acute stress (e.g. smoking), in patients with congenital hemolytic anemia, as well as during RBCs in vivo senescence. In all cases, sCLU reduction paralleled the expression of typical cellular senescence, redox imbalance and erythrophagocytosis markers which are also indicative of the senescence- and oxidative stress-mediated RBCs membrane vesiculation. Conclusions/Significance: We propose that sCLU at the mature RBCs is not a silent remnant of the erythroid precursors, but an active component being functionally implicated in the signalling mechanisms of cellular senescence and oxidative stress-responses in both healthy and diseased organism. The reduced sCLU protein levels in the RBCs membrane following cell exposure to various endogenous or exogenous stressors closely correlates to the levels of cellular senescence and redox imbalance markers, suggesting the usefulness of sCLU as a sensitive biomarker of senescence and cellular stress. [ABSTRACT FROM AUTHOR]