Differential diagnosis of bone marrow failure syndromes guided by machine learning.

The choice to postpone treatment while awaiting genetic testing can result in significant delay in definitive therapies in patients with severe pancytopenia. Conversely, the misdiagnosis of inherited bone marrow failure (BMF) can expose patients to ineffectual and expensive therapies, toxic transplant conditioning regimens, and inappropriate use of an affected family member as a stem cell donor. To predict the likelihood of patients having acquired or inherited BMF, we developed a 2-step data-driven machine-learning model using 25 clinical and laboratory variables typically recorded at the initial clinical encounter. For model development, patients were labeled as having acquired or inherited BMF depending on their genomic data. Data sets were unbiasedly clustered, and an ensemble model was trained with cases from the largest cluster of a training cohort (n = 359) and validated with an independent cohort (n = 127). Cluster A, the largest group, was mostly immune or inherited aplastic anemia, whereas cluster B comprised underrepresented BMF phenotypes and was not included in the next step of data modeling because of a small sample size. The ensemble cluster A-specific model was accurate (89%) to predict BMF etiology, correctly predicting inherited and likely immune BMF in 79% and 92% of cases, respectively. Our model represents a practical guide for BMF diagnosis and highlights the importance of clinical and laboratory variables in the initial evaluation, particularly telomere length. Our tool can be potentially used by general hematologists and health care providers not specialized in BMF, and in under-resourced centers, to prioritize patients for genetic testing or for expeditious treatment.

Plasmodium vivax infection alters the peripheral immunoregulatory network of CD4 T follicular cells and B cells.

Regulatory and effector cell responses to Plasmodium vivax, the most common human malaria parasite outside Africa, remain understudied in naturally infected populations. Here, we describe peripheral CD4+ T- and B-cell populations during and shortly after an uncomplicated P. vivax infection in 38 continuously exposed adult Amazonians. Consistent with previous observations, we found an increased frequency in CD4+ CD45RA- CD25+ FoxP3+ T regulatory cells that express the inhibitory molecule CTLA-4 during the acute infection, with a sustained expansion of CD21- CD27- atypical memory cells within the CD19+ B-cell compartment. Both Th1- and Th2-type subsets of CXCR5+ ICOShi PD-1+ circulating T follicular helper (cTfh) cells, which are thought to contribute to antibody production, were induced during P. vivax infection, with a positive correlation between overall cTfh cell frequency and IgG antibody titers to the P. vivax blood-stage antigen MSP119 . We identified significant changes in cell populations that had not been described in human malaria, such as an increased frequency of CTLA-4+ T follicular regulatory cells that antagonize Tfh cells, and a decreased frequency of circulating CD24hi CD27+ B regulatory cells in response to acute infection. In conclusion, we disclose a complex immunoregulatory network that is critical to understand how naturally acquired immunity develops in P. vivax malaria.

Genome-wide association and functional genomic analyses for various hoof health traits in North American Holstein cattle.

Hoof diseases are a major welfare and economic issue in the global dairy cattle production industry, which can be minimized through improved management and breeding practices. Optimal genetic improvement of hoof health could benefit from a deep understanding of the genetic background and biological underpinning of indicators of hoof health. Therefore, the primary objectives of this study were to perform genome-wide association studies, using imputed high-density genetic markers data from North American Holstein cattle, for 8 hoof-related traits: digital dermatitis, sole ulcer, sole hemorrhage, white line lesion, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, and toe ulcer, and a hoof health index. De-regressed estimated breeding values from 25,580 Holstein animals were used as pseudo-phenotypes for the association analyses. The genomic quality control, genotype phasing, and genotype imputation were performed using the PLINK (version 1.9), Eagle (version 2.4.1), and Minimac4 software, respectively. The functional genomic analyses were performed using the GALLO R package and the DAVID platform. We identified 22, 34, 14, 22, 28, 33, 24, 43, and 15 significant markers for digital dermatitis, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, white line lesion disease, and the hoof health index, respectively. The significant markers were located across all autosomes, except BTA10, BTA12, BTA20, BTA26, BTA27, and BTA28. Moreover, the genomic regions identified overlap with various previously reported quantitative trait loci for exterior, health, meat and carcass, milk, production, and reproduction traits. The enrichment analyses identified 44 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously associated with bone development, metabolism, and infectious and immunological diseases. These findings indicate that hoof health traits are highly polygenic and influenced by a wide range of biological processes.

Imaging associations enhance the understanding of ECG abnormalities in male Brazilian football players: findings from the B-Pro Foot ECG study.

OBJECTIVES: To evaluate the prevalence of abnormal ECG findings and their association with imaging results in male Brazilian football players. METHODS: The 'B-Pro Foot ECG' is a multicentre observational study conducted in 82 Brazilian professional clubs. It analysed 6125 players aged 15-35 years (2496 white, 2004 mixed-race and 1625 black individuals) who underwent cardiovascular screening from 2002 to 2023. All ECGs were reviewed by two experienced cardiologists in the athlete's care. Those with abnormal findings underwent further investigations, including a transthoracic echocardiogram (TTE). Cardiac magnetic resonance (CMR) was subsequently performed based on TTE findings or clinical suspicion. RESULTS: In total, 180 (3%) players had abnormal ECGs and 176 (98%) showed normal TTE results. Athletes aged 26-35 years had a higher prevalence of abnormal ECGs than younger athletes (15-25 years). Black players had a higher prevalence of T-wave inversion (TWI) in the inferior leads than white players (2.6% vs 1.4%; p=0.005), as well as in V5 (2.9%) and V6 (2.1%) compared with white (1.2% and 1.0%; p<0.001) and mixed-race (1.5% and 1.2%; p<0.05) players, respectively. TTE parameters were similar across ethnicities. However, four out of 75 players with inferolateral TWI showed abnormal TTEs and CMR findings consistent with cardiomyopathies. CMR also showed cardiomyopathies or myocarditis in four players with inferolateral TWI and normal TTEs. In total, nine (0.1%) athletes were diagnosed with cardiac diseases and were followed for 40±30 months, with no cardiac events documented. CONCLUSION: This study found a 3% prevalence of abnormal ECGs in male Brazilian football players. Inferolateral TWI was associated with cardiac pathologies confirmed by CMR, even in athletes with a normal TTE.

Expression and purification of active shikimate dehydrogenase from Plasmodium falciparum.

Plasmodium falciparum is known to cause severe malaria, current treatment consists in artemisinin-based combination therapy, but resistance can lead to treatment failure. Knowledge concerning P. falciparum essential proteins can be used for searching new antimalarials, among these a potential candidate is shikimate dehydrogenase (SDH), an enzyme part of the shikimate pathway which is responsible for producing endogenous aromatic amino acids. SDH from P. falciparum (PfSDH) is unexplored by the scientific community, therefore, this study aims to establish the first protocol for active PfSDH expression. Putative PfSDH nucleotide sequence was used to construct an optimized expression vector pET28a+PfSDH inserted in E. coli BL21(DE3). As a result, optimal expression conditions were acquired by varying IPTG and temperature through time. Western Blot analysis was applied to verify appropriate PfSDH expression, solubilization and purification started with lysis followed by two-steps IMAC purification. Enzyme activity was measured spectrophotometrically by NADPH oxidation, optimal PfSDH expression occur at 0.1 mM IPTG for 48 hours growing at 37 °C and shaking at 200 rpm, recombinant PfSDH obtained after purification was soluble, pure and its physiological catalysis was confirmed. Thus, this study describes the first protocol for heterologous expression of PfSDH in soluble and active form.

In silico analysis of non-structural protein 12 sequences from SARS-COV-2 found in Manaus, Amazonas, Brazil, reveals mutations linked to higher transmissibility.

The disease coronavirus COVID-19 has been the cause of millions of deaths worldwide. Among the proteins of SARS-CoV-2, non-structural protein 12 (NSP12) plays a key role during COVID infection and is part of the RNA-dependent RNA polymerase complex. The monitoring of NSP12 polymorphisms is extremely important for the design of new antiviral drugs and monitoring of viral evolution. This study analyzed the NSP12 mutations detected in circulating SARS-CoV-2 during the years 2020 to 2022 in the population of the city of Manaus, Amazonas, Brazil. The most frequent mutations found were P323L and G671S. Reports in the literature indicate that these mutations are related to transmissibility efficiency, which may have contributed to the extremely high numbers of cases in this location. In addition, two mutations described here (E796D and R914K) are close and have RMSD that is similar to the mutations M794V and N911K, which have been described in the literature as influential on the performance of the NSP12 enzyme. These data demonstrate the need to monitor the emergence of new mutations in NSP12 in order to better understand their consequences for the treatments currently used and in the design of new drugs.

Analysis of Variance Combined with Optimized Gradient Boosting Machines for Enhanced Load Recognition in Home Energy Management Systems.

Load recognition remains not comprehensively explored in Home Energy Management Systems (HEMSs). There are gaps in current approaches to load recognition, such as enhancing appliance identification and increasing the overall performance of the load-recognition system through more robust models. To address this issue, we propose a novel approach based on the Analysis of Variance (ANOVA) F-test combined with SelectKBest and gradient-boosting machines (GBMs) for load recognition. The proposed approach improves the feature selection and consequently aids inter-class separability. Further, we optimized GBM models, such as the histogram-based gradient-boosting machine (HistGBM), light gradient-boosting machine (LightGBM), and XGBoost (extreme gradient boosting), to create a more reliable load-recognition system. Our findings reveal that the ANOVA-GBM approach achieves greater efficiency in training time, even when compared to Principal Component Analysis (PCA) and a higher number of features. ANOVA-XGBoost is approximately 4.31 times faster than PCA-XGBoost, ANOVA-LightGBM is about 5.15 times faster than PCA-LightGBM, and ANOVA-HistGBM is 2.27 times faster than PCA-HistGBM. The general performance results expose the impact on the overall performance of the load-recognition system. Some of the key results show that the ANOVA-LightGBM pair reached 96.42% accuracy, 96.27% F1, and a Kappa index of 0.9404; the ANOVA-HistGBM combination achieved 96.64% accuracy, 96.48% F1, and a Kappa index of 0.9434; and the ANOVA-XGBoost pair attained 96.75% accuracy, 96.64% F1, and a Kappa index of 0.9452; such findings overcome rival methods from the literature. In addition, the accuracy gain of the proposed approach is prominent when compared straight to its competitors. The higher accuracy gains were 13.09, 13.31, and 13.42 percentage points (pp) for the pairs ANOVA-LightGBM, ANOVA-HistGBM, and ANOVA-XGBoost, respectively. These significant improvements highlight the effectiveness and refinement of the proposed approach.

Load Recognition in Home Energy Management Systems Based on Neighborhood Components Analysis and Regularized Extreme Learning Machine.

Efficient energy management in residential environments is a constant challenge, in which Home Energy Management Systems (HEMS) play an essential role in optimizing consumption. Load recognition allows the identification of active appliances, providing robustness to the HEMS. The precise identification of household appliances is an area not completely explored. Gaps like improving classification performance through techniques dedicated to separability between classes and models that achieve enhanced reliability remain open. This work improves several aspects of load recognition in HEMS applications. In this research, we adopt Neighborhood Component Analysis (NCA) to extract relevant characteristics from the data, seeking the separability between classes. We also employ the Regularized Extreme Learning Machine (RELM) to identify household appliances. This pioneering approach achieves performance improvements, presenting higher accuracy and weighted F1-Score values-97.24% and 97.14%, respectively-surpassing state-of-the-art methods and enhanced reliability according to the Kappa index, i.e., 0.9388, outperforming competing classifiers. Such evidence highlights the promising potential of Machine Learning (ML) techniques, specifically NCA and RELM, to contribute to load recognition and energy management in residential environments.

Plastics and plastic-bound toxic metals in municipal solid waste compost from Sri Lanka.

This study examined plastics and toxic metals in municipal solid waste compost from various regions in Sri Lanka. Plastics were extracted using density separation, digested using wet peroxidation, and identified using Fourier Transform Infra-Red Spectroscopy in Attenuated Total Reflection mode. Compost and plastics were acid-digested to quantify total Cd, Cu, Co, Cr, Pb, and Zn concentrations and analyzed for the bioavailable fraction using 0.01 M CaCl2. Notably, plastics were highly abundant in most compost samples. The main plastic types detected were polyethylene, polypropylene, and cellophane. However, the average Cd, Cu, Co, Cr, Pb, and Zn levels were 0.727, 60.78, 3.670, 25.44, 18.95, and 130.7 mg/kg, respectively, which are well below the recommended levels. Zn was the most bioavailable (2.476 mg/kg), and Cd was the least bioavailable (0.053 mg/kg) metal associated with compost. The Contamination factor data show that there is considerable enhancement of Cd and Cu, however, Cr, Cu, Co, and Pb are at low contamination levels. Mean geo accumulation index values were 1.39, 1.07, - 1.06, - 0.84, - 0.32, and 0.08 for Cd, Cu, Co, Cr, Pb, and Zn. Therefore, the contamination level of compost samples with Cd and Cu ranges from uncontaminated to contaminated levels, whereas Co, Cr, Pb, and Zn are at uncontaminated levels. Despite no direct metal-plastic correlation, plastics in compost could harm plants, animals, and humans due to ingestion. Hence, reducing plastic and metal contamination in compost is crucial.

Effect of Processing Methods of Human Saliva on the Proteomic Profile and Protein-Mediated Biological Processes.

The use of saliva as a protein source prior to microbiological and biological assays requires previous processing. However, the effect of these processing methods on the proteomic profile of saliva has not been tested. Stimulated human saliva was collected from eight healthy volunteers. Non-processed saliva was compared with 0.22 µm filtered, 0.45 µm filtered, and pasteurized saliva, by liquid chromatography-mass spectrometry. Data are available via ProteomeXchange with identifier PXD039248. The effect of processed saliva on microbial adhesion was tested using bacterial and fungus species and in biological cell behavior using HaCaT immortalized human keratinocytes. Two hundred and seventy-eight proteins were identified in non-processed saliva, of which 54 proteins (≈19%) were exclusive. Saliva processing reduced identified proteins to 222 (≈80%) for the 0.22 µm group, 219 (≈79%) for the 0.45 µm group, and 201 (≈72%) for the pasteurized saliva, compared to non-processed saliva. The proteomic profile showed similar molecular functions and biological processes. The different saliva processing methods did not alter microbial adhesion (ANOVA, p > 0.05). Interestingly, pasteurized saliva reduced keratinocyte cell viability. Saliva processing methods tested reduced the proteomic profile diversity of saliva but maintained similar molecular functions and biological processes, not interfering with microbial adhesion and cell viability, except for pasteurization, which reduced cell viability.

Effects of nandrolone decanoate on telomere length and clinical outcome in patients with telomeropathies: a prospective trial.

Androgens have been reported to elongate telomeres in retrospective and prospective trials with patients with telomeropathies, mainly with bone marrow failure. In our single-arm prospective clinical trial (clinicaltrials gov. Identifier: NCT02055456), 17 patients with short telomeres and/or germline pathogenic variants in telomere biology genes associated with at least one cytopenia and/or radiologic diagnosis of interstitial lung disease were treated with 5 mg/kg of intramuscular nandrolone decanoate every 15 days for 2 years. Ten of 13 evaluable patients (77%) showed telomere elongation at 12 months by flow-fluorescence in situ hybridization (average increase, 0.87 kb; 95% confidence interval: 0.20-1.55 kb; P=0.01). At 24 months, all ten evaluable patients showed telomere elongation (average increase, 0.49 kb; 95% confidence interval: 0.24-1.23 kb; P=0.18). Hematologic response was achieved in eight of 16 patients (50%) with marrow failure at 12 months, and in ten of 16 patients (63%) at 24 months. Seven patients had interstitial lung disease at baseline, and two and three had pulmonary response at 12 and 24 months, respectively. Two patients died due to pulmonary failure during treatment. In the remaining evaluable patients, the pulmonary function remained stable or improved, but showed consistent decline after cessation of treatment. Somatic mutations in myeloid neoplasm-related genes were present in a minority of patients and were mostly stable during drug treatment. The most common adverse events were elevations in liver function test levels in 88%, acne in 59%, and virilization in 59%. No adverse events grade ≥4 was observed. Our findings indicate that nandrolone decanoate elongates telomeres in patients with telomeropathies, which correlated with clinical improvement in some cases and tolerable adverse events.

Electroluminescence of Tetradentate Pt(II) Complexes: O

Alkylation of one of the phenolic hydroxyl groups in a salen-type tetradentate ligand changes the coordination mode from O^N^N^O to the cyclometallating C^N^N^O type. The ligand was used to synthesize a new cyclometalated luminescent Pt(II) complex 2. While in solution the complex is poorly luminescent, in the solid state the emission is reinstated, which allowed one to evaluate complex 2 as a phosphorescent emitter in organic light-emitting diodes. 2 displays external quantum efficiency (EQE) = 9.1% and a maximum luminance of 9000 cd m-2 in a vacuum-deposited device. We carried out comparative analysis of photo- and electroluminescence of complex 2 with O^N^N^O complex 1 and demonstrated that the similar luminescent properties of the O^N^N^O and C^N^N^O complexes are rather coincidental because they display different excited-state landscapes. Surprisingly, the two complexes display a dramatically different electrochemical behavior, with O^N^N^O coordination leading to the formation of a stable electropolymer but C^N^N^O coordination fully preventing electropolymerization.

Unusual Excimer/Dimer Behavior of a Highly Soluble C,N Platinum(II) Complex with a Spiro-Fluorene Motif.

In this work, we introduce a spiro-fluorene unit into a phenylpyridine (CN)-type ligand as a simple way to deplanarize the structure and increase the solubility of the final platinum(II)···complex. Using a spiro-fluorene unit, orthogonal to the main coordination plane of the complex, reduces intermolecular interactions, leading to increased solubility but without significantly affecting the ability of the complex to form Pt···Pt dimers and excimers. This approach is highly important in the design of platinum(II) complexes, which often suffer from low solubility due to their mainly planar structure, and offers an alternative to the use of bulky alkyl groups. The nonplanar structure is also beneficial for vacuum-deposition techniques as it lowers the sublimation temperature. Importantly, there are no sp3 hybridized carbon atoms in the cyclometalating ligand that contain hydrogens, the undesired feature that is associated with the low stability of the materials in OLEDs. The complex displays high solubility in toluene, ∼10 mg mL-1, at room temperature, which allows producing solution-processed OLEDs in a wide range of doping concentrations, 5-100%, and EQE up to 5.9%, with a maximum luminance of 7400 cd m-2. Concurrently, we have also produced vacuum-deposited OLEDs, which display luminance up to 32 500 cd m-2 and a maximum EQE of 11.8%.

Selective genotyping strategies for a sib test scheme of a broiler breeder program.

BACKGROUND: In broiler breeding, genotype-by-environment interaction is known to result in a genetic correlation between body weight measured in bio-secure and commercial environments that is substantially less than 1. Thus, measuring body weights on sibs of selection candidates in a commercial environment and genotyping them could increase genetic progress. Using real data, the aim of this study was to evaluate which genotyping strategy and which proportion of sibs placed in the commercial environment should be genotyped to optimize a sib-testing breeding program in broilers. Phenotypic body weight and genomic information were collected on all sibs raised in a commercial environment, which allowed to retrospectively analyze different sampling strategies and genotyping proportions. RESULTS: Accuracies of genomic estimated breeding values (GEBV) obtained with the different genotyping strategies were assessed by computing their correlation with GEBV obtained when all sibs in the commercial environment were genotyped. Results showed that, compared to random sampling (RND), genotyping sibs with extreme phenotypes (EXT) resulted in higher GEBV accuracy across all genotyping proportions, especially for genotyping proportions of 12.5% or 25%, which resulted in correlations of 0.91 vs 0.88 for 12.5% and 0.94 vs 0.91 for 25% genotyped. Including pedigree on birds with phenotype in the commercial environment that were not genotyped increased accuracy at lower genotyping proportions, especially for the RND strategy (correlations of 0.88 vs 0.65 at 12.5% and 0.91 vs 0.80 at 25%), and a smaller but still substantial increase in accuracy for the EXT strategy (0.91 vs 0.79 for 12.5% and 0.94 vs 0.88 for 25% genotyped). Dispersion bias was virtually absent for RND if 25% or more birds were genotyped. However, GEBV were considerably inflated for EXT, especially when the proportion genotyped was low, which was further exacerbated if the pedigree of non-genotyped sibs was excluded. CONCLUSIONS: When less than 75% of all animals placed in a commercial environment are genotyped, it is recommended to use the EXT strategy, because it yields the highest accuracy. However, caution should be taken when interpreting the resulting GEBV because they will be over-dispersed. When 75% or more of the animals are genotyped, random sampling is recommended because it yields virtually no bias of GEBV and results in similar accuracies as the EXT strategy.

High-Resolution Liquid Chromatography-Mass Spectrometry-Based Metabolomics for the Classification of Chuquiraga (Barnadesioideae, Asteraceae): New Phenylpropanoid Derivatives as Chemical Markers for Chuquiraga spinosa.

Despite their relatively poorly investigated phytochemistry, species of the genus Chuquiraga are widely commercialized. The present study reports the use of a high-resolution liquid chromatography-mass spectrometry-based metabolomics approach coupled with exploratory and supervised multivariate statistical analyses for species classification and chemical marker identification of four species of Chuquiraga (C. jussieui, C. weberbaueri, C. spinosa, and Chuquiraga sp.) from Ecuador and Peru. Based on these analyses, a high percentage of correct classifications (87% to 100%) allowed the prediction of the taxonomic identity of Chuquiraga species. Through the metabolite selection process, several key constituents with the potential to be chemical markers were identified. Samples of C. jussieui displayed alkyl glycosides and triterpenoid glycosides as discriminating metabolites, while Chuquiraga sp. displayed high concentrations of p-hydroxyacetophenone, p-hydroxyacetophenone 4-O-glucoside, p-hydroxyacetophenone 4-O-(6-O-apiosyl)-glucoside, and quinic acid ester derivatives as the main metabolites. Caffeic acid was characteristic for C. weberbaueri samples, whereas C. spinosa displayed higher concentrations of the following new phenylpropanoid ester derivatives: 2-O-caffeoyl-4-hydroxypentanedioic acid (24), 2-O-p-coumaroyl-4-hydroxypentanedioic acid (34), 2-O-feruloyl-4-hydroxypentanedioic acid (46), 2,4-O-dicaffeoylpentanedioic acid (71), and 2-O-caffeoyl-4-O-feruloylpentanedioic acid (77).

Brain and cortisol responses to smoking cues are linked in tobacco-smoking individuals.

Cues associated with smoking can induce relapse, which is likely driven by cue-induced neurobiological and physiological mechanisms. For instance, greater relapse vulnerability is associated with increases in cue-induced insula activation and heightened cortisol concentrations. Determining if there is a link between such cue-induced responses is critical given the need for biomarkers that can be easily measured in clinical settings and used to drive targeted treatment. Further, comprehensively characterising biological reactions to cues promises to aid in the development of therapies that address this specific relapse risk factor. To determine whether brain and cortisol responses to smoking cues are linked, this study recruited 27 nicotine-dependent tobacco-smoking individuals and acquired whole-brain functional activation during a cue reactivity task; salivary cortisol was measured before and after scanning. The results showed that increases in blood-oxygen-level-dependent activation in the right anterior insula and right dorsolateral prefrontal cortex (DLPFC) when viewing smoking versus neutral cues were positively correlated with a post-scan rise in salivary cortisol concentrations. These brain regions have been previously implicated in substance use disorders for their role in salience, interoception and executive processes. These findings show that those who have a rise in cortisol following smoking cue exposure also have a related rise in cue-induced brain reactivity, in brain regions previously linked with heightened relapse vulnerability. This is clinically relevant as measuring cue-induced cortisol responses is a more accessible proxy for assessing the engagement of cue-induced neurobiological processes associated with the maintenance of nicotine dependence.

Cut yield and meat quality of brown eggshell laying hens housed in an alternative system and submitted to different feeding volumes.

The aim was to evaluate the effect of different feeding volumes on the cut yield and meat quality of brown eggshell laying hens strain Embrapa 051 (E051) during the laying cycle, reared in an alternative system and slaughtered at 73 weeks, with reference to the lineage Lohmann Brown (LB). 600 hens E051 and 200 hens LB were used in an entirely randomized experimental design totalizing 5 replicates with 40 birds each. The treatments were: Control (LB fed with 100% of their dietary requirements), E051 fed with 93% of the control diet, E051 fed with 100% of the control diet, and E051 fed with 107% of the control diet. Birds were supplemented daily with 30g of ground grasses. Different feeding volumes did not alter the physicochemical quality of the meat and the cut yield. Body and cold carcass weight were greater in the E051 fed with 107% of the reference feed compared to the LB or the E051 fed with 7% less than the control diet. Yellow color intensity was greater in the E051 than in LB. The results demonstrated that, at the end of their productive cycle, the E051 without a restricted diet presents good carcass characteristics and potential for industrialized development.

An Interpretable Digital Twin for Self-Aware Industrial Machines.

This paper presents a proposed three-step methodology designed to enhance the performance and efficiency of industrial systems by integrating Digital Twins with particle swarm optimization (PSO) algorithms while prioritizing interpretability. Digital Twins are becoming increasingly prevalent due to their capability to offer a comprehensive virtual representation of physical systems, thus facilitating detailed simulations and optimizations. Concurrently, PSO has demonstrated its effectiveness for real-time parameter estimation, especially in identifying both standard and unknown components that influence the dynamics of a system. Our methodology, as exemplified through DC Motor and Hydraulic Actuator simulations, underscores the potential of Digital Twins to augment the self-awareness of industrial machines. The results indicate that our approach can proficiently optimize system parameters in real-time and unveil previously unknown components, thereby enhancing the adaptive capacities of the Digital Twin. While the reliance on accurate data to develop Digital Twin models is a notable consideration, the proposed methodology serves as a promising framework for advancing the efficiency of industrial applications. It further extends its relevance to fault detection and system control. Central to our approach is the emphasis on interpretability, ensuring a more transparent understanding and effective usability of such systems.

Clodronate disodium is neither cytotoxic nor cytoprotective to normal and recombinant equine interleukin-1ß-treated joint tissues in vitro.

OBJECTIVE: To determine the effects of clodronate disodium (CLO) on control and recombinant equine interleukin-1ß (IL-1ß)-treated equine joint tissues. STUDY DESIGN: In vitro experimental study. SAMPLE POPULATION: Cartilage explants, chondrocytes, and synoviocytes (n = 3 horses). METHODS: Monolayer cultures of chondrocytes and synoviocytes from three horses were subjected to: control media (CON), 5 ng/ml CLO (C/low), 50 ng/ml CLO (C/med), 100 ng/ml CLO (C/high), with and without IL-1ß, and 10 ng/ml IL-1ß (IL) alone for 72 hours. Cartilage explants from three horses were subjected to CON, IL, C/low, and C/med with and without IL-1ß for 72 hours. Culture media was analyzed for prostaglandin-E2 (PGE2 ), interleukin-6 (IL-6), and nitric oxide (NO). Explant media was analyzed for glycosaminoglycan (GAG) content and NO. At 72 hours, explant and monolayer culture viability were assessed, and explant GAG content was measured. RESULTS: IL-1ß treatment resulted in higher media concentrations of GAG, NO, PGE2 , and IL-6 compared to the CON treatment (p < .05), demonstrating a catabolic effect of IL-1ß on explants and monolayer cultures. CLO treatments did not increase media concentrations of GAG, NO, PGE2 , or IL-6 compared to CON, indicating no cytotoxic effect. Nevertheless, CLO treatments administered to IL-1ß-treated monolayer cultures and explants did not significantly reduce the inflammatory response regardless of concentration. CONCLUSION: CLO did not demonstrate cytotoxic nor cytoprotective effects in normal and IL-1ß-stimulated chondrocytes, synoviocytes or explants in culture. CLINICAL SIGNIFICANCE: This study does not support the use of CLO as an anti-inflammatory treatment. Further research is necessary to confirm any anti-inflammatory effects of CLO on joint tissues.

pH and the Breast Cancer Recurrent Mutation D538G Affect the Process of Activation of Estrogen Receptor α.

Estrogen receptor α (ERα) is a regulatory protein that can access a set of distinct structural configurations. ERα undergoes extensive remodeling as it interacts with different agonists and antagonists, as well as transcription activation and repression factors. Moreover, breast cancer tumors resistant to hormone therapy have been associated with the imbalance between the active and inactive ERα states. Cancer-activating mutations in ERα play a crucial role in this imbalance and can promote the progression of cancer. However, the rate of this progression can also be increased by dysregulated pH in the tumor microenvironment. Many molecular aspects of the process of activation of ERα that can be affected by these pH changes and mutations are still unclear. Thus, we applied computational and experimental techniques to explore the activation process dynamics of ER for environments with different pHs and in the presence of one of the most recurrent cancer-activating mutations, D538G. Our results indicated that the effect of the pH increase associated with the D538G mutation promoted a robust stabilization of the active state of ER. We were also able to determine the main protein regions that have the most potential to influence the activation process under different pH conditions, which may provide targets of future therapeutics for the treatment of hormone-resistant breast cancer tumors. Finally, the approach used here can be applied for proteins associated with the proliferation of other cancer types, which can also have their function affected by small pH changes.