Among several complications related to physiotherapy, osteosarcopenia is one of the most frequent in elderly patients. This condition is limiting and quite harmful to the patient's health by ...disabling several basic musculoskeletal activities. Currently, the test to identify this health condition is complex. In this study, we use mid-infrared spectroscopy combined with chemometric techniques to identify osteosarcopenia based on blood serum samples. The purpose of this study was to evaluate the mid-infrared spectroscopy power to detect osteosarcopenia in community-dwelling older women (n = 62, 30 from patients with osteosarcopenia and 32 healthy controls). Feature reduction and selection techniques were employed in conjunction with discriminant analysis, where a principal component analysis with support vector machines (PCA-SVM) model achieved 89% accuracy to distinguish the samples from patients with osteosarcopenia. This study shows the potential of using infrared spectroscopy of blood samples to identify osteosarcopenia in a simple, fast and objective way.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The progressive aging of the world’s population makes a higher prevalence of neurodegenerative diseases inevitable. The necessity for an accurate, but at the same time, inexpensive and minimally ...invasive, diagnostic test is urgently required, not only to confirm the presence of the disease but also to discriminate between different types of dementia to provide the appropriate management and treatment. In this study, attenuated total reflection FTIR (ATR-FTIR) spectroscopy combined with chemometric techniques were used to analyze blood plasma samples from our cohort. Blood samples are easily collected by conventional venepuncture, permitting repeated measurements from the same individuals to monitor their progression throughout the years or evaluate any tested drugs. We included 549 individuals: 347 with various neurodegenerative diseases and 202 age-matched healthy individuals. Alzheimer’s disease (AD; n = 164) was identified with 70% sensitivity and specificity, which after the incorporation of apolipoprotein ε4 genotype (APOE ε4) information, increased to 86% when individuals carried one or two alleles of ε4, and to 72% sensitivity and 77% specificity when individuals did not carry ε4 alleles. Early AD cases (n = 14) were identified with 80% sensitivity and 74% specificity. Segregation of AD from dementia with Lewy bodies (DLB; n = 34) was achieved with 90% sensitivity and specificity. Other neurodegenerative diseases, such as frontotemporal dementia (FTD; n = 30), Parkinson’s disease (PD; n = 32), and progressive supranuclear palsy (PSP; n = 31), were included in our cohort for diagnostic purposes. Our method allows for both rapid and robust diagnosis of neurodegeneration and segregation between different dementias.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Inflammation resolution is an active process that functions to restore tissue homeostasis. The participation of the plasminogen (Plg)/plasmin (Pla) system in the productive phase of inflammation is ...well known, but its involvement in the resolution phase remains unclear. Therefore, we aimed to investigate the potential role of Plg/Pla in key events during the resolution of acute inflammation and its underlying mechanisms. Plg/Pla injection into the pleural cavity of BALB/c mice induced a time-dependent influx of mononuclear cells that were primarily macrophages of anti-inflammatory (M2 F4/80high Gr1– CD11bhigh) and proresolving (Mres F4/80med CD11blow) phenotypes, without changing the number of macrophages with a proinflammatory profile (M1 F4/80low Gr1+ CD11bmed). Pleural injection of Plg/Pla also increased M2 markers (CD206 and arginase-1) and secretory products (transforming growth factor β and interleukin-6) and decreased the expression of inducible nitric oxide synthase (M1 marker). During the resolving phase of lipopolysaccharide (LPS)-induced inflammation when resolving macrophages predominate, we found increased Plg expression and Pla activity, further supporting a link between the Plg/Pla system and key cellular events in resolution. Indeed, Plg or Pla given at the peak of inflammation promoted resolution by decreasing neutrophil numbers and increasing neutrophil apoptosis and efferocytosis in a serine-protease inhibitor–sensitive manner. Next, we confirmed the ability of Plg/Pla to both promote efferocytosis and override the prosurvival effect of LPS via annexin A1. These findings suggest that Plg and Pla regulate several key steps in inflammation resolution, namely, neutrophil apoptosis, macrophage reprogramming, and efferocytosis, which have a major impact on the establishment of an efficient resolution process.
•Plg and Pla induce macrophage reprogramming and promote resolution of acute inflammation.•Plg and Pla enhance the efferocytic capacity of macrophages and override the prosurvival effect of LPS on neutrophils via annexin A1.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In vitro incubation of nanomaterials with plasma offer insights on biological interactions, but cannot fully explain the in vivo fate of nanomaterials. Here, we use a library of polymer nanoparticles ...to show how physicochemical characteristics influence blood circulation and early distribution. For particles with different diameters, surface hydrophilicity appears to mediate early clearance. Densities above a critical value of approximately 20 poly(ethylene glycol) chains (MW 5 kDa) per 100 nm
prolong circulation times, irrespective of size. In knockout mice, clearance mechanisms are identified for nanoparticles with low and high steric protection. Studies in animals deficient in the C3 protein showed that complement activation could not explain differences in the clearance of nanoparticles. In nanoparticles with low poly(ethylene glycol) coverage, adsorption of apolipoproteins can prolong circulation times. In parallel, the low-density-lipoprotein receptor plays a predominant role in the clearance of nanoparticles, irrespective of poly(ethylene glycol) density. These results further our understanding of nanopharmacology.Understanding the interaction between nanoparticles and biomolecules is crucial for improving current drug-delivery systems. Here, the authors shed light on the essential role of the surface and other physicochemical properties of a library of nanoparticles on their in vivo pharmacokinetics.
N-Acylhydrazones as drugs Thota, Sreekanth; Rodrigues, Daniel A.; Pinheiro, Pedro de Sena Murteira ...
Bioorganic & medicinal chemistry letters,
09/2018, Volume:
28, Issue:
17
Journal Article
Peer reviewed
Display omitted
•N-Acylhydrazone (NAH) motif in Drug Design and Medicinal Chemistry.•NAH-related approved drugs.•N-Acylhydrazone motif scaffolds in clinical trials.•Preclinical ...N-acylhydrazones.•Stability and Pharmacokinetic profile of N-acylhydrazones.
Over the last two decades, N-acylhydrazone (NAH) has been proven to be a very versatile and promising motif in drug design and medicinal chemistry. Herein, we discuss the current and future challenges in the emergence of bioactive NAH-based scaffolds and to developing strategies to overcome the failures in drug discovery. The NAH-related approved drugs nitrofurazone, nitrofurantoin, carbazochrome, testosterone 17-enanthate 3-benzilic acid hydrazine, nifuroxazide, dantrolene, and azumolene are already used as therapeutics in various countries. PAC-1 is an NAH-based therapeutic agent that entered clinical trials in 2015. Another NAH-derived scaffold, LASSBio-294, is in preclinical trials. This review highlights the detailed comprehensive assessment and therapeutic landscape of bioactive NAH motif scaffolds in preclinical and clinical studies published to date and their promise and associated challenges in current and future drug discovery of NAH-based drugs that will progress to clinical use.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In situ forming chitosan hydrogels have been prepared via coupled ionic and covalent cross-linking. Thus, different amounts of genipin (0.05, 0.10, 0.15, and 0.20% (w/w)), used as a chemical ...cross-linker, were added to a solution of chitosan that was previously neutralized with a glycerol–phosphate complex (ionic cross-linker). In this way, it was possible to overcome the pH barrier of the chitosan solution, to preserve its thermosensitive character, and to enhance the extent of cross-linking in the matrix simultaneously. To investigate the contributions of the ionic cross-linking and the chemical cross-linking, separately, we prepared the hydrogels without the addition of either genipin or the glycerol–phosphate complex. The addition of genipin to the neutralized solution disturbs the ionic cross-linking process and the chemical cross-linking becomes the dominant process. Moreover, the genipin concentration was used to modulate the network structure and performance. The more promising formulations were fully characterized, in a hydrated state, with respect to any equilibrium swelling, the development of internal structure, the occurrence of in vitro degradability and cytotoxicity, and the creation of in vivo injectability. Each of the hydrogel systems exhibited a notably high equilibrium water content, arising from the fact that their internal structure (examined by conventional SEM, and environmental SEM) was highly porous with interconnecting pores. The porosity and the pore size distribution were quantified by mercury intrusion porosimetry. Although all gels became degraded in the presence of lysozyme, their degradation rate greatly depended on the genipin load. Through in vitro viability tests, the hydrogel-based formulations were shown to be nontoxic. The in vivo injection of a co-cross-linking formulation revealed that the gel was rapidly formed and localized at the injection site, remaining in position for at least 1 week.
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IJS, KILJ, NUK, PNG, UL, UM
Abstract
Background
Recent investigations suggest that obesity may be associated with an increased risk of falls; however, this theory has yet to be definitively confirmed. This systematic review and ...meta-analysis examined the strength of the association between obesity and falls, multiple falls, fall-related injuries, and fall-related fractures among older adults.
Methods
MEDLINE, Embase, CINAHL, PsycINFO, SPORTDiscus, LILACS, and Web of Science databases were searched to identify observational studies that assessed the association between obesity and fall-related outcomes in participants aged 60 years and older. Two independent reviewers performed data extraction and quality assessment. Relative risks and 95% confidence intervals (CI) were pooled using random effect meta-analyses.
Results
Thirty-one studies including a total of 1,758,694 participants were selected from 7,815 references. Pooled estimates showed that obese older adults have an increased risk of falls compared with nonobese counterparts (24 studies; relative risk: 1.16; 95% CI: 1.07–1.26; I2: 90%). Obesity was also associated with an increased risk of multiple falls (four studies; relative risk: 1.18; 95% CI: 1.08–1.29; I2: 0%). There was no evidence, however, of an association between obesity and fall-related injuries (seven studies; relative risk: 1.04; 95% CI: 0.92–1.18; I2: 65%). Fall-related fractures were reported in only one study, which demonstrated a lower risk of hip fracture with obesity (odds ratio: 0.65; 95% CI: 0.63–0.68).
Conclusions
Obesity increases the risk of falls and multiple falls in people aged 60 years and older; however, there is insufficient evidence of an association with fall-related injuries or fractures. Prevention and treatment of obesity may play a role in preventing falls in older age.
This study performs a chemical investigation of blood plasma samples from patients with and without fibromyalgia, combined with some of the symptoms and their levels of intensity used in the ...diagnosis of this disease. The symptoms evaluated were: visual analogue pain scale (VAS); fibromyalgia impact questionnaire (FIQ); Hamilton anxiety rating scale (HAM); Tampa Scale for Kinesiophobia (TAMPA); quality of life Questionnaire-physical and mental health (QL); and Pain Catastrophizing Scale (CAT). Plasma samples were analyzed by paper spray ionization mass spectrometry (PSI-MS). Spectral data were organized into datasets and related to each of the symptoms measured. The datasets were submitted to multivariate classification using supervised models such as principal component analysis with linear discriminant analysis (PCA-LDA), successive projections algorithm with linear discriminant analysis (SPA-LDA), genetic algorithm with linear discriminant analysis (GA-LDA) and their versions with quadratic discriminant analysis (PCA/SPA/GA-QDA) and support vector machines (PCA/SPA/GA-SVM). These algorithm combinations were performed aiming the best class separation. Good discrimination between the controls and fibromyalgia samples were observed using PCA-LDA, where the spectral data associated with the CAT symptom achieved 100% classification sensitivity, and associated with the VAS symptom achieved 100% classification specificity, with both symptoms at the moderate level of intensity. The spectral variable at 579 m/z was found to be substantially significant for classification according to the PCA loadings. According to the human metabolites database, this variable can be associated with a LysoPC compound, which comprises a class of metabolites already evidenced in other studies for fibromyalgia diagnosis. This study proposed an investigation of spectral data combined with clinical data to compare the classification ability of different datasets. The good classification results obtained confirm this technique is as a good analytical tool for the detection of fibromyalgia, and provides theoretical support for other studies about fibromyalgia diagnosis.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Deep learning has already been successfully used in the development of decision support systems in various domains. Therefore, there is an incentive to apply it in other important domains such as ...agriculture. Fertilizers, electricity, chemicals, human labor, and water are the components of total energy consumption in agriculture. Yield estimates are critical for food security, crop management, irrigation scheduling, and estimating labor requirements for harvesting and storage. Therefore, estimating product yield can reduce energy consumption. Two deep learning models, Long Short-Term Memory and Gated Recurrent Units, have been developed for the analysis of time-series data such as agricultural datasets. In this paper, the capabilities of these models and their extensions, called Bidirectional Long Short-Term Memory and Bidirectional Gated Recurrent Units, to predict end-of-season yields are investigated. The models use historical data, including climate data, irrigation scheduling, and soil water content, to estimate end-of-season yield. The application of this technique was tested for tomato and potato yields at a site in Portugal. The Bidirectional Long Short-Term memory outperformed the Gated Recurrent Units network, the Long Short-Term Memory, and the Bidirectional Gated Recurrent Units network on the validation dataset. The model was able to capture the nonlinear relationship between irrigation amount, climate data, and soil water content and predict yield with an MSE of 0.017 to 0.039. The performance of the Bidirectional Long Short-Term Memory in the test was compared with the most commonly used deep learning method, the Convolutional Neural Network, and machine learning methods including a Multi-Layer Perceptrons model and Random Forest Regression. The Bidirectional Long Short-Term Memory outperformed the other models with an R2 score between 0.97 and 0.99. The results show that analyzing agricultural data with the Long Short-Term Memory model improves the performance of the model in terms of accuracy. The Convolutional Neural Network model achieved the second-best performance. Therefore, the deep learning model has a remarkable ability to predict the yield at the end of the season.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
This study aimed to analyse the trend and spatial–temporal clusters of risk of transmission of COVID-19 in northeastern Brazil. We conducted an ecological study using spatial and temporal trend ...analysis. All confirmed cases of COVID-19 in the Northeast region of Brazil were included, from 7 March to 22 May 2020. We used the segmented log-linear regression model to assess time trends, and the local empirical Bayesian estimator, the global and local Moran indexes for spatial analysis. The prospective space–time scan statistic was performed using the Poisson probability distribution model. There were 113 951 confirmed cases of COVID-19. The average incidence rate was 199.73 cases/100 000 inhabitants. We observed an increasing trend in the incidence rate in all states. Spatial autocorrelation was reported in metropolitan areas, and 178 municipalities were considered a priority, especially in the states of Ceará and Maranhão. We identified 11 spatiotemporal clusters of COVID-19 cases; the primary cluster included 70 municipalities from Ceará state. COVID-19 epidemic is increasing rapidly throughout the Northeast region of Brazil, with dispersion towards countryside. It was identified high risk clusters for COVID-19, especially in the coastal side.
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