Portable NIR spectroscopy: the route to green analytical chemistry.

There is a growing interest for cost-effective and nondestructive analytical techniques in both research and application fields. The growing approach by near-infrared spectroscopy (NIRs) pushes to develop handheld devices devoted to be easily applied for in situ determinations. Consequently, portable NIR spectrometers actually result definitively recognized as powerful instruments, able to perform nondestructive, online, or in situ analyses, and useful tools characterized by increasingly smaller size, lower cost, higher robustness, easy-to-use by operator, portable and with ergonomic profile. Chemometrics play a fundamental role to obtain useful and meaningful results from NIR spectra. In this review, portable NIRs applications, published in the period 2019-2022, have been selected to indicate starting references. These publications have been chosen among the many examples of the most recent applications to demonstrate the potential of this analytical approach which, not having the need for extraction processes or any other pre-treatment of the sample under examination, can be considered the "true green analytical chemistry" which allows the analysis where the sample to be characterized is located. In the case of industrial processes or plant or animal samples, it is even possible to follow the variation or evolution of fundamental parameters over time. Publications of specific applications in this field continuously appear in the literature, often in unfamiliar journal or in dedicated special issues. This review aims to give starting references, sometimes not easy to be found.

Classification-based QSARs for predicting dietary biomagnification in fish.

The assessment of bioaccumulation is an important step to describe the environmental behaviour and the potential risk due to exposure to potentially hazardous chemicals. In the last two decades, several in silico tools have been made available to predict bioconcentration, which is commonly used to assess bioaccumulation in risk assessment frameworks all over the world. However, only a few QSAR studies address the prediction of the biomagnification factor (BMF), which describes the accumulation of chemicals into organisms due to exposure through the diet. No classification models are currently available to this end. In this work, we developed classification QSARs to predict classes based on dietary biomagnification, using three different classifiers (i.e. LDA, ANN and RF). We started from a recently published dataset that includes more than 300 curated dietary BMF values measured in fish. The new models have high-quality performances (accuracy in fitting: from 94 to 96%; accuracy in prediction from 84 to 86%). The good performances of the here proposed QSARs confirm the quality of the original input data and highlight the importance of data curation and data sharing to support the development of new in silico approaches to assist risk assessment and chemicals screening.

Topological QSAR Modelling of Carboxamides Repellent Activity to Aedes Aegypti.

Aedes aegypti vector control is of paramount importance owing to the damages induced by the various severe diseases that these insects may transmit, and the increasing risk of important outbreaks of these pathologies. Search for new chemicals efficient against Aedes aegypti, and devoid of side-effects, which have been associated to the currently most used active substance i. e. N,N-diethyl-m-toluamide (DEET), is therefore an important issue. In this context, we developed various Quantitative Structure Activity Relationship (QSAR) models to predict the repellent activity against Aedes aegypti of 43 carboxamides, by using Multiple Linear Regression (MLR) and various machine learning approaches. The easy computation of the four topological descriptors selected in this study, compared to the CODESSA descriptors used in the literature, and the predictive ability of the here proposed MLR and machine learning models developed using the software QSARINS and R, make the here proposed QSARs attractive. As demonstrated in this study, these models can be applied at the screening level, to guide the design of new alternatives to DEET.

Prediction of PAH mutagenicity in human cells by QSAR classification.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants of high environmental concern. The experimental data of a mutagenicity test on human B-lymphoblastoid cells (alternative to the Ames bacterial test) for a set of 70 oxo-, nitro- and unsubstituted PAHs, detected in particulate matter (PM), were modelled by Quantitative Structure-Activity Relationships (QSAR) classification methods (k-NN, k-Nearest Neighbour, and CART, Classification and Regression Tree) based on different theoretical molecular descriptors selected by Genetic Algorithms. The best models were validated for predictivity both externally and internally. For external validation, Self Organizing Maps (SOM) were applied to split the original data set. The best models, developed on the training set alone, show good predictive performance also on the prediction set chemicals (sensitivity 69.2-87.1%, specificity 62.5-87.5%). The classification of PAHs according to their mutagenicity, based only on a few theoretical molecular descriptors, allows a preliminary assessment of the human health risk, and the prioritisation of these compounds.

Neutrophils invade lumbar dorsal root ganglia after chronic constriction injury of the sciatic nerve.

To test whether neutrophils (PMN) target lumbar dorsal root ganglia (DRG) following axonal injury leading to neuropathic pain, we visualized PMN infiltration in DRG tissue sections and estimated PMN count by flow cytometry following sciatic chronic constriction injury (CCI). Seven days after CCI, results show PMN within DRG where their count increased by three fold ipsilateral to injury compared to contralateral or sham, concomitant with peak neuropathic pain behavior. Superoxide burst in PMN isolated from rats d7 after CCI was elevated by 170% +/-18 compared to naïve and MCP-1 mRNA expression in DRG increased by 8.9+/-2.9 fold, but that of MIP-2, CINC-1, and RANTES did not change. We conclude that CCI causes PMN invasion of the DRG whereby the functional implication of their close proximity to neuronal axon and soma remains unknown.

Linear QSAR regression models for the prediction of bioconcentration factors by physicochemical properties and structural theoretical molecular descriptors.

The development of QSAR models useful for the prediction of fish bioconcentration factor (BCF) for a wide range of different chemical classes is crucial for the assessment and prioritisation of potentially persistent bioaccumulative and toxic substances. In this study we present QSAR models for BCF developed on a wide range of chemical structural classes of environmental and toxicological interest (such as dyes and various chlorinated and brominated compounds). The aim is to provide valid QSAR models, statistically validated for predictivity, for the prediction of BCF in general, but also for problematical chemical classes such as highly hydrophobic chemicals. Several descriptors, calculated by different commercially available software packages, have been employed in order to take into account relevant information provided by physicochemical properties (octanol/water partition coefficient and water solubility) and molecular features (structural and quantum-chemical molecular descriptors). The best descriptor subsets for the models were selected using the Genetic Algorithm-Variable Subset Selection strategy (GA-VSS) and calculations were performed by ordinary least squares regression. Starting from a data set of 640 compounds (logK(ow) range from -2.34 to 12.66), we developed linear QSARs, firstly for a data set of 620 compounds (logK(ow) range from -2.34 to 10.35) and secondly specifically for 87 highly hydrophobic chemicals (logK(ow) range from 6.00 to 10.35). All these models have been statistically validated (both internally by cross-validation and bootstrap and externally, by "a priori" splitting of available data by Kohonen Map-ANN in training and prediction sets) and their structural chemical domain has been verified by the leverage approach.

Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity.

Nitrated Polycyclic Aromatic Hydrocarbons (nitro-PAHs), ubiquitous environmental pollutants, are recognized mutagens and carcinogens. A set of mutagenicity data (TA100) for 48 nitro-PAHs was modeled by the Quantitative Structure-Activity Relationships (QSAR) regression method, and OECD principles for QSAR model validation were applied. The proposed Multiple Linear Regression (MLR) models are based on two topological molecular descriptors. The models were validated for predictivity by both internal and external validation. For the external validation, three different splitting approaches, D-optimal Experimental Design, Self Organizing Maps (SOM) and Random Selection by activity sampling, were applied to the original data set in order to compare these methodologies and to select the best descriptors able to model each prediction set chemicals independently of the splitting method applied. The applicability domain was verified by the leverage approach.

QSAR models for predicting the toxicity of piperidine derivatives against Aedes aegypti.

QSAR models are proposed for predicting the toxicity of 33 piperidine derivatives against Aedes aegypti. From 2D topological descriptors, calculated with the PaDEL software, ordinary least squares multilinear regression (OLS-MLR) treatment from the QSARINS software and machine learning and related approaches including linear and radial support vector machine (SVM), projection pursuit regression (PPR), radial basis function neural network (RBFNN), general regression neural network (GRNN) and k-nearest neighbours (k-NN), led to four-variable models. Their robustness and predictive ability were evaluated through both internal and external validation. Determination coefficients (r2) greater than 0.85 on the training sets and 0.8 on the test sets were obtained with OLS-MLR and linear SVM. They slightly outperform PPR, radial SVM and RBFNN, whereas GRNN and k-NN showed lower performance. The easy availability of the involved structural descriptors and the simplicity of the MLR model make the corresponding model attractive at an exploratory level for proposing, from this limited dataset, guidelines in the design of new potentially active molecules.

Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches.

The understanding of the mechanisms and interactions that occur when nanomaterials enter biological systems is important to improve their future use. The adsorption of proteins from biological fluids in a physiological environment to form a corona on the surface of nanoparticles represents a key step that influences nanoparticle behaviour. In this study, the quantitative description of the composition of the protein corona was used to study the effect on cell association induced by 84 surface-modified gold nanoparticles of different sizes. Quantitative relationships between the protein corona and the activity of the gold nanoparticles were modelled by using several machine learning-based linear and non-linear approaches. Models based on a selection of only six serum proteins had robust and predictive results. The Projection Pursuit Regression method had the best performances (r(2) = 0.91; Q(2)loo = 0.81; r(2)ext = 0.79). The present study confirmed the utility of protein corona composition to predict the bioactivity of gold nanoparticles and identified the main proteins that act as promoters or inhibitors of cell association. In addition, the comparison of several techniques showed which strategies offer the best results in prediction and could be used to support new toxicological studies on gold-based nanomaterials.

Mesenchymal stromal cell-derived extracellular vesicles rescue radiation damage to murine marrow hematopoietic cells.

Mesenchymal stromal cells (MSCs) have been shown to reverse radiation damage to marrow stem cells. We have evaluated the capacity of MSC-derived extracellular vesicles (MSC-EVs) to mitigate radiation injury to marrow stem cells at 4 h to 7 days after irradiation. Significant restoration of marrow stem cell engraftment at 4, 24 and 168 h post irradiation by exposure to MSC-EVs was observed at 3 weeks to 9 months after transplant and further confirmed by secondary engraftment. Intravenous injection of MSC-EVs to 500cGy exposed mice led to partial recovery of peripheral blood counts and restoration of the engraftment of marrow. The murine hematopoietic cell line, FDC-P1 exposed to 500cGy, showed reversal of growth inhibition, DNA damage and apoptosis on exposure to murine or human MSC-EVs. Both murine and human MSC-EVs reverse radiation damage to murine marrow cells and stimulate normal murine marrow stem cell/progenitors to proliferate. A preparation with both exosomes and microvesicles was found to be superior to either microvesicles or exosomes alone. Biologic activity was seen in freshly isolated vesicles and in vesicles stored for up to 6 months in 10% dimethyl sulfoxide at -80 °C. These studies indicate that MSC-EVs can reverse radiation damage to bone marrow stem cells.

Linear and non-linear modelling of the cytotoxicity of TiO2 and ZnO nanoparticles by empirical descriptors.

Titanium oxide (TiO2) and zinc oxide (ZnO) nanoparticles are among the most widely used in different applications in daily life. In this study, local regression and classification models were developed for a set of ZnO and TiO2 nanoparticles tested at different concentrations for their ability to disrupt the lipid membrane in cells. Different regression techniques were applied and compared by checking the robustness of the models and their external predictive ability. Additionally, a simple classification model was developed, which predicts the potential for disruption of the studied nanoparticles with good accuracy (overall accuracy, specificity, and sensitivity >80%) on the basis of two empirical descriptors. The present study demonstrates that empirical descriptors, such as experimentally determined size and tested concentrations, are relevant to modelling the activity of nanoparticles. This information may be useful to screen the potential for harmful effect of nanoparticles in different experimental conditions and to optimize the design of toxicological tests. Results from the present study are useful to support and refine the future application of in silico tools to nanoparticles, for research and regulatory purposes.

Pneumatization of the temporal portion of the zygomatic arch: The contribution of computed tomography to the reconstruction in volumetric two-dimensional and three-dimensional, with the aid of image rendering protocols.

Pneumatization refers to the asymptomatic development of cavities containing air within them. There is great variability in the extent of temporal bone pneumatization. Nevertheless, in a few cases it extends to the zygomatic process. Images are presented in which the panoramic radiograph and hypocycloidal tomography reveal this variation from the norm, to which professionals must be alert, since the images may simulate the presence of pathology. In this case report we describe the presence of pneumatization of the petrous and zygomatic portions of the temporal bone, demonstrating the contribution of CT to reconstruction in volumetric 2D and 3D, with the aid of image rendering protocols.

Sit-to-stand motor strategies investigated in able-bodied young and elderly subjects.

For the execution of a certain motor task, a motor strategy is chosen by each individual among those that are consistent with the structural and functional constraints of his/her locomotor system, and that tends to maximise the effectiveness of the motor act. The identification of this strategy allows for the assessment of the individual's functional status. This study aimed at identifying the motor strategies adopted for the execution of the sit-to-stand motor task, at different speeds and initial postures, in a sample of 35 community-dwelling elders and in a sample of 16 young able-bodied individuals. This was done using a method, least perceivable to the test subject and "economical" for the experimenter, which entailed the recording of external forces only. A musculo-skeletal system model, based on a telescopic inverted-pendulum (TIP) moved by a linear and two rotational muscle-equivalent actuators, was then used. Parameters describing the kinematics and dynamics of these actuators were extracted and submitted to statistical analysis. Different motor strategies were identified in the two age groups, as well as associated with both a different initial posture (ankle dorsiflexion angle) and speed of execution of the motor task. In particular, the elder group, as compared with the young group, prior to seat-off tended to flex the trunk more, thus bringing the CM closer to the base of support, and at a higher velocity, thus gaining a higher momentum. After seat-off, elders rotated the body forward and, only after having brought their CM over the base of support, effectively started elevation. Both global muscular effort and coordination effort associated with the achievement of balance and raising were lower. However, maximal speed was also lower. The above results indicated that the elders could count on a lower functional reserve than the young individuals and, from the methodological viewpoint, that the TIP approach is a good candidate for subject-specific functional evaluation in a clinical context.

A telescopic inverted-pendulum model of the musculo-skeletal system and its use for the analysis of the sit-to-stand motor task.

For field applicability of biomechanical methodologies aiming at assessing motor ability in disabled, or at risk of disablement (e.g. elderly), subjects, measurements must be carried out using a least perceivable to the subject and essential experimental apparatus. Since data thus obtained do not necessarily lend themselves to straightforward interpretation, they should be fed to a model of the portion of the musculo-skeletal system involved that already embodies the invariant aspects of both the modelled system and the motor task. Through such a minimum measured-input model, richer, physiology-related, and thus easier to interpret, information may be expected. In this framework, the present study investigated the sit-to-stand motor task using information obtained only from a force plate located under seat and subject's feet, a seat uniaxial load-cell and basic anthropometric parameters. Data were collected in a sample of 12 able-bodied subjects while executing the motor task at different speeds. The musculo-skeletal system was modelled as a telescopic inverted pendulum (TIP) that could vary its length (shortening or elongation) by effect of a force actuator and its orientation in space by effect of two couple actuators that were looked upon as muscle equivalent effectors. The TIP model output consisted in the kinematics and dynamics of these actuators. It allowed the identification of four functional phases in which the seat-to-stand motor task could be divided, and a detailed description of the relevant mechanics in terms of balance control and centre of mass elevation. Motor strategy modifications associated with speed variation could also be identified. For a global evaluation of the motor act it showed to be no less informative than more demanding multi-segment models. Although it is true that specific musculo-articular functions can only be inferred, the more compact information yielded by the TIP model is expected to facilitate subject and/or disability classification.

Macrophage phenotype during cholestatic injury and repair: the persistent inflammatory response.

BACKGROUND/PURPOSE: Biliary decompression for congenital or acquired obstruction (eg, biliary atresia) does not uniformly lead to liver repair, restore function, or prevent cholangitis. The authors hypothesize that failed repair is caused by altered macrophage (Mo) phenotypes central to an ongoing inflammatory and fibrogenic response. METHODS: In adult rats, biliary obstruction was performed by suspension of the common bile duct for 5 or 7 days. Decompression followed release of the loop until death during the course of liver repair. To determine Mo phenotype in the presence or absence of resident macrophages, animals were either administered gadolinium chloride or saline before injury and repair. At death, hepatic Mo were isolated, stained with MAC-1 (CD11b/CD 18) and OX-3 (MHC class II), and quantified with flow cytometry. Liver sections were immunostained for ED-1 and ED2; positive Mo were counted per square millimeter of tissue. RESULTS: Obstruction led to bile duct proliferation, fibrosis, and inflammation. Decompression relieved jaundice and ductal hyperplasia. After injury, hepatic Mo showed an 80% phenotypic conversion to MAC-1 and OX-3-positive cells. Cells isolated from livers at 9 days of repair persisted with 60% MAC-1 and 77% OX-3 expression. Gadolinium reduced Kupffer cells at all stages of repair. Recruited Mo in treated animals increased 4-fold greater than controls. CONCLUSIONS: Kupffer cells appear to limit the recruitment and persistence of a systemic macrophage phenotype in liver injury and repair. Cell surface markers for systemic macrophages appear after injury and persist during repair, despite adequate biliary decompression. After biliary decompression, this macrophage phenotype accounts for inflammatory complications such as cholangitis and ongoing fibrosis.

Inter- and intra-individual variability of ground reaction forces during sit-to-stand with principal component analysis.

Variable reduction is an important issue in biomechanics, because the definition of a non-redundant set of variables necessary for a complete description of a given motor act provides information about the motor strategy. A systematic tool for dealing with variable reduction problems is Principal Component Analysis. In this paper, as an example of an application of this technique, the set of Ground Reaction Forces (GRFs) provided by a six-component force plate, gained during standing up in a heterogeneous population of 82 normal individuals, was reduced to a set of fewer variables. Each subject was required to stand up from a chair five times at different, randomly self selected, speeds, obtaining a data set of 410 trials. Principal Components (PCs) of GRFs were computed for each trial. On average, over the ensemble of trials, first and second PCs (PC1 and PC2) explained together 90% of PCs. Inter- and intra-individual repeatability of the first two PCs was investigated by examining the correlation coefficient between PC waveforms obtained from the whole set of trials and within the set of trials performed by the same subject, respectively. While the PC1 exhibited repeatable patterns, the second one, although repeatable within the group of trials performed by the same subject, displayed marked inter-individual variability. Therefore, PC1 was related to intrinsic aspects of the motor task and PC2 to inter-subject features.

Ranking of volatile organic compounds for tropospheric degradability by oxidants: a QSPR approach.

The limited availability and variability of data related to atmospheric degradation reaction is a very relevant issue in studies related to environmental fate and behavior of chemicals. For screening purposes, the experimental data of the oxidation rate constants for the reactions with the radicals OH, NO3 and with ozone of 65 heterogeneous organic compounds were explored by Principal Component Analysis: a ranking of volatile organic chemicals (VOC) according to their relative overall atmospheric degradability and an atmospheric persistence index (ATPIN) is proposed. This index has been modeled by theoretical molecular descriptors to obtain MLR models with high predictive power, both internally and externally validated, and the definition of chemical domain applicability. This procedure allows a fast ranking of VOCs according to their tendency to be degraded by atmospheric oxidants, starting only from the knowledge of their molecular structure.

[Treatment of pulmonary thromboembolism with extrinsic plasminogen activator. A case report]. / Tratamento do tromboembolismo pulmonar com ativador extrínseco do plasminogênio. Relato de caso.

A 49 year-old woman with acute pulmonary thromboembolism and severe hemodynamic impairment was successfully treated with tissue-type plasminogen activator (r-TPA). She did not have previous pulmonary or cardiac diseases. Thirty days after immobilization of the right ankle, she had a sudden onset of dyspnea, epigastrial pain and syncope. As heparin therapy was unsuccessful, 90 mg of IV r-TPA was administered. There was rapid clinical and hemodynamic improvement of her condition. Pulmonary scanning one week later was normal and she was discharged without symptoms 12 days after the acute episode.

Semivolatile PAH and n-alkane gas/particle partitioning using the dual model: up-to-date coefficients and comparison with experimental data.

The gas/particle partitioning coefficient K p, of a semivolatile compound is a key parameter for its atmospheric fate. The most complete method of predicting K p for polycyclic aromatic hydrocarbons (PAHs) is offered by the dual model, as it describes both the adsorption on soot and absorption into organic matter processes. However, experimental and model data exist almost exclusively for PAHs. In order to bridge this gap, experimental data on the phase partitioning of both PAHs and n-alkanes were collected at an urban and a remote site. Moreover, all the necessary parameters (e.g., octanol-air and soot-air partitioning coefficients) for the dual model have been collected and updated or (if missing) estimated for the first time. The results point out that both absorption and adsorption seem to contribute to the partitioning of PAHs and n-alkanes. However, it seems that the dual model always underestimates the particle sorption not only for PAHs but also for n-alkanes.

The murine long-term multi-lineage renewal marrow stem cell is a cycling cell.

Prevailing wisdom holds that hematopoietic stem cells (HSCs) are predominantly quiescent. Although HSC cycle status has long been the subject of scrutiny, virtually all marrow stem cell research has been based on studies of highly purified HSCs. Here we explored the cell cycle status of marrow stem cells in un-separated whole bone marrow (WBM). We show that a large number of long-term multi-lineage engraftable stem cells within WBM are in S/G2/M phase. Using bromodeoxyuridine, we show rapid transit through the cell cycle of a previously defined relatively dormant purified stem cell, the long-term HSC (LT-HSC; Lineage(-)/c-kit(+)/Sca-1(+)/Flk-2(-)). Actively cycling marrow stem cells have continually changing phenotype with cell cycle transit, likely rendering them difficult to purify to homogeneity. Indeed, as WBM contains actively cycling stem cells, and highly purified stem cells engraft predominantly while quiescent, it follows that the population of cycling marrow stem cells within WBM are lost during purification. Our studies indicate that both the discarded lineage-positive and lineage-negative marrow cells in a stem cell separation contain cycling stem cells. We propose that future work should encompass this larger population of cycling stem cells that is poorly represented in current studies solely focused on purified stem cell populations.