'God is the one who give child': An abductive analysis of barriers to postnatal care using the Health Equity Implementation Framework.

Background: Postnatal care is recommended as a means of preventing maternal mortality during the postpartum period, but many women in low- and middle-income countries (LMICs) do not access care during this period. We set out to examine sociocultural preferences that have been portrayed as barriers to care. Methods: We performed an abductive analysis of 63 semi-structured interviews with women who had recently given birth in three regions of Ethiopia using the Health Equity Implementation Framework (HEIF) and an inductive-deductive codebook to understand why women in Ethiopia do not use recommended postnatal care. Results: We found that, in many cases, health providers do not consider women's cultural safety a primary need, but rather as a barrier to care. However, women's perceived refusal to participate in postnatal visits was, for many, an expression of agency and asserting their needs for cultural safety. Trial registration: n/a. Conclusions: We propose adding cultural safety to HEIF as a process outcome, so that implementers consider cultural needs in a dynamic manner that does not ask patients to choose between meeting their cultural needs and receiving necessary health care during the postnatal period.

"Even though they insult us, the delivery they give us is the greatest thing": a qualitative study contextualizing women's experiences with facility-based maternal health care in Ethiopia.

BACKGROUND: Globally, amidst increased utilization of facility-based maternal care services, there is continued need to better understand women's experience of care in places of birth. Quantitative surveys may not sufficiently characterize satisfaction with maternal healthcare (MHC) in local context, limiting their interpretation and applicability. The purpose of this study is to untangle how contextual and cultural expectations shape women's care experience and what women mean by satisfaction in two Ethiopian regions. METHODS: Health center and hospital childbirth care registries were used to identify and interview 41 women who had delivered a live newborn within a six-month period. We used a semi-structured interview guide informed by the Donabedian framework to elicit women's experiences with MHC and delivery, any prior delivery experiences, and recommendations to improve MHC. We used an inductive analytical approach to compare and contrast MHC processes, experiences, and satisfaction. RESULTS: Maternal and newborn survival and safety were central to women's descriptions of their MHC experiences. Women nearly exclusively described healthy and safe deliveries with healthy outcomes as 'satisfactory'. The texture behind this 'satisfaction', however, was shaped by what mothers bring to their delivery experiences, creating expectations from events including past births, experiences with antenatal care, and social and community influences. Secondary to the absence of adverse outcomes, health provider's interpersonal behaviors (e.g., supportive communication and behavioral demonstrations of commitment to their births) and the facility's amenities (e.g., bathing, cleaning, water, coffee, etc) enhanced women's experiences. Finally, at the social and community levels, we found that family support and material resources may significantly buffer against negative experiences and facilitate women's overall satisfaction, even in the context of poor-quality facilities and limited resources. CONCLUSION: Our findings highlight the importance of understanding contextual factors including past experiences, expectations, and social support that influence perceived quality of MHC and the agency a woman has to negotiate her care experience. Our finding that newborn and maternal survival primarily drove women's satisfaction suggests that quantitative assessments conducted shortly following delivery may be overly influenced by these outcomes and not fully capture the complexity of women's care experience.

Provider perspectives on emotional health care for adults with type 2 diabetes mellitus in the Dominican Republic.

The emotional burden of type 2 diabetes mellitus (T2D) can complicate self-management. Exploring the feasibility of mental and physical health co-management in limited-resourced settings is needed. Thus, we assessed providers' awareness of the emotional burden their patients experience and their roles in supporting their patients with T2D. We conducted a formative qualitative study using in-depth interviews with 14 providers, including physicians, nurses, and community health workers recruited at two rural health clinics in the Dominican Republic. We coded transcripts using inductive and deductive codes and developed themes through iterative comparative analysis. All providers recognized that patients experience an emotional burden managing life with T2D. Some providers viewed the provision of emotional support as integral to their role and believed that they could do so. Others viewed it as the responsibility of the family or expressed the need for additional guidance on how to provide emotional support. Providers also identified several barriers to integrating emotional support into routine clinical care including personality characteristics, lack of training, and insufficient staffing. While providers recognize the need for emotional support, they identified individual, clinical, and systems-level barriers. Strategies to address these barriers include training specific providers on emotional support provision, balancing workload, and building or strengthening referral systems.

Seasonal Urinary Levels of Glyphosate in Children From Agricultural Communities.

BACKGROUND: Glyphosate is one of the most commonly used pesticides in agricultural activities worldwide. For the last 20 years, its use has increased rapidly becoming a public health concern. The IARC classified glyphosate as probably carcinogenic; however, the reported evidence is not enough to establish a statement. OBJECTIVE: This work aimed to measure glyphosate levels in the urine of children from a single rural community in an endemic region of chronic kidney disease and malnutrition. METHODS: A cross-sectional study was carried out in a rural community in western Mexico. The study included 95 children between the ages of 6 and 16. A urine sample (first-morning spot) was obtained from children and processed to measure glyphosate levels using high-performance liquid chromatography coupled with tandem mass spectrometry. RESULTS: All samples tested positive for glyphosate levels. Urine glyphosate levels were related to the season and the age of the children. CONCLUSION: Glyphosate is present in children of all ages in the community even if they were not in direct contact with it. No toxicity cases were reported, nor were there other health problems related to glyphosate. However, more long-term studies should be done that provide a statement regarding the harmful effects that glyphosate has on public health.

SARS-CoV-2 RBD-Tetanus toxoid conjugate vaccine induces a strong neutralizing immunity in preclinical studies

Controlling the global COVID-19 pandemic depends, among other measures, on developing preventive vaccines at an unprecedented pace. Vaccines approved for use and those in development intend to use neutralizing antibodies to block viral sites binding to the hosts cellular receptors. Virus infection is mediated by the spike glycoprotein trimer on the virion surface via its receptor binding domain (RBD). Antibody response to this domain is an important outcome of the immunization and correlates well with viral neutralization. Here we show that macromolecular constructs with recombinant RBD conjugated to tetanus toxoid induce a potent immune response in laboratory animals. Some advantages of the immunization with the viral antigen coupled to tetanus toxoid have become evident such as predominant IgG immune response due to affinity maturation and long-term specific B-memory cells. This paper demonstrates that subunit conjugate vaccines can be an alternative for COVID-19, paving the way for other viral conjugate vaccines based on the use of small viral proteins involved in the infection process.

Foliar mineral content of five shrub species with nutritional potential for small ruminants in semiarid regions in northeastern Mexico / Conteúdo mineral foliar de cinco espécies de arbustos com potencial nutricional para pequenos ruminantes em regiões semiáridas do nordeste do México

ABSTRACT: This study was conducted to determine the monthly composition of the minerals Ca, P, K, Mg, Cu, Fe, Mn and Zn in five shrub species that are consumed by small ruminants in the semi-arid regions of northeastern Mexico. Leaves samples of shrub species; Celtis pallida, Croton suaveolens, Forestiera angustifolia, Guaiacum angustifolium and Parkinsonia aculeata were randomly collected during twelve consecutive months from July 2018 to June 2019 in two sites, located in Linares and Los Ramones counties, in the state of Nuevo Leon, Mexico. Mineral content was analyzed using an atomic absorption spectrophotometer, while phosphorus was measured by the colorimetry method. The Linares county showed the highest content of macro- and micro-minerals. Among species, C. pallida showed the highest values of macro-minerals and P. aculeata content of micro-minerals was highest. Ca (total mean = 40.0 g kg-1 DM), K (15.4 g kg-1), Mg (3.7 g kg-1), Fe (87.2 mg kg-1), Mn (35.5 mg kg-1) were available in adequate quantities, while P (1.3 g kg-1 DM), Cu (6.4 mg kg-1) and Zn (17.7 mg kg-1) were found deficient. Shrub species in this study can be considered as a good source of Ca, K, Mg, Fe and Mn except in C. suaveolens. However, P, Cu and Zn must be supplemented.

RESUMO: O presente estudo foi realizado com o intuito de determinar os teores dos minerais Ca, P, K, Mg, Cu, Fe, Mn e Zn, ao longo do ano, em cinco espécies de arbustos consumidas por pequenos ruminantes nas regiões semiáridas do nordeste do México. Amostras de folhas de espécies arbustivas; Celtis pallida, Croton suaveolens, Forestiera angustifolia, Guaiacum angustifolium e Parkinsonia aculeata foram coletadas aleatoriamente durante doze meses consecutivos, de Julho de 2018 a Junho de 2019, em dois locais, nos municípios de Linares e Los Ramones, no estado de Nuevo Leon, México. O conteúdo mineral foi analisado através de um espectrofotômetro de absorção atômica, enquanto o fósforo foi medido pelo método da colorimetria. O município de Linares apresentou o maior conteúdo de macro e microminerais. Entre as espécies, C. pallida apresentou os maiores valores de macrominerais, enquanto o teor de microminerais foi maior na P. aculeata. Ca (média = 40.0 g kg-1 MS), K (15.4 g kg-1), Mg (3.7 g kg-1), Fe (87.2 mg kg-1), Mn (35.5 mg kg-1) estavam disponíveis em quantidades adequadas, enquanto P (1.3 g kg-1 MS), Cu (6.4 mg kg-1) e Zn (17.7 mg kg-1) foram encontrados deficientes. As espécies arbustivas deste estudo podem ser consideradas uma boa fonte de Ca, K, Mg, Fe e Mn, exceto na espécie C. suaveolens. No entanto, P, Cu e Zn devem ser suplementados.

Optimizing testing methods and collection of reference data for differentiating critical illness polyneuropathy from critical illness MYOPATHIES.

INTRODUCTION: In severe acute quadriplegic myopathy in intensive care unit (ICU) patients, muscle fibers are electrically inexcitable; in critical illness polyneuropathy, the excitability remains normal. Conventional electrodiagnostic methods do not provide the means to adequately differentiate between them. In this study we aimed to further optimize the methodology for the study of critically ill ICU patients and to create a reference database in healthy controls. METHODS: Different electrophysiologic protocols were tested to find sufficiently robust and reproducible techniques for clinical diagnostic applications. RESULTS: Many parameters show large test-retest variability within the same healthy subject. Reference values have been collected and described as a basis for studies of weakness in critical illness. CONCLUSIONS: Using the ratio of neCMAP/dmCMAP (response from nerve and direct muscle stimulation), refractory period, and stimulus-response curves may optimize the electrodiagnostic differentiation of patients with critical illness myopathy from those with critical illness polyneuropathy.

Classification and ordination of main plant communities along an altitudinal gradient in the arid and temperate climates of northeastern Mexico.

Quantitative data on the ecology of the main plant communities along an altitudinal gradient in northeastern Mexico were obtained with the aim of identifying the most important environmental variables that affect plant distribution and composition. The main threats to these communities were also investigated. Importance value index (IVi) of the 39 most important species and 16 environmental variables were recorded at 35 altitudinal gradients each spaced at intervals of at least 100-m altitude. Classification and ordination of vegetation showed six well-differentiated but overlapping plant communities: alpine meadow, cold conifer forest, mesic mixed forest, xeric scrub, Tamaulipan piedmont scrub, and halophytic grassland. Altitude, minimum and average temperatures, and organic matter content are the main variables affecting the plant distribution in northeastern Mexico. Urban growth, mechanized agriculture, and changes in land use are the main threats in the short and medium term to plant communities in this area. Climate change also seems to be having an impact at present or in the near future as shown by the presence of exotic shrubs from warmer areas in mesic and temperate areas inhabited by oak and oak-pine forest.

[The antihypertensive effect of fermented milks]. / El efecto antihipertensivo de las leches fermentadas.

There is a great variety of fermented milks containing lactic acid bacteria that present health-promoting properties. Milk proteins are hydrolyzed by the proteolytic system of these microorganisms producing peptides which may also perform other functions in vivo. These peptides are encrypted within the primary structure of proteins and can be released through food processing, either by milk fermentation or enzymatic hydrolysis during gastrointestinal transit. They perform different activities, since they act in the cardiovascular, digestive, endocrine, immune and nervous systems. Bioactive peptides that have an antihypertensive, antithrombotic, antioxidant and hypocholesterolemic effect on the cardiovascular system can reduce the risk factors for chronic disease manifestation and help improve human health. Most studied bioactive peptides are those which exert an antihypertensive effect by inhibiting the angiotensin-converting enzyme (ACE). Recently, the study of these peptides has focused on the implementation of tests to prove that they have an effect on health. This paper focuses on the production of ACEinhibitory antihypertensive peptides from fermented milks, its history, production and in vivo tests on rats and humans, on which its hypotensive effect has been shown.

El efecto antihipertensivo de las leches fermentadas. / [The antihypertensive effect of fermented milks].

There is a great variety of fermented milks containing lactic acid bacteria that present health-promoting properties. Milk proteins are hydrolyzed by the proteolytic system of these microorganisms producing peptides which may also perform other functions in vivo. These peptides are encrypted within the primary structure of proteins and can be released through food processing, either by milk fermentation or enzymatic hydrolysis during gastrointestinal transit. They perform different activities, since they act in the cardiovascular, digestive, endocrine, immune and nervous systems. Bioactive peptides that have an antihypertensive, antithrombotic, antioxidant and hypocholesterolemic effect on the cardiovascular system can reduce the risk factors for chronic disease manifestation and help improve human health. Most studied bioactive peptides are those which exert an antihypertensive effect by inhibiting the angiotensin-converting enzyme (ACE). Recently, the study of these peptides has focused on the implementation of tests to prove that they have an effect on health. This paper focuses on the production of ACEinhibitory antihypertensive peptides from fermented milks, its history, production and in vivo tests on rats and humans, on which its hypotensive effect has been shown.

Aplicación de una biblioteca de anticuerpos lineales humanos frente al polisacárido capsular de Neisseria meningitidis serogrupo B / Application of a human linear antibody library against the capsular polysaccharide from Neisseria meningitidis serogroup B

Neisseria meningitidis serogrupo B produce aún morbimortalidad significativa. Su polisacárido capsular muestra similitud estructural con proteínas humanas y pobre inmunogenicidad, obstaculizando así el desarrollo de vacunas y anticuerpos monoclonales (AcM) y policlonales contra esta bacteria. Recientemente se han creado bibliotecas artificiales de anticuerpos humanos expresados en bacteriófagos que reconocen específicamente a moléculas diana existentes, con la ventaja sobre los AcM convencionales por su rápida obtención, sin utilización de animales de laboratorio, lo que emerge como alternativa atractiva para la producción de AcM contra antígenos peculiares o complejos. Se realizó un trabajo de investigación básica, utilizando una biblioteca de fagos filamentosos que expresan constitutivamente regiones variables de anticuerpos humanos, que se enfrentó al polisacárido capsular de N. meningitidis serogrupo B. Los resultados que se obtuvieron mediante ELISA policlonal sugieren la existencia de anticuerpos humanos expresados en fagos que lo reconocen(AU)

Neisseria meningitidis serogroup B still produces a significant morbidity and mortality. Bacterial capsular polysaccharide in serogroup B shows structural homologies with human proteins and poor immunogenicity which make difficult the development of vaccines and polyclonal and monoclonal antibodies (MAb) against it. Artificial libraries of human antibodies via the expression and selection of them in bacteriophages have become known. Those antibodies are used as specific recognizing molecules capable to join to almost any existing target, with advantages over conventional MAb due to its faster obtainment without needing animal immunization, emerging as an attractive alternative for the production of MAb against complex or particular antigens. This was a basic experimental piece of work, using a phage library that expresses variable regions of human immunoglobulins to identify ligands with the capacity to recognize N. meningitidis serogroup B polysaccharide. Polyclonal ELISA screening suggests the existence of human antibodies expressed in phages which recognized the antigen of interest(AU)

Stochastic-based descriptors studying biopolymers biological properties: extended MARCH-INSIDE methodology describing antibacterial activity of lactoferricin derivatives.

Lactoferricin are a number of related peptides derived from the enzymatic cleavage of lactoferrin, an iron-binding protein. These peptides, and other peptides derived from them by simple amino acid substitutions, have shown interesting antibacterial activity. In this paper we applied the MARCH-INSIDE methodology extended to peptide and proteins, to a QSAR study related to antibacterial activity of 31 derivatives of lactoffericin against E. Coli and S. Aureus by means of Linear Discriminant (LDA) and Multiple Linear Regression Analysis (MLR). In the case of LDA we obtained models that classify correctly more than 80% of all cases (85.7% for E. Coli antibacterial activity and 83.9 for S. Aureus). With the application of a Leave-One-Out Cross Validation Procedure, the percentage of good classification of both classification models remained near the above reported values (87.1% for E. Coli antibacterial activity and 83.9 for S. Aureus). We obtained several linear regression models taking into account total and local descriptors. The inclusion of those local descriptors improved the correlation parameters, the statistical quality, and the predictive power of the former model obtained only with total descriptors. The best models explained more than 80% of the experimental variance in the antimicrobial activity of those compounds. These results are comparable with those reported previously by Strom (Strom, M. B.; Rekdal, O.; Svendesen, J. S. J Peptide Res 2001, 57, 127-139.) and Tore-Lejon (Lejon, T.; Strom, M.; Svendsen, S. J Protein Sci 2001, 7, 74-78.; Lejon, T.; Svendsen J. S.; Haug, B. E. J Peptide Sci 2002, 8, 302-306.) in a smaller dataset applying Z-scales and volume-based descriptors and PLS as statistical techniques.

A topological sub-structural approach for predicting human intestinal absorption of drugs.

The human intestinal absorption (HIA) of drugs was studied using a topological sub-structural approach (TOPS-MODE). The drugs were divided into three classes according to reported cutoff values for HIA. "Poor" absorption was defined as HIA < or =30%, "high" absorption as HIA > or =80%, whereas "moderate" absorption was defined between these two values (30% < HIA < 79%). Two linear discriminant analyses were carried out on a training set of 82 compounds. The percentages of correct classification, for both models, were 89.02%. The predictive power of the models were validated by three test: a leave-one-out cross validation procedure (88.9% and 87.9%), an external prediction set of 127 drugs (92.9% and 80.31%) and a test set of 109 oral drugs with bioavailability values reported (93.58% and 91.84%). Finally, positive and negative sub-structural contributions to the HIA were identified and their possibilities in the lead generation and optimization process were evaluated.

3D-chiral quadratic indices of the 'molecular pseudograph's atom adjacency matrix' and their application to central chirality codification: classification of ACE inhibitors and prediction of sigma-receptor antagonist activities.

Quadratic indices of the 'molecular pseudograph's atom adjacency matrix' have been generalized to codify chemical structure information for chiral drugs. These 3D-chiral quadratic indices make use of a trigonometric 3D-chirality correction factor. These indices are nonsymmetric and reduced to classical (2D) descriptors when symmetry is not codified. By this reason, it is expected that they will be useful to predict symmetry-dependent properties. 3D-Chirality quadratic indices are real numbers and thus, can be easily calculated in TOMOCOMD-CARDD software. These descriptors circumvent the inability of conventional 2D quadratic indices (Molecules 2003, 8, 687-726. http://www.mdpi.org) and other (chirality insensitive) topological indices to distinguish sigma-stereoisomers. In this paper, we extend our earlier work by applying 3D-chirality quadratic indices to two data sets containing chiral compounds. Consequently, in order to test the potential of this novel approach in drug design we have modelled the angiotesin-converting enzyme inhibitory activity of perindoprilate's sigma-stereoisomers combinatorial library. Two linear discriminant analysis (LDA) models were obtained. The first one model was performed considering all data set as training series and classifies correctly 88.89% of active compounds and 100.00% of nonactive one for a global good classification of 96.87%. The second one LDA-QSAR model classified correctly 83.33% of the active and 100.00% of the inactive compounds in a training set, result that represent a total of 95.65% accuracy in classification. On the other hand, the model classifies 100.00% of these compounds in the test set. Similar predictive behaviour was observed in a leave-one-out cross-validation procedure for both equations. Canonical regression analysis corroborated the statistical quality of these models (R(can) of 0.82 and of 0.76, respectively) and was also used to compute biology activity canonical scores for each compound. Finally, prediction of the biological activities of chiral 3-(3-hydroxyphenyl)piperidines, which are sigma-receptor antagonists, by linear multiple regression analysis was carried out. Two statistically significant QSAR models were obtained (R2=0.940, s=0.270 and R2=0.977, s=0.175). These models showed high stability to data variation in the leave-one-out cross-validation procedure (q2=0.912, scv=0.289 and q2=0.957, scv=0.211). The results of this study compare favourably with those obtained with other chirality descriptors applied to the same data set. The 3D-chiral TOMOCOMD-CARDD approach provides a powerful alternative to 3D-QSAR.

Simple stochastic fingerprints towards mathematical modelling in biology and medicine. 1. The treatment of coccidiosis.

We have developed a classification function that is capable of discriminating between anticoccidial and nonanticoccidial compounds with different structural patterns. For this purpose, we calculated the Markovian electron delocalization negentropies of several compounds. These molecular descriptors, which act as molecular fingerprints, are derived from an electronegativity-weighted stochastic matrix (1Pi). The method attempts to describe the delocalization of electrons with time during the process of molecule formation by considering the 3D environment of the atoms. Accordingly, the entropies of this random process are used as molecular descriptors. The present study involves a stochastic generalization of the original idea described by Kier, which concerned the use of molecular negentropies in QSAR. Linear discriminant analysis allowed us to fit the discriminant function. This function has given rise to a good classification of 82.35% (28 anticoccidials out of 34) and 91.8% of inactive compounds (56/61) in training series. An overall classification of 88.42% (84/95) was achieved. Validation of the model was carried out by means of an external predicting series and this gave a global predictability of 93.1%. Finally, we report the experimental assay (more than 95% of lesion control) of two compounds selected from a large data set through virtual screening. We conclude that the approach described here seems to be a promising 3D-QSAR tool based on the mathematical theory of stochastic processes.

TOPS-MODE based QSARs derived from heterogeneous series of compounds. Applications to the design of new anti-inflammatory compounds.

A new application of TOPological Sub-structural MOlecular DEsign (TOPS-MODE) was carried out in anti-inflammatory compounds using computer-aided molecular design. Two series of compounds, one containing anti-inflammatory and the other containing nonanti-inflammatory compounds were processed by a k-means cluster analysis in order to design the training and prediction sets. A linear classification function to discriminate the anti-inflammatory from the inactive compounds was developed. The model correctly and clearly classified 88% of active and 91% of inactive compounds in the training set. More specifically, the model showed a good global classification of 90%, that is, (399 cases out of 441). While in the prediction set, they showed an overall predictability of 88% and 84% for active and inactive compounds, being the global percentage of good classification of 85%. Furthermore this paper describes a fragment analysis in order to determine the contribution of several fragments towards anti-inflammatory property, also the present of halogens in the selected fragments were analyzed. It seems that the present TOPS-MODE based QSAR is the first alternate general 'in silico' technique to experimentation in anti-inflammatory discovery.

Designing antibacterial compounds through a topological substructural approach.

A novel application of TOPological Substructural MOlecular DEsign (TOPS-MODE) was carried out in antibacterial drugs using computer-aided molecular design. Two series of compounds, one containing antibacterial and the other containing non-antibacterial compounds, were processed by a k-means cluster analysis in order to design training and predicting series. All clusters had a p-level < 0.005. Afterward, a linear classification function has been derived toward discrimination between antibacterial and non-antibacterial compounds. The model correctly classifies 94% of active and 86% of inactive compounds in the training series. More specifically, the model showed a global good classification of 91%, i.e., 263 cases out of 289. In predicting series, the model has shown overall predictabilities of 91 and 83% for active and inactive compounds, respectively. Thereby, the model has a global percentage of good classification of 89%. The TOPS-MODE approach, also, similarly compares with respect to one of the most useful models for antimicrobials selection reported to date.

A novel approach to predict a toxicological property of aromatic compounds in the Tetrahymena pyriformis.

The TOPological Substructural MOlecular DEsign (TOPS-MODE) has been successfully used in order to explain the toxicity in the Tetrahymena pyriformis on a large data set. The obtained models for the training set had good statistical parameters (R(2)=0.72-0.81, p<0.05) an also the prediction power of the models found was adequate (Q(2)=0.70-0.80). A detailed study of the influence of variable numbers in the equation and the statistical outliers was carried out; leading to a good final model with a better physicochemical interpretation than the rest of the published models. Only two molecular descriptors codifying dipolar and hydrophobic features were introduced. Finally, the fragment contributions to the toxicity prediction evidenced the powerful of this topological approach.

Protein quadratic indices of the "macromolecular pseudograph's alpha-carbon atom adjacency matrix". 1. Prediction of Arc repressor alanine-mutant's stability.

This report describes a new set of macromolecular descriptors of relevance to protein QSAR/QSPR studies, protein's quadratic indices. These descriptors are calculated from the macromolecular pseudograph's alpha-carbon atom adjacency matrix. A study of the protein stability effects for a complete set of alanine substitutions in Arc repressor illustrates this approach. Quantitative Structure-Stability Relationship (QSSR) models allow discriminating between near wild-type stability and reduced-stability A-mutants. A linear discriminant function gives rise to excellent discrimination between 85.4% (35/41)and 91.67% (11/12) of near wild-type stability/reduced stability mutants in training and test series, respectively. The model's overall predictability oscillates from 80.49 until 82.93, when n varies from 2 to 10 in leave-n-out cross validation procedures. This value stabilizes around 80.49% when n was > 6. Additionally, canonical regression analysis corroborates the statistical quality of the classification model (Rcanc = 0.72, p-level <0.0001). This analysis was also used to compute biological stability canonical scores for each Arc A-mutant. On the other hand, nonlinear piecewise regression model compares favorably with respect to linear regression one on predicting the melting temperature (tm)of the Arc A-mutants. The linear model explains almost 72% of the variance of the experimental tm (R = 0.85 and s = 5.64) and LOO press statistics evidenced its predictive ability (q2 = 0.55 and scv = 6.24). However, this linear regression model falls to resolve t(m) predictions of Arc A-mutants in external prediction series. Therefore, the use of nonlinear piecewise models was required. The tm values of A-mutants in training (R = 0.94) and test(R = 0.91) sets are calculated by piecewise model with a high degree of precision. A break-point value of 51.32 degrees C characterizes two mutants' clusters and coincides perfectly with the experimental scale. For this reason, we can use the linear discriminant analysis and piecewise models in combination to classify and predict the stability of the mutants' Arc homodimers. These models also permit the interpretation of the driving forces of such a folding process. The models include protein's quadratic indices accounting for hydrophobic (z1), bulk-steric (z2), and electronic (z3) features of the studied molecules. Preponderance of z1 and z3 over z2 indicates the higher importance of the hydrophobic and electronic side chain terms in the folding of the Arc dimer. In this sense, developed equations involve short-reaching (k < or = 3), middle- reaching (3 < k < or = 7) and far-reaching (k= 8 or greater) z1, 2, 3-protein's quadratic indices. This situation points to topologic/topographic protein's backbone interactions control of the stability profile of wild-type Arc and its A-mutants. Consequently, the present approach represents a novel and very promising way to mathematical research in biology sciences.

Vibrational Markovian modelling of footprints after the interaction of antibiotics with the packaging region of HIV type 1.

The design of novel anti-HIV compounds has now become a crucial area for scientists working in numerous interrelated fields of science such as molecular biology, medicinal chemistry, mathematical biology, molecular modelling and bioinformatics. In this context, the development of simple but physically meaningful mathematical models to represent the interaction between anti-HIV drugs and their biological targets is of major interest. One such area currently under investigation involves the targets in the HIV-RNA-packaging region. In the work described here, we applied Markov chain theory in an attempt to describe the interaction between the antibiotic paromomycin and the packaging region of the RNA in Type-1 HIV. In this model, a nucleic acid squeezed graph is used. The vertices of the graph represent the nucleotides while the edges are the phosphodiester bonds. A stochastic (Markovian) matrix was subsequently defined on this graph, an operation that codifies the probabilities of interaction between specific nucleotides of HIV-RNA and the antibiotic. The strength of these local interactions can be calculated through an inelastic vibrational model. The successive power of this matrix codifies the probabilities with which the vibrations after drug-RNA interactions vanish along the polynucleotide main chain. The sums of self-return probabilities in the k-vicinity of each nucleotide represent physically meaningful descriptors. A linear discriminant function was developed and gave rise to excellent discrimination in 80.8% of interacting and footprinted nucleotides. The Jackknife method was employed to assess the stability and predictability of the model. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the antibiotic (R(2)=0.91, Q(2)=0.86). These kinds of models could play an important role either in the discovery of new anti-HIV compounds or the study of their mode of action.