Enhancing Bone Infection Diagnosis with Raman Handheld Spectroscopy: Pathogen Discrimination and Diagnostic Potential

Osteomyelitis is a bone disease caused by bacteria that can damage bone. Raman handheld spectroscopy has emerged as a promising diagnostic tool for detecting bone infection and can be used intraoperatively during surgical procedures. This study involved 120 bone samples from 40 patients, with 80 samples infected with either Staphylococcus aureus or Staphylococcus epidermidis. Raman handheld spectroscopy demonstrated successful differentiation between healthy and infected bone samples and between the two types of bacterial pathogens. Raman handheld spectroscopy appears to be a promising diagnostic tool in bone infection and holds the potential to overcome many of the shortcomings of traditional diagnostic procedures. Further research, however, is required to confirm its diagnostic capabilities and consider other factors, such as the limit of pathogen detection and optimal calibration standards.

Comparison of Mid-Infrared Handheld and Benchtop Spectrometers to Detect Staphylococcus epidermidis in Bone Grafts

Bone analyses using mid-infrared spectroscopy are gaining popularity, especially with handheld spectrometers that enable on-site testing as long as the data quality meets standards. In order to diagnose Staphylococcus epidermidis in human bone grafts, this study was carried out to compare the effectiveness of the Agilent 4300 Handheld Fourier-transform infrared with the Perkin Elmer Spectrum 100 attenuated-total-reflectance infrared spectroscopy benchtop instrument. The study analyzed 40 non-infected and 10 infected human bone samples with Staphylococcus epidermidis, collecting reflectance data between 650 cm-1 and 4000 cm-1, with a spectral resolution of 2 cm-1 (Agilent 4300 Handheld) and 0.5 cm-1 (Perkin Elmer Spectrum 100). The acquired spectral information was used for spectral and unsupervised classification, such as a principal component analysis. Both methods yielded significant results when using the recommended settings and data analysis strategies, detecting a loss in bone quality due to the infection. MIR spectroscopy provides a valuable diagnostic tool when there is a tissue shortage and time is of the essence. However, it is essential to conduct further research with larger sample sizes to verify its pros and cons thoroughly.

Computational insight into the binding of bryostatin 1 with ferritin: implication of natural compounds in Alzheimer's disease therapeutics

Neuronal damage in iron-sensitive brain regions occurs as a result of iron dyshomeostasis. Increased iron levels and iron-related pathogenic triggers are associated with neurodegenerative diseases, including Alzheimer's disease (AD). Ferritin is a key player involved in iron homeostasis. Major pathological hallmarks of AD are amyloid plaques, neurofibrillary tangles (NFTs) and synaptic loss that lead to cognitive dysfunction and memory loss. Natural compounds persist in being the most excellent molecules in the area of drug discovery because of their different range of therapeutic applications. Bryostatins are naturally occurring macrocyclic lactones that can be implicated in AD therapeutics. Among them, Bryostatin 1 regulates protein kinase C, a crucial player in AD pathophysiology, thus highlighting the importance of bryostatin 1 in AD management. Thus, this study explores the binding mechanism of Bryotstain 1 with ferritin. In this work, the molecular docking calculations revealed that bryostatin 1 has an appreciable binding potential towards ferritin by forming stable hydrogen bonds (H-bonds). Molecular dynamics simulation studies deciphered the binding mechanism and conformational dynamics of ferrritin-bryostatin 1 system. The analyses of root mean square deviation, root mean square fluctuations, R_g, solvent accessible surface area, H-bonds and principal component analysis revealed the stability of the ferritin-bryostatin 1 docked complex throughout the trajectory of 100 ns. Moreover, the free energy landscape analysis advocated that the ferritin-bryostatin 1 complex stabilized to the global minimum. Altogether, the present work delineated the binding of bryostatin 1 with ferritin that can be implicated in the management of AD.Communicated by Ramaswamy H. Sarma.

Dietary Patterns among Adolescents Are Associated with Growth, Socioeconomic Features, and Health-Related Behaviors

Dietary patterns (DPs), usually established in adolescents, are important modifiable risk factors in the etiology of malnutrition and chronic diseases. This study aimed to identify DPs of adolescents and examine their associations with growth, sociodemographic, and lifestyle characteristics. A nationally representative, school-based, cross-sectional study was conducted in Israeli adolescents aged 11-18 years during 2015-2016. A self-administered survey queried sociodemographics, health behaviors, and diet. Weight and height were measured, and WHO height z-scores and BMI cutoffs were calculated. Food frequency questionnaire data were analyzed using principal components analysis (PCA) to identify DPs. Associations between growth, lifestyle, and sociodemographic characteristics and DPs were modeled using multivariable logistic regressions. A total of 3902 adolescents (46% males, mean age 15.2 ± 1.6 years) completed the survey. PCA identified five DPs, accounting for 38.3% of the total variance. The first two prominent DPs were the 'plant-based food' DP, which was associated with the female sex, higher socioeconomic status, overweight/obesity, and healthy lifestyle and the 'junk food' DP, which was associated with lower SES, unhealthy lifestyle, and lower height z-scores. Our results elucidate major DPs that strongly correlate with lifestyle risk behaviors and suboptimal growth among adolescents. Implementing screening for DPs should be further examined to identify higher risk health factors among youth.

Application of mid-infrared microscopic imaging for the diagnosis and classification of human lymphomas

Mid-infrared (MIR) microscopic imaging of indolent and aggressive lymphomas was performed including formalin-fixed and paraffin-embedded samples of six follicular lymphomas and 12 diffuse large B-cell-lymphomas as well as reactive lymph nodes to investigate benefits and challenges for lymphoma diagnosis. MIR images were compared to defined pathological characteristics such as indolent versus aggressive versus reactive, germinal centre versus activated cell-of-origin (COO) subtypes, or a low versus a high proliferative index and level of PD-L1 expression. We demonstrated that MIR microscopic imaging can differentiate between reactive lymph nodes, indolent and aggressive lymphoma samples. Also, it has potential to be used in the subtyping of lymphomas, as shown with the differentiation between COO subtypes, the level of proliferation and PD-L1 expression. MIR microscopic imaging is a promising tool for diagnosis and subtyping of lymphoma and further evaluation is needed to fully explore the advantages and disadvantages of this method for pathological diagnosis.

The evolution of trait correlations constrains phenotypic adaptation to high CO2 in a eukaryotic alga

Microbes form the base of food webs and drive biogeochemical cycling. Predicting the effects of microbial evolution on global elemental cycles remains a significant challenge due to the sheer number of interacting environmental and trait combinations. Here, we present an approach for integrating multivariate trait data into a predictive model of trait evolution. We investigated the outcome of thousands of possible adaptive walks parameterized using empirical evolution data from the alga Chlamydomonas exposed to high CO₂. We found that the direction of historical bias (existing trait correlations) influenced both the rate of adaptation and the evolved phenotypes (trait combinations). Critically, we use fitness landscapes derived directly from empirical trait values to capture known evolutionary phenomena. This work demonstrates that ecological models need to represent both changes in traits and changes in the correlation between traits in order to accurately capture phytoplankton evolution and predict future shifts in elemental cycling.

Phylogenetic Structure and Sequential Dominance of Sub-Lineages of PRRSV Type-2 Lineage 1 in the United States

The genetic diversity and frequent emergence of novel genetic variants of porcine reproductive and respiratory syndrome virus type-2 (PRRSV) hinders control efforts, yet drivers of macro-evolutionary patterns of PRRSV remain poorly documented. Utilizing a comprehensive database of >20,000 orf5 sequences, our objective was to classify variants according to the phylogenetic structure of PRRSV co-circulating in the U.S., quantify evolutionary dynamics of sub-lineage emergence, and describe potential antigenic differences among sub-lineages. We subdivided the most prevalent lineage (Lineage 1, accounting for approximately 60% of available sequences) into eight sub-lineages. Bayesian coalescent SkyGrid models were used to estimate each sub-lineage's effective population size over time. We show that a new sub-lineage emerged every 1 to 4 years and that the time between emergence and peak population size was 4.5 years on average (range: 2-8 years). A pattern of sequential dominance of different sub-lineages was identified, with a new dominant sub-lineage replacing its predecessor approximately every 3 years. Consensus amino acid sequences for each sub-lineage differed in key GP5 sites related to host immunity, suggesting that sub-lineage turnover may be linked to immune-mediated competition. This has important implications for understanding drivers of genetic diversity and emergence of new PRRSV variants in the U.S.

Placental Characteristics Classification of Various Native Turkish Sheep Breeds

Simple Summary

The aim of this study was to classify placental characteristics of Akkaraman, Morkaraman, Karayaka, Awassi, Malya, and Bafra native sheep breeds using the hierarchical clustering method. As a result, six breeds were separated into three clusters: the first cluster consisted of Bafra, Karayaka, and Awassi breeds; the second consisted of Akkaraman and Malya breeds; and the third cluster included only the Morkaraman breed.

Abstract

The aim of this study was to classify placental characteristics of Akkaraman, Morkaraman, Karayaka, Awassi, Malya, and Bafra sheep breeds using the hierarchical clustering method. In total, 240 individual data records were used as experimental material. Placental characteristics such as total cotyledon surface area, small and large cotyledon length, small cotyledon depth, etc. were used as explanatory variables to classify the breeds’ characteristics. Hierarchical clustering was used with the nearest neighbour method with Euclidean distance in order to classify the sheep breeds’ variations. As a result, six breeds were separated into three clusters: the first cluster consisted of Bafra, Karayaka, and Awassi breeds; the second consisted of Akkaraman and Malya breeds; and the third cluster included only the Morkaraman breed. Bafra and Karayaka were pointed as the nearest breeds, with a similarity of 98.7% in terms of placental characteristics. The similarity rate of the Akkaraman and Malya breeds was at a level of 97.5%, whereas it was 96.8% for Bafra, Karayaka, and Awassi breeds. The similarity of Akkaraman, Karayaka, Awassi, Malya, and Bafra sheep breeds was estimated as 95.7%. The overall similarity was found to be at a level of 93.2% among sheep breeds. The outcomes of the study might be useful as a selection tool for reproductivity and can be used to select the breed to be reared.

Soybean Root Growth in Response to Chemical, Physical, and Biological Soil Variations

Environmental conditions affect crop yield, and water deficit has been highlighted by the negative impact on soybean grain production. Radicial growth in greater volume and depth can be an alternative to minimize losses caused by a lack of water. Therefore, knowledge of how soybean roots behave before the chemical, physical, and biological attributes of the soil can help establish managements that benefit in-depth root growth. The objective was to evaluate the growth of soybean roots in response to chemical, physical, and biological variations in the soil, in different soil locations and depths. Six experiments were conducted in different locations. Soil samples were collected every 5 cm of soil up to 60 cm of soil depth for chemical, physical, and biological analysis. The roots were collected every 5 cm deep up to 45 cm deep from the ground. The six sites presented unsatisfactory values of pH and organic matter, and presented phosphorus, potassium, and calcium at high concentrations in the first centimeters of soil depth. The total porosity of the soil was above 0.50 m³ m^-3, but the proportion of the volume of macropores, micropores, and cryptopores resulted in soils with resistance to penetration to the roots. Microbial biomass was higher on the soil surface when compared to deeper soil layers, however, the metabolic quotient was higher in soil depth, showing that microorganisms in depth have low ability to incorporate carbon into microbial biomass. Root growth occurred in a greater proportion in the first centimeters of soil-depth, possibly because the soil attributes that favor the root growth is concentrated on the soil surface.

Clinical Heterogeneity of Acquired Idiopathic Isolated Adrenocorticotropic Hormone Deficiency

OBJECTIVE

Heterogeneous clinical characteristics are observed in acquired isolated adrenocorticotropic hormone (ACTH) deficiency (IAD); however, its classification remains to be established because of its largely unknown pathophysiology. In IAD, anti-pituitary antibodies have been detected in some patients, although their significance remains unclear. Therefore, this study aimed to classify patients with IAD and to clarify the significance of anti-pituitary antibodies.

DESIGN AND METHODS

We analyzed 46 consecutive patients with IAD. Serum anti-pituitary antibodies were analyzed via immunofluorescence staining using a mouse pituitary tissue. Principal component and cluster analyses were performed to classify IAD patients based on clinical characteristics and autoantibodies.

RESULTS

Immunofluorescence analysis using the sera revealed that 58% of patients showed anti-corticotroph antibodies and 6% of patients showed anti-follicular stellate cell (FSC) antibodies. Principal component analysis demonstrated that three parameters could explain 70% of the patients. Hierarchical cluster analysis showed three clusters: Groups A and B comprised patients who were positive for anti-corticotroph antibodies, and plasma ACTH levels were extremely low. Groups A and B comprised middle-aged or elderly men and middle-aged women, respectively. Group C comprised patients who were positive for the anti-FSC antibody and elderly men; plasma ACTH levels were relatively high.

CONCLUSIONS

Patients with IAD were classified into three groups based on clinical characteristics and autoantibodies. The presence of anti-corticotroph antibody suggested severe injury to corticotrophs. This new classification clearly demonstrated the heterogeneity in the pathogenesis of IAD.

Data-Driven, Visual Framework for the Characterization of Aphasias Across Stroke, Post-resective, and Neurodegenerative Disorders Over Time

Aphasia classifications and specialized language batteries differ across the fields of neurodegenerative disorders and lesional brain injuries, resulting in difficult comparisons of language deficits across etiologies. In this study, we present a simplified framework, in which a widely-used aphasia battery captures clinical clusters across disease etiologies and provides a quantitative and visual method to characterize and track patients over time. The framework is used to evaluate populations representing three disease etiologies: stroke, primary progressive aphasia (PPA), and post-operative aphasia. A total of 330 patients across three populations with cerebral injury leading to aphasia were investigated, including 76 patients with stroke, 107 patients meeting criteria for PPA, and 147 patients following left hemispheric resective surgery. Western Aphasia Battery (WAB) measures (Information Content, Fluency, answering Yes/No questions, Auditory Word Recognition, Sequential Commands, and Repetition) were collected across the three populations and analyzed to develop a multi-dimensional aphasia model using dimensionality reduction techniques. Two orthogonal dimensions were found to explain 87% of the variance across aphasia phenotypes and three disease etiologies. The first dimension reflects shared weighting across aphasia subscores and correlated with aphasia severity. The second dimension incorporates fluency and comprehension, thereby separating Wernicke's from Broca's aphasia, and the non-fluent/agrammatic from semantic PPA variants. Clusters representing clinical classifications, including late PPA presentations, were preserved within the two-dimensional space. Early PPA presentations were not classifiable, as specialized batteries are needed for phenotyping. Longitudinal data was further used to visualize the trajectory of aphasias during recovery or disease progression, including the rapid recovery of post-operative aphasic patients. This method has implications for the conceptualization of aphasia as a spectrum disorder across different disease etiology and may serve as a framework to track the trajectories of aphasia progression and recovery.

Signatures of T and B Cell Development, Functional Responses and PD-1 Upregulation After HCMV Latent Infections and Reactivations in Nod.Rag.Gamma Mice Humanized With Cord Blood CD34+ Cells

Human cytomegalovirus (HCMV) latency is typically harmless but reactivation can be largely detrimental to immune compromised hosts. We modeled latency and reactivation using a traceable HCMV laboratory strain expressing the Gaussia luciferase reporter gene (HCMV/GLuc) in order to interrogate the viral modulatory effects on the human adaptive immunity. Humanized mice with long-term (more than 17 weeks) steady human T and B cell immune reconstitutions were infected with HCMV/GLuc and 7 weeks later were further treated with granulocyte-colony stimulating factor (G-CSF) to induce viral reactivations. Whole body bio-luminescence imaging analyses clearly differentiated mice with latent viral infections vs. reactivations. Foci of vigorous viral reactivations were detectable in liver, lymph nodes and salivary glands. The number of viral genome copies in various tissues increased upon reactivations and were detectable in sorted human CD14⁺, CD169⁺, and CD34⁺ cells. Compared with non-infected controls, mice after infections and reactivations showed higher thymopoiesis, systemic expansion of Th, CTL, Treg, and Tfh cells and functional antiviral T cell responses. Latent infections promoted vast development of memory CD4⁺ T cells while reactivations triggered a shift toward effector T cells expressing PD-1. Further, reactivations prompted a marked development of B cells, maturation of IgG⁺ plasma cells, and HCMV-specific antibody responses. Multivariate statistical methods were employed using T and B cell immune phenotypic profiles obtained with cells from several tissues of individual mice. The data was used to identify combinations of markers that could predict an HCMV infection vs. reactivation status. In spleen, but not in lymph nodes, higher frequencies of effector CD4⁺ T cells expressing PD-1 were among the factors most suited to distinguish HCMV reactivations from infections. These results suggest a shift from a T cell dominated immune response during latent infections toward an exhausted T cell phenotype and active humoral immune response upon reactivations. In sum, this novel in vivo humanized model combined with advanced analyses highlights a dynamic system clearly specifying the immunological spatial signatures of HCMV latency and reactivations. These signatures can be merged as predictive biomarker clusters that can be applied in the clinical translation of new therapies for the control of HCMV reactivation.

Cancer-related cognitive impairment in breast cancer survivors: An examination of conceptual and statistical cognitive domains using principal component analysis

There is a great deal of variability in the composition of neuropsychological test batteries used in the assessment of cancerrelated cognitive impairment (CRCI). Not only the development of a gold standard approach for CRCI assessment would allow for easier identification of women suffering from CRCI but it would also promote optimal care for survivors. As a first step towards the development of a valid and reliable unified test battery, the objective of this study was to verify whether the theoretical domains commonly used in CRCI assessment are statistically supported, before and after breast cancer treatment. Principal component analyses (PCA) were performed on the results from 23 neuropsychological tests grouped into eight conceptual domains. For baseline data, the Kaiser-Meyer-Olkin was .82 and Bartlett's X2(253, N=95) = 949.48, P<0.001. A five-component solution explained 60.94% of the common variance. For the post-treatment data, the Kaiser-Meyer-Olkin was .83 and Bartlett's X2(253, N=95) = 1007.21, P<0.001 and a five component solution explained 62.03% of the common variance. Although a visual comparison of the theoretical model with those determined via PCA indicated important overlap between conceptual domains and statistical components, significant dissimilarities were also observed.

Neanderthal and Denisova genetic affinities with contemporary humans: introgression versus common ancestral polymorphisms

Analyses of the genetic relationships among modern humans, Neanderthals and Denisovans have suggested that 1-4% of the non-Sub-Saharan African gene pool may be Neanderthal derived, while 6-8% of the Melanesian gene pool may be the product of admixture between the Denisovans and the direct ancestors of Melanesians. In the present study, we analyzed single nucleotide polymorphism (SNP) diversity among a worldwide collection of contemporary human populations with respect to the genetic constitution of these two archaic hominins and Pan troglodytes (chimpanzee). We partitioned SNPs into subsets, including those that are derived in both archaic lineages, those that are ancestral in both archaic lineages and those that are only derived in one archaic lineage. By doing this, we have conducted separate examinations of subsets of mutations with higher probabilities of divergent phylogenetic origins. While previous investigations have excluded SNPs from common ancestors in principal component analyses, we included common ancestral SNPs in our analyses to visualize the relative placement of the Neanderthal and Denisova among human populations. To assess the genetic similarities among the various hominin lineages, we performed genetic structure analyses to provide a comparison of genetic patterns found within contemporary human genomes that may have archaic or common ancestral roots. Our results indicate that 3.6% of the Neanderthal genome is shared with roughly 65.4% of the average European gene pool, which clinally diminishes with distance from Europe. Our results suggest that Neanderthal genetic associations with contemporary non-Sub-Saharan African populations, as well as the genetic affinities observed between Denisovans and Melanesians most likely result from the retention of ancient mutations in these populations.

Inter-Laboratory Variability in Array-Based RNA Quantification Methods

Ribonucleic acids (RNA) are hypothesized to have preceded their derivatives, deoxyribonucleic acids (DNA), as the molecular media of genetic information when life emerged on earth. Molecular biologists are accustomed to the dramatic effects a subtle variation in the ribose moiety composition between RNA and DNA can have on the stability of these molecules. While DNA is very stable after extraction from biological samples and subsequent treatment, RNA is notoriously labile. The short half-life property, inherent to RNA, benefits cells that do not need to express their entire repertoire of proteins. The cellular machinery turns off the production of a given protein by shutting down the transcription of its cognate coding gene and by either actively degrading the remaining mRNA or allowing it to decay on its own. The steady-state level of each mRNA in a given cell varies continuously and is specified by changing kinetics of synthesis and degradation. Because it is technically possible to simultaneously measure thousands of nucleic acid molecules, these quantities have been studied by the life sciences community to investigate a range of biological problems. Since the RNA abundance can change according to a wide range of perturbations, this makes it the molecule of choice for exploring biological systems; its instability, on the other hand, could be an underestimated source of technical variability. We found that a large fraction of the RNA abundance originally present in the biological system prior to extraction was masked by the RNA labeling and measurement procedure. The method used to extract RNA molecules from cells and to label them prior to hybridization operations on DNA arrays affects the original distribution of RNA. Only if RNA measurements are performed according to the same procedure can biological information be inferred from the assay read out.