Biological Relationships Research Articles

Biological mechanism and functional verification of key genes related to major depressive disorder and type 2 diabetes mellitus.

Major depressive disorder (MDD) and type 2 diabetes (T2D) have been shown to be linked, but a comprehensive understanding of the underlying molecular mechanisms remains elusive. The purpose of this study was to explore the biological relationship between MDD and T2D and verify the functional roles of key genes. We used the Gene Expression Omnibus database to investigate the targets associated with MDD and T2D. Using linear models for microarray data, differentially expressed genes associated with MDD and T2D were identified in GSE76826 and GSE95849, respectively, and 126 shared genes were significantly upregulated. Weighted gene coexpression network analysis identified modules associated with MDD and T2D in the GSE38206 and GSE20966 datasets and identified 8 common genes. Functional enrichment analysis revealed that these genes were enriched in cell signaling, enzyme activity, cell structure and amino acid biosynthesis and involved in cell death pathways. Finally, combined with the CTD and GeneCards databases, lysophosphatidylglycerol acyltransferase 1 (LPGAT1) was identified as a key gene. LPGAT1 was validated in GSE201332 and GSE182117, and the subject operating characteristic curve showed good diagnostic potential for MDD and T2D. Additionally, we used an in vitro model of MDD related to T2D to verify the expression of LPGAT1. A subsequent gene knockdown assay revealed that the downregulation of LPGAT1 improved mitochondrial function and reduced apoptosis in damaged neurons. Taken together, our results highlight the role of LPGAT1 in the connection between MDD and T2D, and these findings provide new insights into potential therapeutic targets for depression associated with diabetes.

Endophytic Mycorrhiza-mediated Phytogen resistance in plants

Objective: Mycorrhizal fungi are a group of microorganisms that live insithusants, thus, maintaining perceptible associations with their host plants in certain parts of their life cycle. They can be characterized by their capacity to synthesize secondary metabolites and to promote growth and induce plant-disease resistance, therefore, gaining greater biotechnological importance in pest and diseases management for crops of agricultural relevance. The study of these microorganisms has been a widely researched area subject for more than half a century. Design/methodology/approach: Their biology and molecular relationships in plant-microorganism interactions, on the other hand, have only recently begun to gain relevance for understanding the colonization process in recent decades. There has been observed a complexity in the generation of formulations that can guarantee the permanence of fungi outside the host plant. Findings/conclusions: This review article will address topics related to their biology, ecological role, possible negative effects on commercially important animals, and successful cases in Mexico regarding biotechnological products based on these microorganisms.

Laboratory Hosts: Postcolonial Parasites, Growth Factors, and the Fabrication of a Molecular Gaze

From the final decades of the nineteenth century onward, physicians and scientists trained in Europe’s colonial powers devoted considerable attention to the lives of parasitic organisms found in the bloodstreams of humans and other animal hosts. Initially, this work required direct access to blood freshly sampled from a host and was spurred by desires to reduce the incidence of so-called tropical diseases such as malaria and sleeping sickness, which were especially prevalent in parts of the world that European powers had claimed as colonies. Soon, noting the successes of bacteriologists in cultivating pathogenic bacteria in sterilized glass containers, some researchers set out to domesticate parasitic protozoa, as well. By the early twentieth century, these investigators had codified recipes for culturing a range of blood parasites, dramatically increasing the mobility of these organisms between colonial and metropolitan laboratories. This essay explores a handful of the many meanings that researchers attached to parasites in vitro. As pathogens, these organisms stubbornly confounded colonial campaigns to staunch their spread between human and animal hosts, yet as laboratory organisms, they posed timely and tractable intellectual puzzles, such as how molecularly defined nutrients functioned in the broader metabolic contexts of living cells. This essay traces a genealogy of experimental practices that gave rise to laboratory hosts. By mimicking or supplanting the functions of living hosts’ bodies, laboratory hosts transformed blood parasites into experimental tools. In time, they additionally came to incorporate synthetic and manufactured ingredients, further alienating parasites from their former dependencies on hosts’ blood. Through these nutritional negotiations, researchers reimagined specific biological relationships as generic chemical ones, thus rendering parasites viable models of metabolic processes unfolding in a great many living things. While eliciting skepticism from some commentators, such chemical views of nature’s order grew enormously influential in midcentury biology and medicine. In examining a selection of the materials and techniques that made up laboratory hosts, this essay illuminates significant yet overlooked continuities between the practices of colonial era tropical medicine and postwar molecular life science.

Comorbidity alters the genetic relationship between anxiety disorders and major depression.

There is extensive comorbidity between anxiety disorders (ANX) and major depression (MD). Most studies on the genetics of ANX do not exclude comorbid cases of MD, and vice versa, therefore confounding genetic association analyses. Disorder-specific analysis of genomic data may reveal more precise biological pathways and causal relationships. To investigate the genetic relationship between disorder-specific ANX and MD compared to samples with comorbidity, including their causal relationship. Data from UK Biobank was used to perform genome-wide association studies (GWAS) of ANX-only and MD-only, and generate disorder-specific polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa) was used to test the associations of PRS with diagnosis and symptoms. MD and ANX GWAS data including comorbidities (MD-co and ANX-co) were used as comparators. Genetic correlation was assessed using LDSC, and Mendelian randomization was employed to infer causal relationships. GWAS of ICD-10 diagnoses of ANX, MD, or both. Genetic correlations between pairs of ANX and MD phenotypes. PRS associations with diagnoses of ANX, MD, and their comorbid states, and anxiety or depressive symptoms. The GWAS of ANX-only (9,980 cases and 179,442 controls) and MD-only (15,301 cases and 179,038 controls) showed a lower genetic correlation (0.53) than the one between ANX-co and MD-co (0.90). ANX-only showed a causal relationship with MD-only (P FDR =1.5e-02), but not vice versa , while comorbid cases showed a significant bidirectional causal relationship (P FDR =2.9e-12, P FDR =9.3e-06). The PRS-MD-only were differentially associated with MD-only compared to ANX-only cases (β= -0.08; 95%CI: -0.11, -0.03); however, this differential association was not observed for the PRS-MD-co. A similar pattern of differential association with anxiety and depressive symptoms was observed for PRS-ANX-only, but not for PRS-MD-co. The genetics and underlying biology of ANX and MD are more distinct when comorbid cases are excluded from analyses and reveals that ANX may be causal for MD. This confounding of genetic relationships as a result of comorbidity is likely to apply to other psychiatric disorders. Disorder-specific genetic studies may help uncover more relevant biological mechanisms and guide more targeted clinical interventions. Question: Is the high genetic correlation between anxiety disorders (ANX) and major depression (MD) due to phenotypic overlap (comorbidity) and will disorder-specific (non-comorbid) analysis provide insight into their underlying causal factors?Findings: Applying statistical genetics tools in two large population samples (UK Biobank, n=500,000; and MoBa, n= 130,000), we found a smaller genetic correlation between MD and ANX when comorbid cases were excluded. Additionally, after excluding comorbid cases, Mendelian randomization revealed that genetic liability to ANX is causally linked to MD but not vice versa . Meaning: The genetic overlap between ANX and MD may be driven by phenotypic comorbidity, which inflates their genetic correlation. The results support that ANX has a causal link to MD, suggesting that early interventions for ANX may prevent subsequent development of MD. Further, investigating the genetic underpinnings of ANX and MD, while excluding their comorbid states, may help advance precision medicine and uncover novel biological mechanisms.

Multi-modal characterization of rodent tooth development.

Craniofacial tissues undergo hard tissue development through mineralization and changes in physicochemical properties. This study investigates the mechanical and chemical properties of developing enamel, dentin, and bone in the mouse mandible. We employ a multi-modal, multi-scale analysis of the developing incisor and first molar at postnatal day 12 by integrating micro-computed tomography (microCT), nanoindentation (NI), energy dispersive spectroscopy (EDS), and Raman spectroscopy. Our findings demonstrate distinct patterns of mechanical, elemental, and chemical changes across mineralized tissues. These results suggest that mineral composition drives mechanical properties across different craniofacial hard tissues. Integrating multi-modal characterization of mineralized tissues opens new opportunities for investigating structure-function relationships in craniofacial biology and genetics.

Biomolecular analysis of the Epigravettian human remains from Riparo Tagliente in northern Italy

The Epigravettian human remains from Riparo Tagliente in northern Italy represent some of the earliest evidence of human occupation in the southern Alpine slopes after the Last Glacial Maximum. Genomic analyses of the 17,000-year-old Tagliente 2 mandible revealed the oldest presence of a genetic profile with affinities to the Near East in the Italian peninsula, which later became the most widespread hunter-gatherer ancestry across Europe. However, a comparable biomolecular characterization of the Tagliente 1 burial remains unavailable, preventing us from defining its biological relationships with Tagliente 2. Here, we apply paleogenomic, isotopic, and radiocarbon dating analyses on a femur fragment of Tagliente 1 and compare the reconstructed data with previously reported results from Tagliente 2. Despite their different isotopic signatures and non-overlapping radiocarbon dates, we reveal that the two human remains belong to the same male individual. We determine that the distinct isotopic values can be explained by different dietary practices during lifetime, whereas the non-overlapping radiocarbon dates can be caused by minimal radiocarbon contamination, possibly deriving from chemical treatments for conservation purposes. These findings highlight the importance of interdisciplinary biomolecular studies in offering new perspectives on the Palaeolithic fossil record and addressing long-standing bioarchaeological questions.

NeuroSCAN: Exploring Neurodevelopment via Spatiotemporal Collation of Anatomical Networks.

Volume electron microscopy (vEM) datasets such as those generated for connectome studies allow nanoscale quantifications and comparisons of the cell biological features underpinning circuit architectures. Quantifications of cell biological relationships in the connectome result in rich multidimensional datasets that benefit from data science approaches, including dimensionality reduction and integrated graphical representations of neuronal relationships. We developed NeuroSCAN, an online open-source platform that bridges sophisticated graph analytics from data science approaches with the underlying cell biological features in the connectome. We analyze a series of published C. elegans brain neuropils and demonstrate how these integrated representations of neuronal relationships facilitate comparisons across connectomes, catalyzing new insights on the structure-function relationships of the circuits and their changes during development. NeuroSCAN is designed for intuitive examination and comparisons across connectomes, enabling synthesis of knowledge from high-level abstractions of neuronal relationships derived from data science techniques to the detailed identification of the cell biological features underpinning these abstractions.

Successional changes in aphyllophorales macromycetes at different stages of coniferous xylolysis

The state of modern protective plantations in coniferous-deciduous forests of the Non-Chernozem zone is characterized by great heterogeneity. Currently, both protective forest plantations and protective tree plantations are managed by an extensive method, often without taking into account biological relationships in the agrophytocenosis. Successional changes in Aphyllophorales macromycetes (AFMM) at different stages of xylolysis of large tree debris represent a complex biochemical process. The limiting conditions for the active growth of fungal mycelium inside wood include light, access to moisture and air, violations in water transport. As mycogenic xylolysis develops, there is an increase in the biodiversity of AFMM species, which reaches a maximum at stage III–IV. On a large data set of 332 model trees and 3,543 basidiomes of xylotrophic basidiomycetes, the presence of correlations between the settlement on the substrate of various ecological groups of AFMM involved in xylolysis was established. It has also been shown that the fruit bodies of fungi are actively formed under conditions of abiotic stress and their number increases in subsequent seasons. When using AFMM as indicators of the xylolysis stage of coniferous species, it is necessary to take into account that the development of mycelium depends on the structural features of the wood. The course of mycelium development in the trunk cross-section is associated with both the action of external environmental factors and interference processes between species. At the same time, the frequency of basidioma formation and their age are of great importance in field identification.

Deep Learning-Based Integration of Morphology and Immunophenotype Predicts Molecular Genetic Subtypes of Multiple Myeloma

Abstract Multiple myeloma, the second most common hematologic malignancy, is characterized by recurrent molecular genetic variants which portend important prognostic and therapeutic implications. These variants, which include chromosomal aneuploidies, translocations, and other structural changes, are currently identified by performing karyotyping and fluorescence in situ hybridization analysis on bone marrow biopsy samples. Comprehensive variant testing for full characterization of multiple myeloma cases can take days to weeks, is costly, and is not available to all patients. Past studies have explored to what extent cellular morphologic information from bone marrow aspirates or immunophenotypic information from flow cytometry can predict these genetic variants via the use of machine learning algorithms. However, the integration of multiple hematopathology data modalities using machine learning towards improving the diagnosis and characterization of hematologic neoplasms has yet to be explored. To this end, we developed a deep learning-based algorithm which, for individual patients, integrates tens-of-thousands of cell images from Wright-stained bone marrow aspirate smears with hundreds-of-thousands of events from myeloma flow cytometry panels to predict the presence or absence of particular molecular genetic variants among 85 cases of multiple myeloma. Attention-based multi-instance learning models were developed utilizing convolutional neural networks to analyze cell image data and multi-layer perceptrons to analyze flow cytometry data. Models trained solely on cell image data showed variable performance in predicting genetic subtypes of multiple myeloma cases: t(11;14), AUROC = 0.795; 1q+, AUROC = 0.743; del(17p), AUROC = 0.520. Similar models trained solely on flow cytometry data showed fair performance for all subtypes: t(11;14), AUROC = 0.761; 1q+, AUROC = 0.761; del(17p), AUROC = 0.787. However, models which combine features among high-attention events from both cell image and flow cytometry data yield significantly improved performance: t(11;14), AUROC = 0.892; 1q+, AUROC = 0.789; del(17p), AUROC = 0.876. Similarly, models trained to predict established prognostic classifications of multiple myeloma cases performed best when cell image and flow cytometry data is integrated: cell images alone, AUROC = 0.721; flow cytometry alone, AUROC = 0.827; both data combined, AUROC = 0.839. Additional improvements in prognostic classification were obtained when utilizing a Kronecker product to more completely utilize pairwise interactions between cell image and flow cytometry features: AUROC = 0.864. This study is, to our knowledge, the first to utilize deep learning to integrate multiple hematopathology data modalities towards automated diagnosis or subclassification of hematologic neoplasms in individual patients. The results of this study demonstrate the feasibility of accurately predicting molecular genetic subtypes of multiple myeloma cases solely from cell morphology and flow cytometric information. With further refinement, these promising models could be applied in low resource settings as well as research settings to better understand the biological relationship between plasma cell genetics with morphology and immunophenotype.

Building, benchmarking, and exploring perturbative maps of transcriptional and morphological data.

The continued scaling of genetic perturbation technologies combined with high-dimensional assays such as cellular microscopy and RNA-sequencing has enabled genome-scale reverse-genetics experiments that go beyond single-endpoint measurements of growth or lethality. Datasets emerging from these experiments can be combined to construct perturbative "maps of biology", in which readouts from various manipulations (e.g., CRISPR-Cas9 knockout, CRISPRi knockdown, compound treatment) are placed in unified, relatable embedding spaces allowing for the generation of genome-scale sets of pairwise comparisons. These maps of biology capture known biological relationships and uncover new associations which can be used for downstream discovery tasks. Construction of these maps involves many technical choices in both experimental and computational protocols, motivating the design of benchmark procedures to evaluate map quality in a systematic, unbiased manner. Here, we (1) establish a standardized terminology for the steps involved in perturbative map building, (2) introduce key classes of benchmarks to assess the quality of such maps, (3) construct 18 maps from four genome-scale datasets employing different cell types, perturbation technologies, and data readout modalities, (4) generate benchmark metrics for the constructed maps and investigate the reasons for performance variations, and (5) demonstrate utility of these maps to discover new biology by suggesting roles for two largely uncharacterized genes.

Non-partner Sexual Violence Among International College Students in the United States

The prevalence of non-partner sexual violence among college students is a pressing concern that demands urgent attention. Although an integral part of the education system, international college students are often underrepresented in various studies. This calls attention to understanding the cultural nuances and multiple factors affecting this population. The current research delves into the experiences of sexual abuse among international students within the last 12 months, focusing specifically on incidents where sexual penetration or unwanted sexual touching occurred without consent. The study sheds light on the frequency and demographics associated with these distressing incidents using data from a large-scale survey conducted over the past year, encompassing a sample size of 13,242 international student respondents. Results reveal alarming statistics, with a substantial proportion of international students reporting experiences of non-partner sexual violence. Specifically, 4.8% of participants reported being sexually touched without consent, 1.9% reported attempted sexual penetration without consent, and 1.6% reported actual sexual penetration or being made to penetrate someone without consent. Moreover, the analysis indicates significant associations between experiences of sexual abuse and key demographic variables such as gender, relationship status, and number of sexual partners. Further exploration through univariate regression unveils compelling insights into the intersectionality of sexual violence, highlighting disparities based on biological sex, relationship status, and number of sexual partners among international students. The present study underscores the urgent need for comprehensive prevention and intervention strategies to address the pervasive issue of non-partner sexual violence among international college students. By understanding the dynamics of these incidents and their correlates, institutions can tailor support services, advocacy efforts, and educational initiatives to create safer and more inclusive environments for all international students.

Fossilized soft tissues in tentaculitids from the Upper Devonian of Armenia: Towards solving the mystery of their phylogenetic affinities

The tentaculitids represent a significant and diverse group of mysterious fossils found in Palaeozoic strata. Their biology and evolutionary relationships remain poorly understood due to limited information about their soft body anatomy. The discovery of fossilized soft tissues in tentaculitids from the Upper Devonian of Armenia helps to resolve the old mystery of tentaculitid phylogenetic affinities. The thick bundles of phosphatic bars in the tentaculitid interior closely resemble the musculature of several tubicolous invertebrates, such as phoronids and bryozoans. Based on this similarity, we interpret these structures as fossilized muscles of the tentaculitid animal. The attachment of tentaculitid body muscles in a honeycomb pattern to the body wall is unlike that of any mollusc. Based on this muscle arrangement, molluscan affinities of tentaculitoids can be refuted. The muscle arrangement in tentaculitids is more akin to that of bryozoans than to phoronids. Presumably, tentaculitids and bryozoans shared a common ancestor. This ancestor was probably a solitary animal, with coloniality emerging later in the bryozoan branch of the phylogenetic tree. Alternatively, tentaculitoids might have evolved from a bryozoan-like ancestor by losing their coloniality.

Secreted protein TNA: a promising biomarker for understanding the adipose-bone axis and its impact on bone metabolism

BackgroundOsteoporosis (OP) is a systemic bone disease characterized by reduced bone mass and deterioration of bone microstructure, leading to increased bone fragility. Platelets can take up and release cytokines, and a high platelet count has been associated with low bone density. Obesity is strongly associated with OP, and adipose tissue can influence platelet function by secreting adipokines. However, the biological relationship between these factors remains unclear.MethodsWe conducted differential analysis to identify OP platelet-related plasma proteins. And, making comprehensive analysis, including functional enrichment, protein-protein interaction network analysis, and Friends analysis. The key protein, Tetranectin (TNA/CLEC3B), was identified through screening. Then, we analyzed TNA’s potential roles in osteogenic and adipogenic differentiation using multiple RNA-seq data sets and validated its effect on osteoclast differentiation and bone resorption function through in vitro experiments.ResultsSix OP-platelet-related proteins were identified via differential analysis. Then, we screened the key protein TNA, which was found to be highly expressed in adipose tissue. RNA-seq data suggested that TNA may promote early osteoblast differentiation. In vitro experiments showed that knockdown of TNA expression significantly increased the expression of osteoclast markers, thereby promoting osteoclast differentiation and bone resorption.ConclusionsWe identified TNA as a secreted protein that inhibits osteoclast differentiation and bone resorption. While, it potentially promoted early osteoblast differentiation from bioinformatic results. TNA may play a role in bone metabolism through the adipose-bone axis.

Female sex bias in Iberian megalithic societies through bioarchaeology, aDNA and proteomics

Uncertainties regarding traditional osteological methods in biological sex estimation can often be overcome with genomic and proteomic analyses. The combination of the three methodologies has been used for a better understanding of the gender-related funerary rituals at the Iberian megalithic cemetery of Panoría. As a result, 44 individuals have been sexed including, for the first time, non-adults. Contrary to the male bias found in many Iberian and European megalithic monuments, the Panoría population shows a clear sex ratio imbalance in favour of females, with twice as many females as males. Furthermore, this imbalance is found regardless of the criterion considered: sex ratio by tomb, chronological period, method of sex estimation, or age group. Biological relatedness was considered as possible sociocultural explanations for this female-related bias. However, the current results obtained for Panoría are indicative of a female-centred social structure potentially influencing rites and cultural traditions.

Genetic support of causal association between lipid and glucose metabolism and stress urinary incontinence in women: a bidirectional Mendelian randomization and multivariable-adjusted study.

Stress urinary incontinence (SUI) is a common condition characterized by urethral sphincter failure and urine leakage. Its prevalence in women is higher than in men, and estimates of crude prevalence rates vary widely due to factors such as research methodologies, study populations, and underreporting by patients. This variability hinders research and impacts patient diagnosis, treatment, and quality of life. The complex etiology of SUI is not fully understood, and previous studies have primarily focused on non-invasive indicators. While emerging observational research suggests a correlation between SUI in women and abnormalities in lipid and blood metabolism, the underlying biological mechanisms and causal relationships require further investigation. This study aims to explore the causalities between SUI in women and lipid and blood metabolism. Using bidirectional univariate Mendelian randomization (MR), we investigated the causal association between SUI liability in women (case/control = 5,924/399,509) from UK Biobank and lipid and glucose metabolism, indicated by total cholesterol (TC, N = 61,166), low-density lipoproteins (LDL, N = 58,381), high-density lipoproteins (HDL, N = 60,812), triglycerides (TG, N = 60,027), fasting glucose (FG, N = 19,745), and fasting insulin (FI, N = 38,238) from ENGAGE consortium. To account for potential confounding effects, multivariable MR (MVMR) analyses were performed, adjusting for body mass index (BMI) and separately among lipid and glucose metabolism. We found that increased genetically proxied TC, LDL, and HDL levels were associated with an elevated risk of SUI in women (OR: 1.090-1.117, all P < 0.05), These associations were further supported by MVMR analyses with adjustment for BMI (OR: 1.087-1.114, all P < 0.05). Conversely, increased FG and FI were associated with reduced SUI reliability in women (OR: 0.731-0.815, all P < 0.05). When adjusting among lipid and glucose metabolism, only HDL and FI demonstrated causal effects. Reverse MR analyses provided no genetic evidence supporting the causal effect of SUI in women on lipid and blood metabolism (all P > 0.05). Our results reported that increased TC, LDL, and HDL are linked to higher SUI susceptibility in women, while higher FG and FI levels have a protective effect. In overweight/obese women with metabolic abnormalities, the positive associations between TC, LDL, and HDL levels and SUI indicate a higher risk.

Analysis of non-metric dental traits for ethnicity identification in a mixed population of Uttar Pradesh

BackgroundForensic odontology involves the identification of individuals through dental records, making it a crucial tool in legal investigations. Non-metric dental traits (NMDT), which are variations in dental morphology play a key role as these traits are inherited characteristics that can help establish biological relationships or ancestry. Thus, we aim to assess the frequency and variability of NMDT in the human dentition of four ethnically mixed populations in Uttar Pradesh. This study can aid in the future by maintaining records of ethnic groups and their variability, which can be crucial for disaster victim management and forensic odontology. MethodsThe study was conducted on a total of 100 patients coming to the OPD of Oral Medicine and Oral Pathology and Microbiology of King George's Medical University from January 2022 to July 2023. Impressions of both arches were made for participants using irreversible hydrocolloid (alginate), and casts were examined under a stereomicroscope to assess 15 different morphological characteristics. ResultsNMDTs such as winging, shoveling, double-shoveling interruption groove, canine mesial ridge, hypocone, metacone, carabelli's trait, peg-shaped incisors, peg-shaped molar, premolar lingual cusp variation, deflecting wrinkle, protostylid, metaconulid, entoconulid was evaluated. The NMDTS were evaluated in four different ethnics Nordics, Mediterranean, Oriental Mediterranean, and Protoaustraloid amongst which various traits showed a statistically significant variation among the population of Uttar Pradesh. ConclusionThe sample studied presented confirmed supernumerary traits like metacone, protostylid, carabellis trait, metaconulid, premolar lingual cusp variation, and deflecting wrinkle were seen highest in Nordic, Mediterranean, Oriental Mediterranean, and Protoaustraloid ethnicity have a significant association with the Uttar Pradesh population.

Automated computer vision based individual salmon (Salmo salar) breathing rate estimation (SaBRE) for improved state observability

Salmon farming plays an important role in the Norwegian food industry, supplying a large portion of the world's salmon. Despite its economic importance, salmon farming faces unique biological challenges impacting the health and welfare of the fish. These factors limit the growth of salmon and the full economic potential of salmon farms, highlighting the need for advanced techniques in aquaculture to enhance productivity and sustainability. A key technical challenge is the unavailability of effective monitoring tools, leading to greater difficulties assessing the condition of salmon in water compared to the assessment of the animal stock on land-based farms. To improve the observability of salmon farms, we designed and created a computer-vision based approach for salmon breathing rate estimation (SaBRE), which allows the automatic monitoring of the respiration frequency of each individual salmon in a group of fish, seamlessly covering the entire workflow from video-stream input to the final data output (end-to-end). We thoroughly evaluated the capabilities of our method in two ways. Firstly, we performed a quantitative analysis of the constituent modules of SaBRE, revealing that all modules were highly accurate, including a salmon re-identification module that achieved an accuracy of 99.51 %. Secondly, we analyzed data from a salmon experiment with SaBRE, demonstrating that our algorithm provides high-quality respiration frequency information that can be compared with other types of experimental data to infer biological relationships. For the fish in our experiment, we observed that the ranking of the respiration frequencies in individual salmon remains relatively unchanged both in the short term and over longer periods (i.e., a salmon with a high breathing rate consistently remains among those with the highest rates, regardless of changes in the environment). Furthermore, a significant negative correlation (Pearson correlation coefficients with r values between −0.61 and −0.90 and p values below 0.01) was observed between our algorithm's estimated respiration frequency and the dissolved oxygen (dO2) content in the water. In addition, the average breathing rate of the salmon was observed to increase in response to incidents potentially causing stress.

It’s all relative: A multi-generational study using ForenSeq™ Kintelligence

The successful application of Forensic Investigative Genetic Genealogy (FIGG) to the identification of unidentified human remains and perpetrators of serious crime has led to a growing interest in its use internationally, including Australia. Routinely, FIGG has relied on the generation of high-density single nucleotide polymorphism (SNP) profiles from forensic samples using whole genome array (WGA) (∼650,000 or more SNPs) or whole genome sequencing (WGS) (millions of SNPs) for DNA segment-based comparisons in commercially available genealogy databases. To date, this approach has required DNA of a quality and quantity that is often not compatible with forensic samples. Furthermore, it requires the management of large data sets that include SNPs of medical relevance. The ForenSeq™ Kintelligence kit, comprising of 10,230 SNPs including 9867 for kinship association, was designed to overcome these challenges using a targeted amplicon sequencing-based method developed for low DNA inputs, inhibited and/or degraded forensic samples. To assess the ability of the ForenSeq™ Kintelligence workflow to correctly predict biological relationships, a comparative study comprising of 12 individuals from a family (with varying degrees of relatedness from 1st to 6th degree relatives) was undertaken using ForenSeq™ Kintelligence and a WGA approach using the Illumina Global Screening Array-24 version 3.0 Beadchip. All expected 1st, 2nd, 3rd, 4th and 5th degree relationships were correctly predicted using ForenSeq™ Kintelligence, while the expected 6th degree relationships were not detected. Given the (often) limited availability of forensic samples, findings from this study will assist Australian Law enforcement and other agencies considering the use of FIGG, to determine if the ForenSeq™ Kintelligence is suitable for existing workflows and casework sample types considered for FIGG.

Premature aging effects on COVID-19 pathogenesis: new insights from mouse models

Aging is identified as a significant risk factor for severe coronavirus disease-2019 (COVID-19), often resulting in profound lung damage and mortality. Yet, the biological relationship between aging, aging-related comorbidities, and COVID-19 remains incompletely understood. This study aimed to elucidate the age-related COVID19 pathogenesis using an Hutchinson-Gilford progeria syndrome (HGPS) mouse model, a premature aging disease model, with humanized ACE2 receptors. Pathological features were compared between young, aged, and HGPS hACE2 mice following SARS-CoV-2 challenge. We demonstrated that young mice display robust interferon response and antiviral activity, whereas this response is attenuated in aged mice. Viral infection in aged mice results in severe respiratory tract hemorrhage, likely contributing a higher mortality rate. In contrast, HGPS hACE2 mice exhibit milder disease manifestations characterized by minor immune cell infiltration and dysregulation of multiple metabolic processes. Comprehensive transcriptome analysis revealed both shared and unique gene expression dynamics among different mouse groups. Collectively, our studies evaluated the impact of SARS-CoV-2 infection on progeroid syndromes using a HGPS hACE2 mouse model, which holds promise as a useful tool for investigating COVID-19 pathogenesis in individuals with premature aging.

READv2: advanced and user-friendly detection of biological relatedness in archaeogenomics

The advent of genome-wide ancient DNA analysis has revolutionized our understanding of prehistoric societies. However, studying biological relatedness in these groups requires tailored approaches due to the challenges of analyzing ancient DNA. READv2, an optimized Python3 implementation of the most widely used tool for this purpose, addresses these challenges while surpassing its predecessor in speed and accuracy. For sufficient amounts of data, it can classify up to third-degree relatedness and differentiate between the two types of first-degree relatedness, full siblings and parent-offspring. READv2 enables user-friendly, efficient, and nuanced analysis of biological relatedness, facilitating a deeper understanding of past social structures.