Hasil untuk "Biology (General)"

Supratim Pradhan, Dhruba Dhar, Debolina Manna et al.

Elizabeth Fahsbender, Alma Andersson, Jeremy Ash et al.

Artificial intelligence holds immense promise for transforming biology, yet a lack of standardized, cross domain, benchmarks undermines our ability to build robust, trustworthy models. Here, we present insights from a recent workshop that convened machine learning and computational biology experts across imaging, transcriptomics, proteomics, and genomics to tackle this gap. We identify major technical and systemic bottlenecks such as data heterogeneity and noise, reproducibility challenges, biases, and the fragmented ecosystem of publicly available resources and propose a set of recommendations for building benchmarking frameworks that can efficiently compare ML models of biological systems across tasks and data modalities. By promoting high quality data curation, standardized tooling, comprehensive evaluation metrics, and open, collaborative platforms, we aim to accelerate the development of robust benchmarks for AI driven Virtual Cells. These benchmarks are crucial for ensuring rigor, reproducibility, and biological relevance, and will ultimately advance the field toward integrated models that drive new discoveries, therapeutic insights, and a deeper understanding of cellular systems.

Samuel Koovely

We introduce a queueing-based sampling framework for continuous-time temporal networks. We focus on a Markovian parametrization in which link start times follow a homogeneous Poisson process and link durations are exponentially distributed. We derive stochastic properties of the resulting link streams and exploit them to generate synthetic temporal networks with controllable smoothness and prescribed event patterns, relevant for the validation and interpretation of methods for community, scale, change-point, and periodicity detection. By coupling this temporal mechanism with block-structured endpoint distributions, we obtain a continuous-time analogue of stochastic block models. We also discuss extensions of the framework, including discrete-time and instantaneous-contact limits.

Fernando Parisio

In this work, we investigate how quantum coherence can scatter among the several off-diagonal elements of an arbitrary quantum state, defining coherence dispersion ($Δ_{\rm c}$). It turns out that this easily computable quantity is maximized for intermediate values of an appropriate entropy, a prevalent signature of complexity quantifiers across different fields, from linguistics and information science to evolutionary biology. By focusing on out-of-equilibrium systems, we use the developed framework to address a simplified model of cellular energetics, involving remanent coherence. Within the context of this model, the precise energy of 30.5 kJ/mol (the yield of ATP-ADP conversion) causes the temperature range where $Δ_{\rm c}$ is maximized to be compatible with temperatures for which unicellular life is reported to exist. Low levels of coherence suffice to support this conclusion.

Mohamed Amine Ouchdiri, Hamza Faquir, Saad Benjelloun et al.

Reaction-diffusion systems offer a powerful framework for understanding self-organized patterns in biological systems, yet controlling these patterns remains a significant challenge. As a consequence, we present a rigorous framework of optimal control for a class of coupled reaction-diffusion systems. The couplings are justified by the shared regulatory mechanisms encountered in synthetic biology. Furthermore, we introduce inputs and polynomial input-gain functions to guarantee well-posedness of the control system while maintaining biological relevance. As a result, we formulate an optimal control problem and derive necessary optimality conditions. We demonstrate our framework on an instance of such equations modeling the Nodal-Lefty interactions in mammalian cells. Numerical simulations showcase the effectiveness in directing pattern towards diverse targeted ones.

Yanyan Yang, Qianqian Li, Xinrui Yang et al.

Background At present, there are no available genetic data on the AGCU EX22 Kit from the Wuhu Han population.Aim This study investigates the applicability of the AGCU EX22 kit, designed for the Chinese population for forensic analysis and population genetics of the Wuhu Han population.Subjects and methods Bloodstains from 1565 unrelated healthy individuals in Wuhu city, Anhui Province, were collected for analysis. The AGCU EX22 kit was used for amplification, and capillary electrophoresis was used to separate the amplification products. Allele frequencies and forensic parameters were determined. The Wuhu Han population was compared to 10 reference populations through genetic distance, a phylogenetic neighbor-joining tree and principal component analysis.Results In total, 281 alleles and 1187 genotypes were observed. No significant deviations from Hardy-Weinberg equilibrium at any locus were found after Bonferroni’s correction. The 21 autosomal short tandem repeat (STR) genetic markers exhibited high informativeness and polymorphism. The cumulative power of discrimination and power of exclusion were 0.999999999999999999999999913380 and 0.999999996752339, respectively. Population comparisons revealed a genetic affinity between Wuhu Han and southern Han populations, except for the Guangdong Han population, which aligned with the traditional geographical division in China.Conclusion The AGCU EX22 Kit, containing 21 STR loci, is suitable for forensic application and population genetics studies in the Wuhu Han population.

Zan Zhang, Beiju Huang, Zanyun Zhang et al.

In contrast to cumbersome benchtop spectrometers, integrated on-chip spectrometers are well-suited for portable applications in health monitoring and environmental sensing. In this paper, we have developed an on-chip spectrometer with a programmable silicon photonic filter by simply using parallel cascaded micro-ring resonators (MRs). By altering the transmission spectrum of the filter, multiple and diverse sampling of the input spectrum is achieved. Then, combined with an artificial neural network (ANN) model, the incident spectrum is reconstructed from the sampled signals. Each MR is coupled to adjacent ones, and the phase shifts within each MR can be independently tuned. Through dynamic programming of the phases of these MRs, sampling functions featuring diverse characteristics are obtained based on a single programmable filter with an adjustable number of sampling channels. This eliminates the need for a filter array, significantly reducing the area of the on-chip reconstructive spectrometer. The simulation results demonstrate that the proposed design can achieve the reconstruction of continuous and sparse spectra within the wavelength range of 1450 nm to 1650 nm, with a tunable resolution ranging from 2 nm to 0.2 nm, depending on the number of sampling states employed. This benefit arises from the programmable nature of the device. The device holds tremendous potential for applications in wearable optical sensing, portable spectrometry, and other related scenarios.

Thomas A Sasani, Aaron R Quinlan, Kelley Harris

Maintaining germline genome integrity is essential and enormously complex. Although many proteins are involved in DNA replication, proofreading, and repair, mutator alleles have largely eluded detection in mammals. DNA replication and repair proteins often recognize sequence motifs or excise lesions at specific nucleotides. Thus, we might expect that the spectrum of de novo mutations – the frequencies of C>T, A>G, etc. – will differ between genomes that harbor either a mutator or wild-type allele. Previously, we used quantitative trait locus mapping to discover candidate mutator alleles in the DNA repair gene Mutyh that increased the C>A germline mutation rate in a family of inbred mice known as the BXDs (Sasani et al., 2022, Ashbrook et al., 2021). In this study we developed a new method to detect alleles associated with mutation spectrum variation and applied it to mutation data from the BXDs. We discovered an additional C>A mutator locus on chromosome 6 that overlaps Ogg1, a DNA glycosylase involved in the same base-excision repair network as Mutyh (David et al., 2007). Its effect depends on the presence of a mutator allele near Mutyh, and BXDs with mutator alleles at both loci have greater numbers of C>A mutations than those with mutator alleles at either locus alone. Our new methods for analyzing mutation spectra reveal evidence of epistasis between germline mutator alleles and may be applicable to mutation data from humans and other model organisms.

Nil Patil, Rupal Dhariwal, Arifullah Mohammed et al.

Alzheimer's disease (AD) is increasingly becoming a major public health concern in our society. While many studies have explored the use of natural polyketides, alkaloids, and other chemical components in AD treatment, there is an urgent need to clarify the concept of multi-target treatment for AD. This study focuses on using network pharmacology approach to elucidate how secondary metabolites from Dictyostelium discoideum affect AD through multi-target or indirect mechanisms. The secondary metabolites produced by D. discoideum during their development were obtained from literature sources and PubChem. Disease targets were selected using GeneCards, DisGeNET, and CTD databases, while compound-based targets were identified through Swiss target prediction and Venn diagrams were used to find intersections between these targets. A network depicting the interplay among disease, drugs, active ingredients, and key target proteins (PPI network) was formed utilizing the STRING (Protein-Protein Interaction Networks Functional Enrichment Analysis) database. To anticipate the function and mechanism of the screened compounds, GO and KEGG enrichment analyses were conducted and visually presented using graphs and bubble charts. After the screening phase, the top interacting targets in the PPI network and the compound with the most active target were chosen for subsequent molecular docking and molecular dynamic simulation studies. This study identified nearly 50 potential targeting genes for each of the screened compounds and revealed multiple signaling pathways. Among these pathways, the inflammatory pathway stood out. COX-2, a receptor associated with neuroinflammation, showed differential expression in various stages of AD, particularly in pyramidal neurons during the early stages of the disease. This increase in COX-2 expression is likely induce by higher levels of IL-1, which is associated with neuritic plaques and microglial cells in AD. Molecular docking investigations demonstrated a strong binding interaction between the terpene compound PQA-11 and the neuroinflammatory receptor COX2, with a substantial binding affinity of −8.4 kcal/mol. Subsequently, a thorough analysis of the docked complex (COX2-PQA11) through Molecular Dynamics Simulation showed lower RMSD, minimal RMSF fluctuations, and a reduced total energy of −291.35 kJ/mol compared to the standard drug. These findings suggest that the therapeutic effect of PQA-11 operates through the inflammatory pathway, laying the groundwork for further in-depth research into the role of secondary metabolites in AD treatment.

Roberta Coletti, Mónica Leiria de Mendonça, Susana Vinga et al.

Tumor heterogeneity is a challenge to designing effective and targeted therapies. Glioma-type identification depends on specific molecular and histological features, which are defined by the official World Health Organization (WHO) classification of the central nervous system (CNS). These guidelines are constantly updated to support the diagnosis process, which affects all the successive clinical decisions. In this context, the search for new potential diagnostic and prognostic targets, characteristic of each glioma type, is crucial to support the development of novel therapies. Based on The Cancer Genome Atlas (TCGA) glioma RNA-sequencing data set updated according to the 2016 and 2021 WHO guidelines, we proposed a 2-step variable selection approach for biomarker discovery. Our framework encompasses the graphical lasso algorithm to estimate sparse networks of genes carrying diagnostic information. These networks are then used as input for regularized Cox survival regression model, allowing the identification of a smaller subset of genes with prognostic value. In each step, the results derived from the 2016 and 2021 classes were discussed and compared. For both WHO glioma classifications, our analysis identifies potential biomarkers, characteristic of each glioma type. Yet, better results were obtained for the WHO CNS classification in 2021, thereby supporting recent efforts to include molecular data on glioma classification.

Suparmi Suparmi, Harka Prasetya, Harka Prasetya et al.

IntroductionNight blindness is the first sign of vitamin A deficiency (VAD), which can lead to blindness if left untreated. University students may be at risk of VAD-related night blindness due to unhealthy eating attitudes and inadequate vitamin A intake. This study aimed to determine the relationship between knowledge and attitudes toward vitamin A consumption affecting night blindness in university students.MethodsThis cross-sectional study involved 409 third-year university students of Universitas Islam Sultan Agung, Semarang, Indonesia. Participants completed questionnaires about socio-demographics, their knowledge of vitamin A, and attitudes toward vitamin A consumption. Night blindness symptoms among university students were assessed using the Low Luminance Questionnaire (LLQ), followed by a bivariate analysis of the Chi-Square test. Multivariate binary logistic regressions were used to determine whether the independent variables were associated with night blindness. A p-value less than 0.05 indicated significance.ResultsThe prevalence of high-symptom night blindness was higher among males (26.4%) than females (5.7%). Out of 409 university students, 48 from the non-medicine cluster of the study program had a night blindness symptom. The prevalence was lower in students who studied in the medicine cluster program. The level of knowledge on vitamin A had a significant relationship with symptoms of night blindness [prevalence ratio (PR) = 2.239 (95% CI = 1.110–4.516)]. The attitudes toward vitamin A consumption were significantly associated with night blindness (PR = 2.560, 95% CI = 1.215–5.392).DiscussionThe results of this study show that the risk of night blindness in university students can be prevented by increasing their knowledge and attitudes toward consuming vitamin A-rich food. The university can provide health promotion and vitamin A supplementation to avoid night blindness among academia.

Ellinor O Alseth, Rafael Custodio, Sarah A Sundius et al.

Where there are bacteria, there will be bacteriophages. These viruses are known to be important players in shaping the wider microbial community in which they are embedded, with potential implications for human health. On the other hand, bacteria possess a range of distinct immune mechanisms that provide protection against bacteriophages, including the mutation or complete loss of the phage receptor, and CRISPR-Cas adaptive immunity. While our previous work showed how a microbial community may impact phage resistance evolution, little is known about the inverse, namely how interactions between phages and these different phage resistance mechanisms affect the wider microbial community in which they are embedded. Here, we conducted a 10-day, fully factorial evolution experiment to examine how phage impact the structure and dynamics of an artificial four-species bacterial community that includes either Pseudomonas aeruginosa wild-type or an isogenic mutant unable to evolve phage resistance through CRISPR-Cas. Additionally, we used mathematical modelling to explore the ecological interactions underlying full community behaviour, as well as to identify general principles governing the impacts of phage on community dynamics. Our results show that the microbial community structure is drastically altered by the addition of phage, with Acinetobacter baumannii becoming the dominant species and P. aeruginosa being driven nearly extinct, whereas P. aeruginosa outcompetes the other species in the absence of phage. Moreover, we find that a P. aeruginosa strain with the ability to evolve CRISPR-based resistance generally does better when in the presence of A. baumannii, but that this benefit is largely lost over time as phage is driven extinct. Finally, we show that pairwise data alone is insufficient when modelling our microbial community, both with and without phage, highlighting the importance of higher order interactions in governing multispecies dynamics in complex communities. Combined, our data clearly illustrate how phage targeting a dominant species allows for the competitive release of the strongest competitor while also contributing to community diversity maintenance and potentially preventing the reinvasion of the target species, and underline the importance of mapping community composition before therapeutically applying phage.

Tesfu Fekensa Tujuba, Roman V. Yakovlev, Aidas Saldaitis et al.

African golden-spotted lappet moths from the genera Haplopacha Aurivillius, 1905 and Dasychirinula Hering, 1926 are reviewed. Antennae, heads and legs are investigated in addition to the traditional comparison of habitus, genitalia, and distribution areas. Two new genera are established and four new species are described as a result: Eudoumbia gen. n. with the type-species Eudoumbia thorogood sp. n. from Angola, Namibia, and Botswana; Auripluvia gen. n. with the type species Auripluvia sophia sp. n. from Ethiopia; Haplopacha mason sp. n. from Tanzania; and Dasychirinula julia sp. n. from Ethiopia. One species is reattributed to the new genus as Eudoumbia ndoumoi (Dupont, Simonsen & Zilli, 2016) stat. n. One new synonymy is established for two Tanzanian species: Dasychirinula chrysogramma Hering, 1926 = Haplopacha lunata Dupont, Simonsen & Zilli, 2016 syn. n.; and one potential synonymy is remarked between Haplopacha tangani Dupont, Simonsen & Zilli, 2016 from Tanzania and Malawi and Haplopacha riftensis Dupont, Simonsen & Zilli, 2016 from Malawi. Photos of the related material stored in the main collections of Ditsong National Museum of Natural History (Pretoria, RSA) and Natural History Museum of Zimbabwe (Bulawayo, Zimbabwe) are showed.

Sarwan Ali, Prakash Chourasia, Bipin Koirala et al.

Molecular sequence analysis is crucial for comprehending several biological processes, including protein-protein interactions, functional annotation, and disease classification. The large number of sequences and the inherently complicated nature of protein structures make it challenging to analyze such data. Finding patterns and enhancing subsequent research requires the use of dimensionality reduction and feature selection approaches. Recently, a method called Correlated Clustering and Projection (CCP) has been proposed as an effective method for biological sequencing data. The CCP technique is still costly to compute even though it is effective for sequence visualization. Furthermore, its utility for classifying molecular sequences is still uncertain. To solve these two problems, we present a Nearest Neighbor Correlated Clustering and Projection (CCP-NN)-based technique for efficiently preprocessing molecular sequence data. To group related molecular sequences and produce representative supersequences, CCP makes use of sequence-to-sequence correlations. As opposed to conventional methods, CCP doesn't rely on matrix diagonalization, therefore it can be applied to a range of machine-learning problems. We estimate the density map and compute the correlation using a nearest-neighbor search technique. We performed molecular sequence classification using CCP and CCP-NN representations to assess the efficacy of our proposed approach. Our findings show that CCP-NN considerably improves classification task accuracy as well as significantly outperforms CCP in terms of computational runtime.

Sergei M. Danilov, Mark S. Jain, Pavel A. Petukhov et al.

<b>Background</b>: The angiotensin-converting enzyme (ACE) metabolizes a number of important peptides participating in blood pressure regulation and vascular remodeling. Elevated blood ACE is a marker for granulomatous diseases and elevated ACE expression in tissues is associated with increased risk of cardiovascular diseases. <b>Objective and Methodology:</b> We applied a novel approach —ACE phenotyping—to find a reason for conformationally impaired ACE in the blood of one particular donor. Similar conformationally altered ACEs were detected previously in 2–4% of the healthy population and in up to 20% of patients with uremia, and were characterized by significant increase in the rate of angiotensin I hydrolysis. <b>Principal findings:</b> This donor has (1) significantly increased level of endogenous ACE inhibitor in plasma with MW less than 1000; (2) increased activity toward angiotensin I; (3) M71V mutation in <i>ABCG2</i> (membrane transporter for more than 200 compounds, including bilirubin). We hypothesize that this patient may also have the decreased level of free bilirubin in plasma, which normally binds to the N domain of ACE. Analysis of the local conformation of ACE in plasma of patients with Gilbert and Crigler-Najjar syndromes allowed us to speculate that binding of mAbs 1G12 and 6A12 to plasma ACE could be a natural sensor for estimation of free bilirubin level in plasma. Totally, 235 human plasma/sera samples were screened for conformational changes in soluble ACE. <b>Conclusions/Significance:</b> ACE phenotyping of plasma samples allows us to identify individuals with conformationally altered ACE. This type of screening has clinical significance because this conformationally altered ACE could not only result in the enhancement of the level of angiotensin II but could also serve as an indicator of free bilirubin levels.

Amy J. C. Trappey, Ching-Hung Lee, John P. T. Mo

Three levels, namely the device level, the connection level, and the systems management level, are frequently used to conceptualize intelligent machinery and Industry 4 [...]

Jonathan Hammond, Katherine Checkland, Igor Francetic et al.

Introduction Primary care networks (PCNs) are claimed to be an effective model to organise and deliver primary healthcare through collaborative relationships and effective coordination of primary care activities. Though increasingly implemented in different contexts, there is limited evidence on the effectiveness of PCNs in low-income and lower middle-income countries (LLMICs).Objective Our scoping review aims to understand how PCNs in LLMICs have been conceptualised, implemented and analysed in the literature and further explores the evidence of the effectiveness of these networks.Methods We structured our review using Arksey and O’Malley’s framework for scoping reviews and recommendations by Levac et al. We also used the population, concept and context (PCC) guide of the Joanna Briggs Institute (JBI) methodology for scoping reviews to define the search strategy. The identified documents were then mapped, using Cunningham’s evaluation framework for health networks, to understand how PCNs are conceived in LLMIC settings.Results We identified 20 documents describing PCNs in five LLMICs. The selected documents showed differing forms and complexities of networks, with a majority resourced by government, non-governmental and donor entities. Most networks were mandated, and established with defined goals, although these were not always understood by stakeholders. Unlike PCNs in developed settings, the scoping review did not identify integration of care as a major goal for the establishment of PCNs in LLMICs. Network evaluation relationships, outputs and outcomes also varied across the five networks in the identified documents, and perceptions of effectiveness differed across stakeholder groups.Conclusion PCNs in LLMICs benefit from clearly stated goals and measurable outcomes, which facilitates evaluation. In order to maximise the benefits, careful attention to the aspects of network design and operation is required. Future research work could shed light on some of the missing pieces of evidence on their effectiveness by, for example, considering differential consequences of modes of network establishment and operation, including unintended consequences in the systems within which they reside, and evaluating long-term implications.

Md Nurul Anwar, Lauren Smith, Angela Devine et al.

Plasmodium vivax is one of the most geographically widespread malaria parasites in the world due to its ability to remain dormant in the human liver as hypnozoites and subsequently reactivate after the initial infection (i.e. relapse infections). More than 80% of P. vivax infections are due to hypnozoite reactivation. Mathematical modelling approaches have been widely applied to understand P. vivax dynamics and predict the impact of intervention outcomes. In this article, we provide a scoping review of mathematical models that capture P. vivax transmission dynamics published between January 1988 and May 2023 to provide a comprehensive summary of the mathematical models and techniques used to model P. vivax dynamics. We aim to assist researchers working on P. vivax transmission and other aspects of P. vivax malaria by highlighting best practices in currently published models and highlighting where future model development is required. We provide an overview of the different strategies used to incorporate the parasite's biology, use of multiple scales (within-host and population-level), superinfection, immunity, and treatment interventions. In most of the published literature, the rationale for different modelling approaches was driven by the research question at hand. Some models focus on the parasites' complicated biology, while others incorporate simplified assumptions to avoid model complexity. Overall, the existing literature on mathematical models for P. vivax encompasses various aspects of the parasite's dynamics. We recommend that future research should focus on refining how key aspects of P. vivax dynamics are modelled, including spatial heterogeneity in exposure risk, the accumulation of hypnozoite variation, the interaction between P. falciparum and P. vivax, acquisition of immunity, and recovery under superinfection.

B. Hallgrímsson, Rebecca M. Green, David C. Katz et al.

Canalization, or robustness to genetic or environmental perturbations, is fundamental to complex organisms. While there is strong evidence for canalization as an evolved property that varies among genotypes, the developmental and genetic mechanisms that produce this phenomenon are very poorly understood. For evolutionary biology, understanding how canalization arises is important because, by modulating the phenotypic variation that arises in response to genetic differences, canalization is a determinant of evolvability. For genetics of disease in humans and for economically important traits in agriculture, this subject is important because canalization is a potentially significant cause of missing heritability that confounds genomic prediction of phenotypes. We review the major lines of thought on the developmental-genetic basis for canalization. These fall into two groups. One proposes specific evolved molecular mechanisms while the other deals with robustness or canalization as a more general feature of development. These explanations for canalization are not mutually exclusive and they overlap in several ways. General explanations for canalization are more likely to involve emergent features of development than specific molecular mechanisms. Disentangling these explanations is also complicated by differences in perspectives between genetics and developmental biology. Understanding canalization at a mechanistic level will require conceptual and methodological approaches that integrate quantitative genetics and developmental biology.

G. Samuel, D. Kennett

Genetic genealogy databases have become particularly attractive to law enforcement agencies, especially in the United States (US), which have started to employ genealogists to search them with unknown origin DNA from unidentified human remains (suicides, missing persons) or from a serious crime scene, to help identify the victim, or a potential suspected perpetrator, respectively. While this investigative genetic genealogy (IGG) technique holds much promise, its use – particularly during serious criminal investigations – has sparked a range of social and ethical concerns. Receiving consent for IGG from genetic genealogy database users has been argued as a way to address such concerns. While critiques of the importance of consent are well documented in the biomedical and forensic biobanking literature, this has not been explored for IGG. We sought to address this gap by exploring the views of UK stakeholders. Our research question was: what are UK public and professional stakeholders’ views about the importance of the consent process for IGG when used for serious criminal cases? The methodological approach was interview-based and exploratory. Our analysis identified that all interviewees stressed the importance of consent, though interviewees’ narratives pointed to inadequacies of individual-based consent as an ethical panacea for IGG.