Sci Rep. 2023 Aug 7;13(1):12787. doi: 10.1038/s41598-023-39418-6.

ABSTRACT

We present an artificial neural network architecture, termed STENCIL-NET, for equation-free forecasting of spatiotemporal dynamics from data. STENCIL-NET works by learning a discrete propagator that is able to reproduce the spatiotemporal dynamics of the training data. This data-driven propagator can then be used to forecast or extrapolate dynamics without needing to know a governing equation. STENCIL-NET does not learn a governing equation, nor an approximation to the data themselves. It instead learns a discrete propagator that reproduces the data. It therefore generalizes well to different dynamics and different grid resolutions. By analogy with classic numerical methods, we show that the discrete forecasting operators learned by STENCIL-NET are numerically stable and accurate for data represented on regular Cartesian grids. A once-trained STENCIL-NET model can be used for equation-free forecasting on larger spatial domains and for longer times than it was trained for, as an autonomous predictor of chaotic dynamics, as a coarse-graining method, and as a data-adaptive de-noising method, as we illustrate in numerical experiments. In all tests, STENCIL-NET generalizes better and is computationally more efficient, both in training and inference, than neural network architectures based on local (CNN) or global (FNO) nonlinear convolutions.

PMID:37550328 | DOI:10.1038/s41598-023-39418-6

SLAS Discov. 2023 Aug 5:S2472-5552(23)00053-9. doi: 10.1016/j.slasd.2023.08.001. Online ahead of print.

ABSTRACT

Three series of compounds were prioritized from a high content screening campaign that identified molecules that blocked dihydrotestosterone (DHT) induced formation of Androgen Receptor (AR) protein-protein interactions (PPIs) with the Transcriptional Intermediary Factor 2 (TIF2) coactivator and also disrupted preformed AR-TIF2 PPI complexes; the hydrobenzo-oxazepins (S1), thiadiazol-5-piperidine-carboxamides (S2), and phenyl-methyl-indoles (S3). Compounds from these series inhibited AR PPIs with TIF2 and SRC-1, another p160 coactivator, in mammalian 2-hybrid assays and blocked transcriptional activation in reporter assays driven by full length AR or AR-V7 splice variants. Compounds inhibited the growth of five prostate cancer cell lines, with many exhibiting differential cytotoxicity towards AR positive cell lines. Representative compounds from the 3 series substantially reduced both endogenous and DHT-enhanced expression and secretion of the prostate specific antigen (PSA) cancer biomarker in the C4-2 castration resistant prostate cancer (CRPC) cell line. The comparatively weak activities of series compounds in the H3-DHT and/or TIF2 box 3 LXXLL-peptide binding assays to the recombinant ligand binding domain of AR suggest that direct antagonism at the orthosteric ligand binding site or AF-2 surface respectively are unlikely mechanisms of action. Cellular enhanced thermal stability assays (CETSA) indicated that compounds engaged AR and reduced the maximum efficacy and right shifted the EC50 of DHT-enhanced AR thermal stabilization consistent with the effects of negative allosteric modulators. Molecular docking of potent representative hits from each series to AR structures suggest that S1-1 and S2-6 engage a novel binding pocket (BP-1) adjacent to the orthosteric ligand binding site, while S3-11 occupies the AR binding function 3 (BF-3) allosteric pocket. Hit binding poses indicate spaces and residues adjacent to the BP-1 and BF-3 pockets that will be exploited in future medicinal chemistry optimization studies. Small molecule allosteric modulators that prevent/disrupt AR PPIs with coactivators like TIF2 to alter transcriptional activation in the presence of orthosteric agonists might evade the resistance mechanisms to existing prostate cancer drugs and provide novel starting points for medicinal chemistry lead optimization and future development into therapies for metastatic CRPC.

PMID:37549772 | DOI:10.1016/j.slasd.2023.08.001

Biochim Biophys Acta Mol Cell Res. 2023 Aug 5:119558. doi: 10.1016/j.bbamcr.2023.119558. Online ahead of print.

ABSTRACT

Cytoglobin (Cygb) is an evolutionary ancient heme protein with yet unclear physiological function(s). Mammalian Cygb is ubiquitously expressed in all tissues and is proposed to be involved in reactive oxygen species (ROS) detoxification, nitric oxide (NO) metabolism and lipid-based signaling processes. Loss-of-function studies in mouse associate Cygb with apoptosis, inflammation, fibrosis, cardiovascular dysfunction or oncogenesis. In zebrafish (Danio rerio), two cygb genes exist, cytoglobin 1 (cygb1) and cytoglobin 2 (cygb2). Both have different coordination states and distinct expression sites within zebrafish tissues. The biological roles of the cygb paralogs are largely uncharacterized. We used a CRISPR/Cas9 genome editing approach and generated a knockout of the penta-coordinated cygb1 for in vivo analysis. Adult male cygb1 knockouts develop phenotypic abnormalities, including weight loss. To identify the molecular mechanisms underlying the occurrence of these phenotypes and differentiate between function and effect of the knockout we compared the transcriptomes of cygb1 knockout at different ages to age-matched wild-type zebrafish. We found that immune regulatory and cell cycle regulatory transcripts (e.g. tp53) were up-regulated in the cygb1 knockout liver. Additionally, the expression of transcripts involved in lipid metabolism and transport, the antioxidative defense and iron homeostasis was affected in the cygb1 knockout. Cygb1 may function as an anti-inflammatory and cytoprotective factor in zebrafish liver, and may be involved in lipid-, iron-, and ROS-dependent signaling.

PMID:37549740 | DOI:10.1016/j.bbamcr.2023.119558

PLoS Pathog. 2023 Aug 7;19(8):e1011533. doi: 10.1371/journal.ppat.1011533. eCollection 2023 Aug.

ABSTRACT

The Bunyavirales order is a large and diverse group of segmented negative-strand RNA viruses. Several virus families within this order contain important human pathogens, including Sin Nombre virus (SNV) of the Hantaviridae. Despite the high epidemic potential of bunyaviruses, specific medical countermeasures such as vaccines or antivirals are missing. The multifunctional ~250 kDa L protein of hantaviruses, amongst other functional domains, harbors the RNA-dependent RNA polymerase (RdRp) and an endonuclease and catalyzes transcription as well as replication of the viral RNA genome, making it a promising therapeutic target. The development of inhibitors targeting these key processes requires a profound understanding of the catalytic mechanisms. Here, we established expression and purification protocols of the full-length SNV L protein bearing the endonuclease mutation K124A. We applied different biochemical in vitro assays to provide an extensive characterization of the different enzymatic functions as well as the capacity of the hantavirus L protein to interact with the viral RNA. By using single-particle cryo-EM, we obtained a 3D model including the L protein core region containing the RdRp, in complex with the 5' promoter RNA. This first high-resolution model of a New World hantavirus L protein shows striking similarity to related bunyavirus L proteins. The interaction of the L protein with the 5' RNA observed in the structural model confirms our hypothesis of protein-RNA binding based on our biochemical data. Taken together, this study provides an excellent basis for future structural and functional studies on the hantavirus L protein and for the development of antiviral compounds.

PMID:37549153 | DOI:10.1371/journal.ppat.1011533

STAR Protoc. 2023 Aug 6;4(3):102438. doi: 10.1016/j.xpro.2023.102438. Online ahead of print.

ABSTRACT

Boolean networks are commonly used in systems biology to dynamically model gene regulatory interactions. Here, we present a protocol for implementing Boolean network dynamics as quantum circuits. We describe steps for accessing cloud-based quantum processing units offered by IBM and IonQ and downloading and parsing logic for gene regulatory networks. We then detail procedures for performing simulations of quantum circuits on local devices and visualizing measurement results. For complete details on the use and execution of this protocol, please refer to Weidner et al.1.

PMID:37549034 | DOI:10.1016/j.xpro.2023.102438

Glob Chang Biol. 2023 Aug 7. doi: 10.1111/gcb.16901. Online ahead of print.

ABSTRACT

Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution of alien species. Since citizen science presence-only data suffer from some fundamental issues, efforts have been made to combine these data with those provided by scientifically structured surveys. Surprisingly, only a few studies proposing data integration evaluated the contribution of this process to the effective sampling of species' environmental niches and, consequently, its effect on model predictions on new time intervals. We relied on niche overlap analyses, machine learning classification algorithms and ecological niche models to compare the ability of data from citizen science and scientific surveys, along with their integration, in capturing the realized niche of 13 invasive alien species in Italy. Moreover, we assessed differences in current and future invasion risk predicted by each data set under multiple global change scenarios. We showed that data from citizen science and scientific surveys captured similar species niches though highlighting exclusive portions associated with clearly identifiable environmental conditions. In terrestrial species, citizen science data granted the highest gain in environmental space to the pooled niches, determining an increased future biological invasion risk. A few aquatic species modelled at the regional scale reported a net loss in the pooled niches compared to their scientific survey niches, suggesting that citizen science data may also lead to contraction in pooled niches. For these species, models predicted a lower future biological invasion risk. These findings indicate that citizen science data may represent a valuable contribution to predicting future spread of invasive alien species, especially within national-scale programmes. At the same time, citizen science data collected on species poorly known to citizen scientists, or in strictly local contexts, may strongly affect the niche quantification of these taxa and the prediction of their future biological invasion risk.

PMID:37548610 | DOI:10.1111/gcb.16901

New Phytol. 2023 Aug 7. doi: 10.1111/nph.19145. Online ahead of print.

ABSTRACT

Biofilm-forming benthic diatoms are key primary producers in coastal habitats, where they frequently dominate sunlit intertidal substrata. The development of gliding motility in raphid diatoms was a key molecular adaptation that contributed to their evolutionary success. However, the structure-function correlation between diatom adhesives utilized for gliding and their relationship to the extracellular matrix that constitutes the diatom biofilm is unknown. Here, we have used proteomics, immunolocalization, comparative genomics, phylogenetics and structural homology analysis to investigate the evolutionary history and function of diatom adhesive proteins. Our study identified eight proteins from the adhesive trails of Craspedostauros australis, of which four form a new protein family called Trailins that contain an enigmatic Choice-of-Anchor A (CAA) domain, which was acquired through horizontal gene transfer from bacteria. Notably, the CAA-domain shares a striking structural similarity with one of the most widespread domains found in ice-binding proteins (IPR021884). Our work offers new insights into the molecular basis for diatom biofilm formation, shedding light on the function and evolution of diatom adhesive proteins. This discovery suggests that there is a transition in the composition of biomolecules required for initial surface colonization and those utilized for 3D biofilm matrix formation.

PMID:37548082 | DOI:10.1111/nph.19145

Front Genet. 2023 Jul 21;14:1250548. doi: 10.3389/fgene.2023.1250548. eCollection 2023.

NO ABSTRACT

PMID:37547469 | PMC:PMC10401834 | DOI:10.3389/fgene.2023.1250548

Front Genet. 2023 Jul 21;14:1195480. doi: 10.3389/fgene.2023.1195480. eCollection 2023.

ABSTRACT

Background: There is growing interest in the genetic improvement of fertility traits in female goats. With high-throughput genotyping, single-cell RNA sequencing (scRNA-seq) is a powerful tool for measuring gene expression profiles. The primary objective was to investigate comparative transcriptome profiling of granulosa cells (GCs) of high- and low-fertility goats, using scRNA-seq. Methods: Thirty samples from Ji'ning Gray goats (n = 15 for high fertility and n = 15 for low fertility) were retrieved from publicly available scRNA-seq data. Functional enrichment analysis and a literature mining approach were applied to explore modules and hub genes related to fertility. Then, interactions between types of RNAs identified were predicted, and the ceRNA regulatory network was constructed by integrating these interactions with other gene regulatory networks (GRNs). Results and discussion: Comparative transcriptomics-related analyses identified 150 differentially expressed genes (DEGs) between high- and low-fertility groups, based on the fold change (≥5 and ≤-5) and false discovery rate (FDR <0.05). Among these genes, 80 were upregulated and 70 were downregulated. In addition, 81 mRNAs, 58 circRNAs, 8 lincRNAs, 19 lncRNAs, and 55 miRNAs were identified by literature mining. Furthermore, we identified 18 hub genes (SMAD1, SMAD2, SMAD3, SMAD4, TIMP1, ERBB2, BMP15, TGFB1, MAPK3, CTNNB1, BMPR2, AMHR2, TGFBR2, BMP4, ESR1, BMPR1B, AR, and TGFB2) involved in goat fertility. Identified biological networks and modules were mainly associated with ovary signature pathways. In addition, KEGG enrichment analysis identified regulating pluripotency of stem cells, cytokine-cytokine receptor interactions, ovarian steroidogenesis, oocyte meiosis, progesterone-mediated oocyte maturation, parathyroid and growth hormone synthesis, cortisol synthesis and secretion, and signaling pathways for prolactin, TGF-beta, Hippo, MAPK, PI3K-Akt, and FoxO. Functional annotation of identified DEGs implicated important biological pathways. These findings provided insights into the genetic basis of fertility in female goats and are an impetus to elucidate molecular ceRNA regulatory networks and functions of DEGs underlying ovarian follicular development.

PMID:37547465 | PMC:PMC10400778 | DOI:10.3389/fgene.2023.1195480

Int J Crit Illn Inj Sci. 2023 Apr-Jun;13(2):66-72. doi: 10.4103/ijciis.ijciis_10_23. Epub 2023 Jun 26.

ABSTRACT

BACKGROUND: Absent or delusional memories are experienced by many patients following an intensive care unit (ICU) stay. Up to 70% may have delusional or hallucinatory intrusive memories, which may persist long term. This study aims to investigate how spiritual health (SH) impacts ICU patients' memories and quality of communication (QoC) between patients and physicians (PP) or nurses (PN).

METHODS: This cross-sectional study was conducted across the country on ICU patients discharged from 45 medical centers in 31 provinces of Iran, to evaluate the direct and indirect effects of SH and ICU characteristics on patients' memory. Two valid and standard ICU memory tools (ICU-MT) and SH questionnaires were administered to patients 1 day post-ICU discharge used.

RESULTS: No significant direct effect of SH scores on ICU-MT items was observed. No significant correlation was observed between PP-QoC and PN-QoC variables and primary items of the ICU-MT. Female sex positively correlated with the development of delusional memories (odds ratio [OR]: 1.730, 95% confidence interval [CI]: 1.025-2.915, P < 0.05). Subjects admitted to the medical ICU were less likely to remember being in the ICU (OR: 0.398, 95% CI: 0.159-0.996, P < 0.05), and were less likely to report intrusive memories from their time in the hospital or events that led to their admission (OR: 0.19, 95% CI: 0.086-0.419, P < 0.001).

CONCLUSIONS: The results of this study indicate that the spiritual health indirectly increased coping with intrusive memories, however, no direct effect was observed on ICU-MT items. The quality of communication between patients and physicians and nurses significantly mediated development of intrusive memories.

PMID:37547189 | PMC:PMC10401560 | DOI:10.4103/ijciis.ijciis_10_23

JACC Basic Transl Sci. 2023 Apr 5;8(7):801-816. doi: 10.1016/j.jacbts.2022.12.014. eCollection 2023 Jul.

ABSTRACT

In the past 2 decades, research on atherosclerotic cardiovascular disease has uncovered inflammation to be a key driver of the pathophysiological process. A pressing need therefore exists to quantitatively and longitudinally probe inflammation, in preclinical models and in cardiovascular disease patients, ideally using non-invasive methods and at multiple levels. Here, we developed and employed in vivo multiparametric imaging approaches to investigate the immune response following myocardial infarction. The myocardial infarction models encompassed either transient or permanent left anterior descending coronary artery occlusion in C57BL/6 and Apoe-/-mice. We performed nanotracer-based fluorine magnetic resonance imaging and positron emission tomography (PET) imaging using a CD11b-specific nanobody and a C-C motif chemokine receptor 2-binding probe. We found that immune cell influx in the infarct was more pronounced in the permanent occlusion model. Further, using 18F-fluorothymidine and 18F-fluorodeoxyglucose PET, we detected increased hematopoietic activity after myocardial infarction, with no difference between the models. Finally, we observed persistent systemic inflammation and exacerbated atherosclerosis in Apoe-/- mice, regardless of which infarction model was used. Taken together, we showed the strengths and capabilities of multiparametric imaging in detecting inflammatory activity in cardiovascular disease, which augments the development of clinical readouts.

PMID:37547068 | PMC:PMC10401290 | DOI:10.1016/j.jacbts.2022.12.014

ACS Omega. 2023 Jul 21;8(30):27386-27397. doi: 10.1021/acsomega.3c02763. eCollection 2023 Aug 1.

ABSTRACT

Identifying noncoding RNAs (ncRNAs)-drug resistance association computationally would have a marked effect on understanding ncRNA molecular function and drug target mechanisms and alleviating the screening cost of corresponding biological wet experiments. Although graph neural network-based methods have been developed and facilitated the detection of ncRNAs related to drug resistance, it remains a challenge to explore a highly trusty ncRNA-drug resistance association prediction framework, due to inevitable noise edges originating from the batch effect and experimental errors. Herein, we proposed a framework, referred to as RDRGSE (RDR association prediction by using graph skeleton extraction and attentional feature fusion), for detecting ncRNA-drug resistance association. Specifically, starting with the construction of the original ncRNA-drug resistance association as a bipartite graph, RDRGSE took advantage of a bi-view skeleton extraction strategy to obtain two types of skeleton views, followed by a graph neural network-based estimator for iteratively optimizing skeleton views aimed at learning high-quality ncRNA-drug resistance edge embedding and optimal graph skeleton structure, jointly. Then, RDRGSE adopted adaptive attentional feature fusion to obtain final edge embedding and identified potential RDRAs under an end-to-end pattern. Comprehensive experiments were conducted, and experimental results indicated the significant advantage of a skeleton structure for ncRNA-drug resistance association discovery. Compared with state-of-the-art approaches, RDRGSE improved the prediction performance by 6.7% in terms of AUC and 6.1% in terms of AUPR. Also, ablation-like analysis and independent case studies corroborated RDRGSE generalization ability and robustness. Overall, RDRGSE provides a powerful computational method for ncRNA-drug resistance association prediction, which can also serve as a screening tool for drug resistance biomarkers.

PMID:37546619 | PMC:PMC10398708 | DOI:10.1021/acsomega.3c02763

F1000Res. 2023 Mar 21;12:308. doi: 10.12688/f1000research.131333.1. eCollection 2023.

ABSTRACT

Transmembrane protein 106B (TMEM106B), a protein that is localized to the lysosome, is genetically linked to many neurodegenerative diseases and forms fibrils in diseased brains. The reproducibility of TMEM106B research would be enhanced if the community had access to well-characterized anti-TMEM106B antibodies. In this study, we characterized six commercially available TMEM106B antibodies for their performance in Western blot, immunoprecipitation, and immunofluorescence, using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. We identified many high-performing antibodies and encourage readers to use this report as a guide to select the most appropriate antibody for their specific needs.

PMID:37545650 | PMC:PMC10403746 | DOI:10.12688/f1000research.131333.1

Am J Physiol Cell Physiol. 2023 Aug 7. doi: 10.1152/ajpcell.00588.2022. Online ahead of print.

ABSTRACT

The ovarian cancer tumor microenvironment (TME) consists of a constellation of abundant cellular components, extracellular matrix, and soluble factors. Soluble factors such as cytokines, chemokines, structural proteins, extracellular vesicles, and metabolites are critical means of non-contact cellular communication acting as messengers to convey pro- or anti-tumorigenic signals. Vast advancements have been made in our understanding of how cancer cells adapt their metabolism to meet environmental demands and utilize these adaptations to promote survival, metastasis, and therapeutic resistance. The stromal TME contribution to this metabolic rewiring has been relatively underexplored, particularly in ovarian cancer. Thus, metabolic activity alterations in the TME hold promise for further study and potential therapeutic exploitation. In this review, we focus on the cellular components of the TME with emphasis on: 1) metabolic signatures of ovarian cancer; 2) understanding the stromal cell network and their metabolic crosstalk with tumor cells; and 3) how stromal and tumor cell metabolites alter intratumoral immune cell metabolism and function. Together, these elements provide insight into the metabolic influence of the TME and emphasize the importance of understanding how metabolic performance drives cancer progression.

PMID:37545409 | DOI:10.1152/ajpcell.00588.2022

J Immunother Cancer. 2023 Aug;11(8):e007180. doi: 10.1136/jitc-2023-007180.

ABSTRACT

BACKGROUND: CD8+tumor infiltrating lymphocytes (TILs) are often observed in non-small cell lung cancers (NSCLC). However, the characteristics of CD8+ TILs, especially T-cell populations specific for tumor antigens, remain poorly understood.

METHODS: High throughput single-cell RNA sequencing and single-cell T-cell receptor (TCR) sequencing were performed on CD8+ TILs from three surgically-resected lung cancer specimens. Dimensional reduction for clustering was performed using Uniform Manifold Approximation and Projection. CD8+ TIL TCR specific for the cancer/testis antigen KK-LC-1 and for predicted neoantigens were investigated. Differentially-expressed gene analysis, Gene Set Enrichment Analysis (GSEA) and single sample GSEA was performed to characterize antigen-specific T cells.

RESULTS: A total of 6998 CD8+ T cells was analyzed, divided into 10 clusters according to their gene expression profile. An exhausted T-cell (exhausted T (Tex)) cluster characterized by the expression of ENTPD1 (CD39), TOX, PDCD1 (PD1), HAVCR2 (TIM3) and other genes, and by T-cell oligoclonality, was identified. The Tex TCR repertoire (Tex-TCRs) contained nine different TCR clonotypes recognizing five tumor antigens including a KK-LC-1 antigen and four neoantigens. By re-clustering the tumor antigen-specific T cells (n=140), it could be seen that the individual T-cell clonotypes were present on cells at different stages of differentiation and functional states even within the same Tex cluster. Stimulating these T cells with predicted cognate peptide indicated that TCR signal strength and subsequent T-cell proliferation and cytokine production was variable but always higher for neoantigens than KK-LC-1.

CONCLUSIONS: Our approach focusing on T cells with an exhausted phenotype among CD8+ TILs may facilitate the identification of tumor antigens and clarify the nature of the antigen-specific T cells to specify the promising immunotherapeutic targets in patients with NSCLC.

PMID:37544663 | DOI:10.1136/jitc-2023-007180

Brief Bioinform. 2023 Aug 7:bbad281. doi: 10.1093/bib/bbad281. Online ahead of print.

ABSTRACT

Gene regulatory networks (GRNs) reveal the complex molecular interactions that govern cell state. However, it is challenging for identifying causal relations among genes due to noisy data and molecular nonlinearity. Here, we propose a novel causal criterion, neighbor cross-mapping entropy (NME), for inferring GRNs from both steady data and time-series data. NME is designed to quantify 'continuous causality' or functional dependency from one variable to another based on their function continuity with varying neighbor sizes. NME shows superior performance on benchmark datasets, comparing with existing methods. By applying to scRNA-seq datasets, NME not only reliably inferred GRNs for cell types but also identified cell states. Based on the inferred GRNs and further their activity matrices, NME showed better performance in single-cell clustering and downstream analyses. In summary, based on continuous causality, NME provides a powerful tool in inferring causal regulations of GRNs between genes from scRNA-seq data, which is further exploited to identify novel cell types/states and predict cell type-specific network modules.

PMID:37544659 | DOI:10.1093/bib/bbad281

WIREs Mech Dis. 2023 Aug 6:e1625. doi: 10.1002/wsbm.1625. Online ahead of print.

ABSTRACT

Cystic fibrosis (CF) is widely known as a disease of the lung, even though it is in truth a systemic disease, whose symptoms typically manifest in gastrointestinal dysfunction first. CF ultimately impairs not only the pancreas and intestine but also the lungs, gonads, liver, kidneys, bones, and the cardiovascular system. It is caused by one of several mutations in the gene of the epithelial ion channel protein CFTR. Intense research and improved antimicrobial treatments during the past eight decades have steadily increased the predicted life expectancy of a person with CF (pwCF) from a few weeks to over 50 years. Moreover, several drugs ameliorating the sequelae of the disease have become available in recent years, and notable treatments of the root cause of the disease have recently generated substantial improvements in health for some but not all pwCF. Yet, numerous fundamental questions remain unanswered. Complicating CF, for instance in the lung, is the fact that the associated insufficient chloride secretion typically perturbs the electrochemical balance across epithelia and, in the airways, leads to the accumulation of thick, viscous mucus and mucus plaques that cannot be cleared effectively and provide a rich breeding ground for a spectrum of bacterial and fungal communities. The subsequent infections often become chronic and respond poorly to antibiotic treatments, with outcomes sometimes only weakly correlated with the drug susceptibility of the target pathogen. Furthermore, in contrast to rapidly resolved acute infections with a single target pathogen, chronic infections commonly involve multi-species bacterial communities, called "infection microbiomes," that develop their own ecological and evolutionary dynamics. It is presently impossible to devise mathematical models of CF in its entirety, but it is feasible to design models for many of the distinct drivers of the disease. Building upon these growing yet isolated modeling efforts, we discuss in the following the feasibility of a multi-scale modeling framework, known as template-and-anchor modeling, that allows the gradual integration of refined sub-models with different granularity. The article first reviews the most important biomedical aspects of CF and subsequently describes mathematical modeling approaches that already exist or have the potential to deepen our understanding of the multitude aspects of the disease and their interrelationships. The conceptual ideas behind the approaches proposed here do not only pertain to CF but are translatable to other systemic diseases. This article is categorized under: Congenital Diseases > Computational Models.

PMID:37544654 | DOI:10.1002/wsbm.1625

Clin Nutr. 2023 Jul 31;42(9):1749-1758. doi: 10.1016/j.clnu.2023.07.025. Online ahead of print.

ABSTRACT

BACKGROUND & AIMS: The bioelectrical impedance vector analysis (BIVA) represents a qualitative analysis of body composition. The vector, defined by resistance (R) and reactance (Xc) standardized by stature, can be evaluated compared to the 50%,75%, and 95% tolerance ellipses representative of the reference populations. The tolerance ellipses for healthy adults have been provided in 1995 and were developed by mixing underage, adult, and elderly subjects, possibly misrepresenting the actual adult population. The current multicentric, cross-sectional study aimed to provide new tolerance ellipses specific for the general adult population and as a secondary aim to present centile curves for the bioelectrical phase angle.

METHODS: R, Xc, and phase angle were measured in 2137 and 2230 males and females using phase-sensitive foot-to-hand analyzers at 50 kHz. A minimum of 35 subjects were included for each sex and age category from 18 to 65 years.

RESULTS: The new mean vectors showed a leftward shift on the R-Xc graph with respect to the former reference values (males: F = 75.3; p < 0.001; females: F = 36.6, p < 0.001). The results provided new 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentile curves for phase angle, identifying time point phases of decrement (males: -0.03° per year at 33.0-51.0 years and -0.05° per year after 51 years; females: -0.03° per year from 37.2 to 57.9 years).

CONCLUSIONS: Compared to the original references, the new data are characterized by a different distribution within the R-Xc graph with a higher phase angle. Thirty years after the BIVA invention, the current study presents new tolerance ellipses and phase angle reference values for the adult population.

PMID:37544246 | DOI:10.1016/j.clnu.2023.07.025

Adv Sci (Weinh). 2023 Aug 6:e2301609. doi: 10.1002/advs.202301609. Online ahead of print.

ABSTRACT

With rapid urbanization and global population growth, the amount of wasted aluminum foil is significantly increasing. Most deformed and contaminated foil is difficult to recycle; hence, it is landfilled or incinerated, causing environmental pollution. Therefore, using aluminum foil waste for electricity may be conducive to addressing environmental problems. In this regard, various literatures have explored the concept of energy generation using foil, while a crumple ball design for this purpose has not been studied. Thus, a recycled foil-based crumpled ball triboelectric nanogenerator (RFCB-TENG) is proposed. The crumpled ball design can minimize the effects of contamination on foil, ensuring efficient power output. Moreover, owing to novel crumpled design, the RFCB-TENG has some outstanding characteristics to become a sustainable power source, such as ultralight weight, low noise, and high durability. By introducing the air-breakdown model, the RFCB-TENG achieved an output peak voltage of 648 V, a current of 8.1 mA cm3 , and an optimum power of 162.7 mW cm3 . The structure of the RFCB-TENG is systemically optimized depending on the design parameters to realize the optimum output performance. Finally, the RFCB-TENG operated 500 LEDs and 30-W commercial lamps. This work paves the guideline for effectively fabricating the TENG using waste-materials while exhibiting outstanding characteristics.

PMID:37544923 | DOI:10.1002/advs.202301609

Semin Cell Dev Biol. 2023 Aug 4:S1084-9521(23)00151-9. doi: 10.1016/j.semcdb.2023.07.013. Online ahead of print.

ABSTRACT

The Calvin-Benson-Bassham (CBB) cycle is the ancestral CO2 assimilation pathway and is found in all photosynthetic organisms. Biochemical extensions to the CBB cycle have evolved that allow the resulting pathways to act as CO2 concentrating mechanisms, either spatially in the case of C4 photosynthesis or temporally in the case of Crassulacean acid metabolism (CAM). While the biochemical steps in the C4 and CAM pathways are known, questions remain on their integration and regulation with CBB cycle activity. The application of omic and transgenic technologies is providing a more complete understanding of the biochemistry of C4 and CAM species and will also provide insight into the CBB cycle in these plants. As the global population increases, new solutions are required to increase crop yields and meet demands for food and other bioproducts. Previous work in C3 species has shown that increasing carbon assimilation through genetic manipulation of the CBB cycle can increase biomass and yield. There may also be options to improve photosynthesis in species using C4 photosynthesis and CAM through manipulation of the CBB cycle in these plants. This is an underexplored strategy and requires more basic knowledge of CBB cycle operation in these species to enable approaches for increased productivity.

PMID:37544777 | DOI:10.1016/j.semcdb.2023.07.013