Genesis. 2024 Apr;62(2):e23591. doi: 10.1002/dvg.23591.

ABSTRACT

Reversible transitions between epithelial and mesenchymal cell states are a crucial form of epithelial plasticity for development and disease progression. Recent experimental data and mechanistic models showed multiple intermediate epithelial-mesenchymal transition (EMT) states as well as trajectories of EMT underpinned by complex gene regulatory networks. In this review, we summarize recent progress in quantifying EMT and characterizing EMT paths with computational methods and quantitative experiments including omics-level measurements. We provide perspectives on how these studies can help relating fundamental cell biology to physiological and pathological outcomes of EMT.

PMID:38553870 | DOI:10.1002/dvg.23591

Cardiovasc Diabetol. 2024 Mar 29;23(1):109. doi: 10.1186/s12933-024-02202-5.

ABSTRACT

BACKGROUND: In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state.

METHODS: An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D.

RESULTS: A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D.

CONCLUSIONS: Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.

PMID:38553758 | DOI:10.1186/s12933-024-02202-5

BMC Bioinformatics. 2024 Mar 29;25(1):138. doi: 10.1186/s12859-024-05761-2.

ABSTRACT

Even though high-throughput transcriptome sequencing is routinely performed in many laboratories, computational analysis of such data remains a cumbersome process often executed manually, hence error-prone and lacking reproducibility. For corresponding data processing, we introduce Curare, an easy-to-use yet versatile workflow builder for analyzing high-throughput RNA-Seq data focusing on differential gene expression experiments. Data analysis with Curare is customizable and subdivided into preprocessing, quality control, mapping, and downstream analysis stages, providing multiple options for each step while ensuring the reproducibility of the workflow. For a fast and straightforward exploration and visualization of differential gene expression results, we provide the gene expression visualizer software GenExVis. GenExVis can create various charts and tables from simple gene expression tables and DESeq2 results without the requirement to upload data or install software packages. In combination, Curare and GenExVis provide a comprehensive software environment that supports the entire data analysis process, from the initial handling of raw RNA-Seq data to the final DGE analyses and result visualizations, thereby significantly easing data processing and subsequent interpretation.

PMID:38553675 | DOI:10.1186/s12859-024-05761-2

Nat Commun. 2024 Mar 29;15(1):2765. doi: 10.1038/s41467-024-46773-z.

ABSTRACT

Single-cell technologies can measure the expression of thousands of molecular features in individual cells undergoing dynamic biological processes. While examining cells along a computationally-ordered pseudotime trajectory can reveal how changes in gene or protein expression impact cell fate, identifying such dynamic features is challenging due to the inherent noise in single-cell data. Here, we present DELVE, an unsupervised feature selection method for identifying a representative subset of molecular features which robustly recapitulate cellular trajectories. In contrast to previous work, DELVE uses a bottom-up approach to mitigate the effects of confounding sources of variation, and instead models cell states from dynamic gene or protein modules based on core regulatory complexes. Using simulations, single-cell RNA sequencing, and iterative immunofluorescence imaging data in the context of cell cycle and cellular differentiation, we demonstrate how DELVE selects features that better define cell-types and cell-type transitions. DELVE is available as an open-source python package: https://github.com/jranek/delve .

PMID:38553455 | DOI:10.1038/s41467-024-46773-z

Nat Commun. 2024 Mar 29;15(1):2756. doi: 10.1038/s41467-024-46446-x.

ABSTRACT

Protein fibril self-assembly is a universal transition implicated in neurodegenerative diseases. Although fibril structure/growth are well characterized, fibril nucleation is poorly understood. Here, we use a computational-experimental approach to resolve fibril nucleation. We show that monomer hairpin content quantified from molecular dynamics simulations is predictive of experimental fibril formation kinetics across a tau motif mutant library. Hairpin trimers are predicted to be fibril transition states; one hairpin spontaneously converts into the cross-beta conformation, templating subsequent fibril growth. We designed a disulfide-linked dimer mimicking the transition state that catalyzes fibril formation, measured by ThT fluorescence and TEM, of wild-type motif - which does not normally fibrillize. A dimer compatible with extended conformations but not the transition-state fails to nucleate fibril at any concentration. Tau repeat domain simulations show how long-range interactions sequester this motif in a mutation-dependent manner. This work implies that different fibril morphologies could arise from disease-dependent hairpin seeding from different loci.

PMID:38553453 | DOI:10.1038/s41467-024-46446-x

Life Sci. 2024 Mar 28:122590. doi: 10.1016/j.lfs.2024.122590. Online ahead of print.

NO ABSTRACT

PMID:38553273 | DOI:10.1016/j.lfs.2024.122590

J Mol Biol. 2024 Mar 27:168552. doi: 10.1016/j.jmb.2024.168552. Online ahead of print.

ABSTRACT

With advances in protein structure prediction thanks to deep learning models like AlphaFold, RNA structure prediction has recently received increased attention from deep learning researchers. RNAs introduce substantial challenges due to the sparser availability and lower structural diversity of the experimentally resolved RNA structures in comparison to protein structures. These challenges are often poorly addressed by the existing literature, many of which report inflated performance due to using training and testing sets with significant structural overlap. Further, the most recent Critical Assessment of Structure Prediction (CASP15) has shown that deep learning models for RNA structure are currently outperformed by traditional methods. In this paper we present RNA3DB, a dataset of structured RNAs, derived from the Protein Data Bank (PDB), that is designed for training and benchmarking deep learning models. The RNA3DB method arranges the RNA 3D chains into distinct groups (Components) that are non-redundant both with regard to sequence as well as structure, providing a robust way of dividing training, validation, and testing sets. Any split of these structurally-dissimilar Components are guaranteed to produce test and validations sets that are distinct by sequence and structure from those in the training set. We provide the RNA3DB dataset, a particular train/test split of the RNA3DB Components (in an approximate 70/30 ratio) that will be updated periodically. We also provide the RNA3DB methodology along with the source-code, with the goal of creating a reproducible and customizable tool for producing structurally-dissimilar dataset splits for structural RNAs.

PMID:38552946 | DOI:10.1016/j.jmb.2024.168552

J Glob Antimicrob Resist. 2024 Mar 27:S2213-7165(24)00062-6. doi: 10.1016/j.jgar.2024.03.012. Online ahead of print.

ABSTRACT

OBJECTIVES: A concern with the ESKAPE pathogen Enterobacter bugandensis and other species of the E. cloacae complex is the frequent appearance of multidrug resistance against last-resort antibiotics, such as polymyxins.

METHODS: Here, we investigated the responses to polymyxin B (PMB) in two PMB-resistant E. bugandensis clinical isolates by global transcriptomics and deletion mutagenesis.

RESULTS: In both isolates, the genes of the CrrAB-regulated operon, including crrC and kexD, displayed the highest levels of upregulation in response to PMB. ∆crrC and ∆kexD mutants became highly susceptible to PMB and lost the heteroresistant phenotype. Conversely, heterologous expression of CrrC and KexD proteins increased PMB resistance in a sensitive Enterobacter ludwigii clinical isolate and in the Escherichia coli K12 strain W3110. The efflux pump AcrABTolC, and the two component regulators PhoPQ and CrrAB, also contributed to PMB resistance and heteroresistance. Additionally, the lipid A modification with 4-L-aminoarabinose (L-Ara4N), mediated by the arnBCADTEF operon, was critical to determine PMB resistance. Biochemical experiments, supported by mass spectrometry and structural modeling, indicated that CrrC is an inner membrane protein that interacts with the membrane domain of the KexD pump. Similar interactions were modeled for AcrB and AcrD efflux pumps.

CONCLUSION: Our results support a model whereby drug efflux potentiated by CrrC interaction with membrane domains of major efflux pumps combined with resistance to PMB entry by the L-Ara4N lipid A modification, under the control of PhoPQ and CrrAB, confers the bacterium high-level resistance and heteroresistance to PMB.

PMID:38552872 | DOI:10.1016/j.jgar.2024.03.012

Int J Biol Macromol. 2024 Mar 27:131180. doi: 10.1016/j.ijbiomac.2024.131180. Online ahead of print.

ABSTRACT

Phosphorylation modifications play important regulatory roles in most biological processes. However, the functional assignment for the vast majority of the identified phosphosites remains a major challenge. Here, we provide a deep learning framework named FuncPhos-STR as an online resource, for functional prediction and structural visualization of human proteome-level phosphosites. Based on our reported FuncPhos-SEQ framework, which was built by integrating phosphosite sequence evolution and protein-protein interaction (PPI) information, FuncPhos-STR was developed by further integrating the structural and dynamics information on AlphaFold protein structures. The characterized structural topology and dynamics features underlying functional phosphosites emphasized their molecular mechanism for regulating protein functions. By integrating the structural and dynamics, sequence evolutionary, and PPI network features from protein different dimensions, FuncPhos-STR has advantage over other reported models, with the best AUC value of 0.855. Using FuncPhos-STR, the phosphosites inside the pocket regions are accessible to higher functional scores, theoretically supporting their potential regulatory mechanism. Overall, FuncPhos-STR would accelerate the functional identification of huge unexplored phosphosites, and facilitate the elucidation of their allosteric regulation mechanisms. The web server of FuncPhos-STR is freely available at http://funcptm.jysw.suda.edu.cn/str.

PMID:38552697 | DOI:10.1016/j.ijbiomac.2024.131180

Phytomedicine. 2024 Mar 16;128:155524. doi: 10.1016/j.phymed.2024.155524. Online ahead of print.

ABSTRACT

BACKGROUND: Psoriasis is an immune-mediated chronic inflammatory skin disease. Current research suggests that the long-term persistence and recurrence of psoriasis are closely related to the feedback loop formed between keratinocytes and immune cells, especially in Th 17 or DC cells expressing CCR6. CCL20 is the ligand of CCR6. Therefore, drugs that block the expression of CCL20 or CCR6 may have a certain therapeutic effect on psoriasis. Glycyrrhetinic acid (GA) is the main active ingredient of the plant drug licorice and is often used to treat autoimmune diseases, including psoriasis. However, its mechanism of action is still unclear.

METHODS: Psoriasis like skin lesion model was established by continuously applying imiquimod on the back skin of normal mice and CCR6-/- mice for 7 days. The therapeutic and preventive effects of glycyrrhetinic acid (GA) on the model were observed and compared. The severity of skin injury is estimated through clinical PASI scores and histopathological examination. qRT-PCR and multiple cytoline assay were explored to detect the expression levels of cytokines in animal dorsal skin lesions and keratinocyte line HaCaT cells, respectively. The dermis and epidermis of the mouse back were separated for the detection of CCL20 expression. Transcription factor assay was applied to screen, and luciferase activity assay to validate transcription factors regulated by GA. Technology of surface plasmon laser resonance with LC-MS (SPR-MS), molecular docking, and enzyme activity assay were used to identified the target proteins for GA. Finally, we synthesized different derivatives of 18beta-GA and compared their effects, as well as glycyrrhetinic acid (GL), on the skin lesion of imiquimod-induced mice to evaluate the active groups of 18beta-GA.

RESULTS: 18β-glycyrrhetinic acid (GA) improved IMQ-induced psoriatic lesions, and could specifically reduce the chemokine CCL20 level of the epidermis in lesion area, especially in therapeutic administration manner. The process was mainly regulated by transcription factor ATF2 in the keratinocytes. In addition, GUSB was identified as the primary target of 18βGA. Our findings indicated that the subject on molecular target research of glycyrrhizin should be glycyrrhetinic acid (GA) instead of glycyrrhizic acid (GL), because GL showed little activity in vitro or in vivo. Apart from that, α, β, -unsaturated carbonyl in C11/12 positions was crucial or unchangeable to its activity of 18βGA, while proper modification of C3 or C30 position of 18βGA may vastly increase its activity.

CONCLUSION: Our research indicates that 18βGA exerted its anti-psoriasis effect mainly by suppressing ATF2 and downstream molecule CCL20 predominately through α, β, -unsaturated carbonyl at C11/12 position binding to GUSB in the keratinocytes, and then broke the feedback loop between keratinocytes and CCR6-expressing immune cells. GA has more advantages than GL in the external treatment of psoriasis. A highlight of this study is to investigate the influence of special active groups on the pharmacological action of a natural product, inspired by the molecular docking result.

PMID:38552435 | DOI:10.1016/j.phymed.2024.155524

Cortex. 2024 Mar 11;174:164-188. doi: 10.1016/j.cortex.2024.03.002. Online ahead of print.

ABSTRACT

Lesion mapping studies allow us to evaluate the potential causal contribution of specific brain areas to human cognition and complement other cognitive neuroscience methods, as several authors have recently pointed out. Here, we present an updated summary of the findings from the Vietnam Head Injury Study (VHIS) focusing on the studies conducted over the last decade, that examined the social mind and its intricate neural and cognitive underpinnings. The VHIS is a prospective, long-term follow-up study of Vietnam veterans with penetrating traumatic brain injury (pTBI) and healthy controls (HC). The scope of the work is to present the studies from the latest phases (3 and 4) of the VHIS, 70 studies since 2011, when the Raymont et al. paper was published (Raymont et al., 2011). These studies have contributed to our understanding of human social cognition, including political and religious beliefs, theory of mind, but also executive functions, intelligence, and personality. This work finally discusses the usefulness of lesion mapping as an approach to understanding the functions of the human brain from basic science and clinical perspectives.

PMID:38552358 | DOI:10.1016/j.cortex.2024.03.002

ISME J. 2024 Mar 29:wrae055. doi: 10.1093/ismejo/wrae055. Online ahead of print.

ABSTRACT

Viruses impact microbial systems through killing hosts, horizontal gene transfer, and altering cellular metabolism, consequently impacting nutrient cycles. A virus-infected cell, a "virocell", is distinct from its uninfected sister cell as the virus commandeers cellular machinery to produce viruses rather than replicate cells. Problematically, virocell responses to the nutrient-limited conditions that abound in nature are poorly understood. Here we used a systems biology approach to investigate virocell metabolic reprogramming under nutrient limitation. Using transcriptomics, proteomics, lipidomics, and endo- and exo-metabolomics, we assessed how low phosphate (low-P) conditions impacted virocells of a marine Pseudoalteromonas host when independently infected by two unrelated phages (HP1 and HS2). With the combined stresses of infection and nutrient limitation, a set of nested responses were observed. First, low-P imposed common cellular responses on all cells (virocells and uninfected cells), including activating the canonical P-stress response, and decreasing transcription, translation, and extracellular organic matter consumption. Second, low-P imposed infection-specific responses (for both virocells), including enhancing nitrogen assimilation and fatty acid degradation, and decreasing extracellular lipid relative abundance. Third, low-P suggested virocell-specific strategies. Specifically, HS2-virocells regulated gene expression by increasing transcription and ribosomal protein production, whereas HP1-virocells accumulated host proteins, decreased extracellular peptide relative abundance, and invested in broader energy and resource acquisition. These results suggest that although environmental conditions shape metabolism in common ways regardless of infection, virocell-specific strategies exist to support viral replication during nutrient limitation, and a framework now exists for identifying metabolic strategies of nutrient-limited virocells in nature.

PMID:38552150 | DOI:10.1093/ismejo/wrae055

Cell Rep. 2024 Mar 27;43(4):114005. doi: 10.1016/j.celrep.2024.114005. Online ahead of print.

ABSTRACT

The retina is exquisitely patterned, with neuronal somata positioned at regular intervals to completely sample the visual field. Here, we show that phosphatase and tensin homolog (Pten) controls starburst amacrine cell spacing by modulating vesicular trafficking of cell adhesion molecules and Wnt proteins. Single-cell transcriptomics and double-mutant analyses revealed that Pten and Down syndrome cell adhesion moleculeDscam) are co-expressed and function additively to pattern starburst amacrine cell mosaics. Mechanistically, Pten loss accelerates the endocytic trafficking of DSCAM, FAT3, and MEGF10 off the cell membrane and into endocytic vesicles in amacrine cells. Accordingly, the vesicular proteome, a molecular signature of the cell of origin, is enriched in exocytosis, vesicle-mediated transport, and receptor internalization proteins in Pten conditional knockout (PtencKO) retinas. Wnt signaling molecules are also enriched in PtencKO retinal vesicles, and the genetic or pharmacological disruption of Wnt signaling phenocopies amacrine cell patterning defects. Pten thus controls vesicular trafficking of cell adhesion and signaling molecules to establish retinal amacrine cell mosaics.

PMID:38551961 | DOI:10.1016/j.celrep.2024.114005

Biomech Model Mechanobiol. 2024 Mar 29. doi: 10.1007/s10237-024-01831-9. Online ahead of print.

ABSTRACT

Correction to: Biomechanics and Modeling in Mechanobiology (2022) 21:89-118 https://doi.org/10.1007/s10237-021-01539-0.

PMID:38551760 | DOI:10.1007/s10237-024-01831-9

GM Crops Food. 2024 Dec 31;15(1):130-149. doi: 10.1080/21645698.2024.2334476. Epub 2024 Mar 29.

ABSTRACT

Global crop yield has been affected by a number of abiotic stresses. Heat, salinity, and drought stress are at the top of the list as serious environmental growth-limiting factors. To enhance crop productivity, molecular approaches have been used to determine the key regulators affecting stress-related phenomena. MYB transcription factors (TF) have been reported as one of the promising defensive proteins against the unfavorable conditions that plants must face. Different roles of MYB TFs have been suggested such as regulation of cellular growth and differentiation, hormonal signaling, mediating abiotic stress responses, etc. To gain significant insights, a comprehensive in-silico analysis of OsMYB TF was carried out in comparison with 21 dicot MYB TFs and 10 monocot MYB TFs. Their chromosomal location, gene structure, protein domain, and motifs were analyzed. The phylogenetic relationship was also studied, which resulted in the classification of proteins into four basic groups: groups A, B, C, and D. The protein motif analysis identified several conserved sequences responsible for cellular activities. The gene structure analysis suggested that proteins that were present in the same class, showed similar intron-exon structures. Promoter analysis revealed major cis-acting elements that were found to be responsible for hormonal signaling and initiating a response to abiotic stress and light-induced mechanisms. The transformation of OsMYB TF into tobacco was carried out using the Agrobacterium-mediated transformation method, to further analyze the expression level of a gene in different plant parts, under stress conditions. To summarize, the current studies shed light on the evolution and role of OsMYB TF in plants. Future investigations should focus on elucidating the functional roles of MYB transcription factors in abiotic stress tolerance through targeted genetic modification and CRISPR/Cas9-mediated genome editing. The application of omics approaches and systems biology will be indispensable in delineating the regulatory networks orchestrated by MYB TFs, facilitating the development of crop genotypes with enhanced resilience to environmental stressors. Rigorous field validation of these genetically engineered or edited crops is imperative to ascertain their utility in promoting sustainable agricultural practices.

PMID:38551174 | DOI:10.1080/21645698.2024.2334476

iScience. 2024 Mar 11;27(4):109486. doi: 10.1016/j.isci.2024.109486. eCollection 2024 Apr 19.

ABSTRACT

Nuclear factor kappa B (NF-κB) is a key regulator in immune signaling and is known to exhibit a digital activation pattern. Yet the molecular basis underlying the heterogeneity in NF-κB activation at single-cell level is not entirely understood. Here, we show that NF-κB activation in single cells is largely regulated by intrinsic differences at the receptor level. Using the genome editing and time-lapse imaging, we directly characterize endogenous TNFR1 dynamics and NF-κB activation from the same single cells. Total internal reflection fluorescence (TIRF) microscopy shows that endogenous TNFR1 forms pre-ligand clusters in the resting cells. Upon tumor necrosis factor (TNF) stimulation, the diffusion coefficient of membrane TNFR1 was significantly decreased and a substantial level of TNFR1 undergoes oligomerization to form trimers and hexamers. Moreover, multi-color cell imaging reveals that both digital and graded information processing regulate NF-κB activation across different TNFR1 expression levels. Our results indicate that single-cell NF-κB activation potential strongly correlates with its TNFR1 characteristics.

PMID:38551009 | PMC:PMC10973173 | DOI:10.1016/j.isci.2024.109486

iScience. 2024 Mar 7;27(4):109448. doi: 10.1016/j.isci.2024.109448. eCollection 2024 Apr 19.

ABSTRACT

Epidermal growth factor receptor inhibitors (EGFRi) have exhibited promising clinical outcomes in the treatment of various cancers. However, their widespread application has been limited by low patient eligibility and the emergence of resistance. Leveraging a multi-omics approach (>1000 cancer cell lines), we explored molecular signatures linked to EGFRi responsiveness and found that expression signatures involved in the estrogen response could recapitulate cancer cell dependency on EGFR, a phenomenon not solely attributable to EGFR-activating mutations. By correlating genome-wide function screening data with EGFRi responses, we identified chemokine receptor 6 (CCR6) as a potential druggable target to mitigate EGFRi resistance. In isogenic cell models, pharmacological inhibition of CCR6 effectively reversed acquired EGFRi resistance, disrupting mitochondrial oxidative phosphorylation, a cellular process commonly associated with therapy resistance. Our data-driven strategy unveils drug-response biomarkers and therapeutic targets for resistance, thus potentially expanding EGFRi applicability and efficacy.

PMID:38551001 | PMC:PMC10972824 | DOI:10.1016/j.isci.2024.109448

Comput Struct Biotechnol J. 2024 Mar 18;23:1260-1273. doi: 10.1016/j.csbj.2024.03.006. eCollection 2024 Dec.

ABSTRACT

Early identification of human pathogens is crucial for the effective treatment of bloodstream infections to prevent sepsis. Since pathogens that are present in small numbers are usually difficult to detect directly, we hypothesize that the behavior of the immune cells that are present in large numbers may provide indirect evidence about the causative pathogen of the infection. We previously applied time-lapse microscopy to observe that neutrophils isolated from human whole-blood samples, which had been infected with the human-pathogenic fungus Candida albicans or C. glabrata, indeed exhibited a characteristic morphodynamic behavior. Tracking the neutrophil movement and shape dynamics over time, combined with machine learning approach, the accuracy for the differentiation between the two Candida species was about 75%. In this study, the focus is on improving the classification accuracy of the Candida species using advanced deep learning methods. We implemented (i) gated recurrent unit (GRU) networks and transformer-based networks for video data, and (ii) convolutional neural networks (CNNs) for individual frames of the time-lapse microscopy data. While the GRU and transformer-based approaches yielded promising results with 96% and 100% accuracy, respectively, the classification based on videos proved to be very time-consuming and required several hours. In contrast, the CNN model for individual microscopy frames yielded results within minutes, and, utilizing a majority-vote technique, achieved 100% accuracy both in identifying the pathogen-free blood samples and in distinguishing between the Candida species. The applied CNN demonstrates the potential for automatically differentiating bloodstream Candida infections with high accuracy and efficiency. We further analysed the results of the CNN using explainable artificial intelligence (XAI) techniques to understand the critical features and patterns, thereby shedding light on potential key morphodynamic characteristics of neutrophils in response to different Candida species. This approach could provide new insights into host-pathogen interactions and may facilitate the development of rapid, automated diagnostic tools for differentiating fungal species in blood samples.

PMID:38550973 | PMC:PMC10973576 | DOI:10.1016/j.csbj.2024.03.006

Adv Sci (Weinh). 2024 Mar 28:e2400847. doi: 10.1002/advs.202400847. Online ahead of print.

ABSTRACT

Understanding the impact of long-term opioid exposure on the embryonic brain is critical due to the surging number of pregnant mothers with opioid dependency. However, this has been limited by human brain inaccessibility and cross-species differences in animal models. Here, a human midbrain model is established that uses hiPSC-derived midbrain organoids to assess cell-type-specific responses to acute and chronic fentanyl treatment and fentanyl withdrawal. Single-cell mRNA sequencing of 25,510 cells from organoids in different treatment groups reveals that chronic fentanyl treatment arrests neuronal subtype specification during early midbrain development and alters synaptic activity and neuron projection. In contrast, acute fentanyl treatment increases dopamine release but does not significantly alter gene expression related to cell lineage development. These results provide the first examination of the effects of opioid exposure on human midbrain development at the single-cell level.

PMID:38549185 | DOI:10.1002/advs.202400847

BMC Endocr Disord. 2024 Mar 29;24(1):44. doi: 10.1186/s12902-024-01571-y.

ABSTRACT

BACKGROUND: Polycystic ovary syndrome (PCOS) is a serious health condition affecting women of reproductive age. High prevalence of PCOS and associated metabolic complications needs effective treatment and management. This study evaluated the efficacy of optimal nutraceutical combinations in improving PCOS characteristics using system biology-based mathematical modelling and simulation.

METHODS: A shortlisting of eight potent nutraceuticals was carried out with literature search. Menstrual cycle model was used to perform simulations on an in-silico population of 2000 individuals to test individual and combined effects of shortlisted nutraceuticals on five PCOS characteristics [oligomenorrhea, anovulation, hirsutism, infertility, and polycystic ovarian morphology (PCOM)] for a duration of 6 months. Efficacy was tested across lean and obese phenotypes and age groups.

RESULTS: Individual assessment of nutraceuticals revealed seven most potent compounds. Myo-inositol among them was observed to be the most effective in alleviating the PCOS characteristics. The in-silico population analysis showed that the combination of melatonin and ALA along with myo-inositol was efficacious in restoring the hormonal balance across age-groups and Body Mass Index (BMI) categories.

CONCLUSION: Supplementation with the combination of myo-inositol, melatonin, and ALA demonstrated potential in managing PCOS symptoms in our in-silico analysis of a heterogeneous population, including lean and obese phenotypes across various severities and age groups, over a 6-month period. Future clinical studies are recommended to validate these findings.

PMID:38549084 | DOI:10.1186/s12902-024-01571-y