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Insulin/IGF-1 Signaling (IIS) is known to constrain longevity by inhibiting the transcription factor FOXO. How phosphorylation mediated by IIS kinases regulates lifespan beyond FOXO remains unclear. Here, we profile IIS-dependent phosphorylation changes in a large-scale quantitative phosphoproteomic analysis of wild-type and three IIS mutant Caenorhabditis elegans strains. We quantify more than 15,000 phosphosites and find that 476 of these are differentially phosphorylated in the long-lived daf-2/insulin receptor mutant. We develop a machine learning-based method to prioritize 25 potential lifespan-related phosphosites. We perform validations to show that AKT-1 pT492 inhibits DAF-16/FOXO and compensates the loss of daf-2 function, that EIF-2α pS49 potently inhibits protein synthesis and daf-2 longevity, and that reduced phosphorylation of multiple germline proteins apparently transmits reduced DAF-2 signaling to the soma. In addition, an analysis of kinases with enriched substrates detects that casein kinase 2 (CK2) subunits negatively regulate lifespan. Our study reveals detailed functional insights into longevity. How phosphorylation mediated by Insulin/IGF-1 Signaling kinases regulates lifespan remains unclear. Here the authors perform a large-scale quantitative phosphoproteomic analysis of wildtype and IIS mutant C. elegans strains to reveal detailed functional insights into longevity.

To improve chemical cross-linking of proteins coupled with mass spectrometry (CXMS), we developed a lysine-targeted enrichable cross-linker containing a biotin tag for affinity purification, a chemical cleavage site to separate cross-linked peptides away from biotin after enrichment, and a spacer arm that can be labeled with stable isotopes for quantitation. By locating the flexible proteins on the surface of 70S ribosome, we show that this trifunctional cross-linker is effective at attaining structural information not easily attainable by crystallography and electron microscopy. From a crude Rrp46 immunoprecipitate, it helped identify two direct binding partners of Rrp46 and 15 protein-protein interactions (PPIs) among the co-immunoprecipitated exosome subunits. Applying it to E. coli and C. elegans lysates, we identified 3130 and 893 inter-linked lysine pairs, representing 677 and 121 PPIs. Using a quantitative CXMS workflow we demonstrate that it can reveal changes in the reactivity of lysine residues due to protein-nucleic acid interaction. Proteins fold into structures that are determined by the order of the amino acids that they are built from. These structures enable the protein to carry out its role, which often involves interacting with other proteins. Chemical cross-linking coupled with mass spectrometry (CXMS) is a powerful method used to study protein structure and how proteins interact, with a benefit of stabilizing and capturing brief interactions. CXMS uses a chemical compound called a linker that has two arms, each of which can bind specific amino acids in a protein or in multiple proteins. Only when the regions are close to each other can they be “cross-linked” in this way. After cross-linking, the proteins are cut into small pieces known as peptides. The cross-linked peptides are then separated from the non cross-linked ones and characterized. Although CXMS is a popular method, there are aspects about it that limit its use. It does not work well on complex samples that contain lots of different proteins, as it is difficult to separate the cross-linked peptides from the overwhelming amounts of non cross-linked peptides. Also, although it can be used to detect changes in the shape of a protein, which are often crucial to the protein's role, the method has not been smoothed out. Tan, Li et al. have now developed a new cross-linker called Leiker that addresses these limitations. Leiker cross-links the amino acid lysine to another lysine, and contains a molecular tag that allows cross-linked peptides to be efficiently purified away from non cross-linked peptides. As part of a streamlined workflow to detect changes in the shape of a protein, Leiker also contains a region that can be labeled. Analysing a bacterial ribosome, which contains more than 50 proteins, showed that Leiker-based CXMS could detect many more protein interactions than previous studies had. These included interactions that changed too rapidly to be studied by other structural methods. Tan, Li et al. then applied Leiker-based CXMS to the entire contents of bacterial cells at different stages of growth, and identified a protein interaction that is only found in growing cells. In future, Leiker will be useful for analyzing the structure of large protein complexes, probing changes in protein structure, and mapping the interactions between proteins in complex mixtures.

Background Although frailty is highly prevalent in hospitalized older heart failure (HF) patients, its management is often delayed. Understanding the unique experiences of frail elderly HF patients and the perceptions of healthcare professionals (HPs) regarding frailty can facilitate the integration of frailty prevention and intervention into clinical practice. This study aimed to use a descriptive qualitative approach to obtain the experiences of frailty in older HF patients and the perceptions of HPs concerning frailty. Methods Qualitative interviews were conducted with 16 frail elderly HF patients and 13 healthcare providers. Data were analyzed using thematic analysis. Results The interviews yielded several themes with associated subthemes: “a state of predicament,” “hope is gone and social isolation,” “daily adjustment and attempts to do something,” “thoughts on factors contributing to frailty,” “the need for transformation of stakeholders’ mindset regarding frailty,” “management is imperative, but there is still a way to go”. Conclusions Both elderly patients with HF and HPs described frailty as a state of predicament, involving being caught in life difficulties and falling into a treatment dilemma. Due to the overlap of symptoms and evaluating indicators between frailty and HF, it’s essential to thoroughly understand modifiable risk factors that could worsen frailty and develop a specific frailty assessment tool for HF patients. Adequate social support, multidisciplinary collaboration, and a frailty education program for patients, caregivers, and HPs are essential to facilitate frailty management and improvement.

Invasive fractional flow reserve (FFR) is the gold standard to assess the functional coronary stenosis. The non-invasive assessment of diameter stenosis (DS) using coronary computed tomography angiography (CTA) has high false positive rate in contrast to FFR. Combining CTA with computational fluid dynamics (CFD), recent studies have shown promising predictions of FFRCT for superior assessment of lesion severity over CTA alone. The CFD models tend to be computationally expensive, however, and require several hours for completing analysis. Here, we introduce simplified models to predict noninvasive FFR at substantially less computational time. In this retrospective pilot study, 21 patients received coronary CTA. Subsequently a total of 32 vessels underwent invasive FFR measurement. For each vessel, FFR based on steady-state and analytical models (FFRSS and FFRAM, respectively) were calculated non-invasively based on CTA and compared with FFR. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value were 90.6% (87.5%), 80.0% (80.0%), 95.5% (90.9%), 88.9% (80.0%) and 91.3% (90.9%) respectively for FFRSS (and FFRAM) on a per-vessel basis, and were 75.0%, 50.0%, 86.4%, 62.5% and 79.2% respectively for DS. The area under the receiver operating characteristic curve (AUC) was 0.963, 0.954 and 0.741 for FFRSS, FFRAM and DS respectively, on a per-patient level. The results suggest that the CTA-derived FFRSS performed well in contrast to invasive FFR and they had better diagnostic performance than DS from CTA in the identification of functionally significant lesions. In contrast to FFRCT, FFRSS requires much less computational time.

Previous research has explored the factors influencing frailty in older patients with chronic heart failure (CHF), but these studies have not revealed the potential network interactions among the related factors. This study aimed to construct a Bayesian network (BN) model of frailty in older patients with CHF, analyze the predictive factors, and explore the internal relationships between these factors. A total of 439 older patients with CHF were selected using a convenience sampling method from September 2023 to March 2024 at the cardiology department of a comprehensive tertiary hospital in Nanchang, Jiangxi, China. Multivariate logistic regression analysis was used to explore the influencing factors of frailty in older patients with CHF. The BN structure was learned using the max–min hill-climbing algorithm, with parameter estimation achieved through maximum likelihood estimation. Netica software was utilized for prediction and diagnosis. The effectiveness of the model was validated using the Receiver Operating Characteristic (ROC) curve. The prevalence of frailty in older patients with CHF was found to be 53.3%. After using a multivariate logistic regression analysis model that screened the variables, the nutritional risk, physical activity, depression, multimorbidity, grip strength and left atrial diameter were included into the Bayesian network model. The Bayesian network model of frailty related factors in older CHF patients showed that nutritional risk, physical activity, depression, and multimorbidity were directly related to frailty, while grip strength and left atrial diameter were indirectly related. The study results indicated that malnutrition risk, inactivity, depression, and multimorbidity were directly related to frailty, while lower grip strength and a wider left atrial diameter were indirectly related to frailty. Enhancing frailty assessment and implementing measures addressing disease, nutrition, exercise, and psychological well-being are crucial for delaying and potentially reversing the onset and progression of frailty.

Traditionally, cardiac image analysis is done manually. Automatic image processing can help with the repetitive tasks, and also deal with huge amounts of data, a task which would be humanly tedious. This study aims to develop a spectrum-based computer-aided tool to locate the left ventricle using images obtained via cardiac magnetic resonance imaging. Discrete Fourier Transform was conducted pixelwise on the image sequence. Harmonic images of all frequencies were analyzed visually and quantitatively to determine different patterns of the left and right ventricles on spectrum. The first and fifth harmonic images were selected to perform an anisotropic weighted circle Hough detection. This tool was then tested in ten volunteers. Our tool was able to locate the left ventricle in all cases and had a significantly higher cropping ratio of 0.165 than did earlier studies. In conclusion, a new spectrum-based computer aided tool has been proposed and developed for automatic left ventricle localization. The development of this technique, which will enable the automatic location and further segmentation of the left ventricle, will have a significant impact in research and in diagnostic settings. We envisage that this automated method could be used by radiographers and cardiologists to diagnose and assess ventricular function in patients with diverse heart diseases.

Sleep is a ubiquitous, tightly regulated, and evolutionarily conserved behavior observed in almost all animals. Prolonged sleep deprivation can be fatal, indicating that sleep is a physiological necessity. However, little is known about its core function. To gain insight into this mystery, we used advanced quantitative proteomics technology to survey the global changes in brain protein abundance. Aiming to gain a comprehensive profile, our proteomics workflow included filter-aided sample preparation (FASP), which increased the coverage of membrane proteins; tandem mass tag (TMT) labeling, for relative quantitation; and high resolution, high mass accuracy, high throughput mass spectrometry (MS). In total, we obtained the relative abundance ratios of 9888 proteins encoded by 6070 genes. Interestingly, we observed significant enrichment for mitochondrial proteins among the differentially expressed proteins. This finding suggests that sleep deprivation strongly affects signaling pathways that govern either energy metabolism or responses to mitochondrial stress. Additionally, the differentially-expressed proteins are enriched in pathways implicated in age-dependent neurodegenerative diseases, including Parkinson's, Huntington's, and Alzheimer's, hinting at possible connections between sleep loss, mitochondrial stress, and neurodegeneration.

Background Oocysts serve as the primary source of Toxoplasma infection. Therefore, understanding oocyst development and exploring effective strategies to prevent oocyst excretion are crucial for controlling toxoplasmosis. Methods In this study, shotgun metagenomics was employed to characterize the functional and compositional changes in the gut microbiota of cats during oocyst development. The Spearman correlation test was utilized to analyze the correlation between differential Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and carbohydrate-active enzymes (CAZymes) in key bacteria regulating oocyst excretion. Results The results revealed that group A (sexual initiation stage) displayed a lower number of functional genes, which were restored to normal levels in group B (oocyst excretion stage), compared with group C ( Toxoplasma -uninfected samples). The abundance of 39 KEGG pathways, 106 CAZymes, and 98 virulence factors (VFs) varied significantly among the three groups. The atrazine degradation pathway, associated with sexual development, was upregulated in group B. CAZymes involved in restoring the intestinal mucosal barrier and VFs related to iron metabolism, antibiotic resistance, and suppression of host immunity were enriched in group B. Sexual initiation and oocyst excretion resulted in reduced gut bacterial diversity and microbiota dysbiosis. Probiotics and bacteria related to linoleic acid (LA) uptake were dominant in both group A and group B. Bacteroides stercoris was the most significantly upregulated bacterium and could influence the expression of carbohydrate-binding modules (CBMs) and glycoside hydrolases (GHs) in group B. Conclusions During the oocyst development/excretion stage, the function and composition of the cat gut microbiota changed significantly. In addition, Bacteroides stercoris may play a crucial role in oocyst excretion by regulating key candidates of CBMs and GHs. Our findings lay the foundation for investigating the regulatory mechanisms of oocyst excretion. Graphical Abstract

Objective To explore the effect of bone marrow mesenchymal stem cells (BM‐MSCs) transplantation on the changes of oligodendrocyte lineage in brain of experimental autoimmune encephalomyelitis (EAE) rats. Methods The animals were divided into normal control group, EAE model group (EAE group), cell culture medium injection treatment group (placebo treatment group), and MSCs treatment group (treatment group). The changes of A2B5‐, O4‐, and CNPase‐positive cells in oligodendrocyte lineage in rat brain were observed after 1, 3, 7, 14, 21, and 28 days. Results The number of A2B5‐positive cells in rat brain of the treatment group at each time point was significantly more than that of the EAE and placebo treatment groups, and most obvious at 14 days. The O4‐positive cells number at each time point in the treatment group was significantly increased compared with the EAE and placebo treatment groups, and most obvious at 14 days. The CNPase‐positive cells number at each time point in the treatment group was significantly increased compared with the EAE and placebo treatment groups, and most obvious at 14 days. Conclusions MSCs treatment can increase cells expression in oligodendrocyte lineage, which laying a solid foundation for myelin regeneration. MSCs treatment can increase cells expression in oligodendrocyte lineage, which laying a solid foundation for myelin regeneration.

With the aid of cardiac imaging techniques, recent numerical simulations of left ventricular flow can be patient-specific to better mimic physiological conditions. However, studies with a dynamic mitral valve (MV) remain extremely limited. Even so, the left atrium (LA) is usually simplified to be tubular regardless of its complex structure. Studies on the effect of this simplification are limited and observations are controversial. In this study, both tubular and generic atriums were incorporated in patient-specific simulations with and without the MV to qualitatively and quantitatively estimate the effects of the atrial model on downstream ventricular flow. The patient-specific model was generated based on cardiac magnetic resonance (CMR) images of a healthy volunteer, and the dynamic motion of the MV was defined by the contours acquired along long-axis images. Based on the simulations, the influence of the atrial vortices on ventricular flow was significant in the valveless models in terms of flow structure, kinetic energy (KE) and circulation. Although these effects were suppressed in the presence of the MV, the atrial vortices that survived the passage were not trivial, which was evidenced by reduced strength of circulation and undesired flow pattern in the apical region. The flow structure in the generic atrium also dominated the development of ventricular flow in the valveless model. After the MV was incorporated, its effects on the downstream ventricular flow were considerably reduced but not eliminated. Therefore, a proper modelling of atrial flow is necessary, especially for subjects with high ejection fraction (EF). •The effect of atrial flow on a patient-specific left ventricular flow has been investigated.•The atrial vorticies dominated the ventricular flow when the mitral valve was absent in the numerical model.•The impacts of atrial vortices were significantly suppressed by the mitral valve but not completely eliminated.•The survived atrial vorticies through mitral valve were capable of altering the apical flow and circulation.•It is reasonable to properly model atrial flow, especially for subjects with high ejection fraction.