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Arousal and motivation interact to profoundly influence behavior. For example, experience tells us that we have some capacity to control our arousal when appropriately motivated, such as staying awake while driving a motor vehicle. However, little is known about how arousal and motivation jointly influence decision computations, including if and how animals, such as rodents, adapt their arousal state to their needs. Here, we developed and show results from an auditory, feature-based, sustained-attention task with intermittently shifting task utility. We use pupil size to estimate arousal across a wide range of states and apply tailored signal-detection theoretic, hazard function, and accumulation-to-bound modeling approaches in a large cohort of mice. We find that pupil-linked arousal and task utility both have major impacts on multiple aspects of task performance. Although substantial arousal fluctuations persist across utility conditions, mice partially stabilize their arousal near an intermediate and optimal level when task utility is high. Behavioral analyses show that multiple elements of behavior improve during high task utility and that arousal influences some, but not all, of them. Specifically, arousal influences the likelihood and timescale of sensory evidence accumulation but not the quantity of evidence accumulated per time step while attending. In sum, the results establish specific decision-computational signatures of arousal, motivation, and their interaction in attention. So doing, we provide an experimental and analysis framework for studying arousal self-regulation in neurotypical brains and in diseases such as attention-deficit/hyperactivity disorder.
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PURPOSE: Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is the primary cause of death in patients with IPF, characterised by diffuse, bilateral ground-glass opacification on high-resolution CT (HRCT). This study proposes a three-dimensional (3D)-based deep learning algorithm for classifying AE-IPF using HRCT images. MATERIALS AND METHODS: A novel 3D-based deep learning algorithm, SlowFast, was developed by applying a database of 306 HRCT scans obtained from two centres. The scans were divided into four separate subsets (training set, n=105; internal validation set, n=26; temporal test set 1, n=79; and geographical test set 2, n=96). The final training data set consisted of 1050 samples with 33 600 images for algorithm training. Algorithm performance was evaluated using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve and weighted κ coefficient. RESULTS: The accuracy of the algorithm in classifying AE-IPF on the test sets 1 and 2 was 93.9% and 86.5%, respectively. Interobserver agreements between the algorithm and the majority opinion of the radiologists were good (κw=0.90 for test set 1 and κw=0.73 for test set 2, respectively). The ROC accuracy of the algorithm for classifying AE-IPF on the test sets 1 and 2 was 0.96 and 0.92, respectively. The algorithm performance was superior to visual analysis in accurately diagnosing radiological findings. Furthermore, the algorithm's categorisation was a significant predictor of IPF progression. CONCLUSIONS: The deep learning algorithm provides high auxiliary diagnostic efficiency in patients with AE-IPF and may serve as a useful clinical aid for diagnosis.
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Aprendizaje Profundo , Neumonías Intersticiales Idiopáticas , Fibrosis Pulmonar Idiopática , Humanos , Fibrosis Pulmonar Idiopática/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Curva ROCRESUMEN
Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive scarring interstitial lung disease with an unknown cause. Some patients may experience acute exacerbations (AE), which result in severe lung damage visible on imaging or through examination of tissue samples, often leading to high mortality rates. However, the etiology and pathogenesis of AE-IPF remain unclear. AE-IPF patients exhibit diffuse lung damage, apoptosis of type II alveolar epithelial cells, and an excessive inflammatory response. Establishing a reliable animal model of AE is critical for investigating the pathogenesis. Recent studies have reported a variety of animal models for AE-IPF, each with its own advantages and disadvantages. These models are usually established in mice with bleomycin-induced pulmonary fibrosis, using viruses, bacteria, small peptides, or specific drugs. In this review, we present an overview of different AE models, hoping to provide a useful resource for exploring the mechanisms and targeted therapies for AE-IPF.
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Fibrosis Pulmonar Idiopática , Humanos , Animales , Ratones , Fibrosis Pulmonar Idiopática/diagnóstico , Pulmón , Modelos Animales , Progresión de la EnfermedadRESUMEN
Lung adenocarcinoma (LUAD) has become the most prevalent histologic subset of primary lung cancer, and effective innovative prognostic models are needed to enhance the feasibility of targeted therapies for the disease. Programmed cell death (PCD) performs an integral function in the origin and treatment of cancer. Some PCD-related effective signatures for predicting prognosis in LUAD patients could provide potential therapeutic options in LUAD. A copper-dependent cell death referred to as cuproptosis is distinct from known PCD. However, whether cuproptosis is associated with LUAD patients' prognoses and the potential roles of cuproptosis-related genes involved is still unknown. For the prediction of LUAD prognosis, we developed a unique cuproptosis-associated gene signature. In The Cancer Genome Atlas (TCGA) cohort, the score derived from the risk signature on the basis of six cuproptosis-related genes was found to independently serve as a risk factor for anticipating lung cancer-related death. The differentially expressed genes between the high- and low-risk groups were linked to the cilium-related function. LUAD patients' prognoses may now be predicted by a unique gene signature identified in this work. This discovery also provides a substantial foundation for future research into the links between cuproptosis-associated genes and cilium-related function in LUAD patients.
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Backgrounds: Growth differentiation factor 15 (GDF-15) is a highly divergent member of the TGF-ß superfamily and has been implicated in various biological functions. However, the expression of GDF-15 in patients with acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is unclear. Method: The study included 47 AE-IPF patients, 61 stable IPF (S-IPF) subjects, and 31 healthy controls (HCs). Serum GDF-15 levels and their expression in the lung were measured. The correlation between serum GDF-15 and other clinical parameters and the risk factors for AE occurrence and the survival of IPF patients were analyzed. Results: Serum GDF-15 levels were significantly elevated in AE-IPF patients (1279.22 ± 540.02 pg/ml) as compared with HCs (891.30 ± 479.90 pg/ml) or S-IPF subjects (107.82 ± 14.21 pg/ml) (both p < 0.001). The protein and mRNA expressions of GDF-15 in the lung of AE-IPF patients were significantly increased as compared with S-IPF cases (p = 0.007 and p = 0.026, respectively). The serum GDF-15 level was correlated with the clinical variables of inflammation, metabolism, and disease severity in IPF subjects (all p < 0.05). The GDF-15 serum concentration was significantly higher in decedents than in survivors (p = 0.005). A serum GDF-15 level above 989.3 pg/ml was a risk factor for AE occurrence (p = 0.04), and the level above 1,075.76 pg/ml was an independent predictor for survival in IPF cases (p = 0.007). Conclusions: The GDF-15 level was significantly elevated in subjects with AE-IPF. GDF-15 could be a promising biomarker for AE occurrence and survival in IPF patients.
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Factor 15 de Diferenciación de Crecimiento/metabolismo , Fibrosis Pulmonar Idiopática , Biomarcadores , Factor 15 de Diferenciación de Crecimiento/genética , Humanos , Fibrosis Pulmonar Idiopática/metabolismo , Inflamación/complicaciones , Pulmón/metabolismoRESUMEN
OBJECTIVE: To develop a putative microRNA (miRNA) and messenger RNA (mRNA) regulatory network of Danggui Buxue decoction's (DGBXD) amelioration of idiopathic pulmonary fibrosis (IPF). METHODS: The Gene Expression Omnibus (GEO) database was used to identify differentially expressed miRNAs (DE-miRNAs) and differentially expressed mRNAs (DE-mRNAs). Using miRNet, the predicted target genes of identified DE-miRNAs were estimated, and then the target genes of DE-miRNAs in IPF were comprehensively examined. The Enrichr database was used to conduct functional enrichment and pathway enrichment. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was employed to obtain the target genes of DGBXD as well as active compounds. A putative miRNA-mRNA regulatory network of DGBXD acting on IPF was developed by intersecting the target genes of DGBXD with the DE-miRNA target genes in IPF. A bleomycin-induced mouse model was established and used to perform histopathology as well as real-time quantitative polymerase chain reaction (qRT-PCR) analyses of some miRNA-mRNA pairs. RESULTS: Fourteen upmodulated DE-miRNAs and six downmodulated DE-miRNAs were screened. The downstream target genes of upmodulated and downmodulated DE-miRNAs were predicted. Subsequently, 1160 upmodulated DE-mRNAs and 1427 downmodulated DE-mRNAs were identified. Then, target genes of DE-miRNAs comprising 49 downmodulated and 53 upmodulated target genes were further screened to perform functional enrichment and pathway enrichment analyses. Subsequently, 196 target genes of DGBXD were obtained from TCMSP, with six downregulated target genes and six upregulated target genes of DGBXD acting on IPF being identified. A promising miRNA-mRNA regulatory network of DGBXD acting on IPF was developed in this study. Moreover, mir-493 together with its target gene Olr1 and mir-338 together with Hif1a were further validated by qRT-PCR. CONCLUSION: This study proposed detailed possible processes of miRNA-mRNA modulatory axis in IPF and constructed a prospective IPF-related miRNA-mRNA modulatory network with the aim of alleviating IPF with DGBXD.
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Vagus nerve stimulation (VNS) is thought to affect neural activity by recruiting brain-wide release of neuromodulators. VNS is used in treatment-resistant epilepsy, and is increasingly being explored for other disorders, such as depression, and as a cognitive enhancer. However, the promise of VNS is only partially fulfilled due to a lack of mechanistic understanding of the transfer function between stimulation parameters and neuromodulatory response, together with a lack of biosensors for assaying stimulation efficacy in real time. We here develop an approach to VNS in head-fixed mice on a treadmill and show that pupil dilation is a reliable and convenient biosensor for VNS-evoked cortical neuromodulation. In an 'optimal' zone of stimulation parameters, current leakage and off-target effects are minimized and the extent of pupil dilation tracks VNS-evoked basal-forebrain cholinergic axon activity in neocortex. Thus, pupil dilation is a sensitive readout of the moment-by-moment, titratable effects of VNS on brain state.
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Pupila/fisiología , Nervio Vago/fisiología , Animales , Encéfalo , Corteza Cerebelosa/fisiología , Epilepsia/fisiopatología , Femenino , Locus Coeruleus/patología , Masculino , Ratones , Ratones Endogámicos C57BL , Estimulación del Nervio Vago , Vigilia/fisiologíaRESUMEN
BACKGROUND: Those with mild cognitive impairment (MCI) are ten times more like to develop Alzheimer's disease (AD) than the general population. MCI diagnosis and early intervention are helpful for the diagnosis and treatment of AD in its early stages, thus delaying its development and improving the quality of life for those with MCI. AIMS: To analyze the relationship between the lifestyle of the elderly in Shanghai communities and mild cognitive impairment and to look for preventative lifestyle measures for the elderly with mild cognitive impairment. METHODS: 1005 elderly persons were randomly selected from the community in Shanghai. Study participants were 265 people with an MCI diagnosis and 607 non-MCI elderly persons. The demographic and lifestyle data of these elderly people were collected for univariate and multivariate analysis to search for statistically significant indicators. RESULTS: The univariate analysis revealed that smoking (χ2 = 10.808, p=0.001), tea drinking (χ2 =11.74, p= 0.001), having hobbies (χ2 = 20.815, p<0.001), reading (χ2 =28.670, p= 0.001), surfing the internet (χ2 =12.623, p= 0.001), and photography (χ2 =4.470, p= 0.034) were protective factors for MCI. The binary logistic regression, a multivariate analysis, revealed that smoking, reading, and surfing the internet had statistical significance. Their OR values were 0.562 (0.358-0.883), 0.428 (0.253-0.726), and 0.238 (0.071-0.797) respectively. Thus, smoking, reading, and surfing the internet were protective factors for MCI. CONCLUSIONS: Lifestyle is associated with the onset of MCI. Good life habits and behaviors are significant in the prevention of MCI developing into Alzheimer's.
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Despite Apolipoprotein E (ApoE) being one of the main apolipoproteins in the blood, the association between its genotype and the high cholesterol or blood glucose levels commonly seen in clinical practice is inconclusive. Such research is also lacking in the Han population. The aim of this study was to investigate the association between APOE genotype, diabetes, and plasma glucose and lipid levels. We included 243 community-dwelling elderly residents in this study. Participant APOE genotypes were assessed and were simultaneously tested for weight, height, blood glucose, triglycerides, cholesterol, and high- and low-density lipoprotein. In addition, gender, age, years of education, cognitive function, and medical history was recorded. Subjects were divided into 3 groups based on APOE genotype: APOE ε2 group (ε2/ε2 and ε2/ε3), APOE ε3 group (ε3/ε3), and APOE ε4 group (ε2/ε4, ε3/ε4 and ε4/ε4). Comparisons between groups were conducted for the incidence of diabetes, high blood pressure, and dementia, as well as for differences in body-mass index, fasting plasma glucose, and blood lipids. The APOE ε3/ε3 genotype exhibited the highest frequency (70.4%) among the subjects. Participants in the APOE ε3 group demonstrated significantly higher levels of fasting plasma glucose than those in the APOE ε2 and APOE ε4 groups (P<0.05). The APOE ε3 group had slightly higher abnormal fasting plasma glucose values than did the APOE ε2 group (P = 0.065). Furthermore, the APOE3 genotype was significantly correlated with both fasting plasma glucose level and glucose abnormality (P< 0.05) and trended toward statistically significant correlation with diabetes (P = 0.082). The correlation between APOE2 and low low-density lipoprotein levels also approached statistical significance (P = 0.052). Thus, elderly community dwelling residents of Han ethnicity carrying the APOE ε3/ε3 genotype might have higher plasma glucose levels and a higher occurrence of diabetes.