Mapping the time-varying functional brain networks in response to naturalistic movie stimuli

One of human brain’s remarkable traits lies in its capacity to dynamically coordinate the activities of multiple brain regions or networks, adapting to an externally changing environment. Studying the dynamic functional brain networks (DFNs) and their role in perception, assessment, and action can significantly advance our comprehension of how the brain responds to patterns of sensory input. Movies provide a valuable tool for studying DFNs, as they offer a naturalistic paradigm that can evoke complex cognitive and emotional experiences through rich multimodal and dynamic stimuli. However, most previous research on DFNs have predominantly concentrated on the resting-state paradigm, investigating the topological structure of temporal dynamic brain networks generated via chosen templates. The dynamic spatial configurations of the functional networks elicited by naturalistic stimuli demand further exploration. In this study, we employed an unsupervised dictionary learning and sparse coding method combing with a sliding window strategy to map and quantify the dynamic spatial patterns of functional brain networks (FBNs) present in naturalistic functional magnetic resonance imaging (NfMRI) data, and further evaluated whether the temporal dynamics of distinct FBNs are aligned to the sensory, cognitive, and affective processes involved in the subjective perception of the movie. The results revealed that movie viewing can evoke complex FBNs, and these FBNs were time-varying with the movie storylines and were correlated with the movie annotations and the subjective ratings of viewing experience. The reliability of DFNs was also validated by assessing the Intra-class coefficient (ICC) among two scanning sessions under the same naturalistic paradigm with a three-month interval. Our findings offer novel insight into comprehending the dynamic properties of FBNs in response to naturalistic stimuli, which could potentially deepen our understanding of the neural mechanisms underlying the brain’s dynamic changes during the processing of visual and auditory stimuli

Establishment of a Mouse Model of Premature Ovarian Failure Using Consecutive Superovulation

Background/Aims: This study investigated the effect of consecutive superovulation on the ovaries and established a premature ovarian failure (POF) model in mice. Methods: The mouse POF model was induced by 5-15 consecutive superovulation treatments with pregnant mare serum gonadotropin (PMSG), human chorionic gonadotropin (HCG) and prostaglandin F2α (PGF2α). Normal adult mice were compared with mice displaying natural ovarian aging. The following serum biochemical parameters were measured: including follicle-stimulating hormone (FSH), luteinizing hormone (LH), progesterone (P), estradiol (E2), inhibin B (INH B), malondialdehyde (MDA), total superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) levels. Follicles were counted using H&E staining. Levels of 8-hydroxyguanosine (8-OhdG), 4-hydroxynonenal (4-HNE), nitrotyrosine (NTY), anti-Mullerian hormone (AMH) and CDKN2A/ p16 (p16) were detected using immunohistochemical staining. Reactive oxygen species (ROS) levels were measured using dihydroethidium (DHE) staining. Cell apoptosis was detected using an in situ TUNEL fluorescence staining assay. Levels of proteins involved in ROS-related pathways and the p16 protein were detected using Western blotting. Sod1, Sod2 and Sod3 mRNA levels were detected using quantitative polymerase chain reaction (Q-PCR). Oocyte quality was evaluated using in vitro fertilization (IVF) and zygote culture. Results: Consecutive superovulation groups presented lower P, E2, SOD, GSH-Px and INH B levels, significantly higher FSH, LH, MDA and ROS levels, and significantly fewer primordial follicles compared with the control group. Consecutive superovulation groups presented significantly increased levels of Sod2, 8-OhdG, 4-HNE, NTY, significantly increased levels of the SIRT1 and FOXO1 proteins, significantly increased levels of the senescence-associated protein p16, as well as decreased AMH, Sod1 and Sod3 levels and increased granulosa cell apoptosis compared with the control group. Conclusion: Consecutive superovulation significantly decreased ovarian function and oocyte quality and increased oxidative stress and apoptosis in the ovary via a mechanism involving the p16 and SIRT1/FOXO1 signaling pathways. These findings suggest that consecutive superovulation may be used to establish a mouse model of ovarian aging

Semen cassiae Extract Inhibits Contraction of Airway Smooth Muscle

β2-adrenoceptor agonists are commonly used as bronchodilators to treat obstructive lung diseases such as asthma and chronic obstructive pulmonary disease (COPD), however, they induce severe side effects. Therefore, developing new bronchodilators is essential. Herbal plants were extracted and the extracts’ effect on airway smooth muscle (ASM) precontraction was assessed. The ethyl alcohol extract of semen cassiae (EESC) was extracted from Semen cassia. The effects of EESC on the ACh- and 80 mM K+-induced sustained precontraction in mouse and human ASM were evaluated. Ca2+ permeant ion channel currents and intracellular Ca2+ concentration were measured. HPLC analysis was employed to determine which compound was responsible for the EESC-induced relaxation. The EESC reversibly inhibited the ACh- and 80 mM K+-induced precontraction. The sustained precontraction depends on Ca2+ influx, and it was mediated by voltage-dependent L-type Ca2+ channels (LVDCCs), store-operated channels (SOCs), TRPC3/STIM/Orai channels. These channels were inhibited by aurantio-obtusin, one component of EESC. When aurantio-obtusin removed, EESC’s action disappeared. In addition, aurantio-obtusin inhibited the precontraction of mouse and human ASM and intracellular Ca2+ increases. These results indicate that Semen cassia-contained aurantio-obtusin inhibits sustained precontraction of ASM via inhibiting Ca2+-permeant ion channels, thereby, which could be used to develop new bronchodilators

Diverse Applications of Nanomedicine

The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic. \ua9 2017 American Chemical Society

RBAP, a Rhodamine B-Based Derivative: Synthesis, Crystal Structure Analysis, Molecular Simulation, and Its Application as a Selective Fluorescent Chemical Sensor for Sn2+

A new fluorescent chemosensor based on a Rhodamine B and a benzyl 3-aminopropanoate conjugate (RBAP) was designed, synthesized, and structurally characterized. Its single crystal structure was obtained and analyzed by X-ray analysis. In a MeOH/H2O (2:3, v/v, pH 5.95) solution RBAP exhibits a high selectivity and excellent sensitivity for Sn2+ ions in the presence of many other metal cations. The binding analysis using the Job’s plot suggested the RBAP formed a 1:1 complex with Sn2+

The Landscape of Noncoding RNA in Pulmonary Hypertension

The transcriptome of pulmonary hypertension (PH) is complex and highly genetically heterogeneous, with noncoding RNA transcripts playing crucial roles. The majority of RNAs in the noncoding transcriptome are long noncoding RNAs (lncRNAs) with less circular RNAs (circRNAs), which are two characteristics gaining increasing attention in the forefront of RNA research field. These noncoding transcripts (especially lncRNAs and circRNAs) exert important regulatory functions in PH and emerge as potential disease biomarkers and therapeutic targets. Recent technological advancements have established great momentum for discovery and functional characterization of ncRNAs, which include broad transcriptome sequencing such as bulk RNA-sequence, single-cell and spatial transcriptomics, and RNA-protein/RNA interactions. In this review, we summarize the current research on the classification, biogenesis, and the biological functions and molecular mechanisms of these noncoding RNAs (ncRNAs) involved in the pulmonary vascular remodeling in PH. Furthermore, we highlight the utility and challenges of using these ncRNAs as biomarkers and therapeutics in PH

A Comprehensive Comparative Analysis of the Basic Theory of the Short Term Bus Passenger Flow Prediction

In order to meet the real-time public travel demands, the bus operators need to adjust the timetables in time. Therefore, it is necessary to predict the variations of the short-term passenger flow. Under the help of the advanced public transportation systems, a large amount of real-time data about passenger flow is collected from the automatic passenger counters, automatic fare collection systems, etc. Using these data, different kinds of methods are proposed to predict future variations of the short-term bus passenger flow. Based on the properties and background knowledge, these methods are classified into three categories: linear, nonlinear and combined methods. Their performances are evaluated in detail in the major aspects of the prediction accuracy, the complexity of training data structure and modeling process. For comparison, some long-term prediction methods are also analyzed simply. At last, it points that, with the help of automatic technology, a large amount of data about passenger flow will be collected, and using the big data technology to speed up the data preprocessing and modeling process may be one of the directions worthy of study in the future

A New Method of Diagnosing the Historical and Projected Changes in Permafrost on the Tibetan Plateau

Abstract The Tibetan Plateau (TP) is the largest permafrost distribution zone at high‐altitude in the mid‐latitude region. Climate change has caused significant permafrost degradation on the TP, which has important impacts for the eco‐hydrological processes. In this study, the frost number is utilized to calculate the frost number (F) based on the air freezing/thawing index obtained from the downscaled Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets. A novel method is proposed to determine the frost number threshold (Ft) for diagnosing permafrost distribution. Then the simulated permafrost distribution maps are compared with the existing permafrost distribution map, employing the Kappa coefficient as the measure of classification accuracy to identify the optimal Ft. Finally, the permafrost distribution on the TP under different Shared Socio‐economic Pathways (SSP) scenarios are diagnosed with the optimal Ft. Simulation results demonstrate that across all scenarios, the rates of permafrost degradation during the mid‐future period (2040–2060) remain comparable to those observed in the baseline period (2000), ranging from 33% ± 3% to 53% ± 4%. Conversely, during the far‐future (2080–2099), the permafrost degradation rates display significant variation across different scenarios, ranging from 37% ± 4% to 96% ± 3%. The profound impacts of permafrost degradation on the TP are reflected in decreasing trends in soil moisture and runoff, as well as a slower increasing trend in Normalized Difference Vegetation Index (NDVI) compared to other regions, indicating negative impacts on vegetation growth