Important Role Research Articles

The role of prothrombin complex concentrate to control critical bleeding after splenectomy for blunt abdominal trauma; A case report

Blunt abdominal trauma is an event that can cause massive internal bleeding and can be life-threatening. Splenectomy is often performed to treat organ injuries in patients with blunt abdominal trauma. However, splenectomy can cause hemostasis problems, which can cause more bleeding and risk complications such as Acute Kidney Injury (AKI).
 This case report aims to discuss the role of prothrombin complex concentrate (PCC) in treating bleeding and preventing AKI in blunt abdominal trauma patients after splenectomy at Fatmawati Hospital, Jakarta, Indonesia.
 A 15-year-old woman experienced blunt abdominal trauma due to a sports accident and sustained internal bleeding. After a thorough evaluation, she underwent an emergency splenectomy to stop the bleeding. However, patients developed hemostasis problem which made the control of postoperative bleeding difficult. To overcome this problem, patient was administered PCC intravenously, which resulted in significant improvement in controlling postoperative bleeding. The hematocrit level and red blood cell count steadily increased, indicating the effectiveness of PCC in improving the patient's hemostasis.
 PCC can play an important role in treating post-splenectomy bleeding in patients with blunt abdominal trauma. Apart from that, the use of PCC can also help prevent AKI, which is a serious and life-threatening complication. Further research and clinical trials are needed to confirm the benefits of using PCC in a broader patient population with similar conditions.
 Abbreviations: AKI- Acute Kidney Injury; PCC- Prothrombin Complex Concentrate
 Keywords: Acute Kidney Injury; Bleeding; Blunt Abdominal Trauma; Prothrombin Complex Concentrate; Splenectomy
 Citation: Laksana AP, Manggala SK, Irawany V. The role of prothrombin complex concentrate to control critical bleeding after splenectomy for blunt abdominal trauma; A case report. Anaesth. pain intensive care 2024;28(1):177−181; DOI: 10.35975/apic.v28i1.2289
 Received: September 13, 2023; Reviewed: October 29, 2023; Accepted: December 19, 2023

One-pot multicomponent reaction: An efficient synthesis of 4-(HET)Aryl-substituted pyrazolo-quinolinones.

Pyrazolo-quinolinones (PQs) are a versatile class of Organic chemistry and it was found that they have very advanced functionally promising as selective compounds due to their scaffold and demonstrated low toxicity and considerable clinical promise. Moreover, these compounds have an important role in different applications such as analytical reagents, technical, pharmaceutical development, and biological markers. So, we aimed to synthesize and characterize new 4-(Het)aryl-substituted Pyrazole-quinolinones. Synthesis of One-Pot Multicomponent Reaction was carried out with the reaction of 5-amino-3-methyl-1H-pyrazole 1a, and 5-amino-3-phenyl-1H-pyrazole 1b and dimedone 2 with some (het)aryl aldehydes 3 using ethanol. Characterizations such as the linear structures and the regiospecificity of the reactions were determined by using NMR, GC-MS, IR, and UV measurements. This research will be very useful for all methods and procedures using multi-one-point reactions which are very popular in the synthesis of heterocyclic systems for pyrazole- quinoline skeleton synthesis.

Antiviral potential of selenium complexes from Brassicaceae by inhibiting protein bond between MAP4 and the spike of SARS-CoV-2

Context: Coronavirus disease 2019 (COVID-19), a highly contagious viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a worldwide pandemic. Selenium derived from the plants of the Brassicaceae family plays an important role in several biological functions, often as an antioxidant or antiviral. In particular, selenium can be used as an adjuvant in the treatment of various viral infections. Aims: To determine the potential drug, as well as the affinity and the bond energy associated with chemical interaction bonds between the complex selenium compounds from Brassicaceae as inhibitors of the SARS-CoV-2 spike protein and MAP4 through the use of in silico studies. Methods: The methods used in this study consisted of receptor and ligand data collection, ADMET analysis, molecular docking, and molecular dynamics. Results: The results of this study indicate that the selenium complex compounds have the potential to be used as a spike inhibitor drug for SARS-CoV-2, as they have passed the Lipinski test and showed promise in the pharmacokinetic analysis. The results of the bond docking show that several complex selenium compounds, such as ethaselen, selenomethionine, and selenocystine, have stronger binding affinity values than the controls. This is compared to the control MAP4, which yielded binding affinities of -6.1 kcal/mol and spike protein -7 kcal/mol, respectively. Controlled bisoxatin and estramustine are drugs with mechanisms targeted to MAP4 and spike protein, which are the usual standards used. Conclusions: The similarity of sites, the binding of several amino acid residues dominated by hydrogen bonds, and the result of molecular dynamic results for the selenium compound derived from Brassicaceae showed a stable bond to the spike protein and MAP4 with low fluctuation levels.

Machine learning-derived multi-omics prognostic signature of pyroptosis-related lncRNA with regard to ZKSCAN2-DT and tumor immune infiltration in colorectal cancer.

Colorectal cancer (CRC) has become the most prevalent gastrointestinal malignant tumor, ranking third (10.2%) in incidence and second (9.2%) in death among all malignancies globally. The most common histological subtype of CRC is colon adenocarcinoma (COAD), although the cause of CRC remains unknown, as there are no valid biomarkers. A thorough investigation was used to build a credible biomolecular risk model based on the pyroptosis-associated lncRNAs discovered for COAD prediction. Furthermore, Cibersort and Tumor Immune Dysfunction and Exclusion (TIDE), the methods of exploring tumor immune infiltration, were adopted in our paper to detect the effects of differential lncRNAs on the tumor microenvironment. Finally, quantitative real-time polymerase chain reaction (qPCR), as the approach of exploring expressions, was utilized on four different cell lines. Seven pyroptosis-related lncRNAs have been identified as COAD predictive risk factors. Cox analysis, both univariate and multivariate, revealed that the established signature might serve as a novel independent factor with prognostic meaning in COAD patients. ZKSCAN2-DT was shown to be considerably overexpressed in the COAD cell line when compared to normal human colonic epithelial cells. Furthermore, ssGSEA analysis results revealed that the immune infiltration percentage of most immune cells dropped considerably as ZKSCAN2-DT expression increased, implying that ZKSCAN2-DT may play an important role in COAD immunotherapy. Our research is the first to identify pyroptosis-related lncRNAs connected with COAD patient prognosis and to construct a predictive prognosis signature, directing COAD patient prognosis in therapeutic interventions.

Denosumab Induces Neoplastic Stromal Cell Apoptosis via p62 Downregulation Dependent on Autophagy Pathway in Giant Cell Tumour of Bone.

As the only humanized monoclonal antibody against receptor activator of nuclear factor-κB ligand (RANKL) for giant cell tumour of bone (GCTB) therapy, denosumab has limited antitumour effect on neoplastic stromal cells. Nevertheless, its mechanism of action has not yet been clarified. A previous study has revealed that p62 may play an important role in the antitumour activity of denosumab. The study aimed to investigate if the mechanism by which denosumab inhibits GCTB neoplastic stromal cells growth is via p62 modulation and other related mechanisms. p62 expression before and after denosumab therapy was analysed by RT‒qPCR, western blot, ELISA, and immunohistochemical assays. Two primary neoplastic stromal cells were isolated from fresh GCTB tumour tissue (L cell) and metastatic tissue (M cell). Cell proliferation, migration, apoptosis, and autophagy were investigated in p62 knockdown neoplastic stromal cells transfected by short hairpin RNA lentivirus in vitro. Tumor growth was evaluated in the chick chorioallantoic membrane model in vivo. p62 expression was found to be downregulated following denosumab therapy. The patients with a decrease in p62 expression had lower recurrence-free survival rates. The proliferation of M cells was not inhibited by denosumab therapy, but it was restored by p62 knockdown. Moreover, p62 knockdown inhibited tumour growth in vivo. Denosumab induced M cell apoptosis and arrested the cell cycle at the G1/G0 transition and these effects were also enhanced by p62 knockdown. Autophagic flux assays revealed p62 modulation to be dependent on autophagy following denosumab incubation. Denosumab induced neoplastic stromal cells apoptosis via p62 downregulation dependent on autophagy pathway. The combination of p62 and RANKL knockdown might be a better strategy than RANKL knockdown alone for GCTB targeted therapy.

The Role of Vasodilator-stimulated Phosphoproteins in the Development of Malignant Tumors.

Vasodilator-stimulated phosphoprotein (VASP) is an actin-binding protein that includes three structural domains: Enabled/VASP homolog1 (EVH1), EVH2, and proline-rich (PRR). VASP plays an important role in various cellular behaviors related to cytoskeletal regulation. More importantly, VASP plays a key role in the progression of several malignant tumors and is associated with malignant cell proliferation, invasion, and metastasis. Here, we have summarized current studies on the impact of VASP on the development of several malignant tumors and their mechanisms. This study provides a new theoretical basis for clinical molecular diagnosis and molecular targeted therapy.

Recent Patents on Rolling Bearing Lubrication Device

Background: Rolling bearings are the core components of mechanical equipment. Lubrication plays an important role in the operating performance of rolling bearings. The research on rolling bearing lubrication devices is beneficial to making the bearings obtain the characteristics which is suitable for the working conditions and improving the bearing's service life. Compared with the traditional lubrication devices, the new ones provide assistance to various bearings, solving many problems. Objective: To review the latest research on rolling bearing lubrication devices, analyze their solutions to rolling bearing lubrication problems, and discuss their advantages and disadvantages for the reference of scholars and engineers. Methods: The representative patents related to rolling bearing lubrication devices are reviewed according to the lubrication method of bearings, including oil lubrication, grease lubrication and solid lubrication. Oil lubrication includes oil mist lubrication, oil-air lubrication, jet lubrication, under ring lubrication and immersion oil lubrication, etc. Grease lubrication includes external and internal lubrication methods. The working principle and characteristics are explained by analyzing the structure of bearing lubrication devices. Results: By comparing different types of rolling bearing lubrication devices, the main problems of the current lubrication devices are summarized and analyzed. The future development of rolling bearing lubrication devices are prospected. Conclusion: The improvement of rolling bearing lubrication devices is conducive to developing bearing lubrication technology. Advanced mechanical equipments require the rolling bearing lubrication devices to have a simple structure, intelligence, and are easy to be installed.

Biological Potential and Therapeutic Effectiveness of Hinokiflavone in Medicine: The Effective Components of Herbal Medicines for Treatment of Cancers and Associated Complications

Background: Plants have been providing us medicines and food material for centuries. Traditional system of medicine, including Ayurveda, and Traditional Chinese medicines have been playing important role in health sectors for the treatment of human disorders since very early age. Plant secondary metabolites, including flavonoids, coumarins, saponins, and tannins have significant therapeutic potential in medicine. Biflavonoids are dimers of flavonoids, linked by a C–O–C or C–C bond. Hinokiflavone is an important class of biflavonoids found to be present in Toxicodendron succedaneum, Isophysis tasmanica, Juniperus rigida, Juniperus phoenicea, Platycladi cacumen, Rhus succedanea, Selaginella tamariscina, Platycladus orientalis, Selaginella bryopteris, and Metasequoia glyptostroboides. Methods: Biological potential of hinokiflavone in medicine have been analyzed in the present work through scientific data analysis of various literature work. Scientific database, including Google, Scopus, Science Direct, and PubMed were searched to collect all the scientific information of the present work using terms flavonoid, biflavonoid, herbal medicine, and hinokiflavone. Pharmacological activities of hinokiflavone were analyzed in the present work in very detailed manner. Analytical data of hinokiflavone were collected and analyzed in present work in order to know the biological source of hinokiflavone. Results: Present work signified the biological importance of hinokiflavone against various types of cancerous disorders, including breast cancer, colorectal cancer, esophageal squamous cancer, adenocarcinoma, hepatocellular carcinoma, myeloid leukemia, and melanoma. Further, its antiinflammatory, hepatoprotective, anti-viral, and anti-oxidant potential were also discussed in the present work. Moreover, its biological potential against COVID-19 and hair loss, and procoagulant activity were also summarized in this paper. Analytical data on hinokiflavone signified the importance of various analytical techniques in the extraction, separation, and identification of hinokiflavone with their pharmacokinetic parameters. Conclusion: Present work signified the biological importance and therapeutic potential of hinokiflavone in medicine.

A two-field formulation for surfactant transport within the algebraic volume of fluid method

Surfactant transport plays an important role in many technical processes and industrial applications such as chemical reactors, microfluidics, printing and coating technology. High fidelity numerical simulations of two-phase flow phenomena reveal rich insights into the flow dynamics, heat, mass and species transport. In the present study, a two-field formulation for surfactant transport within the algebraic volume of fluid method is presented. The slight diffuse nature of representing the interface in the algebraic volume of fluid method is utilized to track the concentration of surfactant at the interface as a volumetric concentration. Transport of insoluble and soluble surfactants is investigated by tracking two different concentrations of the surfactant, one within the bulk of the liquid and the other one at the interface. These two transport equations are in turn coupled by source terms considering the ad-/desorption processes at a liquid-gas interface. Appropriate boundary conditions at a solid-fluid interface are formulated to ensure surfactant conservation, while also enabling to study the ad-/desorption processes at a solid-fluid interface. The developed numerical method is verified by comparing the numerical simulations with well-known analytical and numerical reference solutions and applied to a surfactant-laden drop in shear flow. The presented numerical methodology offers a seamless integration of surfactant transport into the algebraic volume of fluid method, where the latter has many advantages such as volume conservation and an inherent ability of handling large interface deformations and topological changes.

Implementation of a non-linear SVM classification for seizure EEG signal analysis on FPGA

An automatic detection method for disease diagnosis plays an important role in the medical field. A computer-aided diagnosis (CAD) system for seizure detection using electroencephalogram (EEG) data is significant in protecting patients' lives. This paper presents machine learning algorithm-based seizure detection approach implemented in both software and hardware using EEG recordings. The input EEG signal is subjected to pre-processing, decomposition using wavelet transform and classification by a support vector machine (SVM) classifier. The maximum and variance statistical values of the decomposed EEG sub-bands are computed to generate a feature vector, while classification accuracy and computational complexity are taken into account. Gaussian Radial Basis Function (RBF) kernel based Non-Linear SVM (NLSVM) is used in this proposed approach to solve both two-class and three-class classification problems. In three-class classification, the one-against-one (OAO) technique is used. The competency of the proposed technique is evaluated using two distinct datasets provided by Bonn University, Germany & Neurology and Sleep Centre, New Delhi. The adequate parameters of the NLSVM classifier model are determined by using MATLAB software in the training phase and the best performing NLSVM model is selected for implementation on the Field-Programmable Gate Array (FPGA). The proposed seizure detection method is implemented with Verilog code and examined on a Xilinx Zynq-7000 XC7Z020 FPGA board to evaluate its performance. The experimental results show that the proposed method with a minimal number of features achieved a good performance metric for seizure detection and is comparable with that of the state-of-the-art methods.

Omega Invariant of Complement Graphs and Nordhaus-Gaddum Type Results.

The study aimed to obtain relationships between the omega invariants of a graph and its complement. We used some graph parameters, including the cyclomatic numbers, number of components, maximum number of components, order, and size of both graphs G and G. Also, we used triangular numbers to obtain our results related to the cyclomatic numbers and omega invariants of G and G. Several bounds for the above graph parameters have been obtained by the direct application of the omega invariant. We used combinatorial and graph theoretical methods to study formulae, relations, and bounds on the omega invariant, the number of faces, and the number of compo-nents of all realizations of a given degree sequence. Especially so-called Nordhaus-Gaddum type resulted in our calculations. In these calculations, the triangular numbers less than a given number play an important role. Quadratic equations and inequalities are intensively used. Several relations between the size and order of the graph have been utilized in this study. In this paper, we have obtained relationships between the omega invariants of a graph and its complement in terms of several graph parameters, such as the cyclomatic numbers, number of components, maximum number of components, order, and size of G and G, and triangular numbers. Some relationships between the omega invariants of a graph and its complement have been obtained.

IL1R2 is a Novel Prognostic Biomarker for Lung Adenocarcinoma.

The aim of this study is to figure out the role of IL1R2 in LUAD (lung adenocarcinoma). IL1R2, a special member of IL-1 receptor family, binds to IL-1 and plays an important role in inhibiting IL-1 pathway, which seems to be involved in tumorigenesis. Emerging studies demonstrated higher IL1R2 expression levels in several malignancies. In the present study, we assessed the expression of IL1R2 in LUAD tissues with immunohistochemistry and explored various databases to determine whether it could be a potential prognostic biomarker and therapeutic target. The expression level of IL1R2 in lung adenocarcinoma was analyzed by Immunohistochemistry and UALCAN database. The correlation between IL1R2 expression and the patient prognosis was identified by Kaplan-Meier plotter. The correlation of IL1R2 expression with immune infiltrates was clarified by TIMER database. The protein-protein interaction network and gene functional enrichment analysis were constructed and performed by STRING and Metascape database. Immunohistochemistry showed that the expression of IL1R2 was higher in tumor tissues of LUAD patients and that patients with lower IL1R2 level have a better prognosis than their counterparts. We validated our findings in several online databases and found that IL1R2 gene was also positively correlated with B cells and neutrophils and biomarkers of CD8+ T cells and exhausted T cells. PPI network and gene enrichment analyses showed that expression of IL1R2 was also associated with complex functionspecific networks involving IL-1 signal, NF-KappaB transcription factors. According to these findings, we demonstrated that IL1R2 was involved in the progression and prognosis of LUAD and the underlying mechanism needs further investigation.

DOCK4 is a novel prognostic biomarker and correlated with immune infiltrates in colon adenocarcinoma.

Dedicator for cytokinesis 4 (DOCK4) is a guanine nucleotide exchange factor (GEF) for the small GTPase Rac1. However, the functions of DOCK4 concerning the tumor microenvironment (TME) in colon adenocarcinoma (COAD) remain uncertain. The TIMER and GEPIA databases were used to analyze the DOCK4 expression between COAD tissues and adjunct normal tissues. The PrognoScan database was used to assess the prognosis of DOCK4 expression in COAD. The co-expression networks of DOCK4 in COAD were constructed by the LinkedOmics website. Furthermore, the correlation between DOCK4 expression and TME of COAD was explored using TIMER and TISIDB databases. Finally, the clone formation assay was used to further verify the function of DOCK4 in COAD. The Western blotting assay was used to confirm the mechanism related to DOCK4 in COAD. The DOCK4 expression was different significantly in COAD tissues and paracancerous tissues. The DOCK4 was found to play a poor role in the prognosis of patients with COAD. The DOCK4 was found to participate in the TME by promoting immune evasion of COAD. The reduction of DOCK4 expression inhibited the clone formation and Ras-associated protein 1A (Rap1A) expression of HCT116 cells. DOCK4 potentially plays an important role in the regulation of TME in COAD. DOCK4 facilitates the development through the Rap1A pathway, thus becoming a novel prognostic biomarker in COAD.

Role of MicroRNA in Hypoxic Tumours and their Potential as Biomarkers for Early Detection of Cancer.

Hypoxia is a pathophysiological condition characterized by oxygen deficiency in tissues, which negatively affects normal biological functions. It is a typical microenvironment character of almost all solid tumours. Noncoding RNA are small functional RNA molecules that regulate gene expression at chromatin and posttranscriptional levels. Micro-RNAs (miRNAs) are a type of noncoding RNA and are ~12-22 nucleotides long that are crucial in regulating gene expression by partnering with the mRNAs of protein-coding genes. It is widely reported that miRs play an important role in various key processes and pathways during tumour formation, as well as advancement in hypoxic tumors by influencing the HIF pathway. The role of miRNAs in hypoxic tumours, namely in pancreatic, kidney, breast, lung and colorectal, are described. These miRNAs have immense potential as diagnostic and prognostic biomarkers for early cancer detection.

The FJQR Has Synergistic Effect with Fluoropyrimidine in the Maintenance Treatment for HER-2 Negative Gastric Cancer.

Maintenance therapy aimed to strengthen the first-line chemotherapy and improve quality of life is needed for gastric cancer (GC). Currently, many clinical studies have confirmed the important role of fluoropyrimidine in the maintenance stage. Our team has created patented prescriptions "Fuzheng jiedu Quyu Method" recipe (FJQR), which was considered as an adjuvant therapeutic scheme (reduce toxicity and increase the efficacy of chemotherapy). This study aimed to evaluate the efficacy and safety of FJQR combined with fluoropyrimidine as a maintenance treatment in HER-2 negative GC patients. We performed the analysis of 129 patients with HER-2 negative GC who entered the maintenance stage in our hospital and Tianjin Cancer Hospital between January 2018 and December 2020. Out of the 129 eligible patients, 64 were categorized into the maintenance treatment group with FJQR+fluoropyrimidine, and 65 patients were assigned to the control group if they received fluoropyrimidine alone. Capecitabine was orally 1000mg/m2, Qd, half an hour after meals, and FGQR was 15g Bid after capecitabine. The primary endpoint was progression-free survival (PFS). The secondary endpoints were overall survival (OS), overall remission rate (ORR), quality of Life (QOL), TCM syndrome and safety. The mPFS in the treatment group was significantly prolonged compared with the control group (6.3 vs. 5.0 months, p = 0.03), while the mOS was not substantially improved (11.4 vs. 10.5 months, p = 0.38). Gastrointestinal symptoms and pain became better in the treatment group. The number of distant metastatic organs, first-line chemotherapy cycles, and lymph node metastasis were independent risk predictors for PFS. Blood stasis syndrome may be the protective factor. In terms of safety, treatment-related adverse events (AEs) in the treatment group were relatively lighter, and the incidence of grade III-IV AEs could be significantly reduced. FJQR and fluoropyrimidine have synergistic effects as maintenance treatment in HER-2 negative GC, with good efficacy and safety.

Assessment of the Decadal Prediction Skill of Sahel Rainfall in CMIP5 and CMIP6

Abstract Accurately predicting the decadal variations in Sahel rainfall has important implications for the lives and economy in the Sahel. Previous studies found that the decadal variations in sea surface temperature (SST) in the Atlantic, Mediterranean Sea, Indian Ocean, and Pacific contribute to those in Sahel rainfall. This study evaluates the decadal prediction skills of Sahel rainfall from all the available hindcasts contributing to phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6), in comparison with the related uninitialized simulations. A majority of the prediction systems show high skill with regard to Sahel rainfall. The high skill may be partly attributed to external forcings, which are reflected in good performance of the respective uninitialized simulations. The decadal prediction skills of the key SST drivers and their relationships with the Sahel rainfall are also assessed. Both the hindcasts and the uninitialized simulations generally present high skill for the Atlantic multidecadal variability (AMV) and Mediterranean Sea SST indices and low skill for the Indian Ocean basin mode (IOBM) and interdecadal Pacific variability (IPV) indices. The relationship between the Sahel rainfall and the AMV or Mediterranean Sea SST index is reasonably captured by most prediction systems and their uninitialized simulations, while that between the Sahel rainfall and the IOBM or IPV index is captured by only a few systems and their uninitialized simulations. The high skill of the AMV and Mediterranean Sea SST indices as well as the reasonable representations of their relationships with the Sahel rainfall by both the hindcasts and uninitialized simulations probably plays an important role in predicting the Sahel rainfall successfully. Significance Statement Predicting Sahel rainfall on the decadal time scale is of great importance. This study provides a thorough evaluation of the decadal prediction skills of Sahel rainfall in the current decadal prediction systems participating in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). A majority of the systems achieve high prediction skill of Sahel rainfall, which probably results from the high prediction skill of some key sea surface temperature (SST) drivers, especially in the Atlantic and Mediterranean Sea SST, and their relationships with Sahel rainfall. This study provides a reference for better understanding the predictability of Sahel rainfall.

Free-Water Imaging of the Nucleus Basalis of Meynert in Patients With Idiopathic REM Sleep Behavior Disorder and Parkinson Disease.

Cognitive impairments are common in idiopathic REM sleep behavior disorder (iRBD), in which the cholinergic degeneration of nucleus basalis of Meynert (NBM) may play an important role. However, the progressive changes of NBM, the relationship between progressive NBM degeneration and progression of cognitive impairments, and whether degeneration of the NBM can predict cognitive decline in patients with iRBD remain unclear. This study aimed to investigate the cross-sectional and longitudinal microstructural alterations in the NBM of patients with iRBD using free-water imaging and whether free water in the NBM is related to cognitive, mood, and autonomic function. We compared the baseline free-water values in the NBM between 59 healthy controls (HCs), 57 patients with iRBD, 57 patients with Parkinson disease (PD) with normal cognition (PD-NC), and 64 patients with PD with cognitive impairment (PD-CI). Thirty patients with iRBD and 40 HCs had one longitudinal data. In patients with iRBD, we explored the associations between baseline and longitudinal changes of free-water values in the NBM and clinical characteristics and whether baseline free-water values in the NBM could predict cognitive decline. IRBD, PD-NC, and PD-CI groups had significantly increased free-water values in the NBM compared with HCs, whereas PD-CI had higher free-water values compared with iRBD and PD-NC. In patients with iRBD, free-water values in the NBM were progressively elevated over follow-up and correlated with the progression of cognitive impairment and depression. Free-water values in the NBM could predict cognitive decline in the iRBD group. Furthermore, we found that patients with iRBD with cognitive impairment had higher relative change of free-water value in the NBM compared with patients with iRBD with normal cognition over follow-up. This study proves that free-water values in the NBM are elevated cross-sectionally and longitudinally and are associated with the progression of cognitive impairment and depression in patients with iRBD. Moreover, the free-water value in the NBM can predict cognitive decline in patients with iRBD. Whether free-water imaging of the NBM has the potential to be a marker for monitoring progressive cognitive impairment and predicting the conversion to dementia in synucleinopathies needs further investigation.

Association of Neurotrophic Factors at Midlife With In Vivo Measures of β-Amyloid and Tau Burden 15 Years Later in Dementia-Free Adults.

Neurotrophic factors (NTFs) play an important role in Alzheimer disease (AD) pathophysiology. Brain-derived neurotrophic factor (BDNF) and vascular endothelial growth factor (VEGF) are important NTFs. However, a direct link of BDNF and VEGF circulating levels with in vivo measures of amyloid-β (Aβ) and tau burden remains to be elucidated. We explored the relationship of BDNF and VEGF serum levels with future brain Aβ and tau pathology in a cohort of cognitively healthy, predominantly middle-aged adults and tested for possible effect modifications by sex and menopausal status. This cross-sectional analysis was conducted using data from the Framingham Heart Study (FHS), a community-based cohort study. The study sample included cognitively healthy participants from the FHS Offspring and Third-generation cohorts. BDNF and VEGF were measured in the third-generation cohort during examination cycles 2 (2005-2008) and 1 (2002-2005), respectively, and in the offspring cohort during examination cycle 7 (1998-2001). Participants underwent 11C-Pittsburgh compound B amyloid and 18F-Flortaucipir tau-PET imaging (2015-2021). Linear regression models were used to assess the relationship of serum BDNF and VEGF levels with regional tau and global Aβ, adjusting for potential confounders. Interactions with sex and menopausal status were additionally tested. The sample included 414 individuals (mean age = 41 ± 9 years; 51% female). Continuous measures of BDNF and VEGF were associated with tau signal in the rhinal region after adjustment for potential confounders (β = -0.15 ± 0.06, p = 0.018 and β = -0.19 ± 0.09, p = 0.043, respectively). High BDNF (≥32,450 pg/mL) and VEGF (≥488 pg/mL) levels were significantly related to lower rhinal tau (β = -0.27 ± 0.11, p = 0.016 and β = -0.40 ± 0.14, p = 0.004, respectively) and inferior temporal tau (β = -0.24 ± 0.11, p = 0.028 and β = -0.26 ± 0.13, p = 0.049, respectively). The BDNF-rhinal tau association was observed only among male individuals. Overall, BDNF and VEGF were not associated with global amyloid; however, high VEGF levels were associated with lower amyloid burden in postmenopausal women (β = -1.96 ± 0.70, p = 0.013, per 1 pg/mL). This study demonstrates a robust association between BDNF and VEGF serum levels with in vivo measures of tau almost 2 decades later. These findings add to mounting evidence from preclinical studies suggesting a role of NTFs as valuable blood biomarkers for AD risk prediction.

Relationship between the Uncertainty of Empirical Orthogonal Function (EOF) Modes and Sampling Sizes in Climate Models

Abstract This study investigates the relationship between the uncertainty of empirical orthogonal function (EOF) modes and sampling size in climate models, using simulated results of preindustrial control (piControl) experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6), and taking the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) as examples. The results indicate that this relationship can be quantified by a concise fitting function [i.e., y = a/(x − b)]. Here, y is the 5%–95% confidence interval of congruence coefficient, x is the sampling size, and a and b are two parameters depending on models or observations. As compared with b, which modulates the sampling size in the fitting function, the parameter a scales the sampling size and thus plays a much more important role. Further analysis indicates that the parameter a, or the uncertainty of EOF1 mode, decreases dramatically with the increase of the difference between variance fractions of EOF1 and EOF2 modes, approximately in the form of a power function. The minimum sampling size to ensure a reliable EOF mode can also be estimated by the fitting function and shows a great diversity among models both for the NAO and ENSO. The diversity suggests the importance of estimating the minimum sampling size before model evaluations on climate variability modes and projections on the future change in modes, particularly when the EOF2 mode explains the variance close to EOF1 mode. Significance Statement Empirical orthogonal function (EOF) analysis, principal component analysis, or eigenvector analysis has been widely used in various research fields. However, it remains as an open question as to how large the sampling size is required to be to obtain reliable modes through the EOF method. In this study, we investigate the relationship between the uncertainty of EOF results and sampling size in current climate models, using adequately long simulated data, and we find that this relationship can be depicted by the fitting function y = a/(x − b). Here, y represents the uncertainty, x is the sampling size, and a and b are parameters. The parameter a is closely related to the difference between variance fractions of first and second EOF modes and plays a more important role in the fitting function. The minimum sampling sizes that are required to obtain reliable EOF modes can also be estimated by the fitting function and vary greatly from model to model. The results provide a basis for judging the reliability of EOF modes, particularly when the first and second EOF modes explain similar variance fractions.

Recognition of music symbol notation using convolutional neural network

Musical notation is one thing that needs to be learned to play music. This notation has an important role in music because it can help in visualizing instructions for playing musical instruments and singing. Unfortunately, musical symbols that are commonly written in musical notation are difficult for beginners who have just started learning music. This research proposed a solution to create an optical music recognition (OMR) using a deep learning model to classify musical notes more accurately with some of the latest convolutional neural network (CNN) architectures. The research was carried out by implementing vision transformer (ViT), CoAtNet-0, and ConvNeXt-Tiny architecture. The training process was also combined with data augmentation to provide more information for the model to learn. Then the accuracy results of each model were compared to find out the best model for the OMR solution in this research. This experiment uses the Andrea dataset and Attwenger dataset which both get the best result by using the augmentation method and ConvNeXt-Tiny as the model. The best accuracy for the Andrea dataset is 98.15% and for the Attwenger dataset is 98.43%.