Leveraging ANFIS with Adam and PSO optimizers for Parkinson's disease.

Parkinson's disease (PD) is an age-related neurodegenerative disorder characterized by motor deficits, including tremor, rigidity, bradykinesia, and postural instability. According to the World Health Organization, about 1 % of the global population has been diagnosed with PD, and this figure is expected to double by 2040. Early and accurate diagnosis of PD is critical to slowing down the progression of the disease and reducing long-term disability. Due to the complexity of the disease, it is difficult to accurately diagnose it using traditional clinical tests. Therefore, it has become necessary to develop intelligent diagnostic models that can accurately detect PD. This article introduces a novel hybrid approach for accurate prediction of PD using an ANFIS with two optimizers, namely Adam and PSO. ANFIS is a type of fuzzy logic system used for nonlinear function approximation and classification, while Adam optimizer has the ability to adaptively adjust the learning rate of each individual parameter in an ANFIS at each training step, which helps the model find a better solution more quickly. PSO is a metaheuristic approach inspired by the behavior of social animals such as birds. Combining these two methods has potential to provide improved accuracy and robustness in PD diagnosis compared to existing methods. The proposed method utilized the advantages of both optimization techniques and applied them on the developed ANFIS model to maximize its prediction accuracy. This system was developed by using an open access clinical and demographic data. The chosen parameters for the ANFIS were selected through a comparative experimental analysis to optimize the model considering the number of fuzzy membership functions, number of epochs of ANFIS, and number of particles of PSO. The performance of the two ANFIS models: ANFIS (Adam) and ANFIS (PSO) focusing at ANFIS parameters and various evaluation metrics are further analyzed in detail and presented, The experimental results showed that the proposed ANFIS (PSO) shows better results in terms of loss and precision, whereas, the ANFIS (Adam) showed the better results in terms of accuracy, f1-score and recall. Thus, this adaptive neural-fuzzy algorithm provides a promising strategy for the diagnosis of PD, and show that the proposed models show their suitability for many other practical applications.

[Study on mechanism of inhibiting proliferation of head and neck cancer cells by citral, active ingredient of lemon essential oil].

To explore the active substances exerting anti-tumour effect in lemon essential oil and the molecular mechanism inhibiting the proliferation of head and neck cancer cells SCC15 and CAL33, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay(MTT) was utilized to identify the active component inhibiting the proliferation of head and neck cancer cells, namely citral. The IC_(50) of citral inhibiting the proliferation of head and neck cancer cells and normal cells were also determined. In addition, a 5-ethynyl-2'-deoxyuridine(EdU) staining assay was used to detect the effect of citral on the proliferation rate of head and neck cancer cells, and a colony formation assay was used to detect the effect of citral on tumor sphere formation of head and neck cancer cells in vitro. The cell cycle arrest and apoptosis induction of head and neck cancer cells by citral were evaluated by flow cytometry, and Western blot was used to detect the effect of citral on the expression levels of cell cycle-and apoptosis-related proteins in head and neck cancer cells. The findings indicated that citral could effectively inhibit the proliferation and growth of head and neck cancer cells, with anti-tumor activity, and its half inhibitory concentrations for CAL33 and SCC15 were 54.78 and 25.23 µg·mL~(-1), respectively. Furthermore, citral arrested cell cycle at G_2/M phase by down-regulating cell cycle-related proteins such as S-phase kinase associated protein 2(SKP2), C-MYC, cyclin dependent kinase 1(CDK1), and cyclin B. Moreover, citral increased the cysteinyl aspartate-specific proteinase-3(caspase-3), cysteinyl aspartate-specific proteinase-9(caspase-9), and cleaved poly ADP-ribose polymerase(PARP). It up-regulated the level of autophagy-related proteins including microtubule associated protein 1 light chain 3B(LC3B), sequestosome 1(P62/SQSTM1), autophagy effector protein Beclin1(Beclin1), and lysosome-associate membrane protein 1(LAMP1), suggesting that citral could effectively trigger cell apoptosis and cell autophagy in head and neck cancer cells. Furthermore, the dual-tagged plasmid system mCherry-GFP-LC3 was used, and it was found that citral impeded the fusion of autophagosomes and lysosomes, leading to autophagic flux blockage. Collectively, our findings reveal that the main active anti-proliferation component of lemon essential oil is citral, and this component has a significant inhibitory effect on head and neck cancer cells. Its underlying molecular mechanism is that citral induces apoptosis and autophagy by cell cycle arrest and ultimately inhibits cell proliferation.

Risk factors, impact and treatment of postoperative lymphatic leakage in children with abdominal neuroblastoma operated on by laparotomy.

BACKGROUND: Lymphatic leakage is one of the postoperative complications of neuroblastoma. The purpose of this study is to summarize the clinical characteristics and risk factors of lymphatic leakage and try to find effective prevention and treatment measures. METHODS: A retrospective study included 186 children with abdominal neuroblastoma, including 32 children of lymphatic leakage and 154 children of non-lymphatic leakage. The clinical information, surgical data, postoperative abdominal drainage, treatment of lymphatic leakage and prognosis of the two groups were collected and analyzed. RESULTS: The incidence of lymphatic leakage in this cohort was 14% (32 children). Through univariate analysis of lymphatic leakage group and non-lymphatic leakage group, we found that lymphatic leakage increased the complications, prolonged the time of abdominal drainage and hospitalization, and delayed postoperative chemotherapy (p < 0.05). In this cohort, the median follow-up time was 46 (95% CI: 44-48) months. The follow-up data of 7 children were partially missing. 147 children survived, of which 23 had tumor recurrence (5 children recurred in the surgical area). 37 children died, of which 32 had tumor recurrence (9 children recurred in the operation area). In univariate analysis, there was no statistical difference in overall survival (p = 0.21) and event-free survival (p = 0.057) between lymphatic leakage group and non-lymphatic leakage group, while 3-year cumulative incidence of local progression was higher in lymphatic leakage group (p = 0.015). However, through multivariate analysis, we found that lymphatic leakage did not affect event-free survival, overall survival and cumulative incidence of local progression in children with neuroblastoma. Resection of 5 or more lymphatic regions was an independent risk factor for lymphatic leakage after neuroblastoma surgery. All 32 children with lymphatic leakage were cured by conservative treatment without surgery. Of these, 75% (24/32) children were cured by fat-free diet or observation, 25% (8/32) children were cured by total parenteral nutrition. The median drain output at diagnosis in total parenteral nutrition group was higher than that in non-total parenteral nutrition group (p < 0.001). The cut-off value was 17.2 ml/kg/day. CONCLUSIONS: Lymphatic leakage does not affect the prognosis of children with neuroblastoma, but long-term drain output caused by lymphatic leakage will still adversely affect postoperative complications and follow-up treatment, which requires attention and active treatment measures. More attention should be paid to the children with 5 or more lymphatic regions resection, and the injured lymphatic vessels should be actively found and ligated after tumor resection to reduce the postoperative lymphatic leakage. Early application of total parenteral nutrition is recommended for those who have drain output at diagnosis of greater than 17.2 ml/kg/day. LEVEL OF EVIDENCE: Level III, Treatment study (Retrospective comparative study).

Extracellular cold-inducible RNA-binding protein mediated neuroinflammation and neuronal apoptosis after traumatic brain injury.

Background: Extracellular cold-inducible RNA-binding protein (eCIRP) plays a vital role in the inflammatory response during cerebral ischaemia. However, the potential role and regulatory mechanism of eCIRP in traumatic brain injury (TBI) remain unclear. Here, we explored the effect of eCIRP on the development of TBI using a neural-specific CIRP knockout (KO) mouse model to determine the contribution of eCIRP to TBI-induced neuronal injury and to discover novel therapeutic targets for TBI. Methods: TBI animal models were generated in mice using the fluid percussion injury method. Microglia or neuron lines were subjected to different drug interventions. Histological and functional changes were observed by immunofluorescence and neurobehavioural testing. Apoptosis was examined by a TdT-mediated dUTP nick end labelling assay in vivo or by an annexin-V assay in vitro. Ultrastructural alterations in the cells were examined via electron microscopy. Tissue acetylation alterations were identified by non-labelled quantitative acetylation via proteomics. Protein or mRNA expression in cells and tissues was determined by western blot analysis or real-time quantitative polymerase chain reaction. The levels of inflammatory cytokines and mediators in the serum and supernatants were measured via enzyme-linked immunoassay. Results: There were closely positive correlations between eCIRP and inflammatory mediators, and between eCIRP and TBI markers in human and mouse serum. Neural-specific eCIRP KO decreased hemispheric volume loss and neuronal apoptosis and alleviated glial cell activation and neurological function damage after TBI. In contrast, eCIRP treatment resulted in endoplasmic reticulum disruption and ER stress (ERS)-related death of neurons and enhanced inflammatory mediators by glial cells. Mechanistically, we noted that eCIRP-induced neural apoptosis was associated with the activation of the protein kinase RNA-like ER kinase-activating transcription factor 4 (ATF4)-C/EBP homologous protein signalling pathway, and that eCIRP-induced microglial inflammation was associated with histone H3 acetylation and the α7 nicotinic acetylcholine receptor. Conclusions: These results suggest that TBI obviously enhances the secretion of eCIRP, thereby resulting in neural damage and inflammation in TBI. eCIRP may be a biomarker of TBI that can mediate the apoptosis of neuronal cells through the ERS apoptotic pathway and regulate the inflammatory response of microglia via histone modification.

Comparison of the Global Leadership Initiative on Malnutrition and the Patient-Generated Subjective Global Assessment for diagnosing malnutrition in patients undergoing surgery for hepatobiliary and pancreatic malignancies.

OBJECTIVE: to analyse the differences in malnutrition assessment between the Global Leadership Initiative on Malnutrition (GLIM) criteria and the Patient-Generated Subjective Global Assessment (PG-SGA) among patients with hepatobiliary and pancreatic malignancies. METHOD: this study was a cross-sectional study and included 126 hospitalised patients who underwent surgery for hepatobiliary and pancreatic malignancies between November 1, 2019 and August 1, 2020. The patients' clinical data were collected, and malnutrition assessments were completed using the different nutritional assessment tools. The consistency of both tools was analysed using Cohen's kappa coefficient. RESULTS: the prevalence of malnutrition showed a difference in diagnosis results between the GLIM criteria (36.51 %) and the PG-SGA (55.56 %). The two methods had moderate consistency (kappa = 0.590, p < 0.01). The sensitivity of a malnutrition diagnosis using a combination of GLIM and PG-SGA was 65.7 % (53.3 % and 76.4 %, respectively), and specificity was 100 % (92 % and 100 %, respectively). When malnutrition was evaluated using only PG-SGA, sensitivity was 88.9 % (95 % confidence interval (CI) 63.9 % to 98.1 %), whereas when only the GLIM score was used for malnutrition evaluation, sensitivity was 98.2 % (95 % CI, 92.8 % to 99.7 %). In addition, the PG-SGA score and the GLIM score had significant correlations. CONCLUSION: GLIM performed better than PG-SGA in the correlation analysis of nutritional indicators. GLIM is more suitable for patients with hepatobiliary and pancreatic malignancies than PG-SGA.

Total Synthesis of (±)-Simonsol C.

Total synthesis of simonsol C has been achieved, focusing on the postdearomatization transformations. Our methodology integrates an efficient combination of dearomatization and Zn/AcOH reduction to introduce an allyl group, followed by oxo-Michael addition, to construct the 6/5/6 benzofuran skeleton. It offers a novel method for synthesizing allyl-containing quaternary carbon atoms in a straightforward manner.

A Primary Report 166 Cases of Abdominal or Pelvic Neuroblastoma Surgery Utilizing the International Neuroblastoma Surgical Report Form (INSRF).

BACKGROUND AND AIMS: Surgery is pivotal in the management of neuroblastoma (NB), particularly in patients with Image-Defined Risk Factors (IDRFs). The International Neuroblastoma Surgical Report Form (INSRF) was introduced to enhance surgical reporting quality and analyze the defining role of extensive surgery in NB. This study reports our experience with INSRF and explores new criteria for evaluating the extent of surgical resection. METHODS: INSRF was deployed to critically analyze 166 patients with abdominal or pelvic NB who underwent surgery at our department between October 2021 and June 2023. Patient demographics, clinical characteristics, surgical datasets, and postoperative complications were described in detail. Receiver operating characteristic (ROC) curves were used to explore a new method to evaluate the extent of resection. A questionnaire was formulated to obtain attitudes/feedback and commentary from surgical oncologists with INSRF. RESULTS: 166 neuroblastoma patients with a median disease age 36.50 months. This study collated 320 INSRF reports. Among the 166 index cases, 137 were documented by two surgeons, with a concordance rate of 16.78%. Items with high inconsistency were (i) the extent of tumor resection (29.20%), (ii) renal vein involvement (25.55%), (iii) abdominal aorta encasement (16.79%), and (iv) mesenteric infiltration (17.52%). According to INSRF, the extent of resection was complete excision in 86 (51.81%) patients, minimal residual tumor < 5 cm3 in 67 (40.36%) patients, and incomplete excision > 5 cm3 in 13 (7.83%) patients. In ROC curve analysis, the number of vessels encased by tumors > 3 had a high predictive value in determining that a tumor could not be completely resected (AUC 0.916, sensitivity 0.838, specificity 0.826) using INSRF as the gold standard reference. The questionnaires showed that surgeons agreed that the extent of resection and tumor involvement of organ/vascular structures were important, while the definition and intervention(s) of intraoperative complications were less operational and understandable. CONCLUSIONS: INSRF has significant clinical application in neuroblastoma surgery. The extent of resection can be predicted based on the number of tumor-encased blood vessels. Supplementary information should be considered with the INSRF to aid practitioner reporting. Multicenter studies are needed to explore the defining role of INSRF in NB surgical management.

Weighted Bayesian Belief Network for diabetics: a predictive model.

Diabetes is an enduring metabolic condition identified by heightened blood sugar levels stemming from insufficient production of insulin or ineffective utilization of insulin within the body. India is commonly labeled as the "diabetes capital of the world" owing to the widespread prevalence of this condition. To the best of the authors' last knowledge updated on September 2021, approximately 77 million adults in India were reported to be affected by diabetes, reported by the International Diabetes Federation. Owing to the concealed early symptoms, numerous diabetic patients go undiagnosed, leading to delayed treatment. While Computational Intelligence approaches have been utilized to improve the prediction rate, a significant portion of these methods lacks interpretability, primarily due to their inherent black box nature. Rule extraction is frequently utilized to elucidate the opaque nature inherent in machine learning algorithms. Moreover, to resolve the black box nature, a method for extracting strong rules based on Weighted Bayesian Association Rule Mining is used so that the extracted rules to diagnose any disease such as diabetes can be very transparent and easily analyzed by the clinical experts, enhancing the interpretability. The WBBN model is constructed utilizing the UCI machine learning repository, demonstrating a performance accuracy of 95.8%.

BT-CNN: a balanced binary tree architecture for classification of brain tumour using MRI imaging.

Deep learning is a very important technique in clinical diagnosis and therapy in the present world. Convolutional Neural Network (CNN) is a recent development in deep learning that is used in computer vision. Our medical investigation focuses on the identification of brain tumour. To improve the brain tumour classification performance a Balanced binary Tree CNN (BT-CNN) which is framed in a binary tree-like structure is proposed. It has a two distinct modules-the convolution and the depthwise separable convolution group. The usage of convolution group achieves lower time and higher memory, while the opposite is true for the depthwise separable convolution group. This balanced binarty tree inspired CNN balances both the groups to achieve maximum performance in terms of time and space. The proposed model along with state-of-the-art models like CNN-KNN and models proposed by Musallam et al., Saikat et al., and Amin et al. are experimented on public datasets. Before we feed the data into model the images are pre-processed using CLAHE, denoising, cropping, and scaling. The pre-processed dataset is partitioned into training and testing datasets as per 5 fold cross validation. The proposed model is trained and compared its perforarmance with state-of-the-art models like CNN-KNN and models proposed by Musallam et al., Saikat et al., and Amin et al. The proposed model reported average training accuracy of 99.61% compared to other models. The proposed model achieved 96.06% test accuracy where as other models achieved 68.86%, 85.8%, 86.88%, and 90.41% respectively. Further, the proposed model obtained lowest standard deviation on training and test accuracies across all folds, making it invariable to dataset.

Phenotypic comparison and the potential antitumor function of immortalized bone marrow-derived macrophages (iBMDMs).

Introduction: Macrophages are an important component of innate immunity and involved in the immune regulation of multiple diseases. The functional diversity and plasticity make macrophages to exhibit different polarization phenotypes after different stimuli. During tumor progression, the M2-like polarized tumor-associated macrophages (TAMs) promote tumor progression by assisting immune escape, facilitating tumor cell metastasis, and switching tumor angiogenesis. Our previous studies demonstrated that functional remodeling of TAMs through engineered-modifying or gene-editing provides the potential immunotherapy for tumor. However, lack of proliferation capacity and maintained immune memory of infused macrophages restricts the application of macrophage-based therapeutic strategies in the repressive tumor immune microenvironment (TIME). Although J2 retrovirus infection enabled immortalization of bone marrow-derived macrophages (iBMDMs) and facilitated the mechanisms exploration and application, little is known about the phenotypic and functional differences among multi kinds of macrophages. Methods: HE staining was used to detect the biosafety of iBMDMs, and real-time quantitative PCR, immunofluorescence staining, and ELISA were used to detect the polarization response and expression of chemokines in iBMDMs. Flow cytometry, scratch assay, real-time quantitative PCR, and crystal violet staining were used to analyze its phagocytic function, as well as its impact on tumor cell migration, proliferation, and apoptosis. Not only that, the inhibitory effect of iBMDMs on tumor growth was detected through subcutaneous tumor loading, while the tumor tissue was paraffin sectioned and flow cytometry was used to detect its impact on the tumor microenvironment. Results: In this study, we demonstrated iBMDMs exhibited the features of rapid proliferation and long-term survival. We also compared iBMDMs with RAW264.7 cell line and mouse primary BMDMs with in vitro and in vivo experiments, indicating that the iBMDMs could undergo the same polarization response as normal macrophages with no obvious cellular morphology changes after polarization. What's more, iBMDMs owned stronger phagocytosis and pro-apoptosis functions on tumor cells. In addition, M1-polarized iBMDMs could maintain the anti-tumor phenotypes and domesticated the recruited macrophages of receptor mice, which further improved the TIME and repressed tumor growth. Discussion: iBMDMs can serve as a good object for the function and mechanism study of macrophages and the optional source of macrophage immunotherapy.

Melatonin pretreatment improves endometrial regenerative cell-mediated therapeutic effects in experimental colitis.

BACKGROUND: Endometrial regenerative cells (ERCs) have been proven to be an effective strategy for attenuating experimental colitis, but the complex in vivo microenvironment such as oxidative stress may largely limit and weaken ERC efficacy. Melatonin (MT) works as an anti-oxidative agent in a variety of preclinical diseases, and has been identified to promote mesenchymal stem cell-mediated therapeutic effects in different diseases. However, the ability of MT to enhance ERC-mediated effects in colitis is currently poorly understood. METHODS: Menstrual blood was collected from healthy female volunteers to obtain ERCs and identified. In vitro, H2O2-induced oxidative stress was introduced to test if MT could prevent ERCs from damage through detection of intracellular reactive oxidative species (ROS) and apoptosis assay. In vivo, dextran sodium sulfate (DSS)-induced acute colitis was treated by ERCs and MT-primed ERCs, therapeutic effects were assayed by the disease activity index (DAI), histological features, and macrophage and CD4+ T cell in the spleen and colon, and cytokine profiles in the sera and colon were also measured. RESULTS: In vitro, ERCs that underwent MT-precondition were found to possess more anti-oxidative potency in comparison to naïve ERCs, which were characterized by decreased apoptosis rate and intracellular ROS under H2O2 stimulation. In vivo, MT pretreatment can significantly enhance the therapeutic effects of ERCs in the attenuation of experimental colitis, including decreased DAI index and damage score. In addition, MT pretreatment was found to promote ERC-mediated inhibition of Th1, Th17, and M1 macrophage and pro-inflammatory cytokines, increase of Treg, and immunomodulation of cytokines in the spleen and colon. CONCLUSIONS: MT pretreatment facilitates the promotion of cell viability under oxidative stress in vitro, while also enhancing ERC-mediated therapeutic effects in experimental colitis.

Examining the Pathogenesis of MAFLD and the Medicinal Properties of Natural Products from a Metabolic Perspective.

Metabolic-associated fatty liver disease (MAFLD), characterized primarily by hepatic steatosis, has become the most prevalent liver disease worldwide, affecting approximately two-fifths of the global population. The pathogenesis of MAFLD is extremely complex, and to date, there are no approved therapeutic drugs for clinical use. Considerable evidence indicates that various metabolic disorders play a pivotal role in the progression of MAFLD, including lipids, carbohydrates, amino acids, and micronutrients. In recent years, the medicinal properties of natural products have attracted widespread attention, and numerous studies have reported their efficacy in ameliorating metabolic disorders and subsequently alleviating MAFLD. This review aims to summarize the metabolic-associated pathological mechanisms of MAFLD, as well as the natural products that regulate metabolic pathways to alleviate MAFLD.

Recombinant human IL-37 attenuates acute cardiac allograft rejection in mice.

BACKGROUND: Allograft rejection remains a major obstacle to long-term graft survival. Although previous studies have demonstrated that IL-37 exhibited significant immunomodulatory effects in various diseases, research on its role in solid organ transplantation has not been fully elucidated. In this study, the therapeutic effect of recombinant human IL-37 (rhIL-37) was evaluated in a mouse cardiac allotransplantation model. METHODS: The C57BL/6 recipients mouse receiving BALB/c donor hearts were treated with rhIL-37. Graft pathological and immunohistology changes, immune cell populations, and cytokine profiles were analyzed on postoperative day (POD) 7. The proliferative capacities of Th1, Th17, and Treg subpopulations were assessed in vitro. Furthermore, the role of the p-mTOR pathway in rhIL-37-induced CD4+ cell inhibition was also elucidated. RESULTS: Compared to untreated groups, treatment of rhIL-37 achieved long-term cardiac allograft survival and effectively alleviated allograft rejection indicated by markedly reduced infiltration of CD4+ and CD11c+ cells and ameliorated graft pathological changes. rhIL-37 displayed significantly less splenic populations of Th1 and Th17 cells, as well as matured dendritic cells. The percentages of Tregs in splenocytes were significantly increased in the therapy group. Furthermore, rhIL-37 markedly decreased the levels of TNF-α and IFN-γ, but increased the level of IL-10 in the recipients. In addition, rhIL-37 inhibited the expression of p-mTOR in CD4+ cells of splenocytes. In vitro, similar to the in vivo experiments, rhIL-37 caused a decrease in the proportion of Th1 and Th17, as well as an increase in the proportion of Treg and a reduction in p-mTOR expression in CD4+ cells. CONCLUSIONS: We demonstrated that rhIL-37 effectively suppress acute rejection and induce long-term allograft acceptance. The results highlight that IL-37 could be novel and promising candidate for prevention of allograft rejection.

Oxymatrine combined with rapamycin to attenuate acute cardiac allograft rejection.

Background and aim: Solid organ transplantation remains a life-saving therapeutic option for patients with end-stage organ dysfunction. Acute cellular rejection (ACR), dominated by dendritic cells (DCs) and CD4+ T cells, is a major cause of post-transplant mortality. Inhibiting DC maturation and directing the differentiation of CD4+ T cells toward immunosuppression are keys to inhibiting ACR. We propose that oxymatrine (OMT), a quinolizidine alkaloid, either alone or in combination with rapamycin (RAPA), attenuates ACR by inhibiting the mTOR-HIF-1α pathway. Methods: Graft damage was assessed using haematoxylin and eosin staining. Intragraft CD11c+ and CD4+ cell infiltrations were detected using immunohistochemical staining. The proportions of mature DCs, T helper (Th) 1, Th17, and Treg cells in the spleen; donor-specific antibody (DSA) secretion in the serum; mTOR-HIF-1α expression in the grafts; and CD4+ cells and bone marrow-derived DCs (BMDCs) were evaluated using flow cytometry. Results: OMT, either alone or in combination with RAPA, significantly alleviated pathological damage; decreased CD4+ and CD11c+ cell infiltration in cardiac allografts; reduced the proportion of mature DCs, Th1 and Th17 cells; increased the proportion of Tregs in recipient spleens; downregulated DSA production; and inhibited mTOR and HIF-1α expression in the grafts. OMT suppresses mTOR and HIF-1α expression in BMDCs and CD4+ T cells in vitro. Conclusions: Our study suggests that OMT-based therapy can significantly attenuate acute cardiac allograft rejection by inhibiting DC maturation and CD4+ T cell responses. This process may be related to the inhibition of the mTOR-HIF-1α signaling pathway by OMT.

Multimodal Physiological Analysis of Impact of Emotion on Cognitive Control in VR.

Cognitive control is often perplexing to elucidate and can be easily influenced by emotions. Understanding the individual cognitive control level is crucial for enhancing VR interaction and designing adaptive and self-correcting VR/AR applications. Emotions can reallocate processing resources and influence cognitive control performance. However, current research has primarily emphasized the impact of emotional valence on cognitive control tasks, neglecting emotional arousal. In this study, we comprehensively investigate the influence of emotions on cognitive control based on the arousal-valence model. A total of 26 participants are recruited, inducing emotions through VR videos with high ecological validity and then performing related cognitive control tasks. Leveraging physiological data including EEG, HRV, and EDA, we employ classification techniques such as SVM, KNN, and deep learning to categorize cognitive control levels. The experiment results demonstrate that high-arousal emotions significantly enhance users' cognitive control abilities. Utilizing complementary information among multi-modal physiological signal features, we achieve an accuracy of 84.52% in distinguishing between high and low cognitive control. Additionally, time-frequency analysis results confirm the existence of neural patterns related to cognitive control, contributing to a better understanding of the neural mechanisms underlying cognitive control in VR. Our research indicates that physiological signals measured from both the central and autonomic nervous systems can be employed for cognitive control classification, paving the way for novel approaches to improve VR/AR interactions.

EvoAI enables extreme compression and reconstruction of the protein sequence space.

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Predictive healthcare modeling for early pandemic assessment leveraging deep auto regressor neural prophet.

In this paper, NeuralProphet (NP), an explainable hybrid modular framework, enhances the forecasting performance of pandemics by adding two neural network modules; auto-regressor (AR) and lagged-regressor (LR). An advanced deep auto-regressor neural network (Deep-AR-Net) model is employed to implement these two modules. The enhanced NP is optimized via AdamW and Huber loss function to perform multivariate multi-step forecasting contrast to Prophet. The models are validated with COVID-19 time-series datasets. The NP's efficiency is studied component-wise for a long-term forecast for India and an overall reduction of 60.36% and individually 34.7% by AR-module, 53.4% by LR-module in MASE compared to Prophet. The Deep-AR-Net model reduces the forecasting error of NP for all five countries, on average, by 49.21% and 46.07% for short-and-long-term, respectively. The visualizations confirm that forecasting curves are closer to the actual cases but significantly different from Prophet. Hence, it can develop a real-time decision-making system for highly infectious diseases.

Nutritional, Textural, and Sensory Attributes of Protein Bars Formulated with Mycoproteins.

Research accumulated over the past decades has shown that mycoprotein could serve as a healthy and safe alternative protein source, offering a viable substitute for animal- and plant-derived proteins. This study evaluated the impact of substituting whey protein with fungal-derived mycoprotein at different levels (10%, 20%, and 30%) on the quality of high-protein nutrition bars (HPNBs). It focused on nutritional content, textural changes over storage, and sensory properties. Initially, all bars displayed similar hardness, but storage time significantly affected textural properties. In the early storage period (0-5 days), hardness increased at a modest rate of 0.206 N/day to 0.403 N/day. This rate dramatically escalated from 1.13 N/day to 1.36 N/day after 5 days, indicating a substantial textural deterioration over time. Bars with lower mycoprotein levels (10%) exhibited slower hardening rates compared with those with higher substitution levels (20% and 30%), pointing to a correlation between mycoprotein content and increased bar hardness during storage. Protein digestibility was assessed through in vitro gastric and intestinal phases. Bars with no or low-to-medium levels of mycoprotein substitution (PB00, PB10, and PB20) showed significantly higher digestibility (40.3~43.8%) compared with those with the highest mycoprotein content (PB30, 32.9%). However, digestibility rates for all mycoprotein-enriched bars were lower than those observed for whey-protein-only bars (PB00, 84.5%), especially by the end of the intestinal digestion phase. The introduction of mycoprotein enriched the bars' dietary fiber content and improved their odor, attributing a fresh mushroom-like smell. These findings suggest that modest levels of mycoprotein can enhance nutritional value and maintain sensory quality, although higher substitution levels adversely affect texture and protein digestibility. This study underscores the potential of mycoprotein as a functional ingredient in HPNBs, balancing nutritional enhancement with sensory acceptability, while also highlighting the challenges of textural deterioration and reduced protein digestibility at higher substitution levels.