查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Mental Health Diseases and Conditions - Depression is the subject of a report. According to news repor ting originating in Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Major depressive disorder (MDD) is a pervasive mental and mood disorder with complicated and heterogeneous etiology. Mitophagy, a selective au tophagy of cells, specifically eliminates dysfunctional mitochondria.” The news reporters obtained a quote from the research from the Beijing Universit y of Chinese Medicine, “The mitochondria dysfunction in the astrocytes is regard ed as a critical pathogenetic mechanism of MDD. However, studies on the mitophag y of astrocytes in MDD are scarce. To explore the impact of mitophagy on the ast rocytes, we used bioinformatic methods to analyze the correlation between astroc yte-related genes and mitophagy-related genes in MDD. The microarray dataset of MDD was downloaded from the Gene Expression Omnibus database and identified astr ocyte- and mitophagy-related differentially expressed genes (AMRDEGs). We used t hree machine learning algorithms to identify hub AMRDEGs and constructed a diagn ostic prediction model. Also, we analyzed transcription factor-gene and gene-mic roRNA interaction networks, and the immune infiltration in MDD and healthy contr ols. Besides, we performed consensus clustering analysis, immune infiltration an alysis, and gene set variation analysis of MDD samples. The present research ide ntified 3 hub AMRDEGs (GRN, NDUFAF4, and SNCA), and a good diagnostic model with potential clinical applications was constructed and validated. Besides, we iden tified 6 transcription factors and 14 microRNAs. The immune infiltration analysi s showed that MDD was closely related to immune cells. Gene set variant analysis showed that MDD was related to immune and mitochondrial metabolism and inflamma tory signaling pathways. We identified 3 hub AMRDEGs, new biomarkers for treatin g and diagnosing MDD and associated with immuno-inflammation.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Lymphoma is the subject of a report. According to news reporting originating in Chengdu, Pe ople’s Republic of China, by NewsRx journalists, research stated, “New cases of lymphoma are rising, and the symptom burden, like cancer-related fatigue (CRF), severely impacts the quality of life of lymphoma survivors. However, clinical di agnosis and treatment of CRF are inadequate and require enhancement.” The news reporters obtained a quote from the research from the University of Ele ctronic Science and Technology of China, “The main objective of this study is to construct machine learning-based CRF prediction models for lymphoma survivors t o help healthcare professionals accurately identify the CRF population and bette r personalize treatment and care for patients. A cross-sectional study in China recruited lymphoma patients from June 2023 to March 2024, dividing them into two datasets for model construction and external validation. Six machine learning a lgorithms were used in this study: Logistic Regression (LR), Random Forest, Sing le Hidden Layer Neural Network, Support Vector Machine, eXtreme Gradient Boostin g, and Light Gradient Boosting Machine (LightGBM). Performance metrics like the area under the receiver operating characteristic (AUROC) and calibration curves were compared. The clinical applicability was assessed by decision curve, and Sh apley additive explanations was employed to explain variable significance. CRF i ncidence was 40.7 % (dataset I) and 44.8 % (dataset II). LightGBM showed strong performance in training and internal validation. LR excelled in external validation with the highest AUROC and best calibration. Pai n, total protein, physical function, and sleep disturbance were important predic tors of CRF.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ar tificial Intelligence. According to news originating from Gdansk, Poland, by New sRx correspondents, research stated, “Artificial intelligence (AI) and machine l earning were used to obtain more effective methods for conducting the digestion process and achieving final products. Data acquisition was carried out by an aut omatic monitoring and anal. research.” Financial support for this research came from Norway Grants via the National Cen tre for Research and Development.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of Munich, Germany , by NewsRx editors, research stated, “Recurrent and metastatic head and neck sq uamous cell carcinoma (HNSCC) is characterized by a complex therapeutic manageme nt that needs to be discussed in multidisciplinary tumor boards (MDT). While art ificial intelligence (AI) improved significantly to assist healthcare profession als in making informed treatment decisions for primary cases, an application in the even more complex recurrent/metastatic setting has not been evaluated yet.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news reporting originating in Brussels, Belgium, by NewsRx journalists, research stated, “Median arcuate ligament syndrome (MALS) po ses a rare challenge in diagnosis and management. We present a case of MALS in a 50-year-old male with recurrent epigastric pain, vomiting, and diarrhea.” The news reporters obtained a quote from the research from Saint-Pierre Universi ty Hospital, “Diagnostic imaging revealed celiac artery stenosis and gastroduode nal artery collateral dilatation. Robotic-assisted median arcuate ligament relea se successfully alleviated symptoms. Utilizing the da Vinci X system (Intuitive Surgical, Inc.), the procedure involved meticulous dissection of the celiac arte ry and surrounding tissue. Postoperative duplex ultrasound confirmed improved ar terial flow. Literature underscores the diagnostic hurdles of MALS and the advan tages of minimally invasive approaches over conventional open surgery. The robot ic approach may help smoothen the learning curve associated with this procedure, by providing improved operative flexibility.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Tianjin, People’s Repu blic of China, by NewsRx correspondents, research stated, “Low-cost, efficient c atalyst high-throughput screening is crucial for future renewable energy technol ogy. Interpretable machine learning is a powerful method for accelerating cataly st design by extracting physical meaning but faces huge challenges.”Our news journalists obtained a quote from the research from Tianjin University, “This paper describes an interpretable descriptor model to unify activity and s electivity prediction for multiple electrocatalytic reactions (i.e., O/CO/N redu ction and O evolution reactions), utilizing only easily accessible intrinsic pro perties. This descriptor, named ARSC, successfully decouples the atomic property (A), reactant ®, synergistic (S), and coordination effects (C) on the d-band sh ape of dual-atom sites, which is built upon our developed physically meaningful feature engineering and feature selection/sparsification (PFESS) method. Driven by this descriptor, we can rapidly locate optimal catalysts for various products instead of over 50,000 density functional theory calculations. The model’s univ ersality has been validated by abundant reported works and subsequent experiment s, where Co-Co/Ir-Qv3 are identified as optimal bifunctional oxygen reduction an d evolution electrocatalysts.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news originating from Budapest, Hunga ry, by NewsRx correspondents, research stated, “Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRN As) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages o ver small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases.” Financial support for this research came from European Commission.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news originating from Derio, Spain, by NewsRx correspond ents, research stated, “In the rapidly evolving domain of machine learning, the ability to adapt to unforeseen circumstances and novel data types is of paramoun t importance. The deployment of Artificial Intelligence is progressively aimed a t more realistic and open scenarios where data, tasks, and conditions are variab le and not fully predetermined, and therefore where a closed set assumption cann ot be hold.” Financial support for this research came from Basque Government.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news reporting originating in Fairfax, Virginia, by NewsRx journalists, research stated, “Robots are being introduced into increasin gly social environments. As these robots become more ingrained in social spaces, they will have to abide by the social norms that guide human interactions.” The news reporters obtained a quote from the research from George Mason Universi ty, “At times, however, robots will violate norms and perhaps even deceive their human interaction partners. This study provides some of the first evidence for how people perceive and evaluate robot deception, especially three types of dece ption behaviors theorized in the technology ethics literature: External state de ception (cues that intentionally misrepresent or omit details from the external world: e.g., lying), Hidden state deception (cues designed to conceal or obscure the presence of a capacity or internal state the robot possesses), and Superfic ial state deception (cues that suggest a robot has some capacity or internal sta te that it lacks). Participants (N = 498) were assigned to read one of three vig nettes, each corresponding to one of the deceptive behavior types. Participants provided responses to qualitative and quantitative measures, which examined to w hat degree people approved of the behaviors, perceived them to be deceptive, fou nd them to be justified, and believed that other agents were involved in the rob ots’ deceptive behavior. Participants rated hidden state deception as the most d eceptive and approved of it the least among the three deception types. They cons idered external state and superficial state deception behaviors to be comparably deceptive; but while external state deception was generally approved, superfici al state deception was not. Participants in the hidden state condition often imp licated agents other than the robot in the deception. This study provides some o f the first evidence for how people perceive and evaluate the deceptiveness of r obot deception behavior types. This study found that people people distinguish a mong the three types of deception behaviors and see them as differently deceptiv e and approve of them differently.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news reporting out of the Jozef Ste fan Institute by NewsRx editors, research stated, “Monte Carlo simulations are a crucial component when analysing the Standard Model and New physics processes a t the Large Hadron Collider.” Financial supporters for this research include Javna Agencija Za Raziskovalno De javnost Rs. The news editors obtained a quote from the research from Jozef Stefan Institute: “This paper aims to explore the performance of generative models for complement ing the statistics of classical Monte Carlo simulations in the final stage of da ta analysis by generating additional synthetic data that follows the same kinema tic distributions for a limited set of analysis-specific observables to a high p recision. Several deep generative models are adapted for this task and their per formance is systematically evaluated using a well-known benchmark sample contain ing the Higgs boson production beyond the Standard Model and the corresponding i rreducible background. The paper evaluates the autoregressive models and normali zing flows and the applicability of these models using different model configura tions is investigated. The best performing model is chosen for a further evaluat ion using a set of statistical procedures and a simplified physics analysis.”
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