bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neural Network Models for Ionospheric Electron Density Prediction at a Fixed Altitude Using Neural Architecture Search
Authors: Pan Yang , Jin Mingwu , Zhang Shun‐Rong , Wing Simon , Deng Yue 
Published: August 2024

AbstractSpecification and forecast of ionospheric parameters, such as ionospheric electron density (Ne), have been an important topic in space weather and ionospheric research. Neural networks (NNs) emerge as a powerful modeling tool for Ne prediction. However, heavy manual adjustments are time consuming to determine the optimal NN structures. In this work, we propose to use neural architecture search (NAS), an automatic machine learning method, to mitigate this problem. NAS aims to find the optimal network structure through the alternate optimization of the hyperparameters and the corresponding network parameters within a pre‐defined hyperparameter search space. A total of 16‐year data from Millstone Hill incoherent scatter radar (ISR) are used for the NN models. One single‐layer NN (SLNN) model and one deep NN (DNN) model are both trained with NAS, namely SLNN‐NAS and DNN‐NAS, for Ne prediction and compared with their manually tuned counterparts (SLNN and DNN) based on previous studies. Our results show that SLNN‐NAS and DNN‐NAS outperformed SLNN and DNN, respectively. These NN predictions of Ne daily variation patterns reveal a 27‐day mid‐latitude topside Ne variation, which cannot be reasonably represented by traditional empirical models developed using monthly averages. DNN‐NAS yields the best prediction accuracy measured by quantitative metrics and rankings of daily pattern prediction, especially with an improvement in mean absolute error more than 10% compared to the SLNN model. The limited improvement of NAS is likely due to the network complexity and the limitation of fully connected NN without the time histories of input parameters.
Clinical efficacy and immune response of neoadjuvant camrelizumab plus chemotherapy in resectable locally advanced oesophageal squamous cell carcinoma: a phase 2 trial
Authors: Chen Yue-Yun , Wang Pei-Pei , Hu Yang , Yuan Yong , Yang Yu-Shang , Shi Hua-Shan , Hao Qing , Lin Zhen , Tian Jiang-Fang , Zheng Yue , Liu Ting , Lin Pan-Pan , Xu Heng , Ma Xue-Lei , Yang Li , Ding Zhen-Yu 
Published: August 2024

Abstract
Background
Neoadjuvant immunotherapy is under intensive investigation for esophageal squamous cell carcinoma (ESCC). This study assesses the efficacy and immune response of neoadjuvant immunochemotherapy (nICT) in ESCC.

Methods
In this phase II trial (ChiCTR2100045722), locally advanced ESCC patients receiving nICT were enrolled. The primary endpoint was the pathological complete response (pCR) rate. Multiplexed immunofluorescence, RNA-seq and TCR-seq were conducted to explore the immune response underlying nICT.

Results
Totally 42 patients were enrolled, achieving a 27.0% pCR rate. The 1-year, 2-year DFS and OS rates were 89.2%, 64.4% and 97.3%, 89.2%, respectively. RNA-seq analysis highlighted T-cell activation as the most significantly enriched pathway. The tumour immune microenvironment (TIME) was characterised by high CD4, CD8, Foxp3, and PD-L1 levels, associating with better pathological regression (TRS0/1). TIME was categorised into immune-infiltrating, immune-tolerant, and immune-desert types. Notably, the immune-infiltrating type and tertiary lymphoid structures correlated with improved outcomes. In the context of nICT, TIM-3 negatively influenced treatment efficacy, while elevated TIGIT/PD-1 expression post-nICT correlated positively with CD8+ T cell levels. TCR-seq identified three TCR rearrangements, underscoring the specificity of T-cell responses.

Conclusions
Neoadjuvant camrelizumab plus chemotherapy is effective for locally advanced, resectable ESCC, eliciting profound immune response that closely associated with clinical outcomes.
Targeting of mutant-p53 and MYC as a novel strategy to inhibit oncogenic SPAG5 activity in triple negative breast cancer
Authors: Canu Valeria , Vaccarella Sebastiano , Sacconi Andrea , Pulito Claudio , Goeman Frauke , Pallocca Matteo , Rutigliano Daniela , Lev Sima , Strano Sabrina , Blandino Giovanni 
Published: August 2024

AbstractTriple negative breast cancer (TNBC) is an aggressive disease which currently has no effective therapeutic targets and prominent biomarkers. The Sperm Associated antigen 5 (SPAG5) is a mitotic spindle associated protein with oncogenic function in several human cancers. In TNBC, increased SPAG5 expression has been associated with tumor progression, chemoresistance, relapse, and poor clinical outcome. Here we show that high SPAG5 expression in TNBC is regulated by coordinated activity of YAP, mutant p53 and MYC. Depletion of YAP or mutant p53 proteins reduced SPAG5 expression and the recruitment of MYC onto SPAG5 promoter. Targeting of MYC also reduced SPAG5 expression and concomitantly tumorigenicity of TNBC cells. These effects of MYC targeting were synergized with cytotoxic chemotherapy and markedly reduced TNBC oncogenicity in SPAG5-expression dependent manner. These results suggest that mutant p53-MYC-SPAG5 expression can be considered as bona fide predictors of patient’s outcome, and reliable biomarkers for effective anticancer therapies.
Cysteine sulfenylation contributes to liver fibrosis via the regulation of EphB2-mediated signaling
Authors: Han Yueqing , Gao Qi , Xu Yating , Chen Ke , Li Rongxin , Guo Weiran , Wang Shuzhen 
Published: August 2024

AbstractSulfenylation is a reversible oxidative posttranslational modification (PTM) of proteins on cysteine residues. Despite the dissection of various biological functions of cysteine sulfenylation, its roles in hepatic fibrosis remain elusive. Here, we report that EphB2, a receptor tyrosine kinase previously implicated in liver fibrosis, is regulated by cysteine sulfenylation during the fibrotic progression of liver. Specifically, EphB2 is sulfenylated at the residues of Cys636 and Cys862 in activated hepatic stellate cells (HSCs), leading to the elevation of tyrosine kinase activity and protein stability of EphB2 and stronger interactions with focal adhesion kinase for the activation of downstream mitogen-activated protein kinase signaling. The inhibitions of both EphB2 kinase activity and cysteine sulfenylation by idebenone (IDE), a marketed drug with potent antioxidant activity, can markedly suppress the activation of HSCs and ameliorate hepatic injury in two well-recognized mouse models of liver fibrosis. Collectively, this study reveals cysteine sulfenylation as a new type of PTM for EphB2 and sheds a light on the therapeutic potential of IDE for the treatment of liver fibrosis.
Engineered mitochondria exert potent antitumor immunity as a cancer vaccine platform
Authors: Luo Jingwen , Mo Fei , Zhang Zhe , Hong Weiqi , Lan Tianxia , Cheng Yuan , Fang Chunju , Bi Zhenfei , Qin Furong , Yang Jingyun , Zhang Ziqi , Li Xue , Que Haiying , Wang Jiayu , Chen Siyuan , Wu Yiming , Yang Li , Li Jiong , Wang Wei , Chen Chong , Wei Xiawei 
Published: August 2024

AbstractThe preferable antigen delivery profile accompanied by sufficient adjuvants favors vaccine efficiency. Mitochondria, which feature prokaryotic characteristics and contain various damage-associated molecular patterns (DAMPs), are easily taken up by phagocytes and simultaneously activate innate immunity. In the current study, we established a mitochondria engineering platform for generating antigen-enriched mitochondria as cancer vaccine. Ovalbumin (OVA) and tyrosinase-related protein 2 (TRP2) were used as model antigens to synthesize fusion proteins with mitochondria-localized signal peptides. The lentiviral infection system was then employed to produce mitochondrial vaccines containing either OVA or TRP2. Engineered OVA- and TRP2-containing mitochondria (OVA-MITO and TRP2-MITO) were extracted and evaluated as potential cancer vaccines. Impressively, the engineered mitochondria vaccine demonstrated efficient antitumor effects when used as both prophylactic and therapeutic vaccines in murine tumor models. Mechanistically, OVA-MITO and TRP2-MITO potently recruited and activated dendritic cells (DCs) and induced a tumor-specific cell-mediated immunity. Moreover, DC activation by mitochondria vaccine critically involves TLR2 pathway and its lipid agonist, namely, cardiolipin derived from the mitochondrial membrane. The results demonstrated that engineered mitochondria are natively well-orchestrated carriers full of immune stimulants for antigen delivery, which could preferably target local dendritic cells and exert strong adaptive cellular immunity. This proof-of-concept study established a universal platform for vaccine construction with engineered mitochondria bearing alterable antigens for cancers as well as other diseases.
Description and first insights on a large genomic biobank of lung transplantation
Authors: Brocard Simon , Morin Martin , dos Santos Brito Silva Nayane , Renaud-Picard Benjamin , Coiffard Benjamin , Demant Xavier , Falque Loïc , Le Pavec Jérome , Roux Antoine , Villeneuve Thomas , Knoop Christiane , Mornex Jean-François , Salpin Mathilde , Boussaud Véronique , Rousseau Olivia , Mauduit Vincent , Durand Axelle , Magnan Antoine , Gourraud Pierre-Antoine , Vince Nicolas , Südholt Mario , Tissot Adrien , Limou Sophie ,   COLT consortium, Le Pavec Jérome 
Published: August 2024

AbstractThe main limitation to long-term lung transplant (LT) survival is chronic lung allograft dysfunction (CLAD), which leads to irreversible lung damage and significant mortality. Individual factors can impact CLAD, but no large genetic investigation has been conducted to date. We established the multicentric Genetic COhort in Lung Transplantation (GenCOLT) biobank from a rich and homogeneous sub-part of COLT cohort. GenCOLT collected DNA, high-quality GWAS (genome-wide association study) genotyping and robust HLA data for donors and recipients to supplement COLT clinical data. GenCOLT closely mirrors the global COLT cohort without significant variations in variables like demographics, initial disease and survival rates (P > 0.05). The GenCOLT donors were 45 years-old on average, 44% women, and primarily died of stroke (54%). The recipients were 48 years-old at transplantation on average, 45% women, and the main underlying disease was chronic obstructive pulmonary disease (45%). The mean follow-up time was 67 months and survival at 5 years was 57.3% for the CLAD subgroup and 97.4% for the non-CLAD subgroup. After stringent quality controls, GenCOLT gathered more than 7.3 million SNP and HLA genotypes for 387 LT pairs, including 91% pairs composed of donor and recipient of European ancestry. Overall, GenCOLT is an accurate snapshot of LT clinical practice in France and Belgium between 2009 and 2018. It currently represents one of the largest genetic biobanks dedicated to LT with data available simultaneously for donors and recipients. This unique cohort will empower to run comprehensive GWAS investigations of CLAD and other LT outcomes.
Low serum testosterone is associated with an increased risk of first-time renal calculi in men without testosterone replacement therapy
Authors: Thompson Austin , Omil-Lima Danly , Rhodes Stephen , Jevnikar Benjamin , Obery Dana , Kaelber David , Thirumavalavan Nannan 
Published: August 2024

AbstractThe incidence of low serum testosterone has been increasing in men of all ages across a period which also corresponds to an increasing prevalence of kidney stones. Currently, the relationship between testosterone and kidney stones is unclear. Using the TriNetX Research Network, we performed a retrospective cohort study to evaluate the risk of developing an initial kidney stone in men based on their total testosterone level. Men aged ≥18 were divided into a low testosterone (<300 ng/dL) and normal testosterone (≥ 300 ng/dL) cohort. Men were excluded if they had a history of a kidney stone encounter diagnosis before testosterone measurement and a history of testosterone therapy prescription at any point. Propensity score matching was employed with an absolute standardized mean difference of less than 0.1 used as an indicator of successful matching. Our main outcome of interest was risk of developing an initial kidney stone in men aged ≥18 and within age-based subgroups. In men 18 and older, low testosterone was associated with a higher risk of one or more kidney stone encounter diagnoses (HR 1.12, 95% CI [1.09–1.15]). When stratified by age, no significant association between low testosterone and kidney stone encounter diagnoses was seen in men aged 18–24 (HR 1.09, 95% CI [0.85–1.39]). The highest risk was observed in men with low testosterone aged 34-44 (HR 1.29, 95% CI [1.17–1.38]). In this study, low serum testosterone was associated with an increased risk of initial kidney stone diagnosis in adult men without testosterone therapy prescriptions at any point in their life. Stratifying by age, the increased risk appears to begin in men aged 25, with the highest observed risk in men aged 33-44.
Fast and robust analog in-memory deep neural network training
Authors: Rasch Malte J. , Carta Fabio , Fagbohungbe Omobayode , Gokmen Tayfun 
Published: August 2024

AbstractAnalog in-memory computing is a promising future technology for efficiently accelerating deep learning networks. While using in-memory computing to accelerate the inference phase has been studied extensively, accelerating the training phase has received less attention, despite its arguably much larger compute demand to accelerate. While some analog in-memory training algorithms have been suggested, they either invoke significant amount of auxiliary digital compute—accumulating the gradient in digital floating point precision, limiting the potential speed-up—or suffer from the need for near perfectly programming reference conductance values to establish an algorithmic zero point. Here, we propose two improved algorithms for in-memory training, that retain the same fast runtime complexity while resolving the requirement of a precise zero point. We further investigate the limits of the algorithms in terms of conductance noise, symmetry, retention, and endurance which narrow down possible device material choices adequate for fast and robust in-memory deep neural network training.
Optimizing oocyte yield utilizing a machine learning model for dose and trigger decisions, a multi-center, prospective study
Authors: Canon Chelsea , Leibner Lily , Fanton Michael , Chang Zeyu , Suraj Vaishali , Lee Joseph A. , Loewke Kevin , Hoffman David 
Published: August 2024

AbstractThe objective of this study was to evaluate clinical outcomes for patients undergoing IVF treatment where an artificial intelligence (AI) platform was utilized by clinicians to help determine the optimal starting dose of FSH and timing of trigger injection. This was a prospective clinical trial with historical control arm. Four physicians from two assisted reproductive technology treatment centers in the United States participated in the study. The treatment arm included patients undergoing autologous IVF cycles between December 2022–April 2023 where the physician use AI to help select starting dose of follicle stimulating hormone (FSH) and trigger injection timing (N = 291). The control arm included historical patients treated where the same doctor did not use AI between September 2021 and September 2022. The main outcome measures were total FSH used and average number of mature metaphase II (MII) oocytes. There was a non-significant trend towards improved patient outcomes and a reduction in FSH with physician use of AI. Overall, the average number of MIIs in the treatment vs. control arm was 12.20 vs 11.24 (improvement = 0.96, p = 0.16). The average number of oocytes retrieved in the treatment vs. control arm was 16.01 vs 14.54 (improvement = 1.47, p = 0.08). The average total FSH in the treatment arm was 3671.95 IUs and the average in the control arm was 3846.29 IUs (difference = −174.35 IUs, p = 0.13). These results suggests that AI can safely assist in refining the starting dose of FSH while narrowing down the timing of the trigger injection during ovarian stimulation, benefiting the patient in optimizing the count of MII oocytes retrieved.
Connected smart elevator systems for smart power and time saving
Authors: Rashed Ahmed Nabih Zaki , Yarrarapu Manasa , Prabu Ramachandran Thandaiah , Raj Antony Gnana Sagaya , Edeswaran Logashanmugam , Kumar E. Santosh , Aswitha K. , Snehith N. , Ahammad Shaik Hasane 
Published: August 2024

AbstractSmart elevators provide substantial promise for time and energy management applications by utilizing cutting edge artificial intelligence and image processing technology. In order to improve operating efficiency, this project designs an elevator system that uses the YOLO model for object detection. Compared to traditional methods, our results show a 15% improvement in wait times and a 20% reduction in energy use. Due to the elevator’s increased accuracy and dependability, users’ qualitative feedback shows a high degree of pleasure. These results imply that intelligent elevator systems can make a significant contribution to more intelligent building management. Due to the elevator’s increased accuracy and dependability, users’ qualitative feedback shows a high degree of pleasure. These results imply that intelligent elevator systems can make a significant contribution to more intelligent building management. The successful integration of artificial intelligence (AI) and image processing technologies in elevator systems presents a promising foundation for future research and development. Further advancements in object detection algorithms, such as refining YOLO models for even higher accuracy and real-time adaptability, hold potential to enhance operational efficiency. Integrating smart elevators more deeply into IoT networks and building management systems could enable comprehensive energy management strategies and real-time decision-making. Predictive maintenance models tailored to elevator components could minimize downtime and optimize service schedules, enhancing overall reliability. Additionally, exploring adaptive user interfaces and personalized scheduling algorithms could further elevate user satisfaction by tailoring elevator interactions to individual preferences. Sustainable practices, including energy-efficient designs and integration of renewable energy sources, represent crucial avenues for reducing environmental impact. Addressing security concerns through advanced encryption and access control mechanisms will be essential for safeguarding sensitive data in smart elevator systems.
Opportunity to view the starry night sky is linked to human emotion and behavioral interest in astronomy
Authors: Barragan Rodolfo Cortes , Meltzoff Andrew N. 
Published: August 2024

AbstractPrior to the modern era, the stars in the night sky were readily visible across the globe, but light pollution has created disparities in the opportunity to see these astronomical objects with the naked eye. This alteration may measurably impact human behavior. We hypothesize that light pollution is related to the development of people’s interest in astronomy, which often serves as a “gateway” to science more broadly. In a state-by-state analysis, we used location information to examine astronomy interest data for millions of US residents. Results show that, among populations with low light pollution, a feeling of “wonder about the universe” is prevalent (r = 0.50). We found that this human emotion mediates the association between low light pollution and behavioral interest in astronomy. Although the effects of light pollution on astronomy, biology, ecology, and health are well-known, the present work demonstrates that light pollution is also relevant to human scientific behavior, with broad implications for science education and society.
The potential of residual clinical Group B Streptococcus swabs for assessing the vaginorectal microbiome in late pregnancy
Authors: Boelsen Laura K. , Williams Melanie J. , Mangwiro Yeukai TM. , Hansji Herah , Czajko Anna , Marcelino Vanessa , Forster Samuel , Said Joanne M. , Satzke Catherine , Saffery Richard 
Published: August 2024

AbstractThe maternal pregnancy microbiome (including genitourinary and gut) has been linked to important pregnancy/birth and later childhood health outcomes. However, such sampling as part of large population cohort studies is logistically and financially challenging. Many countries routinely collect vaginal or vaginal-rectal swabs in late pregnancy for Group B Streptococcus (GBS) screening, but their utility for population-based research is still unclear. As part of planning for the Generation Victoria population-based cohort study beginning in pregnancy, we assessed the utility and reliability of residual clinical GBS vaginal/vaginal-rectal swabs for generating late pregnancy microbiome data. We carried out a two-phased pilot study. Phase one assessed the level of microbial diversity apparent in ‘residual’ clinical vaginal/vaginal-rectal swabs post clinical testing and storage for 7–10 days at 4 °C (routine clinical practice). Phase two directly assessed the impact of storage time and temperature on the microbial composition of vaginal/vaginal-rectal swabs collected specifically for research purposes. The microbiota composition in the ‘residual’ clinical swabs aligned with published studies. The ‘research’ swabs, stored at 4 °C for up to ten days, showed minimal changes in microbiota profile, compared to swabs examined on the day of collection. In contrast, significant variation in diversity was seen in swabs stored at room temperature for up to 48 h. Residual clinical material from swabs collected primarily for GBS screening in late pregnancy represent a reliable and abundant source of material for assessing the late pregnancy maternal microbiome for research purposes. This represents a low-burden opportunity for population-representative pregnancy studies to assess the potential of late pregnancy microbiome for prediction and understanding maternal and child health outcomes.
Proportional‐integral‐differential‐inspired acceleration in distributed optimal control strategy for direct current microgrids
Authors: Tao Peng , Sun Shengbo , Guo Wei , Nan Kai , Bai Xinlei , Ding Jianyong 
Published: August 2024

AbstractA PID‐inspired accelerated distributed optimal control algorithm is proposed for the economic dispatch problem of a multi‐bus DC microgrid, which contains both conventional generators (CGs) and renewable generators (RGs). Firstly, a constrained optimization problem with the aim of minimizing the power generation cost of the DC microgrid is established. To solve the optimization problem, an accelerated distributed optimal control algorithm in the discrete‐time domain is proposed. The convergence speed of the proposed algorithm is significantly improved compared to the existing distributed optimization algorithms without acceleration terms. More importantly, the communication cost is greatly reduced. The proposed algorithm is in a fully distributed manner, which means each controller only relies on the limited information from neighbouring controllers to achieve optimal cooperative control and bus voltage regulation across multiple buses. Finally, the effectiveness of the proposed algorithm is validated through numerical simulations.