bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intramyocardial immunomodulation with human CD16+ monocytes to treat myocardial infarction in pig: a blind randomized preclinical trial
Authors: Ascione Raimondo , Bruno Vito D. , Johnson Tom , Sammut Eva , Bond Andrew , Lopez-Baz Daniel , Deutsch Julia , Bailey Mick , Chiribiri Amedeo , Patel Ashish , Baker Andrew , Modarai Bijan 
Published: August 2024

BackgroundHuman CD16+ monocytes (hCD16+ Ms) have proangiogenic properties. We assessed the feasibility, safety and efficacy of hCD16+ Ms in a porcine model of myocardial infarction (MI).Methods and resultsA total of 27 female Large White pigs underwent MI with reperfusion and cardiac magnetic resonance (CMR). Five days later, animals received intramyocardial injections of hCD16+ Ms in saline (n = 13) or saline only (n = 14). hCD16+ Ms were selected from leucocyte cones. Feasibility/safety endpoints included injury at injected sites, malignant arrhythmias, cancer, haematoma, left ventricular (LV) dilatation, troponin release and downstream organ injury. Co-primary efficacy outcome included LV scar and ejection fraction (LVEF) at 30-day post-injections by CMR. Immunohistochemistry included neo-angiogenesis, fibrosis, markers of myofibroblast and inflammation. Four animals were excluded before injections due to untreatable malignant arrhythmias or lung injury. Median cell number and viability were 48.75 million and 87%, respectively. No feasibility/safety concerns were associated with the use of hCD16+ Ms. The LV scar dropped by 14.5gr (from 25.45 ± 8.24 to 10.8 ± 3.4 gr; −55%) and 6.4gr (from 18.83 ± 5.06 to 12.4 ± 3.9gr; −30%) in the hCD16+ Ms and control groups, respectively (p = 0.015). The 30-day LVEF did not differ between groups, but a prespecified sub-analysis within the hCD16+ Ms group showed that LVEF was 2.8% higher and LV scar 1.9gr lower in the subgroup receiving a higher cell dose. Higher tissue levels of neo-angiogenesis, myofibroblast and IL-6 and lower levels of TGF-β were observed in the hCD16+ Ms group.ConclusionsThe use of hCD16+ Ms in acute MI is feasible, safe and associated with reduced LV scar size, increased tissue levels of neo-angiogenesis, myofibroblasts and IL-6 and reduced pro-fibrotic TGF-β at 30-day post-injections. A higher cell dose might increase the LVEF effect while reducing scar size, but this warrants validation in future studies.
S-Tune: SOT-MTJ manufacturing parameters tuning for securing the next generation of computing
Authors: Chowdhury Muhtasim Alam , Hossain Mousam , Mastrangelo Christopher , DeMara Ronald F. , Salehi Soheil 
Published: August 2024

Hardware-based acceleration approaches for Machine Learning (ML) workloads have been embracing the significant potential of post-CMOS switching devices to attain reduced footprint and/or energy-efficient execution relative to transistor-based GPU and/or TPU-based accelerator architectures. Meanwhile, the promulgation of fabless IC chip manufacturing paradigms has heightened the hardware security concerns inherent in such approaches. Namely, unauthorized access to various supply chain stages may expose significant vulnerabilities resulting in malfunctions including subtle adversarial outcomes via the malicious generation of differentially-corrupted outputs. Whereas the Spin-Orbit Torque Magnetic Tunnel Junction (SOT-MTJ) is a leading spintronic device for use in ML accelerators, as well as holding security tokens, their manufacturing-only security exposures are identified and evaluated herein. Results indicate a novel vulnerability profile whereby an adversary without access to the circuit netlist could differentially-influence the machine learning application’s behavior. Specifically, ML recognition outputs can be significantly swayed via a global modification of oxide thickness (Tox) resulting in bit-flips of the weights in the crossbar array, thus corrupting the recognition of selected digits in MNIST dataset differentially creating an opportunity for an adversary. With just 0.05% of bits in crossbar having a flipped resistance state, digits “4” and “5” show the highest overall error rates, and digit “9” exhibit the lowest impact, with recognition accuracy of digits “2,” “3,” and “8” unaffected by changing the oxide thickness of SOT-MTJs uniformly from 0.75 nm to 1.2 nm without modifying the netlist nor even having access to the circuit design itself. Exposures and mitigation approaches to such novel and potentially damaging manufacturing-side intrusions are identified, postulated, and quantitatively assessed.
Construction of a prognostic model via WGCNA combined with the LASSO algorithm for stomach adenocarcinoma patients
Authors: Huang Zi-duo , Ran Wen-hua , Wang Guo-zhu 
Published: August 2024

ObjectiveThis study aimed to identify prognostic signatures to predict the prognosis of patients with stomach adenocarcinoma (STAD), which is necessary to improve poor prognosis and offer possible treatment strategies for STAD patients.MethodsThe overlapping genes between the key model genes that were screened by the weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) whose expression was different with significance between normal and tumor tissues were extracted to serve as co-expression genes. Then, enrichment analysis was performed on these genes. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression was performed to screen the hub genes among overlapping genes. Finally, we constructed a model to explore the influence of polygenic risk scores on the survival probability of patients with STAD, and interaction effect and mediating analyses were also performed.ResultsDEGs included 2,899 upregulated genes and 2,896 downregulated genes. After crossing the DEGs and light-yellow module genes that were obtained by WGCNA, a total of 39 overlapping genes were extracted. The gene enrichment analysis revealed that these genes were enriched in the prion diseases, biosynthesis of unsaturated fatty acids, RNA metabolic process, hydrolase activity, etc. PIP5K1P1, PTTG3P, and SNORD15B were determined by LASSO-Cox. The prognostic prediction of the three-gene model was established. The Cox regression analysis showed that the comprehensive risk score for three genes was an independent prognosis factor.ConclusionPIP5K1P1, PTTG3P, and SNORD15B are related to the prognosis and overall survival of patients. The three-gene risk model constructed has independent prognosis predictive ability for STAD.
Tumor necrosis factor inhibitors enhance corticosteroid therapy for Stevens-Johnson syndrome and toxic epidermal necrolysis linked to immune checkpoint inhibitors: a prospective study
Authors: He Chun-Xia , Guo Lan , Qu Tao , Jin Hong-Zhong 
Published: August 2024

IntroductionImmune-related epidermal necrolysis (irEN), including Stevens-Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN), represents a potentially lethal reaction to immune checkpoint inhibitors. An optimal treatment strategy remains undefined. This study evaluates the effectiveness and safety of combination therapy with corticosteroids and tumor necrosis factor inhibitors (TNFi) in treating irEN patients.MethodsIn this single-center, prospective, observational study, patients with irEN received either corticosteroid monotherapy or a combination therapy of corticosteroids and TNFi (etanercept for SJS, infliximab for TEN). The primary endpoint was re-epithelization time, with secondary endpoints including corticosteroid exposure, major adverse event incidence, acute mortality rates, and biomarkers indicating disease activity and prognosis. The study was registered at the Chinese Clinical Trial Registry (ChiCTR2100051052).ResultsThirty-two patients were enrolled (21 SJS, 11 TEN); 14 received combination therapy and 18 received corticosteroid monotherapy. IrEN typically occurred after 1 cycle of ICI administration, with a median latency of 16 days. Despite higher SCORTEN scores in the combination group (3 vs. 2, p = 0.008), these patients experienced faster re-epithelization (14 vs. 21 days; p &lt; 0.001), shorter corticosteroid treatment duration (22 vs. 32 days; p = 0.005), and lower prednisone cumulative dose (1177 mg vs. 1594 mg; p = 0.073). Major adverse event rates were similar between groups. Three deaths occurred due to lung infection or disseminated intravascular coagulation, with mortality rates for both groups lower than predicted. Potential risk factors for increased mortality included continuous reduction in lymphocyte subset counts (CD4+ T cells, CD8+ T cells, natural killer cells) and consistent rises in inflammatory markers (serum ferritin, interleukin-6, TNF-α). Re-epithelization time negatively correlated with body mass index and positively correlated with epidermal detachment area and serum levels of interleukin-6 and TNF-α.ConclusionsCorticosteroids combined with TNFi markedly promote re-epithelization, reduce corticosteroid use, and decrease acute mortality in irEN patients without increasing major adverse events, offering a superior alternative to corticosteroid monotherapy. Inflammatory markers and lymphocyte subsets are valuable for assessing disease activity and prognosis.
Enhancing the ophthalmic AI assessment with a fundus image quality classifier using local and global attention mechanisms
Authors: Wang Shengzhan , Shen Wenyue , Gao Zhiyuan , Jiang Xiaoyu , Wang Yaqi , Li Yunxiang , Ma Xiaoyu , Wang Wenhao , Xin Shuanghua , Ren Weina , Jin Kai , Ye Juan 
Published: August 2024

BackgroundThe assessment of image quality (IQA) plays a pivotal role in the realm of image-based computer-aided diagnosis techniques, with fundus imaging standing as the primary method for the screening and diagnosis of ophthalmic diseases. Conventional studies on fundus IQA tend to rely on simplistic datasets for evaluation, predominantly focusing on either local or global information, rather than a synthesis of both. Moreover, the interpretability of these studies often lacks compelling evidence. In order to address these issues, this study introduces the Local and Global Attention Aggregated Deep Neural Network (LGAANet), an innovative approach that integrates both local and global information for enhanced analysis.MethodsThe LGAANet was developed and validated using a Multi-Source Heterogeneous Fundus (MSHF) database, encompassing a diverse collection of images. This dataset includes 802 color fundus photography (CFP) images (302 from portable cameras), and 500 ultrawide-field (UWF) images from 904 patients with diabetic retinopathy (DR) and glaucoma, as well as healthy individuals. The assessment of image quality was meticulously carried out by a trio of ophthalmologists, leveraging the human visual system as a benchmark. Furthermore, the model employs attention mechanisms and saliency maps to bolster its interpretability.ResultsIn testing with the CFP dataset, LGAANet demonstrated remarkable accuracy in three critical dimensions of image quality (illumination, clarity and contrast based on the characteristics of human visual system, and indicates the potential aspects to improve the image quality), recording scores of 0.947, 0.924, and 0.947, respectively. Similarly, when applied to the UWF dataset, the model achieved accuracies of 0.889, 0.913, and 0.923, respectively. These results underscore the efficacy of LGAANet in distinguishing between varying degrees of image quality with high precision.ConclusionTo our knowledge, LGAANet represents the inaugural algorithm trained on an MSHF dataset specifically for fundus IQA, marking a significant milestone in the advancement of computer-aided diagnosis in ophthalmology. This research significantly contributes to the field, offering a novel methodology for the assessment and interpretation of fundus images in the detection and diagnosis of ocular diseases.
Peri- and intra-nodular radiomic features based on 18F-FDG PET/CT to distinguish lung adenocarcinomas from pulmonary granulomas
Authors: Tian Congna , Hu Yujing , Li Shuheng , Zhang Xinchao , Wei Qiang , Li Kang , Chen Xiaolin , Zheng Lu , Yang Xin , Qin Yanan , Bian Yanzhu 
Published: August 2024

ObjectiveTo compare the effectiveness of radiomic features based on 18F-FDG PET/CT images within (intranodular) and around (perinodular) lung nodules/masses in distinguishing between lung adenocarcinoma and pulmonary granulomas.MethodsFor this retrospective study, 18F-FDG PET/CT images were collected for 228 patients. Patients diagnosed with lung adenocarcinoma (n = 156) or granulomas (n = 72) were randomly assigned to a training (n = 159) and validation (n = 69) groups. The volume of interest (VOI) of intranodular, perinodular (1–5 voxels, termed Lesion_margin1 to Lesion_margin5) and total area (intra- plus perinodular region, termed Lesion_total1 to Lesion_total5) on PET/CT images were delineated using PETtumor and Marge tool of segmentation editor. A total of 1,037 radiomic features were extracted separately from PET and CT images, and the optimal features were selected to develop radiomic models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC).ResultsGood and acceptable performance was, respectively, observed in the training (AUC = 0.868, p &lt; 0.001) and validation (AUC = 0.715, p = 0.004) sets for the intranodular radiomic model. Among the perinodular models, the Lesion_margin2 model demonstrated the highest AUC in both sets (0.883 and 0.616, p &lt; 0.001 and p = 0.122). Similarly, in terms of total models, Lesion_total2 model was found to outperform others in the training (AUC = 0.879, p &lt; 0.001) and validation (AUC = 0.742, p = 0.001) sets, slightly surpassing the intranodular model.ConclusionWhen intra- and perinodular radiomic features extracted from the immediate vicinity of the nodule/mass up to 2 voxels distance on 18F-FDG PET/CT imaging are combined, improved differential diagnostic performance in distinguishing between lung adenocarcinomas and granulomas is achieved compared to the intra- and perinodular radiomic features alone.
The association of blood urea nitrogen-to-creatinine ratio and in-hospital mortality in acute ischemic stroke patients with atrial fibrillation: data from the MIMIC-IV database
Authors: Li Bowen , Li Juan , Meng Xin , Yang Shu , Tian Furong , Song Xiang , Liu Junjie 
Published: August 2024

ObjectiveThis research aimed to investigate the association between the blood urea nitrogen-to-creatinine (BUN/Cr) ratio and the rate of in-hospital mortality in patients with acute ischemic stroke (AIS) and atrial fibrillation (AF), who are also receiving care in intensive care unit (ICU).MethodsA retrospective study was conducted using the MIMIC-IV database. We collected data on BUN/Cr levels at admission for patients with AIS and concurrent AF. To assess the association between BUN/Cr and in-hospital mortality rate, statistical analysis was conducted employing multivariable logistic regression models and restricted cubic spline models. These models were utilized to investigate the potential relationship and provide insights into the impact of BUN/Cr on the likelihood of in-hospital mortality. Interaction and subgroup analyses were performed to evaluate the consistency of the correlation.ResultsThere were a total of 856 patients (age ≥ 18 years) with a median age of 78.0 years, of which 466 (54.4%) were female. Out of 856 patients, 182 (21.26%) died in the hospital. Upon controlling for confounding factors, the multivariable logistic regression analysis elucidated that patients falling within the third trisection (Q3 &gt; 22.41 mg/dL) exhibited a noticeably increased susceptibility to in-hospital mortality when contrasted with their counterparts positioned in the second trisection (Q2: 17.2–22.41 mg/dL) (OR = 2.02, 95% CI: 1.26–3.26, p = 0.004). A non-linear J-shaped relationship was observed between BUN/Cr at ICU admission and in-hospital mortality rate (p = 0.027), with a turning point at 19.63 mg/dL. In the threshold analysis, there was a 4% rise in in-hospital mortality for each 1 mg/dL increase in BUN/Cr (OR: 1.04, 95% CI: 1.01–1.06, p = 0.012).ConclusionIn patients with AIS complicated by AF, BUN/Cr at admission shows a J-shaped correlation with in-hospital mortality rate. When BUN/Cr exceeds 19.63 mg/dL, the in-hospital mortality rate increases.
Role of inflammatory biomarkers in mediating the effect of lipids on spontaneous intracerebral hemorrhage: a two-step, two-sample Mendelian randomization study
Authors: Huang Mingsheng , Liu Yiheng , Cheng Yuan , Dai Weiran 
Published: August 2024

BackgroundSpontaneous intracerebral hemorrhage (sICH) is a form of stroke with high mortality rates and significant neurological implications for patients. Abnormalities in lipid metabolism have been implicated in various cardiovascular diseases, yet their relationship with sICH remains insufficiently explored, particularly concerning their association with inflammatory factors.MethodsEmploying a two-sample, two-step Mendelian Randomization approach, combined with data from GWAS datasets, to investigate the causal relationship between plasma lipid levels and sICH. Additionally, the role of inflammatory factors in this relationship was examined, and sensitivity analyses were conducted to ensure the robustness of the results.ResultsThe results indicate a significant causal relationship between 19 plasma lipid metabolites and sICH. Furthermore, mediation analysis revealed that three distinct lipids, namely Sterol ester (27:1/20:2), Phosphatidylcholine (16:0_20:4), and Sphingomyelin (d34:1), exert their influence on sICH through inflammatory factors. TRAIL (OR: 1.078, 95% CI: 1.016–1.144, p = 0.013) and HGF (OR: 1.131, 95% CI: 1.001–1.279, p = 0.049) were identified as significant mediators.ConclusionThis study provides new evidence linking abnormalities in lipid metabolism with sICH and elucidates the role of inflammatory factors as mediators. These findings contribute to a better understanding of the pathogenesis of sICH and offer novel insights and therapeutic strategies for its prevention and treatment.
Inflammo-immune perspective on the association of eight migraine risk factors with migraine: a multi-omics Mendelian randomization study
Authors: Zhao Jiaxi , Chen Rong , Luo Mengqi , Gong Hongping , Li Kaixin , Zhao Qian 
Published: August 2024

BackgroundMigraine risk factors are associated with migraine susceptibility, yet their mechanisms are unclear. Evidence suggests a role for inflammatory proteins and immune cells in migraine pathogenesis. This study aimed to examine the inflammo-immune association between eight migraine risk factors and the disorder.MethodsThis study utilized inverse variance weighted (IVW) method and colocalization analysis to explore potential causal relationships between eight migraine risk factors, migraine, 731 immune cells, and 91 circulating inflammatory proteins. Mediation Mendelian randomization (MR) was further used to confirm the mediating role of circulating inflammatory proteins and immune cells between the eight migraine risk factors and migraine.ResultsMigraine risk factors are linked to 276 immune cells and inflammatory proteins, with cigarettes smoked per day strongly co-localized with CD33-HLA DR+ cells. Despite no co-localization, 23 immune cells/inflammatory proteins relate to migraine. Depression, all anxiety disorders, and sleep apnea are correlated with migraine, and all anxiety disorders are supported by strong co-localization evidence. However, the mediating effect of inflammatory proteins and immune cells between eight migraine risk factors and migraine has not been confirmed.ConclusionWe elucidate the potential causal relationships between eight migraine risk factors, migraine, immune cells, and inflammatory proteins, enhancing our understanding of the molecular etiology of migraine pathogenesis from an inflammatory-immune perspective.
Alpha oscillation mediates the interaction between suicide risk and symptom severity in Major Depressive Disorder
Authors: Zhang Haoran , Liu Xinyu , Su Ziyao , Wang Yingtan , Chen Bingxu , Zhang Zhizhen , Wang Bin , Zhou Jia , Zhang Ling , Zhao Xixi 
Published: August 2024

ObjectiveThe aim of our study was to explore the relationship between changes in neural oscillatory power in the EEG, the severity of depressive-anxiety symptoms, and the risk of suicide in MDD.Methods350 MDD patients’ demographic and clinical data were collected, and their depressive and anxious symptoms were evaluated using HDRS-17 and HAMA-14, along with a suicide risk assessment using the Nurses’ Global Assessment of Suicide Risk (NGASR). EEG data were captured, processed, and analyzed to study brain activity patterns related to MDD. The participants were divided based on suicide risk levels, and statistical analyses, including chi-square, t-tests, Pearson’s correlations were used to explore the associations between brain activity, symptom severity, and suicide risk. Closely related variables were identified and ultimately the optimal model was screened using stepwise regression analysis with a forward strategy, and mediation effects were further used to determine the possible interactions between the variables in the regression model.ResultsThe regression model showed a significant effect of HDRS-17 and alpha power of Medial Occipital Cortex (MOC) on suicide risk, with elevated HDRS-17 increasing suicide risk and elevated alpha power decreasing suicide risk. Mediation effect analyses showed that MOC alpha power partially mediated the effect of depression level on suicide risk, and that an increase in depression severity may lead to a decrease in MOC alpha power, while a decrease in MOC alpha power may lead to an increase in suicide risk.ConclusionThe severity of depression directly increases suicide risk, whereas higher alpha power in the MOC serves as a protective factor, reducing this risk. Notably, MOC alpha power not only directly impacts suicide risk but also mediates the effects of both depression severity and anxiety levels on this risk.LimitationsThe relatively small sample size of this study may limit the representativeness of the overall MDD patient population and the detailed analysis of different subgroups. This study did not delve into the relationship between the severity of cognitive symptoms in MDD patients and suicide risk.
Variability and error in measurement of infant formula powder and water: an experimental study
Authors: Rosenkranz Richard R. , Gonzalez-Alvarez Ana , Acosta Chris , Hooyman Andrew , Hidalgo Jose R. , Ballesteros-Paniagua CindyRomina , Rosenkranz Sara K. 
Published: August 2024

IntroductionFormula feeding is the only viable nutrition alternative for infants 0–6mos who cannot breastfeed. Among the drawbacks of formula feeding, however, is potential dilution or concentration errors in the formula during preparation that may lead to infant health issues. The present study aimed to investigate the accuracy of caregiver measurements as they prepared infant formula under multiple conditions, compared with manufacturer specifications.MethodsA diverse sample of caregivers (N = 84) participated in this cross-over experimental study. Participants hand-scooped infant formula powder and poured water to prepare 4oz. and 7oz. feedings, using both a standardized set of infant formula products and participants’ own products. Linear mixed effects models were used to estimate fixed effects of target amount (4oz. versus 7oz) and products (participant versus researcher) on mean absolute percent error (MAPE) of measurement.ResultsAcross all conditions MAPE was significantly greater for measuring powder than for water (9.0% vs. 4.4%; p &lt; 0.001) with a combined powder and water MAPE at 13.0%. Greater measurement error was associated with the odd-sized 7oz. preparation and participants’ own products.DiscussionWe observed considerable variability and substantial error during infant formula preparation, particularly for hand-scooping of powder, which tended toward higher values than the theoretical gold standard.