bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel CircRNAs in Hub ceRNA Axis Regulate Gastric Cancer Prognosis and Microenvironment
Authors: Li Xianghui , Li Zhiyan , Liu Ping , Ai Shichao , Sun Feng , Hu Qiongyuan , Dong Yuxiang , Xia Xuefeng , Guan Wenxian , Liu Song
Published: November 2021

Gastric cancer (GC) is one of the most prevalent malignancies with an unfavorable survival rate. Immunotherapy may contribute to a better prognosis. However, several phase III trials failed. Circular RNA (circRNA) is a novel type of non-coding RNA, plays a vital role in the progression of tumors. The expression and function of circRNA in the GC immune microenvironment remain obscure. In this study, we utilized a bioinformatic analysis to construct a circRNA/microRNA (miRNA)/messenger RNA (mRNA) network involved in the progression and prognosis of GC. CircRNA DYRK1A_017, circRNA FLNA_118, miR-6512-3p, miR-6270-5p, and VCAN were identified as the key molecules in the hub regulatory axis. Dysregulation of this axis contributed to the cancer-associated signaling pathways (epithelial-mesenchymal transition [EMT], Nuclear factor kappa β-Tumor necrosis factor-α (NFκβ-TNFα) signaling, and angiogenesis) and aberrant immune microenvironment (infiltration by tumor associated macrophage, regulatory T cell, and mast cell). More importantly, the immunosuppressive tumor microenvironment may reveal the mechanism of novel circRNAs in tumors and serve as the target of immunotherapy.
Rule-Based Models for Risk Estimation and Analysis of In-hospital Mortality in Emergency and Critical Care
Authors: Haas Oliver , Maier Andreas , Rothgang Eva
Published: November 2021

We propose a novel method that uses associative classification and odds ratios to predict in-hospital mortality in emergency and critical care. Manual mortality risk scores have previously been used to assess the care needed for each patient and their need for palliative measures. Automated approaches allow providers to get a quick and objective estimation based on electronic health records. We use association rule mining to find relevant patterns in the dataset. The odds ratio is used instead of classical association rule mining metrics as a quality measure to analyze association instead of frequency. The resulting measures are used to estimate the in-hospital mortality risk. We compare two prediction models: one minimal model with socio-demographic factors that are available at the time of admission and can be provided by the patients themselves, namely gender, ethnicity, type of insurance, language, and marital status, and a full model that additionally includes clinical information like diagnoses, medication, and procedures. The method was tested and validated on MIMIC-IV, a publicly available clinical dataset. The minimal prediction model achieved an area under the receiver operating characteristic curve value of 0.69, while the full prediction model achieved a value of 0.98. The models serve different purposes. The minimal model can be used as a first risk assessment based on patient-reported information. The full model expands on this and provides an updated risk assessment each time a new variable occurs in the clinical case. In addition, the rules in the models allow us to analyze the dataset based on data-backed rules. We provide several examples of interesting rules, including rules that hint at errors in the underlying data, rules that correspond to existing epidemiological research, and rules that were previously unknown and can serve as starting points for future studies.
Synthesis of Aminooxy Glycoside Derivatives of the Outer Core Domain of Pseudomonas aeruginosa Lipopolysaccharide
Authors: Si Anshupriya , Sucheck Steven J.
Published: November 2021

Pseudomonas aeruginosa is a highly prevalent gram-negative bacterium that is becoming more difficult to treat because of increasing antibiotic resistance. As chemotherapeutic treatment options diminish, there is an increased need for vaccines. However, the creation of an effective P. aeruginosa vaccine has been elusive despite intensive efforts. Thus, new paradigms for vaccine antigens should be explored to develop effective vaccines. In these studies, we have focused on the synthesis of two L-rhamnose–bearing epitopes common to glycoforms I and II of the outer core domain of Pseudomonas aeruginosa lipopolysaccharide, α-L-Rha-(1→6)-α-D-Glc-(1→4)-α-D-GalN-(Ala)-α-aminooxy (3) and α-L-Rha-(1→3)-β-D-Glc-(1→3)-α-D-GalN-(Ala)-α-aminooxy (4), respectively. The target trisaccharides were both prepared starting from a suitably protected galactosamine glycoside, followed by successive deprotection and glycosylation with suitably protected D-glucose and L-rhamnose thioglycosides. Global deprotection resulted in the formation of targets 3 and 4 in 22 and 35% yield each. Care was required to modify basic reaction conditions to avoid early deprotection of the N-oxysuccinamido group. In summary, trisaccharides related to the L-rhamnose–bearing epitopes common to glycoforms I and II of the outer core domain of Pseudomonas aeruginosa lipopolysaccharide have been prepared as their aminooxy glycosides. The latter are expected to be useful in chemoselective oxime-based bioconjugation reactions to form Pseudomonas aeruginosa vaccines.
Discriminative Dictionary Learning for Autism Spectrum Disorder Identification
Authors: Liu Wenbo , Li Ming , Zou Xiaobing , Raj Bhiksha
Published: November 2021

Autism Spectrum Disorder (ASD) is a group of lifelong neurodevelopmental disorders with complicated causes. A key symptom of ASD patients is their impaired interpersonal communication ability. Recent study shows that face scanning patterns of individuals with ASD are often different from those of typical developing (TD) ones. Such abnormality motivates us to study the feasibility of identifying ASD children based on their face scanning patterns with machine learning methods. In this paper, we consider using the bag-of-words (BoW) model to encode the face scanning patterns, and propose a novel dictionary learning method based on dual mode seeking for better BoW representation. Unlike k-means which is broadly used in conventional BoW models to learn dictionaries, the proposed method captures discriminative information by finding atoms which maximizes both the purity and coverage of belonging samples within one class. Compared to the rich literature of ASD studies from psychology and neural science, our work marks one of the relatively few attempts to directly identify high-functioning ASD children with machine learning methods. Experiments demonstrate the superior performance of our method with considerable gain over several baselines. Although the proposed work is yet too preliminary to directly replace existing autism diagnostic observation schedules in the clinical practice, it shed light on future applications of machine learning methods in early screening of ASD.
Clinical and Genetic Features of Biallelic Mutations in SORD in a Series of Chinese Patients With Charcot-Marie-Tooth and Distal Hereditary Motor Neuropathy
Authors: Liu Xiaoxuan , He Ji , Yilihamu Mubalake , Duan Xiaohui , Fan Dongsheng
Published: November 2021

Biallelic mutations in the sorbitol dehydrogenase (SORD) gene have recently been found to be one of the most frequent causes of autosomal recessive axonal Charcot-Marie-Tooth (CMT2) and distal hereditary motor neuropathy (dHMN). This study was performed to explore the frequency of SORD mutations and correlations of the phenotypic-genetic spectrum in a relatively large Chinese cohort. In this study, we screened a cohort of 485 unrelated Chinese patients with hereditary neuropathy by using Sanger sequencing, next generation sequencing, or whole exome sequencing after PMP22 duplication was initially excluded. SORD mutation was identified in five out of 78 undiagnosed patients. Two individuals carried the previously reported homozygous c.757 delG (p.A253Qfs*27) variant, and three individuals carried the heterozygous c.757delG (p.A253Qfs*27) variant together with a second novel likely pathogenic variant, including c.731 C>T (p.P244L), c.776 C>T (p.A259V), or c.851T>C (p.L284P). The frequency of SORD variants was calculated to be 6.4% (5/78) in unclarified CMT2 and dHMN patients. All patients presented with distal weakness and atrophy in the lower limb, two of whom had minor clinical sensory abnormalities and small fiber neuropathy. Our study provides further information on the genotype and phenotype of patients with SORD mutations.
Risk Factors Promoting External Ventricular Drain Infections in Adult Neurosurgical Patients at the Intensive Care Unit—A Retrospective Study
Authors: Khalaveh Farjad , Fazel Nadia , Mischkulnig Mario , Vossen Matthias Gerhard , Reinprecht Andrea , Dorfer Christian , Roessler Karl , Herta Johannes
Published: November 2021

Objectives: Multiple risk factors have been described to be related to external ventricular drain (EVD) associated infections, with results varying between studies. Former studies were limited by a non-uniform definition of EVD associated infection, thus complicating a comparison between studies. In this regard, we assessed risk factors promoting EVD associated infections and propose a modified practice-oriented definition of EVD associated infections.

Methods: We performed a retrospective, single-center study on patients who were treated with an EVD, at the neurosurgical intensive care unit (ICU) at a tertiary center between 2008 and 2019. Based on microbiological findings and laboratory results, patients were assigned into an infection and a non-infection group. Patient characteristics and potential risk factors were compared between the two groups (p < 0.05). Receiver operating characteristics (ROC) for significant clinical, serum laboratory and cerebrospinal fluid (CSF) parameters were calculated.

Results: In total, 396 patients treated with an EVD were included into the study with a mean age of 54.3 (range: 18–89) years. EVD associated infections were observed in 32 (8.1%) patients. EVD insertion at another hospital (OR 3.86), and an increased CSF sampling frequency of more than every third day (OR 12.91) were detected as major risk factors for an EVD associated infection. The indication for EVD insertion, surgeon's experience, the setting of EVD insertion (ICU vs. operating room) and the operating time did not show any significant differences between the two groups. Furthermore, ROC analysis showed that clinical, serum laboratory and CSF parameters did not provide specific prediction of EVD associated infections (specificity 44.4%). This explains the high overtreatment rate in our cohort with the majority of our patients who received intrathecal vancomycin (63.3%), having either negative microbiological results (n = 12) or were defined as contaminations (n = 7).

Conclusions: Since clinical parameters and blood analyzes are not very predictive to detect EVD associated infections in neurosurgical patients, sequential but not too frequent microbiological and laboratory analysis of CSF are still necessary. Furthermore, we propose a uniform classification for EVD associated infections to allow comparability between studies and to sensitize the treating physician in determining the right treatment.
Loss of Caveolin-1 Impairs Light Flicker-Induced Neurovascular Coupling at the Optic Nerve Head
Authors: Loo Jing Hong , Lee Ying Shi , Woon Chang Yi , Yong Victor H. K. , Tan Bingyao , Schmetterer Leopold , Chong Rachel S.
Published: November 2021

Glaucoma is a neurodegenerative disease, which results in characteristic visual field defects. Intraocular pressure (IOP) remains the main risk factor for this leading cause of blindness. Recent studies suggest that disturbances in neurovascular coupling (NVC) may be associated with glaucoma. The resultant imbalance between vascular perfusion and neuronal stimulation in the eye may precede retinal ganglion cell (RGC) loss and increase the susceptibility of the eye to raised IOP and glaucomatous degeneration. Caveolin-1 (Cav-1) is an integral scaffolding membrane protein found abundantly in retinal glial and vascular tissues, with possible involvement in regulating the neurovascular coupling response. Mutations in Cav-1 have been identified as a major genetic risk factor for glaucoma. Therefore, we aim to evaluate the effects of Cav-1 depletion on neurovascular coupling, retinal vessel characteristics, RGC density and the positive scotopic threshold response (pSTR) in Cav-1 knockout (KO) versus wild type C57/Bl6 mice (WT). Following light flicker stimulation of the retina, Cav-1 KO mice showed a smaller increase in perfusion at the optic nerve head and peripapillary arteries, suggesting defective neurovascular coupling. Evaluation of the superficial capillary plexus in Cav-1 KO mice also revealed significant differences in vascular morphology with higher vessel density, junction density and decreased average vessel length. Cav-1 KO mice exhibited higher IOP and lower pSTR amplitude. However, there was no significant difference in RGC density between Cav-1 KO and wild type mice. These findings highlight the role of Cav-1 in regulating neurovascular coupling and IOP and suggest that the loss of Cav-1 may predispose to vascular dysfunction and decreased RGC signaling in the absence of structural loss. Current treatment for glaucoma relies heavily on IOP-lowering drugs, however, there is an immense potential for new therapeutic strategies that increase Cav-1 expression or augment its downstream signaling in order to avert vascular dysfunction and glaucomatous change.
Toward Learning in Neuromorphic Circuits Based on Quantum Phase Slip Junctions
Authors: Cheng Ran , Goteti Uday S. , Walker Harrison , Krause Keith M. , Oeding Luke , Hamilton Michael C.
Published: November 2021

We explore the use of superconducting quantum phase slip junctions (QPSJs), an electromagnetic dual to Josephson Junctions (JJs), in neuromorphic circuits. These small circuits could serve as the building blocks of neuromorphic circuits for machine learning applications because they exhibit desirable properties such as inherent ultra-low energy per operation, high speed, dense integration, negligible loss, and natural spiking responses. In addition, they have a relatively straight-forward micro/nano fabrication, which shows promise for implementation of an enormous number of lossless interconnections that are required to realize complex neuromorphic systems. We simulate QPSJ-only, as well as hybrid QPSJ + JJ circuits for application in neuromorphic circuits including artificial synapses and neurons, as well as fan-in and fan-out circuits. We also design and simulate learning circuits, where a simplified spike timing dependent plasticity rule is realized to provide potential learning mechanisms. We also take an alternative approach, which shows potential to overcome some of the expected challenges of QPSJ-based neuromorphic circuits, via QPSJ-based charge islands coupled together to generate non-linear charge dynamics that result in a large number of programmable weights or non-volatile memory states. Notably, we show that these weights are a function of the timing and frequency of the input spiking signals and can be programmed using a small number of DC voltage bias signals, therefore exhibiting spike-timing and rate dependent plasticity, which are mechanisms to realize learning in neuromorphic circuits.
Effects of Daily Iron Supplementation on Motor Development and Brain Connectivity in Preterm Infants: A Diffusion Magnetic Resonance Study
Authors: Li Mingyan , Ji Chai , Xuan Weifeng , Chen Weijun , Lv Ying , Liu Tingting , You Yuqing , Gao Fusheng , Zheng Quan , Shao Jie
Published: November 2021

Objectives: The aim of the study is to demonstrate the characteristic of motor development and MRI changes of related brain regions in preterm infants with different iron statuses and to determine whether the daily iron supplementation can promote motor development for preterm in early infancy.

Methods: The 63 preterm infants were grouped into non-anemia with higher serum ferritin (NA-HF) group and anemia with lower serum ferritin (A-LF) group according to their lowest serum Hb level in the neonatal period as well as the sFer at 3 months old. Forty-nine participants underwent MRI scans and Infant Neurological International Battery (INFANIB) at their 3 months. At 6 months of corrected age, these infants received the assessment of Peabody Developmental Motor Scales (PDMS) after 2 mg/kg/day iron supplementation.

Results: In total, 19 preterm infants were assigned to the NA-HF group while 44 preterm infants to the A-LF groups. The serum ferritin (sFer) level of the infants in A-LF group was lower than that in NA-HF group (44.0 ± 2.8 mg/L vs. 65.1 ± 2.8 mg/L, p < 0.05) and was with poorer scores of INFANIB (66.8 ± 0.9 vs. 64.4 ± 0.6, p < 0.05) at 3 months old. The structural connectivity between cerebellum and ipsilateral thalamus in the NA-HF group was significantly stronger than that in the A-LF group (n = 17, 109.76 ± 23.8 vs. n = 32, 70.4 ± 6.6, p < 0.05). The decreased brain structural connectivity was positively associated with the scores of PDMS (r = 0.347, p < 0.05). After 6 months of routine iron supplementation, no difference in Hb, MCV, MCHC, RDW, and sFer was detected between A-LF and NA-HF groups as well as the motor scores of PDMS-2 assessments.

Conclusion: Iron status at early postnatal period of preterm infant is related to motor development and the enrichment of brain structural connectivity. The decrease in brain structural connectivity is related to the motor delay. After supplying 2 mg/kg of iron per day for 6 months, the differences in the iron status and motor ability between the A-LF and NA-HF groups were eliminated.
Challenges Ahead for a Rational Analysis of Vitamin D in Athletes
Authors: Araujo Pedro , Méndez-Dávila Cioly
Published: November 2021

Vitamin D is an essential vitamin for the normal formation of bones and calcium absorption. It is synthesized into our body through sunlight exposure and obtained by consuming foods rich in vitamin D (e.g., fatty fish, eggs yolk, dairy products). Its benefits on the health and performance of athletes are well documented. This article outlines some analytical challenges concerning the analytical quantification of vitamin D for its optimal intake, namely, a comprehensive study of the variability of the assay before categorizing any method as the golden standard, assurance of sample comparability to draw meaningful correlations, revision of the intake guidance based on appropriate statistical power analysis, and the implementation of rational strategies for preventing the underlying mechanism of preanalytical factors. Addressing these challenges will enable the effective management of vitamin D in the sports sector.
Development and Internal Validation of a Preoperative Prediction Model for Sentinel Lymph Node Status in Breast Cancer: Combining Radiomics Signature and Clinical Factors
Authors: Wang Chunhua , Chen Xiaoyu , Luo Hongbing , Liu Yuanyuan , Meng Ruirui , Wang Min , Liu Siyun , Xu Guohui , Ren Jing , Zhou Peng
Published: November 2021

Purpose

To develop and internally validate a nomogram combining radiomics signature of primary tumor and fibroglandular tissue (FGT) based on pharmacokinetic dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical factors for preoperative prediction of sentinel lymph node (SLN) status in breast cancer patients.

Methods

This study retrospectively enrolled 186 breast cancer patients who underwent pretreatment pharmacokinetic DCE-MRI with positive (n = 93) and negative (n = 93) SLN. Logistic regression models and radiomics signatures of tumor and FGT were constructed after feature extraction and selection. The radiomics signatures were further combined with independent predictors of clinical factors for constructing a combined model. Prediction performance was assessed by receiver operating characteristic (ROC), calibration, and decision curve analysis. The areas under the ROC curve (AUCs) of models were corrected by 1,000-times bootstrapping method and compared by Delong’s test. The added value of each independent model or their combinations was also assessed by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. This report referred to the “Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis” (TRIPOD) statement.

Results

The AUCs of the tumor radiomic model (eight features) and the FGT radiomic model (three features) were 0.783 (95% confidence interval [CI], 0.717–0.849) and 0.680 (95% CI, 0.604–0.757), respectively. A higher AUC of 0.799 (95% CI, 0.737–0.862) was obtained by combining tumor and FGT radiomics signatures. By further combining tumor and FGT radiomics signatures with progesterone receptor (PR) status, a nomogram was developed and showed better discriminative ability for SLN status [AUC 0.839 (95% CI, 0.783–0.895)]. The IDI and NRI indices also showed significant improvement when combining tumor, FGT, and PR compared with each independent model or a combination of any two of them (all p < 0.05).

Conclusion

FGT and clinical factors improved the prediction performance of SLN status in breast cancer. A nomogram integrating the DCE-MRI radiomics signature of tumor and FGT and PR expression achieved good performance for the prediction of SLN status, which provides a potential biomarker for clinical treatment decision-making.
A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Population
Authors: Liu Jie , Zhang Jian , Huang Haodong , Wang Yunting , Zhang Zuyue , Ma Yunfeng , He Xiangqian
Published: November 2021

Objective: We explored the risk factors for intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) and constructed a prediction model based on machine learning algorithms.

Methods: A retrospective study including 1,398 KD patients hospitalized in 7 affiliated hospitals of Chongqing Medical University from January 2015 to August 2020 was conducted. All patients were divided into IVIG-responsive and IVIG-resistant groups, which were randomly divided into training and validation sets. The independent risk factors were determined using logistic regression analysis. Logistic regression nomograms, support vector machine (SVM), XGBoost and LightGBM prediction models were constructed and compared with the previous models.

Results: In total, 1,240 out of 1,398 patients were IVIG responders, while 158 were resistant to IVIG. According to the results of logistic regression analysis of the training set, four independent risk factors were identified, including total bilirubin (TBIL) (OR = 1.115, 95% CI 1.067–1.165), procalcitonin (PCT) (OR = 1.511, 95% CI 1.270–1.798), alanine aminotransferase (ALT) (OR = 1.013, 95% CI 1.008–1.018) and platelet count (PLT) (OR = 0.998, 95% CI 0.996–1). Logistic regression nomogram, SVM, XGBoost, and LightGBM prediction models were constructed based on the above independent risk factors. The sensitivity was 0.617, 0.681, 0.638, and 0.702, the specificity was 0.712, 0.841, 0.967, and 0.903, and the area under curve (AUC) was 0.731, 0.814, 0.804, and 0.874, respectively. Among the prediction models, the LightGBM model displayed the best ability for comprehensive prediction, with an AUC of 0.874, which surpassed the previous classic models of Egami (AUC = 0.581), Kobayashi (AUC = 0.524), Sano (AUC = 0.519), Fu (AUC = 0.578), and Formosa (AUC = 0.575).

Conclusion: The machine learning LightGBM prediction model for IVIG-resistant KD patients was superior to previous models. Our findings may help to accomplish early identification of the risk of IVIG resistance and improve their outcomes.
Quantitative Analysis of the Efficacy of PARP Inhibitors as Maintenance Therapy in Recurrent Ovarian Cancer
Authors: Gao Lili , Chen Rui , Li Ting , Li Lujin , Zheng Qingshan
Published: November 2021

Objective: This study aimed to establish a pharmacodynamic model and to screen reasonable covariates to quantitatively describe the efficacy of poly (ADP-ribose) polymerase inhibitors (PARPis) as maintenance treatment for recurrent ovarian cancer (ROC).

Methods: The log normal hazard function model was established by using progression-free survival (PFS) data of 1,169 patients from published randomized trials on FDA-approved PARP inhibitors (olaparib, niraparib, and rucaparib). Monte Carlo simulation was used to compare PFS values in different scenarios, such as monotherapy (administered alone) and combination therapy (PARPis combined with chemo- or target-therapies), different biomarker statuses, and different PARP inhibitors. PFS was also estimated.

Results: The study showed that the median PFS was 8.5 months with monotherapy and 16.0 months with combination therapy. The median PFS of patients with the BRCA mutation, BRCA wild-type, and HRD-positivity were 11.0, 7.5, and 9.0 months in monotherapy, respectively, and 23.0, 14.0 and 17.5 months, in combination therapy, respectively. In addition, the median PFS of olaparib, niraparib, and rucaparib monotherapy were about 9.5, 10.5, and 12.0 months, respectively, and about 19.0, 20.0, and 25 months, respectively, in combination therapy. The median PFS values in combination with cediranib, bevacizumab, and chemotherapy were approximately 17.0, 12.5 and 19.5 months, respectively.

Conclusion: PARPi combination therapy is more effective as maintenance treatment for ROC than monotherapy, and the efficacy of PARPis in combination with chemotherapy is higher than that of the combination with antiangiogenic drugs. We found that the PFS of BRCA wild-type was similar to that of HRD-positive patients, and there was no significant difference in PFS between olaparib, niraparib, and rucaparib, which provides necessary quantitative information for the clinical practice of PARPis in the treatment of ROC.
Recent Research Progress (2015–2021) and Perspectives on the Pharmacological Effects and Mechanisms of Tanshinone IIA
Authors: Zhong Chenhui , Lin Zuan , Ke Liyuan , Shi Peiying , Li Shaoguang , Huang Liying , Lin Xinhua , Yao Hong
Published: November 2021

Tanshinone IIA (Tan IIA) is an important characteristic component and active ingredient in Salvia miltiorrhiza, and its various aspects of research are constantly being updated to explore its potential application. In this paper, we review the recent progress on pharmacological activities and the therapeutic mechanisms of Tan IIA according to literature during the years 2015–2021. Tan IIA shows multiple pharmacological effects, including anticarcinogenic, cardiovascular, nervous, respiratory, urinary, digestive, and motor systems activities. Tan IIA modulates multi-targets referring to Nrf2, AMPK, GSK-3β, EGFR, CD36, HO-1, NOX4, Beclin-1, TLR4, TNF-α, STAT3, Caspase-3, and bcl-2 proteins and multi-pathways including NF-κB, SIRT1/PGC1α, MAPK, SREBP-2/Pcsk9, Wnt, PI3K/Akt/mTOR pathways, TGF-β/Smad and Hippo/YAP pathways, etc., which directly or indirectly influence disease course. Further, with the reported targets, the potential effects and possible mechanisms of Tan IIA against diseases were predicted by bioinformatic analysis. This paper provides new insights into the therapeutic effects and mechanisms of Tan IIA against diseases.
Insulin Resistance Remission Following Laparoscopic Roux-en-Y Gastric Bypass and Laparoscopic Sleeve Gastrectomy in Chinese Type 2 Diabetes Mellitus Patients With a Body Mass Index of 27.5–32.5 kg/m2
Authors: Luo Ping , Cao Yaoquan , Li Pengzhou , Wang Guohui , Song Zhi , Li Weizheng , Su Zhihong , Zhou Hui , Yi Xianhao , Fu Zhibing , Sun Xulong , Tang Haibo , Cui Beibei , Yu Qianqian , Zhu Liyong , Zhu Shaihong
Published: November 2021

Background: Insulin resistance (IR) is closely associated with the pathogenesis of type 2 diabetes mellitus (T2DM). However, remission of insulin sensitivity after bariatric surgery in patients with T2DM and a body mass index (BMI) of 27.5–32.5 kg/m2 has not been fully elucidated.

Methods: Thirty-six T2DM patients with a BMI of 27.5–32.5 kg/m2 were prospectively consecutively recruited for laparoscopic Roux-en-Y gastric bypass (LRYGB) or laparoscopic sleeve gastrectomy (LSG). Hyperinsulinemic euglycemic clamp, oral glucose tolerance test (OGTT), and other indicators were tested at baseline and 6 months postoperative. Glucose disposal rate (GDR), time to reach euglycemia, homeostatic model assessment of IR, quantitative insulin sensitivity check index (QUICKI), triglyceride glucose (TyG) index, 30-min insulinogenic index (IGI30), and disposition index (DI) were calculated at baseline and 6 months after surgery. The criterion for remission in T2DM patients was the achievement of the triple composite endpoint.

Results: Anthropometric and glucolipid metabolism parameters significantly improved following surgery. The GDR increased significantly from baseline to 6 months after LRYGB (from 4.28 ± 1.70 mg/kg/min to 8.47 ± 1.89 mg/kg/min, p < 0.0001) and LSG (from 3.18 ± 1.36 mg/kg/min to 7.09 ± 1.69 mg/kg/min, p < 0.001). The TyG index decreased after surgery (RYGB group, from 9.93 ± 1.03 to 8.60 ± 0.43, p < 0.0001; LSG group, from 10.04 ± 0.79 to 8.72 ± 0.65, p = 0.0002). There was a significant reduction in the IGI30 (RYGB group, from 2.04 ± 2.12 to 0.83 ± 0.47, p = 0.005; LSG group, from 2.12 ± 1.73 to 0.92 ± 0.66, p = 0.001). The mean DI significantly increased from 1.14 ± 1.35 to 7.11 ± 4.93 in the RYGB group (p = 0.0001) and from 1.25 ± 1.78 to 5.60 ± 4.58 in the LSG group (p = 0.003). Compared with baseline, HOMR-IR, QUICKI, area under the curve-C-peptide release test (AUC-CRT), and AUC-OGTT were significantly changed at 6 months postoperative. Overall, 52.63% of patients in the LRYGB group versus 29.41% of patients in the LSG group achieved the triple composite endpoint.

Conclusion: Both LRYGB and LSG effectively induced remission of IR in patients with T2DM and a BMI of 27.5–32.5 kg/m2.
Attentional Capture From Inside vs. Outside the Attentional Focus
Authors: Manini Greta , Botta Fabiano , Martín-Arévalo Elisa , Ferrari Vera , Lupiáñez Juan
Published: November 2021

In this study, we jointly reported in an empirical and a theoretical way, for the first time, two main theories: Lavie’s perceptual load theory and Gaspelin et al.’s attentional dwelling hypothesis. These theories explain in different ways the modulation of the perceptual load/task difficulty over attentional capture by irrelevant distractors and lead to the observation of the opposite results with similar manipulations. We hypothesized that these opposite results may critically depend on the distractor type used by the two experimental procedures (i.e., distractors inside vs. outside the attentional focus, which could be, respectively, considered as potentially relevant vs. completely irrelevant to the main task). Across a series of experiments, we compared both theories within the same paradigm by manipulating both the perceptual load/task difficulty and the distractor type. The results were strongly consistent, suggesting that the influence of task demands on attentional capture varies as a function of the distractor type: while the interference from (relevant) distractors presented inside the attentional focus was consistently higher for high vs. low load conditions, there was no modulation by (irrelevant) distractors presented outside the attentional focus. Moreover, we critically analyzed the theoretical conceptualization of interference using both theories, disentangling important outcomes for the dwelling hypothesis. Our results provide specific insights into new aspects of attentional capture, which can critically redefine these two predominant theories.
Analyzing Healthcare Facility Resilience: Scientometric Review and Knowledge Map
Authors: Li Lingzhi , Liao Shuni , Yuan Jingfeng , Wang Endong , She Jianjun
Published: November 2021

In contemporary “high-risk” society, unexpected disasters (epidemics and extreme weather) and chronic pressures (aging problems) put tremendous pressure on healthcare facilities. Enhancing the healthcare facilities' resilience ability to resist, absorb, and respond to disaster disruptions is urgent. This study presents a scientometric review for healthcare facility resilience research. A total of 374 relevant articles published between 2000 and 2020, collected from Web of Science (WoS) core collection database, Scopus database and MEDLINE database were reviewed and analyzed. The results indicated that research on resilience in healthcare facilities went through three development periods, and the research involved countries or institutions that are relatively scattered. The studies have been focused on the subject categories of engineering, public, environmental, and occupational health. The keywords of “resilience,” “hospital,” “disaster,” “healthcare,” and “healthcare facility” had the most frequency. Furthermore, based on the literature co-citation networks and content analysis, the detected seven co-citation clusters were grouped into four knowledge domains: climate change impact, strengthening resilience in response to war and epidemic, resilience assessment of healthcare facility, and the applications of information system. Moreover, the timeline view of literature reflected the evolution of each domain. Finally, a knowledge map for resilience of healthcare facilities was put forward, in which critical research contents, current knowledge gaps, and future research work were discussed. This contribution will promote researchers and practitioners to detect the hot topics, fill the knowledge gaps, and extend the body of research on resilience of healthcare facilities.
A Prediction Model for High Risk of Positive RT-PCR Test Results in COVID-19 Patients Discharged From Wuhan Leishenshan Hospital, China
Authors: Qian Yawei , Zeng Guang , Pan Yue , Liu Yang , Zhang Limao , Li Kun
Published: November 2021

Several recent studies have reported that a few patients had positive SARS-CoV-2 RNA tests after hospital discharge. The high-risk factors associated with these patients remain to be identified. A total of 463 patients with COVID-19 discharged from Leishenshan Hospital in Wuhan, China, between February 8 and March 8, 2020 were initially enrolled, and 351 patients with at least 2 weeks of follow-up were finally included. Seventeen of the 351 discharged patients had positive tests for SARS-CoV-2 RNA. Based on clinical characteristics and mathematical modeling, patients with shorter hospital stays and less oxygen desaturation were at higher risk of SARS-CoV-2 RNA reoccurrence after discharge. Notably, traditional Chinese medicine treatment offered extensive benefits to reduce risk. Particular attention should be paid to those patients with high risk, and traditional Chinese medicine should be advocated.
Cystatin C and Iris: Advances in the Evaluation of Kidney Function in Critically Ill Dog
Authors: Paes-Leme Fabiola de Oliveira , Souza Eliana M. , Paes Paulo Ricardo Oliveira , Gomes Maderleine Geisa , Muniz Felipe Santos , Campos Marco Túlio Gomes , Peixoto Renata Barbosa , Vaz de Melo Patricia Donado , Arndt Marcio H. L. , Costa Val Adriane
Published: November 2021

Critically ill hospitalized dogs are subject to certain complications, being acute kidney injury (AKI) a common one. Early diagnosis is crucial, and Cystatin C (CysC) is a reliable and early biomarker. The International Society of Renal Interest (IRIS) states that AKI severity can be assessed by mild changes in creatinine serum levels or reduction of urine output that cannot be considered biomarkers of renal injury but failure or insufficiency. Twenty-eight dogs admitted to the Intensive Care Unit under risk factors for the development of AKI were evaluated. Blood samples were collected for determination of sCr and CysC at admission and after 24, 48, and 72 h. Urine output was measured by daily monitoring, measured by collection in a closed system. The results showed the incidence of AKI was 67.9% based on the IRIS criteria and 78.6% based on cystatin C in critically ill patients' dogs. The measurement of serum cystatin C immediately on admission to the ICU was superior in the early identification of patients with AKI when compared to the IRIS classification and serum creatinine in critically ill dogs.
State Monitoring Method for Tool Wear in Aerospace Manufacturing Processes Based on a Convolutional Neural Network (CNN)
Authors: Dai Wei , Liang Kui , Wang Bin
Published: November 2021

In the aerospace manufacturing field, tool conditions are essential to ensure the production quality for aerospace parts and reduce processing failures. Therefore, it is extremely necessary to develop a suitable tool condition monitoring method. Thus, we propose a tool wear process state monitoring method for aerospace manufacturing processes based on convolutional neural networks to recognize intermediate abnormal states in multi-stage processes. There are two innovations and advantages of the proposed approach: one is that the criteria for judging abnormal conditions are extended, which is more useful for practical application. The other is that the proposed approach solved the influence of feature-to-recognition stability. Firstly, the tool wear level was divided into different state modes according to the probability density interval based on the kernel density estimation (KDE), and the corresponding state modes were connected to obtain the point-to-point control limit. Then, the state recognition model based on a convolutional neural network (CNN) was developed, and the sensitivity of the monitoring window was considered in the model. Finally, open-source datasets were used to verify the feasibility of the proposed method, and the results demonstrated the applicability of the proposed method in practice for tool condition monitoring.
Effects of Adding Active Elements to Aluminum-Based Filler Alloys on the Bonding of 6061 Aluminum Alloy and Alumina
Authors: Sun Yu-Kai , Chang Shih-Ying , Tsao Lung-Chuan , Chuang Tung-Han , Zhang Guo-Zhan , Yeh Chih-Yi
Published: November 2021

In this study, AA6061/AA6061 and AA6061/alumina were directly brazed with Al10.8Si10Cu, Al10Si10Cu4Ti and Al10Si10Cu4Ti0.1RE filler alloys at 530 °C for 10 min without the use of flux. The addition of titanium and rare-earth elements into Al10.8Si10Cu alloy effectively improved the bonding shear strengths of AA6061/AA6061 and AA6061/alumina joints. The highest joint shear strengths were 61.1 and 19.2 MPa, respectively. The Al10.8Si10Cu filler alloy without titanium and rare-earth elements could not wet on the alumina and caused failure of the AA6061/alumina joint. The shear strengths of the AA6061/AA6061 and AA6061/alumina joints both strongly depended on the active element addition. Due to the high chemical activity of the rare-earth elements, they formed AlLa between the Al10Si10Cu4Ti0.1RE filler alloy and alumina. The addition of rare-earth elements into Al10Si10Cu4Ti filler alloy resulted in significant enhancement of the average bond strength of AA6061/alumina joints, from 8.0 to 14.8 MPa.
Biological Planning of Radiation Dose Based on In Vivo Dosimetry for Postoperative Vaginal-Cuff HDR Interventional Radiotherapy (Brachytherapy)
Authors: Soror Tamer , Chafii Ramin , Lancellotta Valentina , Tagliaferri Luca , Kovács György
Published: November 2021

(1) Background: Postoperative vaginal-cuff HDR interventional radiotherapy (brachytherapy) is a standard treatment in early-stage endometrial cancer. This study reports the effect of in vivo dosimetry-based biological planning for two different fractionation schedules on the treatment-related toxicities. (2) Methods: 121 patients were treated. Group A (82) received 21 Gy in three fractions. Group B (39) received 20 Gy in four fractions. The dose was prescribed at a 5 mm depth or to the applicator surface according to the distance between the applicator and the rectum. In vivo dosimetry measured the dose of the rectum and/or urinary bladder. With a high measured dose, the dose prescription was changed from a 5 mm depth to the applicator surface. (3) Results: The median age was 66 years with 58.8 months mean follow-up. The dose prescription was changed in 20.7% of group A and in 41% of group B. Most toxicities were grade 1–2. Acute urinary toxicities were significantly higher in group A. The rates of acute and late urinary toxicities were significantly higher with a mean bladder dose/fraction of >2.5 Gy and a total bladder dose of >7.5 Gy. One patient had a vaginal recurrence. (4) Conclusions: Both schedules have excellent local control and acceptable rates of toxicities. Using in vivo dosimetry-based biological planning yielded an acceptable dose to the bladder and rectum.
Innate Immune Mechanisms and Immunotherapy of Myeloid Malignancies
Authors: Small Sara , Numan Yazan , Platanias Leonidas C.
Published: November 2021

Similar to other cancers, myeloid malignancies are thought to subvert the immune system during their development. This subversion occurs via both malignant cell-autonomous and non-autonomous mechanisms and involves manipulation of the innate and adaptive immune systems. Multiple strategies are being studied to rejuvenate, redirect, or re-enforce the immune system in order to fight off myeloid malignancies. So far, the most successful strategies include interferon treatment and antibody-based therapies, though chimeric antigen receptor (CAR) cells and immune checkpoint inhibitors are also promising therapies. In this review, we discuss the inherent immune mechanisms of defense against myeloid malignancies, currently-approved agents, and agents under investigation. Overall, we evaluate the efficacy and potential of immuno-oncology in the treatment of myeloid malignancies.
Human iPSC-Derived Neurons as A Platform for Deciphering the Mechanisms behind Brain Aging
Authors: Chao Chuan-Chuan , Shen Po-Wen , Tzeng Tsai-Yu , Kung Hsing-Jien , Tsai Ting-Fen , Wong Yu-Hui
Published: November 2021

With an increased life expectancy among humans, aging has recently emerged as a major focus in biomedical research. The lack of in vitro aging models—especially for neurological disorders, where access to human brain tissues is limited—has hampered the progress in studies on human brain aging and various age-associated neurodegenerative diseases at the cellular and molecular level. In this review, we provide an overview of age-related changes in the transcriptome, in signaling pathways, and in relation to epigenetic factors that occur in senescent neurons. Moreover, we explore the current cell models used to study neuronal aging in vitro, including immortalized cell lines, primary neuronal culture, neurons directly converted from fibroblasts (Fib-iNs), and iPSC-derived neurons (iPSC-iNs); we also discuss the advantages and limitations of these models. In addition, the key phenotypes associated with cellular senescence that have been observed by these models are compared. Finally, we focus on the potential of combining human iPSC-iNs with genome editing technology in order to further our understanding of brain aging and neurodegenerative diseases, and discuss the future directions and challenges in the field.
Targeting the PI3K/Akt/mTOR Pathway in Hepatocellular Carcinoma
Authors: Sun Eun Jin , Wankell Miriam , Palamuthusingam Pranavan , McFarlane Craig , Hebbard Lionel
Published: November 2021

Despite advances in the treatment of cancers through surgical procedures and new pharmaceuticals, the treatment of hepatocellular carcinoma (HCC) remains challenging as reflected by low survival rates. The PI3K/Akt/mTOR pathway is an important signaling mechanism that regulates the cell cycle, proliferation, apoptosis, and metabolism. Importantly, deregulation of the PI3K/Akt/mTOR pathway leading to activation is common in HCC and is hence the subject of intense investigation and the focus of current therapeutics. In this review article, we consider the role of this pathway in the pathogenesis of HCC, focusing on its downstream effectors such as glycogen synthase kinase-3 (GSK-3), cAMP-response element-binding protein (CREB), forkhead box O protein (FOXO), murine double minute 2 (MDM2), p53, and nuclear factor-κB (NF-κB), and the cellular processes of lipogenesis and autophagy. In addition, we provide an update on the current ongoing clinical development of agents targeting this pathway for HCC treatments.
Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development
Authors: Ruan Yao , Chen Xiao-Hui , Jiang Feng , Liu Yan-Guang , Liang Xiao-Long , Lv Bo-Min , Zhang Hong-Yu , Zhang Qing-Ye
Published: November 2021

The network module-based method has been used for drug repositioning. The traditional drug repositioning method only uses the gene characteristics of the drug but ignores the drug-triggered metabolic changes. The metabolic network systematically characterizes the connection between genes, proteins, and metabolic reactions. The differential metabolic flux distribution, as drug metabolism characteristics, was employed to cluster the agents with similar MoAs (mechanism of action). In this study, agents with the same pharmacology were clustered into one group, and a total of 1309 agents from the CMap database were clustered into 98 groups based on differential metabolic flux distribution. Transcription factor (TF) enrichment analysis revealed the agents in the same group (such as group 7 and group 26) were confirmed to have similar MoAs. Through this agent clustering strategy, the candidate drugs which can inhibit (Japanese encephalitis virus) JEV infection were identified. This study provides new insights into drug repositioning and their MoAs.
Recent Advances on 2D Materials towards 3D Printing
Authors: Gómez I. Jénnifer , Alegret Nuria , Dominguez-Alfaro Antonio , Vázquez Sulleiro Manuel
Published: November 2021

In recent years, 2D materials have been implemented in several applications due to their unique and unprecedented properties. Several examples can be named, from the very first, graphene, to transition-metal dichalcogenides (TMDs, e.g., MoS2), two-dimensional inorganic compounds (MXenes), hexagonal boron nitride (h-BN), or black phosphorus (BP). On the other hand, the accessible and low-cost 3D printers and design software converted the 3D printing methods into affordable fabrication tools worldwide. The implementation of this technique for the preparation of new composites based on 2D materials provides an excellent platform for next-generation technologies. This review focuses on the recent advances of 3D printing of the 2D materials family and its applications; the newly created printed materials demonstrated significant advances in sensors, biomedical, and electrical applications.
Functional Nanoscale Phase Separation and Intertwined Order in Quantum Complex Materials
Authors: Campi Gaetano , Bianconi Antonio
Published: November 2021

Nanoscale phase separation (NPS), characterized by particular types of correlated disorders, plays an important role in the functionality of high-temperature superconductors (HTS). Our results show that multiscale heterogeneity is an essential ingredient of quantum functionality in complex materials. Here, the interactions developing between different structural units cause dynamical spatiotemporal conformations with correlated disorder; thus, visualizing conformational landscapes is fundamental for understanding the physical properties of complex matter and requires advanced methodologies based on high-precision X-ray measurements. We discuss the connections between the dynamical correlated disorder at nanoscale and the functionality in oxygen-doped perovskite superconducting materials.