bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of probiotics for regulation of inflammatory response in radiation-induced enteritis
Authors: Lee Sung Uk , Jang Bum-Sup , Na Yi Rang , Lee Sun Hwa , Han Sunwoo , Chang Ji Hyun , Kim Hak Jae 
Published: February 2023

Abstract
Purpose: The purpose of this study was to investigate the role of probiotics in radiation enteritis using in vivo mice.
Methods: A total of 40 mice were randomly assigned to four groups: control, probiotics, radiotherapy (RT), and RT + probiotics. For the group of probiotics, 0.2 mL of solution that contained 1.0 × 108 colony-forming units (CFU) of Lactobacillus rhamnosus GG (LGG) was used and orally administered daily until sacrifice. For RT, a single dose of 14 Gy was administered using a 6 mega-voltage photon beam to the abdominopelvic area. Mice were sacrifice at day 4 (S1) and day 7 (S2) after RT. Their jejunum, colon, and stool were collected. A multiplex cytokine assay and 16s ribosomal RNA amplicon sequencing were then performed.
Results: Regarding cytokine concentrations in tissues, pro-inflammatory cytokines TNF, IL-6, and MCP-1 showed decreased protein levels in colon tissues of the RT + probiotics group than in the RT group. The abundance of microbes showed no significant difference between RT + probiotics and RT groups except increased alpha-diversity in the stool at S2 of the RT + probiotics group. Probiotics-related and anti-inflammation-related microbes were dominant in the jejunum, colon, and stool from early days after administration of probiotics (probiotics or RT + probiotics groups). Differentially predicted metabolic pathways associated with anti-inflammatory process were found in the RT + probiotics group compared to the RT alone group.
Conclusion: Protective effects of probiotics on radiation enteritis were potentially derived from dominant anti-inflammation-related microbes and metabolites.
Improving air pollutant prediction in Henan Province, China, by enhancing the concentration prediction accuracy using autocorrelation errors and an Informer deep learning model
Authors: Cai Kun , Zhang Xusheng , Zhang Ming , Ge Qiang , Li Shenshen , Qiao Baojun , Liu Yang 
Published: February 2023

Abstract
Air pollution is an important issue affecting sustainable development in China, and accurate air quality prediction has become an important means of air pollution control. At present, traditional methods, such as deterministic and statistical approaches, have large prediction errors and cannot provide effective information to prevent the negative effects of air pollution. Therefore, few existing methods obtain accurate air pollutant time series predictions. To this end, a deep learning-based air pollutant prediction method, namely, the autocorrelation error-Informer (AE-Informer) model, is proposed in this study. The model implements the autocorrelation error (AE) based on the Informer model. The AE-Informer model is used to predict the hourly concentrations of multiple air pollutants, including PM10, PM2.5, NO2, and O3. The experimental results show that the mean absolute error (MAE) and root mean square error (RMSE) values of AE-Informer in multivariate prediction are 3% less than those of the Informer model; thus, the prediction error is effectively reduced. In addition, a stacking ensemble model is proposed to supplement the missing air pollutant time series data. This study uses Henan Province in China as an example to test the validity of the proposed methodology.
Evidence for periodic influences on radon time series was obtained from the active Manisa Fault Zone, Western Anatolia Extensional Province, Turkey
Authors: İçhedef Mutlu , Taşköprü Caner , Sözbilir Hasan , Saç Müslim Murat 
Published: February 2023

Abstract
Soil gas radon anomalies have been used for predicting earthquakes since it was proved that radon is one of the most effective natural process tracers. Analysis of the radon time series is the crucial phase to demonstrate the relationship between an earthquake and radon anomaly. A major part of the analysis of a time series is the characterization of its periodic and non-periodic components. This study, it is aimed to reveal the periodic components in the soil gas radon time series obtained from the Manisa Fault Zone (MFZ), one of the active seismic sources of Western Anatolia. Periodic components of the short-term radon time series were tested with Fast Fourier Transform (FFT). The obtained results show that atmospheric pressure component S1, which acts periodically, has been encountered in the radon time series. It is also found that soil gas radon activity concentrations were quite variable during the study period independently from the periodic components.
Is theoretical chemistry entering a new era of big data learning and reasoning: deep electron cloud-activity and field-activity relationships
Authors: Xu Lu , Yang Qin 
Published: February 2023

Abstract
Chemists have been pursuing the general mathematical laws to explain and predict molecular properties for a long time. However, most of the traditional quantitative structure-activity relationship (QSAR) models have limited application domains, e.g., they tend to have poor generalization performance when applied to molecules with parent structures different from those of the trained molecules. This paper attempts to develop a new QSAR method that could theoretically predict various properties of molecules with diverse structures. The proposed deep electron cloud-activity relationships (DECAR) and deep field-activity relationships (DFAR) methods consist of three essentials: (1) A large number of molecule entities with activity data as training objects and responses; (2) three-dimensional electron cloud density (ECD) or related field data by the accurate density functional theory methods as input descriptors; (3) a deep learning model that is sufficiently flexible and powerful to learn the large data described above. DECAR and DFAR are used to distinguish 977 sweet and 1965 non-sweet molecules (with 6-fold data augmentation) and the classification performance is demonstrated to be significantly better than the traditional least squares support vector machine (LS-SVM) models using traditional descriptors. DECAR and DFAR would provide a feasible and promising way to establish a widely applicable, cumulative, and shareable artificial intelligence-driven QSAR system. They will promote the development of an interactive platform to collect and share the accurate ECD and field data of millions of molecules with annotated activities. With enough input data, we envision the appearance of hundreds of deep networks trained for various molecular activities. Finally, we could anticipate a single DECAR or DFAR network to learn and infer various properties of interest for chemical molecules, which will become an open and shared learning and inference tool for chemists.
Prognostic Value of LINC01600 and CASC15 as Competitive Endogenous RNAs in Lung Adenocarcinoma
Authors: Zhou Fangbin 
Published: February 2023

Abstract
Long non-coding RNAs (lncRNAs) can directly or indirectly regulate gene expression through interacting with microRNAs (miRNAs). Competitive Endogenous RNAs (ceRNAs) render the roles of lncRNAs more complicated in the process of tumor occurrence and progression. However, the prognostic value of lncRNAs as potential biomarkers and their functional roles as ceRNAs have not been clearly described for lung adenocarcinoma (LUAC). In the present study, the aberrant expression profiles of lncRNAs and miRNAs were analyzed at cBioPortal by interrogating LUAD dataset from The Cancer Genome Atlas (TCGA) database with 517 tissue samples. A total of 92 lncRNAs and 125 miRNAs with highly genetic alterations were identified. Further bioinformatics analysis was performed to construct a LUAD-related lncRNA-miRNA-mRNA ceRNA network, which included 24 highly altered lncRNAs, 21 miRNAs and 142 mRNAs. Some key lncRNAs in this network were subsequently identified as LUAD prognosis-related, and of those, LINC01600 and CASC15 both performed the potential prognostic characteristics with LUAD regarding OS and recurrence. Comprehensive analysis indicated that the expression of LINC01600 was significantly associated with KRAS mutation and lymph node metastasis, and CASC15 and LINC01600 were significantly tended towards co-occurrence, which may be due to the similarity of genes co-expressed by these two lncRNAs. Our findings provided novel insight into better understanding of ceRNA regulatory mechanisms in the pathogenesis of LUAD and facilitated the identification of potential biomarkers for prognosis.
Clinical prediction rule for identifying older patients with toxigenic Clostridioides difficile at the time of hospital admission
Authors: Lee Ki-Byung , Lee Mina , Suh Jin Woong , Yang Kyung Sook , Chung Youseung , Kim Jeong Yeon , Kim Sun Bean , Sohn Jang Wook , Yoon Young Kyung 
Published: February 2023

Abstract
Background: This study aimed to develop and validate a clinical prediction rule to screen older patients at risk of being toxigenic Clostridioides difficile carriers at the time of hospital admission.
Methods: This retrospective case-control study was performed at a university-affiliated hospital. Active surveillance using a real-time polymerase chain reaction (PCR) assay for the toxin genes of C. difficilewas conducted among older patients (≥65 years) upon admission to the Division of Infectious Diseases of our institution. This rule was drawn from a derivative cohort between October 2019 and April 2021 using a multivariable logistic regression model. Clinical predictability was evaluated in the validation cohort between May 2021 and October 2021.
Results: Of 628 PCR screenings for toxigenic C. difficile carriage, 101 (16.1%) yielded positive findings. To establish clinical prediction rules in the derivation cohort, the formula was derived using significant predictors for toxigenic C. difficile carriage at admission, such as septic shock, connective tissue diseases, anemia, recent use of antibiotics, and recent use of proton-pump inhibitors. In the validation cohort, the sensitivity, specificity, and positive and negative predictive values of the prediction rule, based on a cut-off value of ≥0.45, were 78.3%, 70.8%, 29.5%, and 95.4%, respectively.
Conclusions: This clinical prediction rule for identifying toxigenic C. difficile carriage at admission may facilitate the selective screening of high-risk groups. To implement it in a clinical setting, more patients from other medical institutions need to be prospectively examined.
Economic Diversity and Growth: Empirical Investigation on the Transmission Channels
Authors: Sukadi Emmanuel Sukadi A 
Published: February 2023

Abstract

This paper empirically assesses the total effect of economic diversity on growth and the contribution of some indirect transmission channels through which part of this effect is carried. Economic diversity, measured by the level of diversity in exports, is found to have a negative direct effect on growth in developing countries that is outweighed by the positive indirect effects through transmission channels, leading to a positive total effect. Overall, higher levels of diversity appear to have a greater positive influence on growth in developing countries in comparison to more advanced economies. For this latter group, although greater diversity tends to favor growth both directly and through some channels, it is also associated with lower openness to trade and contraction in physical capital accumulation, which are detrimental to growth. Human capital and foreign exchange reserve buildup are found to be the most influential transmission channels in the growth and diversity relationship.
Blocking of PI3-kinase beta protects against cerebral ischemia/reperfusion injury by reducing platelet activation and downstream microvascular thrombosis in rats
Authors: Cheng qiong , wang min , jin rong , li guohong 
Published: February 2023

Abstract
Phosphoinositide 3-kinase beta (PI3Kβ) plays an important role in platelet activation and thrombosis, but its role in stroke pathology remains unknown. In this study, we investigated whether inhibition of PI3Kβ protects against cerebral ischemia/reperfusion (I/R) injury by preventing circulating platelet activation and downstream microvascular thrombosis. We used a rat intraluminal filament model of transient middle cerebral artery occlusion (tMCAO) because the rapid restoration of cerebral blood flow to the ischemic area in both tMCAO and endovascular thrombectomy provides clinical relevance for this model. The results showed that TGX221, a selective PI3Kβ inhibitor, treatment immediately before the onset of reperfusion dose-dependently reduced infarct volume and improved neurological function. The protective effects were associated with blocking platelet activation and thrombotic response, thereby reducing downstream microvascular thrombosis, and maintaining reperfusion efficiency. These results suggest that PI3Kβ might be a promising target for treating downstream microvascular thrombosis induced by cerebral I/R injury and offer a novel adjunctive treatment to improve reperfusion therapy for acute ischemic stroke.
The best location for the application of static magnetic fields based on biokinetic coefficients in complete-mix activated sludge process
Authors: Asgari Ghorban , Seid-Mohammadi Abdolmotaleb , Shokoohi Reza , Samarghandi Mohammad Reza , Diger Glen T , Malekolkalami Behrooz , Khoshniyat Ramin 
Published: February 2023

Abstract
The use of the kinetic coefficients for the mathematical expression of the biochemical processes and the relationship between the effective parameters is importance. Change of the biokinetic coefficients in the complete-mix activated sludge processes were calculated for 1 month operation of the activated sludge model (ASM) in a Lab-scale in three series. 15 mT intensity of static magnetic fields (SMFs) applied on the aeration reactor (ASM 1), clarifier reactor (ASM 2) and, sludge returning systems (ASM 3) for 1 hour, daily. During the operation of the systems, five basic biokinetic coefficients such as maximum specific substrate utilization rate (k), heterotrophic half-saturation substrate concentration (Ks), decay coefficient (kd), yield coefficient (Y) and, maximum specific microbial growth rate (μmax) were determined. The rate of k (g COD/g Cells.d) in ASM 1 was 2.69% and, 22.79% higher than ASM 2 and, ASM 3. The value of Ks (mg COD/L) was 54.44 and, 71.13 (mg/L) lower than the ASM 2 and, ASM 3. The rate of kd ASM 1, ASM 2 and, ASM 3 was 0.070, 0.054 and, 0.516 (d-1). The value of Y (kg VSS/kg COD) in ASM 1 was 0.58% and, 0.48% lower than ASM 2 and, ASM 3. The rate of μmax (d−1) in ASM 1 was 0.197, this value for ASM 2 and ASM 3 were 0.324 and 0.309 (d-1). Related to the biokinetic coefficients analyses the best location for the application of 15 mT SMFs was the aeration reactor, where the present of oxygen, substrate and, SMFs have the greatest impact on the positive changes of these coefficients.
H2O2 - mediated SRPED1 Inactivation Contributes to Resisting Ischemia-reperfusion Induced Oxidative Injury to Microglia
Authors: Wei Li , Li Xin , Wei Qianfeng , Chen Lin , Xu Li , Zhou Peng 
Published: February 2023

Abstract
Oxidative stress induced by ischemia-reperfusion is an important reason for the loss of neurons in the brain. In addition to direct oxidative toxicity that causes apoptosis of neurons and glial cells, oxidative stress can also cause complex physiological effects of related cells, such as activation of microglia to promote their repair effects on damaged areas. Here, we found that SPRED1, sprouty-related protein with an EVH1 domain 1, was significantly inhibited after ischemia-reperfusion by MCAO in rats, while the inhibition of SPRED1 responded to the up-expressed p65 proteins with the stimulation of H2O2. What’s more, we further revealed that SPRED1 tended to exert a unique role in maintaining intracellular homeostasis, which can re-activate the instinct of microglia upon the induction of H2O2 to resist oxidative toxicity. However, SPRED1 did not show such ability when it is only over-expressed but without H2O2 induction. In a word, these data revealed a potential role of SPRED1 in preventing cerebral ischemia-induced oxidative stress injury to nerve cells.
Comparative detection of syndecan-2 (SDC2) methylation in preoperative and postoperative stool DNA in patients with colorectal cancer
Authors: Song Ji Hyeong , Oh Tae Jeong , An Sungwhan , Lee Kyung Ha , Kim Ji Yeon , Kim Jin Soo 
Published: February 2023

Abstract
Background: Early detection of colorectal cancer (CRC) is essential to reduce cancer-related morbidity and mortality. Stool DNA (sDNA) testing is an emerging method for early CRC detection. Syndecan-2 (SDC2) methylation is a potential biomarker for the sDNA testing. Aberrant DNA methylation is an early epigenetic event during tumorigenesis, and can occur in the normal colonic mucosa during aging, which can compromise the sDNA test results. This study aimed to determine whether methylated SDC2 in sDNA normalizes after surgical resection of CRC.
Methods: In this prospective study, we enrolled 151 patients with CRC who underwent curative surgical resection between September 2016 and May 2020. Preoperative stool samples were collected from 123 patients and postoperative samples were collected from 122 patients. A total of 104 samples were collected from both preoperative and postoperative patients. Aberrant promoter methylation of SDC2 in sDNA was assessed using linear target enrichment quantitative methylation-specific real-time PCR. Clinicopathological pararmeters were analyzed using the results of SDC2 methylation.
Results: Detection rates of SDC2 methylation in the preoperative and postoperative stool samples were 88.6% and 19.7%, respectively. Large tumor size (³ 3 cm, P = 0.019) and advanced T stage (T3–T4, P = 0.033) were positively associated with the detection rate of SDC2 methylation before surgery. Female sex was associated with false positives after surgery (P = 0.030). Cycle threshold (CT) values were significantly decreased postoperatively compared with preoperative values (P < 0.001). The postoperative negative conversion rate for preoperatively methylated SDC2 was 79.3% (73/92)
Conclusions: Our results suggested that the SDC2 methylation test for sDNA has acceptable sensitivity and specificity. However, small size and early T stage tumors are associated with a low detection rate of SDC2 methylation. As the CT values significantly decreased after surgery, SDC2 methylation test for sDNA had a high diagnostic value and may be used for surveillance after surgical resection of CRC.
Brainstem infarction in common variable immunodeficiency with adenosine deaminase 2 deficiency: case report
Authors: Oster Christoph , Stolte Benjamin , Asan Livia , Pul Refik , Klebe Stephan , Köhrmann Martin , Breuckmann Katharina , Rischpler Christoph , Deuschl Cornelius , Kleinschnitz Christoph , Hagenacker Tim 
Published: February 2023

Abstract
Purpose: We present the case of a 24-year-old male with CNS granulomatosis due to a common variable immunodeficiency (CVID) syndrome and deficiency of adenosine deaminase 2 (DADA2) as a cause of brainstem infarction.
Methods: Case report and review of literature.
Case: The patient’s medical history consisted of an unknown immunodeficiency syndrome. Based on former findings, CVID was diagnosed. The patient suffered from three consecutive brainstem strokes of unknown etiology within three years. An MRI scan detected gadolinium-enhancing, granulomatous-suspect lesions in the interpeduncular cistern, temporal lobe, and tegmentum. Laboratory analysis confirmed CVID, with leukopenia and immunoglobulin deficiency. Because granulomatous CNS inflammation was suspected, the patient received methylprednisolone immunosuppressive therapy, which led to partially-regressive MRI lesions. However, in contrast to imaging the patient showed a progressive cerebellar syndrome, indicating plasma exchange therapy and immunoglobulin treatment, which led to rapid symptom amelioration. After a relapse and a further stroke, expanded analysis confirmed DADA2 as the inflammatory cause, with concomitant CVID for recurrent stroke.
Conclusion: We present the case of a young adult with diagnosis of DADA2 as cause of CVID and recurrent stroke due to vasculitis. This stroke etiology is rare but should be considered as cause of recurrent stroke of unknown origin in young patients.
Non-volatile electrically programmable integrated photonics with a 5-bit operation
Authors: Chen Rui , Fang Zhuoran , Perez Christopher , Miller Forrest , Kumari Khushboo , Saxena Abhi , Zheng Jiajiu , Geiger Sarah , Goodson Kenneth , Majumdar Arka 
Published: February 2023

Abstract
Scalable programmable photonic integrated circuits (PICs) can potentially transform the current state of classical and quantum optical information processing. However, traditional means of programming, including thermo-optic, free carrier dispersion, and Pockels effect result in either large device footprints or high static energy consumptions, significantly limiting their scalability. While chalcogenide-based non-volatile phase-change materials (PCMs) could mitigate these problems thanks to their strong index modulation and zero static power consumption, they often suffer from large absorptive loss, low cyclability, and lack of multilevel operation. Here, we report a wide-bandgap PCM antimony sulfide (Sb2S3)-clad silicon photonic platform simultaneously achieving low loss (< 1.0 dB), high extinction ratio (> 10 dB), high cyclability (> 1,600 switching events), and 5-bit operation. These Sb2S3-based devices are programmed via on-chip silicon PIN diode heaters within sub-ms timescale, with a programming energy density of ∼10fJ/nm3. Remarkably, Sb2S3 is programmed into fine intermediate states by applying multiple identical pulses, providing controllable multilevel operations. Through dynamic pulse control, we achieve 5-bit (32 levels) operations, rendering 0.50 ± 0.16 dB per step. Using this multilevel behavior, we further trim random phase error in a balanced Mach-Zehnder interferometer. Our work opens an attractive pathway toward large-scale energy-efficient programmable PICs with low-loss and multi-bit operations.
Estimating the optimum exercise pattern in upper extremity using musculoskeletal modeling and genetic algorithm
Authors: Sharifi Mesbaholreza , Ghayour Mostafa , Behbahani Saeed 
Published: February 2023

Abstract
Today, numerous training techniques, involving various motion patterns, are used for developing musculoskeletal system abilities in sport activities and rehabilitation programs. The controversial question is that, which of these exercises, have more performance ability to lead to best results in each case. In this paper an optimized tool has been presented to compare different motion patterns in human arm. This tool, not only made it possible to compare different motion pattern but also it can be utilized for suggesting theoretical optimum exercises. These exercises can be generated base on different purposes such as, create more challenge in specific muscle group or decrease injury risk at special joins. The scripts have been developed to interact with the OpenSim software API from Matlab working environment. This is an optimization process based on genetic algorithm to obtain optimum pattern of exercise. The estimated results for muscle activities have been validated by measuring EMG signals during several different trajectories. Two degrees of freedom exoskeleton with haptic controller has been employed for tracing different trajectories and measuring kinematic and kinetic parameters. The results suggest that, small change in specific exercise may be leads to great change in activation pattern of musculotendon actuators. So, it's extremely important to select the good exercise and correct implementation of it. The good correlation between numerical and experimental results confirm that presented numerical procedure provides good way of predicting and understanding the effects of different exercises technique in rehabilitation process or sport activities.