bluuebunny/crossref_metadata_2025_split huggingface dataset:
Early detection of Aspergillus spp. from lower respiratory tract is associated with higher mortality in viral CAP: A multicenter prospective cohort study in China
Authors: Yin Lu , Zhang Ying , Ni Wentao , Zheng Yali , Luo Qiongzhen , Zhao Lili , Xu Yu , Gao Zhancheng 
Published: May 2023

Abstract
Purpose:Community-acquire pneumonia (CAP) is one of the leading causes of death among adults worldwide and one of the world's most burdened diseases. Previous studies have suggested that viral pneumonia, especially severe influenza virus pneumonia, tends to be superinfected with Aspergillus. But the clinical features and prognostics in viral CAP patients with detection of Aspergillus in the early onset of the disease were unclear.
Methods: We conducted a multicenter prospective observational cohort study in China of CAP patients. Adult patients with CAP in 6 hospitals from January 2017 to October 2018 were enrolled. Lower respiratory tract specimens (including sputum and alveolar lavage fluid) were collected within 72 hours after admission. Molecular biology techniques were used to conduct comprehensive pathogenic testing on collected specimens, including bacteria, atypical pathogens, viruses and fungi. A unified electronic medical record website system was used to collect patient clinical data.
Results:A total of 382 adult CAP patients were enrolled. The positive rate of virus was 38% (145/382), and Aspergillus was 11.0% (16/145) in viral CAP. The mortality of Aspergillus-positive patients (25%, 4/16) was significantly higher than that of Aspergillus-negative patients (5.4%, 7/129) in viral CAP (P=0.021). In multivariable Logistic regression models, positive Aspergillus at admission significantly increased the mortality of viral CAP [OR (95%CI) =5.81 (1.48, 22.73), P=0.011]. The lymphocyte count in Aspergillus-positive patients was significantly lower than that of Aspergillus-negative patients (P=0.047).
Conclusion:The positive detection results of Aspergillus from lower respiratory tract were associated with higher mortality in viral CAP.
Trial registration: ClinicalTrials.gov, NCT03093220. Registered retrospectively on 28 March 2017.
Association of triglyceride-glucose index trajectory and frailty in urban older residents: evidence from the 10-year follow-up in a cohort study
Authors: Yuan Yin , Chen Simiao , Lin Chunjin , Huang Xiaoming , Lin Siyang , Huang Feng , Zhu Pengli 
Published: May 2023

Abstract
Background Frailty is an age-related geriatric syndrome that leads to a series of clinically negative events. A better understanding of the factors associated with frailty assists in preventing its progression. The triglyceride-glucose (TyG) index, a simple alternative index of insulin resistance, has not yet been proven to be associated with frailty. The present study aimed to investigate the association between the TyG index and its trajectory with frailty from a cross-sectional, retrospective and prospective level based on an ongoing cohort.
Methods This longitudinal study included 1,866 older residents from the “Fujian prospective aging cohort” (ChiCTR 2000032949). The TyG index was calculated as ln [fasting triglyceride (mg/dL) ╳ fasting plasma glucose (mg/dL)/2] and group-based trajectory model (GBTM) was applied to identify the trajectory of TyG index. The association between different trajectory groups of TyG index with frailty risk were estimated using multinomial logistic regression analysis.
Results In the cross-sectional analysis, the highest quartile of the TyG index was associated with an increased risk of frailty (TyG index Q4 vs. Q1, OR = 1.50, 95% CI 1.00–2.25, P = 0.048). Restricted cubic splines demonstrated an increasing trend for TyG index and frailty risk. During a follow-up of ten years, three distinct trajectories of the TyG index were identified: low-stable (n=697, 38.3%), moderate-stable (n=910, 50.0%) and high-stable (n=214, 11.7%). Compared with those in the stable-low group of TyG index trajectory, the ORs (95% CI) of prefrailty and frailty risk were 1.79 (95% CI 1.11–2.88) and 2.17 (95% CI 1.01–3.88) for the high-stable group, respectively (P=0.017 and P=0.038). In the subgroup analysis, the association of the high-stable trajectory of TyG and frailty status were only observed in subjects with BMI ≥24kg/m2. Prospectively, the highest quartile of the TyG index was associated with a 2.09-fold significantly increased risk of one-year ADL/IADL decline (P = 0.045).
Conclusions The present study suggests a potential role for a high and sustainable level of TyG index in the risk of frailty. The trajectories of the TyG index can help to identify older individuals at a higher risk of frailty who deserve primitive preventive and therapeutic approaches.
Semaphorin 3C enhances putative cancer stemness and accelerates peritoneal dissemination in pancreatic cancer
Authors: Tomizawa Satoshi , Takano Shigetsugu , Eto Ryotaro , Takayashiki Tsukasa , Kuboki Satoshi , Ohtsuka Masayuki 
Published: May 2023

Abstract
Purpose
Semaphorins, axon guidance cues in neuronal network formation, have been implicated in cancer progression. We previously identified semaphorin 3C (SEMA3C) as a secreted protein overexpressed in pancreatic ductal adenocarcinoma (PDAC). We, therefore, hypothesized that SEMA3C supports PDAC progression. In this study, we aimed to investigate the clinical features of SEMA3C, especially its association with chemo-resistance and peritoneal dissemination.
Methods
In resected PDAC tissues, we assessed the relationship between SEMA3C expression and clinicopathological features by immunohistochemistry. In vitro studies, we have shown invasion assay, pancreatosphere formation assay, colony formation assay, cytotoxicity assay, and activation of SEMA3C downstream targets (c-Met, Akt, mTOR). In vivo, we performed a preclinical trial to confirm the efficacy of SEMA3C shRNA knockdown and Gemcitabine and nab-Paclitaxel (GnP) in an orthotopic transplantation mouse model and in peritoneal dissemination mouse model.
Results
In resected PDAC tissues, SEMA3C expression correlated with invasion and peritoneal dissemination after surgery. SEMA3C promoted cell invasion, self-renewal, and colony formation in vitro. We further demonstrated that SEMA3C knockdown increased Gem-induced cytotoxicity by suppressing the activation of the Akt/mTOR pathway via the c-Met receptor. Combination therapy with SEMA3C knockdown and GnP reduced tumor growth and peritoneal dissemination.
Conclusions
SEMA3C enhances peritoneal dissemination by regulating putative cancer stemness and Gem resistance and activates phosphorylation of the Akt/mTOR pathway via c-Met. Our findings provide a new avenue for therapeutic strategies in regulating peritoneal dissemination during PDAC progression.
Toeless and Reversible DNA Strand Displacement based on Hoogsteen-bond Triplex
Authors: Qin Yang , Li Jiangtian , Zhang Xuehao , wang Kaixuan , Zhang Heao , Huang Feiyang , Wang Limei , Li Longjie , Xiao Xianjin 
Published: May 2023

Abstract
Strand displacement reaction is a crucial component in the assembly of diverse DNA-based nanodevices, with the toehold-mediated strand displacement reaction representing the prevailing strategy. However, the single-stranded Watson-Crick sticky region that serves as the trigger for strand displacement can also cause leakage reactions by introducing crosstalk in complex DNA circuits. Here, we proposed the toeless and reversible DNA strand displacement reaction based on the Hoogsteen-bond triplex, which is compatible with most of the existing DNA circuits. We demonstrated that our proposed reaction can occur at pH 5 and can be reversed at pH 9. We also observed an approximately linear relationship between the degree of reaction and pH within the range of pH 5–6, providing the potential for precise regulation of the reaction. Meanwhile, by altering the sequence orientation, we have demonstrated that our proposed reaction can be initiated or regulated through the same toeless mechanism without the requirement for protonation in low pH conditions. Based on the proposed reaction principle, we further constructed a variety of DNA nanodevices, including two types of DNA logic gates that rely on pH = 5/pH = 9 changes for initiating and reversing: the AND gate and the OR gate. We also successfully constructed a DNA Walker based on our proposed reaction modes, which can move along a given track after the introduction of a programmable DNA sequence and complete a cycle after 4 steps. Our findings suggest that this innovative approach will have broad utility in the development of DNA circuits, molecular sensors, and other complex biological systems.
Study of computational model for closing comfort of automotive door system considering work done by components
Authors: Liu Zhiguo , chen xin , Lan Haitao , sun gang , deng guohui , li Tieji 
Published: May 2023

Abstract
Due to the complicated influences of the car door system, the closing comfort is difficult to evaluate in the design of the car door system. In order to solve the problem and increase the development efficiency, based on the work of the whole process and the law of energy conservation, this paper models the power and resistance work under the closing conditions of the door system, and focuses on the construction of the work by door gravity, door limiter, sealing force of the seal, air resistance inside the seal and air resistance inside the vehicle in particular, and designs a computational model of the door closing comfort. The use of the model will effectively guide the development of door system parameterization.
Enigma of the Olyutorskii Earthquake Resolved by SAR interferometry
Authors: Mikhailov Valentin O. , Timoshkina E. P. , Diament M. , Smirnov V. B. 
Published: May 2023

Abstract
The Mw 7.6 Olyutorskii earthquake of April 20, 2006, struck the southern edge of the Koryak Highland, in a region of great complexity at the junction of the North American, Eurasian, and Pacific plates. This seismic event was notable for several remarkable features. Firstly, it had an unexpectedly large magnitude, leading to a reassessment of the seismic hazard in the Northern Kamchatka region. Secondly, the GCMT focal mechanism solution showed two nodal planes corresponding to nearly thrusting displacements on a 40-510 dipping rupture plane. However, geological field studies conducted in the epicentral area allow to map at the surface three primary segments of a120 km long rupture zone. The central segment showed predominant right-lateral strike-slip displacements, while the NE and SW segments exhibited mostly thrusts steeply dipping SE with smaller strike-slip components.
Thirdly, aftershocks were recorded in an area extending over 200 km southwestward from the surface ruptures mapped in the field, with an intense activity observed in a vast area 75 km to the NW from the surface ruptures. Fourthly, although the ruptures found during fieldwork were dipping to the SE, most aftershocks occurred NW of them, with their depth decreasing in the NW direction.
SAR interferometry resolved this apparent discrepancy between seismological and field-geology data, indicating that the primary displacements occurred northwest from the central and southwest segments of the ruptures at the earth's surface.
We present in our study a new rupture model based on SAR, GPS, and field geology data. The model consists of a major blind thrust extending NW and three rear subvertical ruptures that reached the earth's surface and were mapped during the field survey. Additionally, models of the main Мw6.6 aftershocks that occurred on April 29, 2006, and May 22, 2006, are presented.
Our new model reconciles all collected data, with a direction of movements on the major thrust agreeing with the rotation of the previously suggested Beringia microplate around a pole situated in the North of the Chukotka peninsula.
Genome analysis and safety assessment of Achromobacter marplatensis strain YKS2 strain isolated from the rumen of Yaks in China
Authors: Li Dapeng , Han Songwei , Zhang kang , Zhang Hong , Chen Fubing , Wang Lei , Liu Qin , Guo Zhiting , Zhang Jingyan , Li Jianxi 
Published: May 2023

Abstract
Achromobacter marplatensis strain YKS2 isolated from the Yak rumen has a feature of producing cellulose. This study aims to analyze the genome and safety of strainYKS2 in vivo considering its future research and application prospects. The genome of strain YKS2 was sequenced and used for genomic in silico studies. The administration of strain YKS2 with three doses was carried out on mice for 3 days of oral and 7 days of clinical observation tests. The BW, FI, organ indices, gut microbiota, and histological appearances of organs & intestines, along with hematological parameters and serum biochemistry were measured on mice. The chromosome size of strain YKS2 was 5 918 133 bp with GC content of 89.82%. The strain was component of 6 058 coding genes and had multiple functional genes, but no plasmids. The mice in all groups were alive, with good mental states and functional activities. Compared with the control group, there was no significant difference in the three dose groups on BW, FI, hematological parameters (WBC, LYM, etc.) and serum biochemistry (ALB, ALT, etc.). No abnormalities were observed in main visceral organs, intestinal tissue and V/C value in groups. However the IEL number of duodenum and gut microbiota diversity (Shannon index) in the high-dose group was significantly higher than in the control group (p < 0.05). Besides, the low dose of strain YKS2 also significantly affected the bacterial abundance of firmicutes, actinobacteria and desulphurizing bacteroidetes at the phylum. There was no significant effect at genus levels in groups. In a word, the study provided the genome and potential functional genes of strain YKS2, which is beneficial to understand the features of the A. marplatensis strain, and proved train YKS2 without acute toxicity to mice. However, a long-term feeding toxicity experiment in vivo should be performed to further ensure its potential application value strain in the animal industry.
Success of Caries and Periapical Infection Diagnoses on Panoramic images: Artificial Intelligence vs Junior and Specialist Dentists
Authors: Güneç Hüseyin Gürkan 
Published: May 2023

Abstract
Objectives The aim of this study is to evaluate the success rate of radiological diagnoses regarding caries and periapical infection, comparing an artificial intelligence application against junior dentists, based on the valid determinations by specialist dentists.Methods In the initial stage of the study, 2 specialist dentists evaluated the presence of caries and periapical lesions on 500 digital panoramic radiographs, and the detection time was recorded in seconds. In the second stage, 3 junior dentists and an artificial intelligence application performed diagnoses on the same panoramic radiographs, and the diagnostic results and durations were recorded in seconds.Results The artificial intelligence and the three junior dentists, respectively, detected dental caries at an SEN of 0.907,0.889,0.491,0.907; a SPEC of 0.760,0.740,0.454,0.769660; a PPV of 0.693,0.470,0.155,0.666; an NPV of 0.505,0.415,0.275,0.367 and an F1-score of 0.786,0.615,0.236,0.768. The artificial intelligence and the three junior dentists respectively detected periapical lesions at an SEN of 0.973,0.962,0.758,0.958; a SPEC of 0.629,0.421,0.404,0.621; a PPV of 0.861,0.651,0.312,0.648; an NPV of 0.689,0.673,0.278,0.546 and an F1-score of 0.914,0.777,0.442,0.773.Conclusion The artificial intelligence application gave more accurate results, especially in detecting periapical lesions. On the other hand, in caries detection, the underdiagnosis rate was high for both artificial intelligence and junior dentists. Regarding the evaluation time needed, artificial intelligence performed faster, on average.
Artificial Intelligence-enabled Electrocardiography Detects Osteoporosis with chest X-ray and identifies the mortality events
Authors: Tsai Dung-Jang , Lin Chin , Lin Chin-Sheng , Lee Chia-Cheng , Wang Chih-Hung , Fang Wen-Hui 
Published: May 2023

Abstract
SUMMARY
A deep learning model was developed to identify osteoporosis from chest X-ray features with high accuracy in internal and external validation. It has significant prognostic implications, identifying individuals at higher risk of all-cause mortality. This AI-enabled chest X-ray strategy may function as an early detection screening tool for osteoporosis.
OBJECTIVE
The aim of this study was to develop a deep learning model (DLM) to identify osteoporosis via chest X-ray features and investigate the performance and clinical implications.
METHOD
This study collected 48,353 CXRs with the corresponding T score according to DXA from the academic medical center. Among these, 35,633 CXRs were used to identify CXR-OP. Another 12,720 CXRs were used to validate the performance, which was evaluated by the area under the receiver operating characteristic curve (AUC). Furthermore, CXR-OP was tested to assess the long-term risks of mortality, which were evaluated by Kaplan‒Meier survival analysis and the Cox proportional hazards model.
RESULTS
The DLM utilizing CXR achieved AUCs of 0.930 and 0.892 during internal and external validation, respectively. The group that underwent DXA with CXR-OP had a higher risk of all-cause mortality (hazard ratio [HR] 2.59, 95% CI: 1.83–3.67), and those classified as CXR-OP in the group without DXA also had higher all-cause mortality (HR: 1.67, 95% CI: 1.61–1.72) in the internal validation set. The external validation set produced similar results.
CONCLUSION
Our DLM uses chest X-rays for early detection of osteoporosis, aiding physicians to identify those at risk. It has significant prognostic implications, improving life quality and reducing mortality. AI-enabled CXR strategy may serve as a screening tool.
Improving Hierarchical Ecosystem Structures and Multicriteria Evaluations for Current Land Ecosystem Classification
Authors: Zhang Yan , West Neil E. , Hua Xu Jian 
Published: May 2023

Abstract
Background
Ecosystem classification provides a systematic means to organize landscape resources for the purposes of environmental management and planning. The ecosystem classification attempts to capture earth processes over large geographic areas that produce persistent ecosystem patterns on the landscape. Past studies included the hierarchical ecosystem classification in the 300 Dry Domain of the United States and the 100 Polar Domain of Canada. In this paper, the land ecosystem classification (LEC) was developed and simplified as the structure level of organization with the hierarchical system and global ecoregions examined by using hierarchical theory and Multicriteria Evaluations.
Results
The generalized real-world components model relates the classification and level structure as a function of climate, landform, parent material, hydroregime, soil, ecological site, and fauna. Top Domain verification provided physical links and comparison bases for developing mapping ecosystems at continental and global scales. The focal levels were the main national and regional ecosystem classification components. The bottom level and its component were objectively defined by the related ecological site or vegetation stand.
Conclusions
The real-world component model was used to implement the analysis. Once the dimension of the ecosystem classification was significantly reduced to less than ten levels, the component effect ranks and importance ranks demonstrated the comprehension of the level of organizational structures and the land ecosystem classification. Furthermore, the Real-World Component Model quantitatively assessed the component effect and importance features. The component effect values Wi of the ecosystem hierarchies exhibited a significant relationship with the component importance values Vi (R2 = 0.8025, P < 0.01).
Effect of Continued Midwifery Support in Labor on Childbirth Experience
and Self-esteem of Primipara Women: A Randomized Controlled Trial
Authors: Soleimani Nasrin , Refaei Mansoureh , Kazemi Farideh 
Published: May 2023

Introduction:
During labor and delivery, mothers should be supported by people who give them comfort. The present study aims to determine the effect of continued midwifery support in labor on the childbirth experience and self-esteem of nulliparous women 6 weeks after childbirth.

Methods:
This randomized controlled trial was performed in 2021 on 70 pregnant women in the delivery ward. Participants were allocated to two groups through balanced block randomization. First, participants completed questionnaires. In the intervention group, the researcher stayed at the mother’s bedside and accompanied the mother continuously throughout the labor and up to 2 hours after childbirth. Both groups received routine care. Six weeks after childbirth, participants in both groups were contacted to complete the CEQ 2.0 and Rosenberg self-esteem questionnaires. The required data were collected and analyzed at a significance level of 0.05.

Results:
The mean (± SD) of childbirth experience 6 weeks after childbirth was 3.1 (± 0.2) in the intervention group and 2.6 (± 0.3) in the control group, and this difference was statistically significant (p < 0.001) (Cohen’s d = 1.7; 95% CI: 1.1, 2.3). The comparison of the mean of maternal self-esteem showed that this rate in the intervention group was 2.1 scores higher than that in the control group, and the difference was statistically significant (p = 0.02) (Cohen’s d = 0.6; 95% CI: 0.1, 1.1).

Conclusions:
Continued support of the midwife in labor and up to 2 hours after childbirth can lead to a better childbirth experience and enhance the mother’s self-esteem up to 6 weeks after childbirth.
Time and Space Complexity Reduction of KFDA-based LTE Modulation
Classification
Authors: Kadoun Iyad , Bizaki Hossein Khaleghi 
Published: May 2023

Background:
Kernel Fisher discriminant analysis (KFDA) is a nonlinear discrimination
technique for improving automatic modulation classification (AMC) accuracy. Our study showed that
the higher-order cumulants (HOCs) of the Long-term evolution (LTE) modulation types are nonlinearly
separable, so the KFDA technique is a good solution for its modulation classification problem.
Still, research papers showed that the KFDA suffers from high time and space computational complexity.
Some studies concentrated on reducing the KFDA time complexity while preserving the
AMC performance accuracy by finding faster calculation techniques, but unfortunately, they couldn't
reduce the space complexity.

Objective:
This study aims to reduce the time and space computational complexity of the KFDA algorithm
while preserving the AMC performance accuracy.

Methods:
Two new time and space complexity reduction algorithms have been proposed. The first algorithm
is the most discriminative dataset points (MDDP) algorithm, while the second is the k-nearest
neighbors-based clustering (KNN-C) algorithm

Results:
The simulation results show that these algorithms could reduce the time and space complexities,
but their complexity reduction is a function of signal-to-noise ratio (SNR) values. On the other
hand, the KNN-C-based KFDA algorithm has less complexity than the MDDP-based KFDA algorithm

Conclusion:
The time and space computation complexity of the KFDA could be effectively reduced
using MDDP and KNN-C algorithms; as a result, its calculation became much faster and had less
storage size.