bluuebunny/crossref_metadata_2025_split huggingface dataset:
Imaging analysis and predictive nomogram construction for degenerative lumbar spondylolisthesis with severe clinical symptom based on propensity score matching
Authors: He Yi , Wang Wei , Zhou Haiting , Huang Xiaojian , Wang Yinguang , Qu Yunkun , Cheng Hao , You Hongbo 
Published: March 2023

AbstractIntervertebral disc degeneration, local lumbar segmental morphology changes, and atrophy of multifidus muscle have been considered to be associated with degenerative lumbar spondylolisthesis. However, there remains a great deal of controversy. To further investigate their relationship with degenerative lumbar spondylolisthesis, we conducted a retrospective study that included 67 patients with degenerative spondylolisthesis and 182 control subjects. Propensity score matching was employed to match the case group and the control group. Disc height was evaluated by the anterior disc height index (DHIA) and posterior disc height index (DHIP). Local lumbar segmental morphology was assessed by segmental lordosis (SL). The fatty infiltration and atrophy of multifidus muscle was evaluated by multifidus muscle net content (MFNC). Our results indicate that DHIA, DHIP, SL, and MFNC in the case group were significantly lower than in the control group. Furthermore, the DHIA, DHIP, and MFNC of the slipped segment (L4/5) were lower than those of the non-slipped segment (L3/4). Correlation analysis showed a high relationship between DHIA and MFNC and the degree of degenerative lumbar spondylolisthesis. Logistic regression analysis revealed that DHIA and MFNC might act as protective factors against the development of degenerative lumbar spondylolisthesis. Additionally, a prognostic nomogram was developed and validated to assess the likelihood of patients with severe symptoms requiring surgical intervention.
Novel estimation technique for the carrier-to-noise ratio of wireless medical telemetry using software-defined radio with machine-learning
Authors: Kai Ishida 
Published: March 2023

AbstractIn this study, we developed a novel machine-learning model to estimate the carrier-to-noise ratio (CNR) of wireless medical telemetry (WMT) using time-domain waveform data measured by a low-cost software-defined radio. With automatic estimation of CNR, the management of the electromagnetic environment of WMT can be made easier. Therefore, we proposed a machine-learning method for estimating CNR. According to the performance evaluation results by 5-segment cross-validation on 704 types of measured data, CNR was estimated with 99.5% R-square and 0.844 dB mean absolute error using a gradient boosting regression tree. The gradient boosting decision tree classifiers predicted if the CNR exceeded 30 dB with 99.5% accuracy. The proposed method is effective for investigating electromagnetic environments in clinical settings.
Comprehensive pan-cancer analysis of STAT3 as a prognostic and immunological biomarker
Authors: He Zhibo , Song Biao , Zhu Manling , Liu Jun 
Published: March 2023

AbstractNumerous studies have indicated that STAT3 plays a key role in promoting oncogenesis and it is considered a potential therapeutic target for cancer treatment; however, there are no reports on STAT3 using pan-cancer analysis. Therefore, it is important to investigate the role of STAT3 in different types of tumors using pan-cancer analysis. In the present study, we used multiple databases to comprehensively analyze the relationship between STAT3 expression and prognosis, different stages of patients with cancer, investigate the clinical value of STAT3 in predicting prognosis, and the relationship between STAT3 genetic alteration and prognosis, drug sensitivity, and STAT3 expression, to determine whether STAT3 participates in tumor immunity, to provide a rationale for STAT3 as a treatment target for a broad-spectrum malignancies. Our results indicate that STAT3 can serve as a prognostic, sensitivity prediction biomarker and a target for immunotherapy, which has been of great value for pan-cancer treatment. Overall, we found that STAT3 significantly predicted cancer prognosis, drug resistance, and immunotherapy, providing a rationale for further experimental studies.
Associations of cognitive impairment with self-isolation and access to health and care during the COVID-19 pandemic in England
Authors: Beach Brian , Steel Nicholas , Steptoe Andrew , Zaninotto Paola 
Published: March 2023

AbstractThis research explored experiences across three cognitive function groups (no impairment, mild impairment, and dementia) with respect to shielding (either self-isolating or staying at home), COVID-19 infection, and access to health/care services during the COVID-19 pandemic. Analyses were conducted using data from the English Longitudinal Study of Ageing (ELSA) COVID-19 sub-study collected in 2020. We report bivariate estimates across our outcomes of interest by cognitive function group along with multivariate regression results adjusting for demographic, socioeconomic, geographic, and health characteristics. Rates of shielding were high across all cognitive function groups and three measured time points (April, June/July, and Nov/Dec 2020), ranging from 74.6% (95% confidence interval 72.9–76.2) for no impairment in Nov/Dec to 96.7% (92.0–98.7) for dementia in April (bivariate analysis). 44.1% (33.5–55.3) of those with dementia experienced disruption in access to community health services by June/July compared to 34.9% (33.2–36.7) for no impairment. A higher proportion of those with mild impairment reported hospital-based cancellations in June/July (23.1% (20.1–26.4)) and Nov/Dec (16.3% (13.4–19.7)) than those with no impairment (18.0% (16.6–19.4) and 11.7% (10.6–12.9)). Multivariate adjusted models found that those with dementia were 2.4 (1.1–5.0) times more likely than those with no impairment to be shielding in June/July. All other multivariate analyses found no statistically significant differences between cognitive function groups. People with dementia were more likely than people with no impairment to be shielding early in the pandemic, but importantly they were no more likely to experience disruption to services or hospital treatment.
Mitochondrion-targeted antioxidant SkQ1 prevents rapid animal death caused by highly diverse shocks
Authors: Skulachev V. P. , Vyssokikh M. Yu. , Chernyak B. V. , Averina O. A. , Andreev-Andrievskiy A. A. , Zinovkin R. A. , Lyamzaev K. G. , Marey M. V. , Egorov M. V. , Frolova O. J. , Zorov D. B. , Skulachev M. V. , Sadovnichii V. A. 
Published: March 2023

AbstractThe response to stress involves the activation of pathways leading either to protection from the stress origin, eventually resulting in development of stress resistance, or activation of the rapid death of the organism. Here we hypothesize that mitochondrial reactive oxygen species (mtROS) play a key role in stress-induced programmed death of the organism, which we called “phenoptosis” in 1997. We demonstrate that the synthetic mitochondria-targeted antioxidant SkQ1 (which specifically abolishes mtROS) prevents rapid death of mice caused by four mechanistically very different shocks: (a) bacterial lipopolysaccharide (LPS) shock, (b) shock in response to intravenous mitochondrial injection, (c) cold shock, and (d) toxic shock caused by the penetrating cation C12TPP. Importantly, under all these stresses mortality was associated with a strong elevation of the levels of pro-inflammatory cytokines and administration of SkQ1 was able to switch off the cytokine storms. Since the main effect of SkQ1 is the neutralization of mtROS, this study provides evidence for the role of mtROS in the activation of innate immune responses mediating stress-induced death of the organism. We propose that SkQ1 may be used clinically to support patients in critical conditions, such as septic shock, extensive trauma, cooling, and severe infection by bacteria or viruses.
IntelliSleepScorer, a software package with a graphic user interface for automated sleep stage scoring in mice based on a light gradient boosting machine algorithm
Authors: Wang Lei A. , Kern Ryan , Yu Eunah , Choi Soonwook , Pan Jen Q. 
Published: March 2023

AbstractMachine learning has been applied in recent years to categorize sleep stages (NREM, REM, and wake) using electroencephalogram (EEG) recordings; however, a well-validated sleep scoring automatic pipeline in rodent research is still not publicly available. Here, we present IntelliSleepScorer, a software package with a graphic user interface to score sleep stages automatically in mice. IntelliSleepScorer uses the light gradient boosting machine (LightGBM) to score sleep stages for each epoch of recordings. We developed LightGBM models using a large cohort of data, which consisted of 5776 h of sleep EEG and electromyogram (EMG) signals across 519 unique recordings from 124 mice. The LightGBM model achieved an overall accuracy of 95.2% and a Cohen’s kappa of 0.91, which outperforms the baseline models such as the logistic regression model (accuracy = 93.3%, kappa = 0.88) and the random forest model (accuracy = 94.3%, kappa = 0.89). The overall performance of the LightGBM model as well as the performance across different sleep stages are on par with that of the human experts. Most importantly, we validated the generalizability of the LightGBM models: (1) The LightGBM model performed well on two publicly available, independent datasets (kappa >  = 0.80), which have different sampling frequency and epoch lengths; (2) The LightGBM model performed well on data recorded at a lower sampling frequency (kappa = 0.90); (3) The performance of the LightGBM model is not affected by the light/dark cycle; and (4) A modified LightGBM model performed well on data containing only one EEG and one EMG electrode (kappa >  = 0.89). Taken together, the LightGBM models offer state-of-the-art performance for automatic sleep stage scoring in mice. Last, we implemented the IntelliSleepScorer software package based on the validated model to provide an out-of-box solution to sleep researchers (available for download at https://sites.broadinstitute.org/pan-lab/resources).
Modeling of land subsidence using GIS-based artificial neural network in Yunlin County, Taiwan
Authors: Ku Cheng-Yu , Liu Chih-Yu 
Published: March 2023

AbstractIn this study, the land subsidence in Yunlin County, Taiwan, was modeled using an artificial neural network (ANN). Maps of the fine-grained soil percentage, average maximum drainage path length, agricultural land use percentage, electricity consumption of wells, and accumulated land subsidence depth were produced through geographic information system spatial analysis for 5607 cells in the study area. An ANN model based on a backpropagation neural network was developed to predict the accumulated land subsidence depth. A comparison of the model predictions with ground-truth leveling survey data indicated that the developed model had high accuracy. Moreover, the developed model was used to investigate the relationship of electricity consumption reduction with reductions in the total area of land with severe subsidence (> 4 cm per year); the relationship was approximately linear. In particular, the optimal results were obtained when decreasing the electricity consumption from 80 to 70% of the current value, with the area of severe land subsidence decreasing by 13.66%.
Effectiveness of high-flow nasal cannulae compared with noninvasive positive-pressure ventilation in preventing reintubation in patients receiving prolonged mechanical ventilation
Authors: Tseng Chi-Wei , Chao Ke-Yun , Wu Hsiu-Li , Lin Chen-Chun , Hsu Han-Shui 
Published: March 2023

AbstractMany intensive care unit patients who undergo endotracheal extubation experience extubation failure and require reintubation. Because of the high mortality rate associated with reintubation, postextubation respiratory management is crucial, especially for high-risk populations. We conducted the present study to compare the effectiveness of oxygen therapy administered using high-flow nasal cannulae (HFNC) and noninvasive positive pressure ventilation (NIPPV) in preventing reintubation among patients receiving prolonged mechanical ventilation (PMV). This single-center, prospective, unblinded randomized controlled trial was at the respiratory care center (RCC). Participants were randomized to an HFNC group or an NIPPV group (20 patients in each) and received noninvasive respiratory support (NRS) administered using their assigned method. The primary outcome was reintubation within7 days after extubation. None of the patients in the NIPPV group required reintubation, whereas 5 (25%) of the patients in the HFNC group required reintubation (P = 0.047). The 90-day mortality rates of the NIPPV and HFNC groups (four patients [20%] vs. two patients [10%], respectively) did not differ significantly. No significant differences in length of RCC stay, length of hospital stay, time to liberation from NRS, and ventilator-free days at 28-day were identified. The time to event outcome analysis also revealed that the risk of reintubation in the HFNC group was higher than that in the NIPPV group (P = 0.018). Although HFNC is becoming increasingly common as a form of postextubation NRS, HFNC may not be as effective as NIPPV in preventing reintubation among patients who have been receiving PMV for at least 2 weeks. Additional studies evaluating HFNC as an alternative to NIPPV for patients receiving PMV are warranted.ClinicalTrial.gov ID: NCT04564859; IRB number: 20160901R.Trial registration: ClinicalTrial.gov (https://clinicaltrials.gov/ct2/show/NCT04564859).
A retrospective study on comparison of clinical characteristics and outcomes of diabetic ketoacidosis patients with and without acute pancreatitis
Authors: Khan Adeel Ahmad , Ata Fateen , Yousaf Zohaib , Aljafar Mohamad Safwan , Seijari Mohammed Najdat , Matarneh Ahmad , Dakkak Bassel , Halabiya Malik , Muthanna Bassam , Maliyakkal Abdul Majeed , Kartha Anand 
Published: March 2023

AbstractThe co-existence of diabetic ketoacidosis (DKA) with acute pancreatitis (AP) is associated with unfavorable clinical outcomes. However, diagnosing AP in DKA patients is challenging and often missed due to overlapping symptoms. The aim of this retrospective observational study was to compare the clinical characteristics and outcomes of patients with concomitant DKA and AP or DKA alone. Data of patients with DKA admitted between January 2015 to August 2021 to four hospitals in Qatar was extracted from the electronic health record (Cerner). American Diabetes Association criteria and Atlanta criteria were used for DKA and AP diagnosis, respectively. Independent T-test or Mann–Whitney U test was used to analyze continuous variables, whereas categorical variables were analyzed via Chi-square or Fischer exact tests as appropriate. Univariate and multivariate logistic regression models were generated to assess the correlations. A p-value of < 0.05 was considered statistically significant. Of 936 patients with DKA, 84 (9.0%) had coexisting AP. AP was most common in the Asian race (66%, p < 0.001). Patients with DKA and AP were older, had higher admission anion-gap, white cell count, hemoglobin (hb), neutrophil/lymphocyte ratio, urea, creatinine, maximum blood glucose during the episode, total cholesterol and triglyceride level (TGL) (p < 0.05). They had a lower admission venous pH and bicarbonate at 6 h. Patients in the DKA with AP group also had a longer length of stay (LOS), DKA duration and a higher rate of ICU admission (p-values ≤ 0.001). In-hospital mortality, 3-month all-cause readmission, 6-month and 12-month DKA recurrence did not differ between the two groups. Univariate logistic regression analysis showed age, Asian ethnicity, male gender, T2D, admission WBC count, hb, urea, creatinine, potassium, venous pH, bicarbonate, anion gap, total cholesterol, TGL and LDL level were significantly associated with the development of DKA with AP (p < 0.05). In multivariate logistic regression analysis, age and total cholesterol level were associated with concomitant DKA and AP (p < 0.05). Patients with concomitant DKA and AP have more severe derangement in markers of DKA severity, inflammation, kidney injury and metabolic profile, along with a longer DKA duration, LOS and requirement for ICU support compared to DKA patients without AP. This highlights the clinical significance of diagnosing the co-existence of DKA with AP, as the combination results in significantly worse clinical outcomes and greater healthcare utilization than in patients with only DKA.
Effect of redroot pigweed interference on antioxidant enzyme and light response of common bean (Phaseolus vulgaris L.) depends on cultivars and growth stages
Authors: Tabatabaiepour Seyede Zahra , Tahmasebi Zahra , Taab Alireza , Rashidi-Monfared Sajad 
Published: March 2023

AbstractRedroot Pigweed (Amaranthus retroflexus L.) is an important weed that is highly competitive with common bean. Photosynthetic pigments, the activity of antioxidant enzymes, the relative expression of a number of antioxidant enzyme and light response genes, were studied in three of common bean cultivars and in V4 and R7 stages under Redroot Pigweed free and infested. The presence of weeds reduced the content of chlorophyll, relative chlorophyll and anthocyanin of common bean leaves. With the increase of weed competition, the expression of antioxidant genes and enzymes increased, which indicates the increase of their activity in order to reduce the amount of reactive oxygen species. Among the studied antioxidant enzymes, the activity of catalase and ascorbate peroxidase produced in the leaves was higher than that of superoxide dismutase. With the increase of weed interference, the expression of phytochrome interacting factor 3 (PIF3) gene as a positive regulator of light signals is increased and the expression of phytochrome rapidly regulated1 (PAR1) gene as a negative regulator is decreased. Chlorophyll a/b-binding protein (CAB1) and auxin-responsive protein IAA8 (IAA8) genes also down-regulated with increasing competition. Along with the decrease of CAB expression in the conditions of competition with weeds, the chlorophyll a, b content also decreased. Correlation between gene expression and physiological traits related to them highlights the prominent role of CWCP in maintaining yield potential.
New evidence for regional pastoral practice and social complexity in the Eastern Tianshan Mountains in the first millennium BCE
Authors: Wang Yuxuan , Monteith Francesca , Xi Tongyuan , Ren Meng , Li Daren , Hu Songmei , Wang Jianxin , Festa Marcella , Ma Jian 
Published: March 2023

AbstractMobile pastoralism was a key lifeway in the Late Bronze and Iron Age of Northwest China and played a crucial role in the regional socio-cultural development, as well as the formation of transregional networks. In this paper we analyse the complete faunal assemblage from House F2 in Shirenzigou, on the Eastern Tianshan Mountains, in combination with radiocarbon dating and spatial analysis, to explore local animal resources exploitation strategies and related socio-economic implications. Our results show an intensive multipurpose caprine management, while the exploitation of other domestic taxa, cattle, horses and dogs, was limited. This pastoral economy was supplemented with some hunting. The differentiated use of space in F2 indicates that basic domestic tasks were carried out in the structure, however its position within the landscape and the predominance of bone tools related to warfare and socialization activities, suggests that it was not an ordinary dwelling, it may also have served as a watch post for the summer encampment within the gully. Our findings constitute an important contribution on the discussion on animal resources exploitation strategies and their relationship with evolving socio-economic complexity in the Eastern Tianshan region in the late first millennium BCE.
Spectrochemical approach combined with symptoms data to diagnose fibromyalgia through paper spray ionization mass spectrometry (PSI-MS) and multivariate classification
Authors: Alves Marcelo V. S. , Maciel Lanaia I. L. , Passos João O. S. , Morais Camilo L. M. , dos Santos Marfran C. D. , Lima Leomir A. S. , Vaz Boniek G. , Pegado Rodrigo , Lima Kássio M. G. 
Published: March 2023

AbstractThis study performs a chemical investigation of blood plasma samples from patients with and without fibromyalgia, combined with some of the symptoms and their levels of intensity used in the diagnosis of this disease. The symptoms evaluated were: visual analogue pain scale (VAS); fibromyalgia impact questionnaire (FIQ); Hamilton anxiety rating scale (HAM); Tampa Scale for Kinesiophobia (TAMPA); quality of life Questionnaire—physical and mental health (QL); and Pain Catastrophizing Scale (CAT). Plasma samples were analyzed by paper spray ionization mass spectrometry (PSI-MS). Spectral data were organized into datasets and related to each of the symptoms measured. The datasets were submitted to multivariate classification using supervised models such as principal component analysis with linear discriminant analysis (PCA-LDA), successive projections algorithm with linear discriminant analysis (SPA-LDA), genetic algorithm with linear discriminant analysis (GA-LDA) and their versions with quadratic discriminant analysis (PCA/SPA/GA-QDA) and support vector machines (PCA/SPA/GA-SVM). These algorithm combinations were performed aiming the best class separation. Good discrimination between the controls and fibromyalgia samples were observed using PCA-LDA, where the spectral data associated with the CAT symptom achieved 100% classification sensitivity, and associated with the VAS symptom achieved 100% classification specificity, with both symptoms at the moderate level of intensity. The spectral variable at 579 m/z was found to be substantially significant for classification according to the PCA loadings. According to the human metabolites database, this variable can be associated with a LysoPC compound, which comprises a class of metabolites already evidenced in other studies for fibromyalgia diagnosis. This study proposed an investigation of spectral data combined with clinical data to compare the classification ability of different datasets. The good classification results obtained confirm this technique is as a good analytical tool for the detection of fibromyalgia, and provides theoretical support for other studies about fibromyalgia diagnosis.
Physiological responses of three field-grown species (Ceratonia siliqua, Eucalyptus camaldulensis, and Moringa oleifera) to water deficits in a Mediterranean semi-arid climate
Authors: Ezzine Hasna , Metougui Mohamed Louay , Boukcim Hassan , Abbas Younes 
Published: March 2023

AbstractReforestation of degraded drylands calls for the selection of species with the capacity to withstand water scarcity. In this current study we have assessed, the physiological responses of three field-grown species (Ceratonia siliqua, Eucalyptus camaldulensis and Moringa oleifera) to water deficits in semi-arid regions in order to suggest a potential species for rehabilitation programs. The physiological behavior of the given species was studied in three irrigation schemes: subsurface drip irrigation (applied weekly), tank irrigation (applied monthly), and unirrigated plants. In a stressed state, an assessment of relative water content (RWC), water potential (pre-dawn water potential PWP and midday water potential MWP) and stomatal conductance revealed three contrasting physiological responses. First, C. siliqua stomata remained open with a high RWC at low water potentials. Consequently, this species tolerated water deficits by decreasing its leaf water potential, primarily associated with osmotic adjustment. On the other hand, E. camaldulensis was found to be a drought-avoider species, mutated to a water-saving strategy by complete stomatal closure. Finally, for the extreme case, M. oleifera showed leaf shedding under water deficit conditions. These different physiological responses allowed these species to survive water deficits, and consequently, could be considered suitable candidates for rehabilitating degraded semi-arid areas.