bluuebunny/crossref_metadata_2025_split huggingface dataset:
An empirical elastic anisotropy prediction model in self-sourced reservoir shales and its influencing factor analysis
Authors: Zhao Luanxiao , Cai Zhenjia , Qin Xuan , Wang Yang , Long Teng , Han De-Hua , Zhang Fengshou , Geng Jianhua 
Published: February 2023

Organic shales can split into laminae or thin layers due to their fissility and are usually characterized as transverse isotropic media. Understanding their elastic and anisotropic properties plays a significant role in geophysical modeling and imaging, reservoir geomechanics, and reservoir characterization. One can obtain their velocity anisotropy through laboratory and field measurements or rock-physics models. However, the measurements are scarce, and theoretical modeling of Thomsen’s anisotropy parameters generally requires extra inputs, which are sometimes difficult to obtain. We have compiled ultrasonic data from 159 self-sourced reservoir shale samples from the literature and our own measurements. Simple exponential models can capture the trends of the P- and S-wave anisotropy parameters [Formula: see text] and [Formula: see text] decreasing with the increasing vertical P- and S-wave velocities, with [Formula: see text] being above 0.84. The error in estimated anisotropy is small for high-velocity ([Formula: see text]) shales but relatively large for low-velocity ([Formula: see text]) shales. We analyze the influence of multiple geologic factors on the proposed anisotropy-velocity relationships. We observe that velocity anisotropy generally increases with clay content. In addition, mature shales (0.6 < Ro (%) < 1.4) generally have stronger anisotropy strength spreading in a broader range than overmature shales (Ro (%) > 1.4). Overall, no single parameter dominates the source of velocity anisotropy, which is jointly affected by the coupled factors of clay content, organic matter, porosity, maturity level, and geologic history. The empirical model has the potential to offer a fast and straightforward method of predicting P- and S-wave anisotropy strength from vertical P- and S-wave velocities.
Cost-Effectiveness of the First Line Treatment Options For Metastatic Renal Cell Carcinoma in India
Authors: Gupta Dharna , Singh Ashish , Gupta Nidhi , Mehra Nikita , Bahuguna Pankaj , Aggarwal Vipul , Krishnamurthy Manjunath Nookala , Roy Partha Sarathi , Malhotra Pankaj , Gupta Sudeep , Kumar Lalit , Kataki Amal , Prinja Shankar 
Published: February 2023

PURPOSE Tyrosine kinase inhibitors such as sunitinib and pazopanib are the mainstay of treatment of metastatic renal cell carcinoma (mRCC) in India. However, pembrolizumab and nivolumab have shown significant improvement in the median progression-free survival and overall survival among patients with mRCC. In this study, we aimed to determine the cost-effectiveness of the first-line treatment options for the patients with mRCC in India. METHODS A Markov state-transition model was used to measure the lifetime costs and health outcomes associated with sunitinib, pazopanib, pembrolizumab/lenvatinib, and nivolumab/ipilimumab among patients with first-line mRCC. Incremental cost per quality-adjusted life-year (QALY) gained with a given treatment option was compared against the next best alternative and assessed for cost-effectiveness using a willingness to pay threshold of one-time per capita gross-domestic product of India. The parameter uncertainty was analyzed using the probabilistic sensitivity analysis. RESULTS We estimated the total lifetime cost per patient of ₹ 0.27 million ($3,706 US dollars [USD]), ₹ 0.35 million ($4,716 USD), ₹ 9.7 million ($131,858 USD), and ₹ 6.7 million ($90,481 USD) for the sunitinib, pazopanib, pembrolizumab/lenvatinib, and nivolumab/ipilimumab arms, respectively. Similarly, the mean QALYs lived per patient were 1.91, 1.86, 2.75, and 1.97, respectively. Sunitinib incurs an average cost of ₹ 143,269 ($1,939 USD) per QALY lived. Therefore, sunitinib at current reimbursement rates (₹ 10,000 per cycle) has a 94.6% probability of being cost-effective at a willingness to pay threshold of 1-time per capita gross-domestic product (₹ 168,300) in the Indian context. CONCLUSION Our findings support the current inclusion of sunitinib under India's publicly financed health insurance scheme.
Long Noncoding RNA Expression Independently Predicts Outcome in Pediatric Acute Myeloid Leukemia
Authors: Farrar Jason E. , Smith Jenny L. , Othus Megan , Huang Benjamin J. , Wang Yi-Cheng , Ries Rhonda , Hylkema Tiffany , Pogosova-Agadjanyan Era L. , Challa Sneha , Leonti Amanda , Shaw Timothy I. , Triche Timothy J. , Gamis Alan S. , Aplenc Richard , Kolb E. Anders , Ma Xiaotu , Stirewalt Derek L. , Alonzo Todd A. , Meshinchi Soheil 
Published: February 2023

PURPOSE Optimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML. METHODS To identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis. RESULTS Training set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays. CONCLUSION Inclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.
A Data-Driven Approach to Refine Predictions of Differentiated Thyroid Cancer Outcomes: A Prospective Multicenter Study
Authors: Grani Giorgio , Gentili Michele , Siciliano Federico , Albano Domenico , Zilioli Valentina , Morelli Silvia , Puxeddu Efisio , Zatelli Maria Chiara , Gagliardi Irene , Piovesan Alessandro , Nervo Alice , Crocetti Umberto , Massa Michela , Samà Maria Teresa , Mele Chiara , Deandrea Maurilio , Fugazzola Laura , Puligheddu Barbara , Antonelli Alessandro , Rossetto Ruth , D’Amore Annamaria , Ceresini Graziano , Castello Roberto , Solaroli Erica , Centanni Marco , Monti Salvatore , Magri Flavia , Bruno Rocco , Sparano Clotilde , Pezzullo Luciano , Crescenzi Anna , Mian Caterina , Tumino Dario , Repaci Andrea , Castagna Maria Grazia , Triggiani Vincenzo , Porcelli Tommaso , Meringolo Domenico , Locati Laura , Spiazzi Giovanna , Di Dalmazi Giulia , Anagnostopoulos Aris , Leonardi Stefano , Filetti Sebastiano , Durante Cosimo 
Published: February 2023

Abstract

Context
The risk stratification of patients with differentiated thyroid cancer (DTC) is crucial in clinical decision making. The most widely accepted method to assess risk of recurrent/persistent disease is described in the 2015 American Thyroid Association (ATA) guidelines. However, recent research has focused on the inclusion of novel features or questioned the relevance of currently included features.

Objective
To develop a comprehensive data-driven model to predict persistent/recurrent disease that can capture all available features and determine the weight of predictors.

Methods
In a prospective cohort study, using the Italian Thyroid Cancer Observatory (ITCO) database (NCT04031339), we selected consecutive cases with DTC and at least early follow-up data (n = 4773; median follow-up 26 months; interquartile range, 12-46 months) at 40 Italian clinical centers. A decision tree was built to assign a risk index to each patient. The model allowed us to investigate the impact of different variables in risk prediction.

Results
By ATA risk estimation, 2492 patients (52.2%) were classified as low, 1873 (39.2%) as intermediate, and 408 as high risk. The decision tree model outperformed the ATA risk stratification system: the sensitivity of high-risk classification for structural disease increased from 37% to 49%, and the negative predictive value for low-risk patients increased by 3%. Feature importance was estimated. Several variables not included in the ATA system significantly impacted the prediction of disease persistence/recurrence: age, body mass index, tumor size, sex, family history of thyroid cancer, surgical approach, presurgical cytology, and circumstances of the diagnosis.

Conclusion
Current risk stratification systems may be complemented by the inclusion of other variables in order to improve the prediction of treatment response. A complete dataset allows for more precise patient clustering.
Imaging of Central Nervous System Autoimmune, Paraneoplastic, and Neuro-rheumatologic Disorders
Authors: Wahed Lama Abdel , Cho Tracey A. 
Published: February 2023

ABSTRACTOBJECTIVEThis article provides an overview of the imaging modalities used in the evaluation of central nervous system (CNS) autoimmune, paraneoplastic, and neuro-rheumatologic disorders. An approach is outlined for interpreting imaging findings in this context, synthesizing a differential diagnosis based on certain imaging patterns, and choosing further imaging for specific diseases.LATEST DEVELOPMENTSThe rapid discovery of new neuronal and glial autoantibodies has revolutionized the autoimmune neurology field and has elucidated imaging patterns characteristic of certain antibody-associated diseases. Many CNS inflammatory diseases, however, lack a definitive biomarker. Clinicians should recognize neuroimaging patterns suggestive of inflammatory disorders, as well as the limitations of imaging. CT, MRI, and positron emission tomography (PET) modalities all play a role in diagnosing autoimmune, paraneoplastic, and neuro-rheumatologic disorders. Additional imaging modalities such as conventional angiography and ultrasonography can be helpful for further evaluation in select situations.ESSENTIAL POINTSKnowledge of imaging modalities, both structural and functional, is critical in identifying CNS inflammatory diseases quickly and can help avoid invasive testing such as brain biopsy in certain clinical scenarios. Recognizing imaging patterns suggestive of CNS inflammatory diseases can also facilitate the early initiation of appropriate treatments to diminish morbidity and future disability.
Neuroimaging in Dementia
Authors: Risacher Shannon L. , Apostolova Liana G. 
Published: February 2023

ABSTRACT

OBJECTIVE
Neurodegenerative diseases are significant health concerns with regard to morbidity and social and economic hardship around the world. This review describes the state of the field of neuroimaging measures as biomarkers for detection and diagnosis of both slowly progressing and rapidly progressing neurodegenerative diseases, specifically Alzheimer disease, vascular cognitive impairment, dementia with Lewy bodies or Parkinson disease dementia, frontotemporal lobar degeneration spectrum disorders, and prion-related diseases. It briefly discusses findings in these diseases in studies using MRI and metabolic and molecular-based imaging (eg, positron emission tomography [PET] and single-photon emission computerized tomography [SPECT]).

LATEST DEVELOPMENTS
Neuroimaging studies with MRI and PET have demonstrated differential patterns of brain atrophy and hypometabolism in different neurodegenerative disorders, which can be useful in differential diagnoses. Advanced MRI sequences, such as diffusion-based imaging, and functional MRI (fMRI) provide important information about underlying biological changes in dementia and new directions for development of novel measures for future clinical use. Finally, advancements in molecular imaging allow clinicians and researchers to visualize dementia-related proteinopathies and neurotransmitter levels.

ESSENTIAL POINTS
Diagnosis of neurodegenerative diseases is primarily based on symptomatology, although the development of in vivo neuroimaging and fluid biomarkers is changing the scope of clinical diagnosis, as well as the research into these devastating diseases. This article will help inform the reader about the current state of neuroimaging in neurodegenerative diseases, as well as how these tools might be used for differential diagnoses.
Impacts of Statin Therapy Strategies on Incidence of Ischemic Cerebrovascular Events in Patients With Aneurysmal Subarachnoid Hemorrhage: A Systematic Review and Bayesian Network Meta-Analysis
Authors: Zhong Shiyu , Liu Tao , Zhai Qingqing , Zhang Xudong , Jing Huiquan , Li Kunhang , Liu Shengyu , Liu Guojun , Wang Liang , Li Lishuai , Tao Shanwei , Ren Lijie , Shi Xin , Bao Yijun 
Published: February 2023

BACKGROUND:
The exacerbation of neurological outcomes often occurs in aneurysmal subarachnoid hemorrhage (aSAH). Statins have been commonly used for aSAH; however, there is lack of evidence of the pharmacological efficacy of different dosages and types of statins.

OBJECTIVE:
To apply the Bayesian network meta-analysis to analyze the optimal dosage and type of statins for the amelioration of ischemic cerebrovascular events (ICEs) in patients with aSAH.

METHODS:
We developed the Bayesian network meta-analysis and systemic review to analyze the effects of statins on functional prognosis and the impacts of optimal dosage and type of statins on ICEs in patients with aSAH. The outcome variables of the analysis were the incidence of ICEs and functional prognosis.

RESULTS:
A total of 2569 patients with aSAH across 14 studies were included. Analysis of 6 randomized controlled trials showed that statin use significantly improved functional prognosis in patients with aSAH (risk ratio [RR], 0.73; 95% CI, 0.55-0.97). Statins significantly reduced the incidence of ICEs (RR, 0.78; 95% CI, 0.67-0.90). Pravastatin (40 mg/d) decreased the incidence ICEs compared with placebo (RR, 0.14; 95% CI, 0.03-0.65) and was ranked the most effective, presenting with a significantly lower rate of the incidence ICEs than the worst-ranked simvastatin (40 mg/d) (RR, 0.13; 95% CI, 0.02-0.79).

CONCLUSION:
Statins could significantly diminish the incidence of ICEs and enhance functional prognosis in patients with aSAH. Various types and dosages of statins show distinct efficacies.
Effectiveness of precise and quantitative rapid pulmonary rehabilitation nursing program for elderly patients with lung cancer during the perioperative period: A randomized controlled trial
Authors: Chen Bei , Yan Xiaoxia , Wang Xiaojun , Mao Yanjun 
Published: February 2023

Objective: Preoperative rehabilitation should improve the functional condition of patients. Improvements in metabolism, lung mechanics, cardiovascular function, and muscle-function can be achieved by pulmonary rehabilitation. Hence, we focused on elderly patients with lung cancer undergoing surgery, and assessed the effectiveness of a rapid and precise pulmonary rehabilitation nursing program during the perioperative period.
Methods: This randomized controlled trial at the department of thoracic surgery; Shanghai pulmonary hospital, China during 2021 was conducted amongst 218 elderly patients with lung cancer treated by surgical operation into either a precision quantitative nursing model nursing group (experimental group) or a perioperative routine nursing group (control group). After individual planning of the pulmonary rehabilitation nursing outpatient clinic, nurses distributed breathing trainers, instructed the patients in breathing training, and supervised the patients after the operation. For our evaluation we considered pulmonary function tests, postoperative thoracic drainage tube indwelling times, postoperative hospital stays, postoperative complication rates, and postoperative quality of life results.
Results: The experimental group showed better pulmonary function, length of hospital stay, and quality of life outcomes than the control group, but the differences were not statistically significant. However, we found a significantly higher postoperative complications rate in the control group (11.9%) than in the experimental group (3.7%; p=0.02).
Conclusion: Strengthening pulmonary rehabilitation nursing interventions for elderly patients with lung cancer during the perioperative period can reduce their postoperative complications and promote their rapid recovery.
Clinical Trial: Registration Number - ChiCTR2100042916.
doi: https://doi.org/10.12669/pjms.39.2.7103
How to cite this: Chen B, Yan X, Wang X, Mao Y. Effectiveness of precise and quantitative rapid pulmonary rehabilitation nursing program for elderly patients with lung cancer during the perioperative period: A randomized controlled trial. Pak J Med Sci. 2023;39(2):572-577. doi: https://doi.org/10.12669/pjms.39.2.7103
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Biases in Assertions of Self-Rated Health
Authors: Lazarevič Patrick 
Published: February 2023

Comparative analyses frequently examine respondents’ self-rated health (SRH), assuming that it is a valid and comparable measure of generic health. However, given SRH’s vagueness, this assumption is questionable due to (1) manifold non-health influences, such as personal characteristics including optimism, interviewer effects on the rating, and cultural contexts, as well as (2) potential gender, age- or country-specific expectations for one’s health or frames of reference. Conceptually, two major components of SRH can be distinguished: latent health and reporting behavior. While latent health exclusively refers to objective health status, reporting behavior collectively refers to non-health characteristics (NH) affecting SRH. The present paper is primarily concerned with the latter and aims to identify whether and how NH bias SRH, including possible differences by gender, age, and country of residence.
The presented analyses are based on data from 16,183 participants in five countries drawn from the fifth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE). Latent health is controlled via a wide array of health indicators and the residuals are examined with a model covering NH from three different sources: the interviewer, the respondent, and the country of residence. To identify subgroup-specific response behaviors, all analyses are carried out separately by gender, three age groups (50-64, 65-79, and 80+ years), and country of residence.
The analyses uncovered influences of – among others–the interviewer’s SRH, the respondent’s life satisfaction, and the country of residence on SRH, while other factors differed by subgroup. The amount of explained variance due to such reporting behavior (with a mean of seven percent) can be deemed meaningful, considering that controlling for latent health already explains around half of SRH’s variance. The greatest source of non-health influences was respondent characteristics, with the interviewer and country having smaller effects.
These results illustrate the importance of taking NH into account when using SRH measures. Future research on complementing SRH with factual questions in survey design is advisable.
* This article belongs to a special issue on “Levels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivity”.
How the Covid-19 Pandemic Affects Sustainable Development: The Impact on the Social, Economic and Energy Parameters of Sustainable Development
Authors: Martynets Viktoriya , Opanasiuk Yuliia , Matvieieva Yuliia 
Published: February 2023

The Covid-19 pandemic has been a challenge for all countries of the world. Although the most negative impact was on public health, the pandemic also caused damage to the economic, social and energy sectors.
The research puts forward a hypothesis about the differentiation of countries due to the impact of the Covid-19 pandemic on the economic, social and energy parameters of sustainable development. A negative impact on indicators such as GDP, the number of unemployed, electricity generation was identified.
The following methods were used in the article to analyze the impact of the Covid-19 pandemic on the economic, social and energy parameters of sustainable development: systems analysis, deductive approach, regression and correlation analysis and extrapolation.
Theoretical and empirical research show that the economies of countries were not ready for the negative transformation processes caused by the quarantine restrictions. The after-effects of the pandemic will manifest themselves for the long period without concerted action of governments, businesses and the international community. It will negatively affect the social and economic development of countries and undermine the progress towards achieving the sustainable development goals until 2030.
This article will be useful for researchers, political elite and international organizations while developing the anti-crisis programs and programs for the social and economic development of the countries.
Karyotyping of green, yellow and red matoa (Pometia pinnata J.R.Forst. & G.Forst.) from Central Java, Indonesia
Authors: YUNIASTUTI ENDANG , MASAILLA ANANDA PUTRI DEWANTARI , NANDARIYAH NANDARIYAH , RAHMAH NAILU 
Published: February 2023

Abstract. Yuniastuti E, Masailla APD, Nandariyah, Rahmah N. 2023. Karyotyping of green, yellow and red matoa (Pometia pinnata J.R.Forst. & G.Forst.) from Central Java, Indonesia. Biodiversitas 24: 40-46. Matoa (Pometia pinnata J.R.Forst. & G.Forst.) belongs to Sapindaceae family and is widely distributed naturally in Indonesia. However, research on matoa plants,especially for the genetic aspect is poorly reported. Genetic information, through chromosome analysis can be helpful in plant breeding programs. This study aimed to analyze karyotype of chromosomes green, yellow and red matoa collected from Central Java, Indonesia. Chromosome analysis in this study used the squash preparation method. This research was the first karyotyping of matoa using 3 types based on exocarp colors, namely green, yellow and red skin matoa. Each type of matoa was repeated 4 times. The results showed that three types of matoa skin colors have the same number of chromosomes, namely 2n=2x=22 with each chromosome size of green, yellow, and red matoa are 1.070±0.251 ?m, 1.025±0.281 ?m, 006±0.252 ?m, respectively and all of matoa have a metacentric chromosome’s form. The karyotype formula for each type of matoa is 2n=2x=22=11m.