bluuebunny/crossref_metadata_2025_split huggingface dataset:
Treatment outcome of patients with co-existing TB and LC: systematic reviews and meta-analysis
Authors: zhang hongjun , li wen-jie , chen yan-wei , chai ya-qin , Zhao Yanjun , Xing Gu 
Published: February 2023

Abstract

Purpose Treatment effect of patients with co-existing tuberculosis (TB) and lung cancer (LC) is still not conclusive. This systematic review and meta-analysis aim to assess treatment regimen, the efficacy and safety of anti-cancer and anti-TB treatment in non-small cell lung cancer (NSCLC) patients with concomitant active TB. Methods A Systematic and comprehensive search was performed in the following databases: PubMed, Embase, and Web of Science, in articles and abstracts published from 1929 to 2022. Eleven articles (involving 809 co-existing TB and LC cases and 10167 LC controls) met the inconclusive criteria. Review Manager version 5.4 software and Stata version 17.0 software were used for this statistical analysis. Results The result of this meta-analysis demonstrates that OS in coexisting pulmonary TB and NSCLC was decreased compared to NSCLC alone (log HR = 1.07, 95% CI = 0.97–1.18, p＜0.001). After removing AEs related to ICI treatment, other AEs of any grade were similar in patients with or without PTB treated with chemotherapy or target drug (log RR = 0.07, 95% CI=-0.04–0.18, p = 0.64, I2 = 0.00%). Timing to anti-cancer therapy: for 39.0% (102/261) of patients, at least 1–4 weeks after the start of anti-TB therapy; for 3.4% (9/261) of patients, at 2 weeks before the start of anti-TB treatment; for 14.6% (38/261) of patients, at received the anti-TB treatment at the same time. Conclusion The result of this meta-analysis demonstrates that OS in coexisting pulmonary TB and NSCLC was decreased compared to NSCLC alone; LC patients with TB receiving first-line chemotherapy or targeted therapy and anti-TB treatment at least 1–4 weeks after the start of anti-TB treatment or at the same time will not increase the incidence of AEs.
Reused LU factorization as a preconditioner for efficient solution of the Parabolized Stability Equations
Authors: Szabó András , Paál György 
Published: February 2023

Abstract
The parabolized stability equation (PSE) is a widely used, efficient method to calculate the evolution of streamwise traveling instabilities in spatially developing, weakly nonparallel flows. Although the PSE method is very economical, computational time can be significant due to the repeated solution of linear systems of equations in each marching step. The linear systems of equations are typically solved by LU factorization due to the moderate size and the sparsity of the coefficient matrices. In this paper, instead of repeated calculation of the LU factorization, a single LU factorization is calculated in each marching step, and used as a preconditioner for an iterative solver. Numerical experiments are conducted on the incompressible PSE, nonlinear PSE (NLPSE) with explicit discretization of the nonlinear terms, and NLPSE with implicit treatment of the nonlinearities. It is shown that the time spent on the solution of the linear systems of equations was reduced by a factor of 2.5, 4.5-7.5, and 20-60 for the three cases, respectively. The methodology can be generalized to the compressible PSE equations, and extended to similar boundary layer stability problems, or slowly varying parabolic partial differential equations.
Blood Pressure Estimation from Photoplythmography Using Hybrid Scattering–LSTM Networks
Authors: Omer Osama A. , Salah Mostafa , Hassan Ammar M. , Sugita Norihiro , Saijo Yoshifumi 
Published: February 2023

Abstract
One of the most significant indicators of heart and cardiovascular health is blood pressure (BP). Blood pressure (BP) has gained great attention in the last decade. Uncontrolled high blood pressure increases the risk of serious health problems, including heart attack and stroke. Recently, machine/deep learning is leveraged for learning the BP from Photoplethysmography (PPG) signals. Hence, continuous BP monitoring can be introduced based on simple wearable contact sensors or even remotely sensed from a proper camera away from the clinical setup. However, the available training dataset imposes many limitations besides the other difficulties related to the PPG time series as high-dimensional data. This work presents beat-by-beat continuous PPG-based BP monitoring while accounting for the aforementioned limitations. For a better exploration of beats’ features, we propose to use wavelet scattering transform as a better descriptive domain to cope with the limitation of the training dataset and to help the deep learning network accurately learn the relationship between the morphological shapes of PPG beats and the BP. Long Short-Term Memory (LSTM) network is utilized to demonstrate the superiority of the wavelet scattering transform over others domains. The learning scenarios are carried out on a beat basis where the input corresponding PPG beat is used for predicting BP in two scenarios; 1) Beat-by-beat arterial blood pressure (ABP) estimation, and 2) Beat-by-beat estimation of the systolic and diastolic blood pressure values. Different transformations are used to extract the features of the PPG beats in different domains including time, DCT, DWT, and wavelet scattering Domains. The simulation results show that using the wavelet scattering domain outperforms the other domains in the sense of root mean square error (RMSE) and mean absolute error (MAE) for both of the suggested two scenarios.
On preferences and reward policies over rankings
Authors: Faella Marco , Sauro Luigi 
Published: February 2023

Abstract
We study the rational preferences of agents participating in a mech- anism whose outcome is a ranking (i.e., a weak order) among participants. We propose a set of self-interest axioms corresponding to different ways for partici- pants to compare rankings. These axioms vary from minimal conditions that most participants can be expected to agree on, to more demanding requirements that apply to specific scenarios.
Then, we analyze all theories that can be obtained by combining the previous axioms and characterize their mutual relationships, revealing a rich hierarchical structure.
After this broad investigation on preferences over rankings, we consider the case where the mechanism can distribute a fixed monetary reward to the participants in a fair way (that is, depending only on the anonymized output ranking). We show that such mechanisms can induce specific classes of preferences by suitably choosing the assigned rewards, even in the absence of tie breaking.
Three-dimensional Evaluations of Preoperative Planning Reproducibility for Osteosynthesis of Distal Humerus Fractures
Authors: Yoshii Yuichi , Iwabuchi Sho , Ikumi Akira , Kohyama Sho , Ogawa Takeshi , Ishii Tomoo 
Published: February 2023

Abstract
Background: Three-dimensional preoperative planning has been applied to the osteosynthesis of distal humerus fractures. The present study investigated the reproducibility of 3D preoperative planning for the osteosynthesis of distal humerus fractures using 3D parameters.
Methods: Twenty-four elbows of 24 distal humerus fracture patients who underwent osteosynthesis with three-dimensional preoperative planning were evaluated. 3D images of the distal humerus were created after taking preoperative CT scans of the injured elbow. Fracture reduction, implant selection, and placement simulations were performed based on 3D images. Postoperative CT images were taken onemonth after surgery. Reproducibility was evaluated with preoperative plans and postoperative 3D images. The longitudinal axis and coordinates of the humerus were defined on 3D images. The coronal angle (CA) was defined as the angle formed by the long axis and the line connecting the medial and lateral margins of the trochlea of the humerus on a coronal plane image. The sagittal angle (SA) was defined as the angle formed by the long axis and the line connecting the top of the lateral epicondyle and the center of the humeral capitellum on a sagittal plane image. The axial angle (AA) was defined as the angle between the sagittal plane and the line connecting the medial and lateral margins behind the trochlea of the humerus. Reproducibility was assessed by the intraclass correlation coefficient (ICC) of each measurement value on preoperative planning and postoperative images.
Results: Preoperative planning and postoperative measurement values were CA: 85.5±6.0°/86.0±5.9°, SA: 141.3±8.3°/140.0±7.5°, and AA: 83.5±3.4°/82.5±5.0°, respectively. ICCs were CA: 0.75 (P<0.01), SA: 0.75 (P<0.01), and AA: 0.40 (P<0.05), respectively.
Conclusions: The 3D preoperative planning of distal humeral fractures achieved the good reproducibility of coronal and sagittal angles, but the relatively poor reproducibility of the axial angle. This may be attributed to an inability to assess the rotation angle during surgery. We propose the measurement indices shown in the present study as a three-dimensional evaluation index for distal humerus fractures.
Trial registration: Registered as NCT04349319 at ClinicalTrials.gov
Identification of oral bacteria in the gut, atherosclerotic plaque, and cultured blood samples of patients with cardiovascular diseases – A secondary analysis of metagenomic microbiome data
Authors: Jayasinghe Thilini N , Chopra Aditi , Franco-Duarte Ricardo , Rajagopal Anjale , Choowong Phannaphat , Soares Pedro , Rito Teresa , Eberhard Joerg 
Published: February 2023

Abstract
Background: Cardiovascular diseases (CVDs) encompass various conditions affecting the heart and its blood vessels. Some CVDs, such as ischemic heart disease, angina, stroke, and atherosclerosis, are often linked with oral microbes. The link between the oral cavity and CVDs is complex. Certain pathogenic oral microbes invade the systemic circulation via bacteraemia or other methods and can significantly increase pro-inflammatory cytokine production. Studies have linked oral microbes, systemic inflammation and immune cross-reactivity in the pathogenesis of atherogenesis. Our secondary data analysis aimed to identify oral bacteria from other non-oral sites (i.e. gut, arterial plaque and cultured blood) that could be linked with CVDs.
Methods: Taxonomic profiling of the entire data set was performed using Kaiju software; bacteria were identified to the species level and compared with the Human Oral Microbiome Database (HOMD). The oral bacteria in the gut, cultured blood and arterial plaque samples were catalogued, with their average frequency calculated for each sample. Additionally, data were filtered by comparison with the Human Microbiome Project (HMP) database.
Results: We identified 17,243 microbial species, of which 410 were present in the HOMD database and further denominated as “oral”. When considering identifications at the species level, all 410 different oral bacterial species were found in at least one gut sample, but only 221 and 169 species were identified in the cultured blood and plaque samples, respectively. Of the 410 species, 153 were present solely in oral-associated environments after comparison with the HMP database, irrespective of their presence in other body sites. The oral bacterial phyla Actinobacteria, Bacteroidetes, Firmicutes, Fusobacterium, Proteobacteria, Spirochetes, Synergistetes and Tenericutes were identified in all three sample types (faeces, arterial plaque and cultured blood) of patients with CVDs. Streptococcus salivarius species was identified as the highest-represented species in the faeces samples. Cutibacterium acnes and Lactobacillus crispatus were found at the highest frequency in cultured blood and plaque samples, respectively.
Conclusion: Oral bacteria related to gingival and periodontal disease can be identified in the faeces, arterial plaque and blood samples of patients with CVDs. Identifying these oral bacterial species in nonoral sites of patients with CVDs would explore the link between oral health and general health, including diseases of the cardiovascular system via bacterial translocation.
Association of Fibrinogen Levels with Sudden Sensorineural Hearing Loss Incidence and Prognosis: a Meta-Analysis
Authors: Bhattarai Abhinav , Tharu Sunraj , Sunar Pritam Singh , Shayaju Nischal , Poudyal Bikash , Chaudhary Anand , Khanal Pitambar , Sah Sanjit Kumar , Khanal Surendra , Shah Sangam 
Published: February 2023

Abstract
Objective
This meta-analysis aimed to obtain the pooled estimate of fibrinogen levels in SSNHL cases and investigate its association with patient prognosis and recovery.
Data sources
We searched the databases PubMed, medRxiv, and Google Scholar for all relevant literature published until August 1, 2022.
Review methods
The primary objective of the meta-analysis was to assess the association of fibrinogen with the risk of SSNHL and recovery. The search results were screened and selected for review on the basis of eligibility criteria. SSNHL patients were defined as cases and healthy individuals as controls. Data on the level of fibrinogen in SSNHL and controls, as well as recovered and the non-recovered group were subjected to a meta-analysis on Review Manager Version 5.4.1 using a random and fixed-effects model. The pooled estimate was expressed as standardized mean difference (SMD) and forest plots were generated for interpretation
Results
Fourteen studies with a total of 2,077 participants fulfilled the eligibility. The overall risk of bias was moderate. The blood level of fibrinogen was significantly higher in SSNHL patients as compared to controls [SMD = 0.35; 95% CI = 0.04–0.67; p = 0.03]. Likewise, the recovered group had significantly lower fibrinogen prior to treatment as compared to the non-recovered group [SMD= -0.36; 95% CI= -0.58 to -0.14; p = 0.001].
Conclusion
Higher fibrinogen levels were observed in SSNHL patients as compared to controls. Recovered patients had a lower fibrinogen level.
CNN based pulmonary nodule segmentation using lung-range-standardization
Authors: O Chung-Hyok , Ri Jong-Hyok , Om Chol-Nam 
Published: February 2023

Abstract
Lung cancer is one of the most fatal disease with high lethality. In general lung cancers are diagnosed by radiologists. But checking radiological image is a very toilsome work for radiologists because it requires long time practice and high concentration. So, many computer-aided diagnosis (CAD) systems were introduced to cooperate with radiologists and nowadays lots of CAD systems based upon deep learning exceed human experts in diagnosing accuracy. And the remarkable thing is that the much of progress has been made in designing architectures. But, in this paper, a new pre-processing method (lung-range-standardization) is proposed in order to improve the general accuracy of lung-related diagnosis systems and to increase the utility of LIDC dataset. And the efficiency of the proposed pre-processing method is validated through comparison between the nodule segmentation model trained using lung-range-standardization and the nodule segmentation model, which is trained without lung-range-standardization.
Cytokine levels in patients with non-M3 myeloid leukemia are key indicators of how well the disease responds to chemotherapy.
Authors: Hu Rui , Ling Xiaosui , Yang Tonghua , Zhang Jinping , Gu Xuezhong , Li Fan , Chen Heng , Wen Yan , Li Zengzheng , Zou Yunlian , Du Yunyun 
Published: February 2023

Abstract
Acute myeloid leukemia (AML) is a malignant hematological neoplastic disease. Autocrine or paracrine cytokines released by leukemic cells regulate the proliferation of AML cells. It is uncertain whether cytokines can indicate whether patients with AML are in remission with chemotherapy. The goal of this study was to evaluate the levels of Th1/Th2/Th17 cytokines in AML patients before and after chemotherapy to determine whether the cytokine levels could predict disease remission after chemotherapy. It was found that the levels of IL-5, IL-6, IL-8, IL-10, TNF-α, TNF-β, IL-17F, and IL-22 were significantly increased at the time of AML diagnosis in patients who achieved remission after two chemotherapy treatments (P < 0.05). After chemotherapy, the cytokine levels were reduced in patients with remission, while the levels of IL-6 and IL-8 were raised in patients without remission (P < 0.05). A comparison of cytokine levels before and after chemotherapy in patients who achieved remission showed areas under the curve (AUCs) of 0.69 for both IL-6 and IL-8. In addition, a comparison of the remission and non-remission groups after chemotherapy showed an AUC of 0.77 for IL-6. We then calculated the cut-off value using receiver operating characteristic (ROC) curves. Values of IL-6 < 9.99 and IL-8 < 8.46 at the time of diagnosis were predictive of chemotherapy success and remission, while IL-6 >14.89 at diagnosis suggested that chemotherapy would not be successful and remission would not be achieved. In conclusion, IL-6 levels were found to be predictive of the likelihood of remission.
WITHDRAWN: Leadership and Employee’s Turnover
Authors: Josquar Amilea 
Published: February 2023

Abstract

This research represents present intellectual in the developing field of Leadership. For this present research two leadership styles are used, Responsible Leadership and Servant Leadership on Employee Turnover Intentions. The focus of this paper is to study the relationship between leadership styles and incoming turnover intentions. To complete this study total of 121 employee’s data were collected from seven pharmaceutical companies of Himachal Pradesh India. ANOVA technique and descriptive used as statistical techniques. The study suggests the presence of a substantial relationship amongst responsible leadership and servant leadership with turnover intentions. Hence, it is concluded that responsible leadership and servant relationship plays a negative significant role in employee’s turnover intention.
Load quantification and effect evaluation of urban non-point source pollution in the Licun River based on SWAT model
Authors: Zhang Minghui , Wang Lin , Huang Xuda , Yu Zhonghua 
Published: February 2023

Abstract
With the gradual control of point source pollution, the impact of urban nonpoint source pollution on river water quality is becoming more prominent. Regarding the current problem that nonpoint source pollution loads in urban basins are difficult to quantify and the impact on water quality is difficult to analyze, the Licun River basin in Qingdao was selected as the research object. Through the field survey and surface accumulation sampling analysis of the basin, the evaluation model of urban nonpoint source pollution was constructed by revising the land type data of the basin and the urban database of the SWAT model. The results showed that concentration of nitrate in precipitation was most sensitive to the simulation of nitrogen loading; organic P in baseflow was most sensitive to the simulation of phosphorus loading. The Nash–Sutcliffe efficiency coefficient (ENS) and the coefficients of determination (R2) of the SWAT model for runoff, total phosphorus (TP), and total nitrogen (TN) in the simulation validation period meet the model requirements,indicating a good model fit. In addition, the spatial and temporal distribution characteristics of urban nonpoint source pollution of TN and TP in 2021 were analyzed. In July, rainfall-runoff from the Licun River basin was the most polluted.
Acute Right Ventricular Failure: Pathophysiology, Diagnostic Approach with Emphasis on the Role of Echocardiography
Authors: Tun Han Naung , Almaghraby Abdallah , Kavalerchyk Vladyslav , Muraru Denisa , Soliman-Aboumarie Hatem , Abdelnabi Mahmoud 
Published: February 2023

Abstract:Right ventricular function is one of the important predictors of survival in heart failure patients. In the past, there has been only limited knowledge regarding right-sided heart failure when compared to left-sided failure. However, there are more emerging data in recent years, and several studies have emphasized the unique features of the right ventricle regarding its anatomy, pathophysiology, clinical consequences, diagnostic modalities, and treatment options. Despite that, management of acute right ventricular failure is still challenging. This article summarizes an overview of acute right heart failure including pathophysiology, causes, clinical features, and diagnostic work-up with emphasis on the role of echocardiography.
Screening for Gestational Diabetes; Can Apelin Help?
Authors: Salman Dina Akeel , Hussein Zina Abdullah , Eimad Taif , Nori Wassan 
Published: February 2023

Background:
Gestational diabetes (GDM) is a pregnancy-related endocrinopathy. Its etiology
is not well understood. Obesity and insulin resistance coexist in GDM. Apelin is an adipocytokine
secreted by fatty cells and expressed in many organs; it can modulate blood glucose. According to research,
apelin levels are higher in obese and type 2 diabetes patients. We aimed to examine the value
of serum apelin as a reliable marker for GDM at 24-28 weeks of pregnancy.

Methods:
A case-control study recruited 120 pregnant women in an age range of 20-40 years with a
singleton pregnancy at 24-28 weeks of pregnancy; all were matched in BMI and gestational age. They
are divided into 2 groups: 60/120 GDM cases based on the International Association of Diabetes and
Pregnancy and 60/120 matched controls at a gestational age of 24-28 weeks at Al-Yarmouk Teaching
Hospital. Demographics data, serum biochemical permeates including HbA1c, fasting blood sugar
(FBS), fasting insulin level, 1 h plasma glucose, and 2 h plasma glucose, following a 75-gram glucose
loading, and a fasting insulin level were recorded.A case-control study recruited 120 pregnant women in an age range of 20-40 years with a
singleton pregnancy at 24-28 weeks of pregnancy; all were matched in BMI and gestational age. They
are divided into 2 groups: 60/120 GDM cases based on the International Association of Diabetes and
Pregnancy and 60/120 matched controls at a gestational age of 24-28 weeks at Al-Yarmouk Teaching
Hospital. Demographics data, serum biochemical permeates including HbA1c, fasting blood sugar
(FBS), fasting insulin level, 1 h plasma glucose, and 2 h plasma glucose, following a 75-gram glucose
loading, and a fasting insulin level were recorded.

Results:
None of the demographic criteria were significant between the two groups at P < 0.05. FBS,
fasting insulin, OGTT-1 and 2 hours, HbA1c, and serum apelin were significantly higher in GDM cases
with P < 0.0001. Pearson's correlations show that Apelin has a statistically significant correlation
with BMI, FBS, fasting insulin, OGTT-1 and 2 hours, and HbA1c, with r = (0.34, 0.71, 0.65, 0.72, and
0.63) and P < 0.0001. ANOVA confirmed an insignificant effect of BMI centile on serum apelin, P <
0.072. ROC estimated the apelin cut-off at > 11.3 (ng/l), associated with 84% sensitivity and 100%
specificity, P < 0.001.

Conclusion:
Strong and significant apelin correlations with parameters for screening GDM make it a
valuable marker, especially when its levels are unaffected by body mass index. Further studies are
recommended to unveil therapeutic avenues for apelin.