bluuebunny/crossref_metadata_2025_split huggingface dataset:
Land Use Land Cover (LULC) and Land Surface Temperature (LST) Changes and its Relationship with Human Modification in Islamabad Capital Territory, Pakistan
Authors: Ullah Siddique , Ullah Rafi , Javed Muhammad Faisal , Sajjad Raja Umer , Ullah Ikram , Mohamed Abdullah , Ullah Waheed 
Published: January 2023

Abstract
Anthropogenic activities are changing the current Land use Land Cover (LULC) and Land Surface Temperature (LST) patterns worldwide. The current study uses Landsat satellite images (Landsat 5 TM and Landsat 8 OLI) during the years 1988, 2002, and 2016 in an alpine environment of Islamabad Capital Territory, Pakistan, to assess the past patterns of LULC variation using Maximum Likelihood Classification (MLC) method. The LST was derived from thermal bands (6, 10 and 11) of Landsat series data. The Human Modification Index (HMI) relationship with LULC and LST was also assessed using Google Earth Engine (GEE) data. The built-up area expanded by + 9.94%, while agricultural and bare soil dropped by -3.81% and − 3.94%, respectively. The results showed a considerable shift in the LULC and LST with a -1.99% loss in vegetation. The built-up region has the greatest temperature, followed by barren, agricultural, and vegetation classes, according to the LST study for various land cover classes. Similarly, the results of the HMI in different LST classes indicated that high LST classes have high human modification compared to lower LST classes. The statistical analysis between HMI and LST showed a significant association (R-value = 0.61). The results could be used for sustainable urban management and biodiversity conservation.
A Framework for Quantifying the Interacting System of Determinants of Child Malnutrition: A Yemen Case Study
Authors: Hussein Rana A , Gayford Megan , Hailey Peter , Guerrero Saul , Delinger Anne-Celine , Al-Dheeb Najwa , Alajel Senan , Shafique Fouzia , Zaman Muhammad H 
Published: January 2023

Abstract
Background: Several machine learning models, seeking to assess and predict rates of child malnutrition, have been developed in recent years in response to a growing burden of under-five child malnutrition in conflict and crisis settings. These models aim to either identify the strongest predictors of malnutrition among children in a given context, provide a framework for predicting the nutritional status of a given child (classifying them as either malnourished or not) based on individual information about various health-related, socioeconomic, and geographical factors, or do a combination of both. However, these models are often limited in their potential to provide practical or actionable insights due to the often limited interpretability of complex mathematical models, the “black box” nature of some machine learning models, and the complex interactions that exist between various drivers of child malnutrition, which make it difficult to fully conceptualize this system in the form of a model.
Methods: In order to reconcile the complex, highly accurate but hard-to-interpret outputs a machine learning model can provide with conceptual understandings of malnutrition and its interconnected contextual drivers, we sought to understand whether quantitative analysis of the determinants of child malnutrition aligned with conceptual understandings of the causal pathways of child malnutrition. In this study, we take Yemen as a case study for this analysis and using Bayesian analysis, explore the roles of diarrheal disease, food insecurity (quantified through food consumption score) and the interactions between them in driving child malnutrition in Yemen.
Results: Our analysis revealed that, contrary to intuitive reasoning, a progressive increase in food consumption did not necessarily lead to progressive decrease in a child’s risk of malnutrition. We also found that the presence of both diarrhea and poor food consumption together significantly increased the risk of severe malnutrition, as compared to either one on its own. Results of all analyses revealed that exploring the impact of any given factor on child malnutrition risk independently using standard modeling techniques is insufficient for holistically considering the pathways to malnutrition and their complex interactions.
Conclusion: By aiming to quantify the conceptual framework for child malnutrition this way, we can more holistically consider the pathways to malnutrition and their interactions and consider the dependencies and interactions that exist between various health-related interventions in order to maximize their impacts, rather than simply knowing that specific factors may be independently associated with malnutrition risk through quantitative analysis, without fully understanding why this is true or how this can be translated into program-level insights.
GPNMB ameliorates neuroinflammation via the modulation of AMPK/NFκB signaling pathway after SAH in mice
Authors: Li Tao , Zhang Yuansheng , Lu Qixiong , Du Jingshu , Lu Xiaoyang 
Published: January 2023

Abstract
BACKGROUND
Glycoprotein non-metastatic melanoma protein B (GPNMB) got its name from the first discovery in a cell line of non-metastatic melanoma. Later studies found that GPNMB is widely expressed in various tissues and cells of the human body, with the most abundant in neural tissue, epithelial tissue, bone tissue, and monocyte-macrophage system. GPNMB has been shown to have anti-inflammatory effects in a variety of neurological diseases, however, it has not been reported in subarachnoid hemorrhage (SAH).
METHODS
Male CD-1 mice were used and intra-arterial puncture method was applied to establish the SAH model. Exogenous recombinant GPNMB (rGPNMB) was injected intracerebroventricularly 1h after SAH. SAH grading, brain edema and blood-brain barrier (BBB) integrity was quantified, and neurobehavioral tests were performed to evaluate the effect of GPNMB on the outcome. Dorsomorphin, the selective inhibitor on AMPK was introduced to study the downstream signaling through which the GPNMB works. Furthermore, western blot, immunofluorescence staining and ELISA were utilized to confirm the signaling.
RESULTS
After SAH, GPNMB expression increased significantly as a result of the inflammatory response. GPNMB was expressed extensively in mouse microglia, astrocytes and neurons. The administration of rGPNMB could alleviate the brain edema, restore BBB integrity and improve the neurological outcome of mice with SAH. GPNMB treatment significantly magnified the expression of p-AMPK while p-NFκB, IL-1β, IL-6 and TNF-α were suppressed; in the meantime, the combined administration of GPNMB and AMPK inhibitor could decrease the intensity of p-AMPK and reverse the quantity of p-NFκB and the above inflammatory cytokines.
CONCLUSIONS
GPNMB has the potential of ameliorating the brain edema and neuroinflammation, protecting the BBB and improving the neurological outcome, possibly via the AMPK/NFκB signaling pathway.
Genetic architecture of the HLA/MHC locus in cardiometabolic disease, severe mental illness, and related traits.
Authors: Hayman Madeleine , Nicolson Katy , Anderson Jana J , Cullen Breda , Cavanagh Jonathan , Ferguson Lynn D , Graham Nicholas , Ho Frederick K , Lyall Donald M , Lyall Laura M , Parra-Soto Solange , Pell Jill P , Pellicori Pierpaolo , Siebert Stefan , Welsh Paul , Ward Joey , Strawbridge Rona J 
Published: January 2023

Abstract
Background
The Human Leucocyte Antigen/Major Histocompatibility Complex (HLA/MHC) locus is highly complex, with very many genetic variants, extensive linkage disequilibrium blocks, population-specific linkage disequilibrium patterns and many genes. So, whilst many traits have been associated with the HLA/MHC locus, it has largely been omitted from post-genome-wide association study analyses.
Methods
Here we used the UK Biobank cohort to explore the genetic architecture of the HLA/MHC locus in severe mental illness (SMI), cardiometabolic disease (CMD) and related phenotypes. We conducted genetic association analyses of 53,661 variants in up to 402,096 participants, assuming an additive genetic model and adjusting for age, sex, population structure and genotyping chip. In silico follow-up analyses were also conducted.
Results
We demonstrated that the HLA/MHC locus has multiple signals influencing cardiovascular (SBP, DBP, VTE), metabolic (BMI, WHRadjBMI, T2D) and SMI-related traits (mood instability, anhedonia, neuroticism, risk-taking behaviour and smoking), and provided evidence that HLA-B, HLA-C, C4A, BAG6 and ATF6B might contribute to shared mechanisms underlying CMD and SMI.
Conclusions
Current understanding of these candidate genes is in keeping with neuroinflammatory mechanisms linking SMI and CMD. Future analyses considering haplotypes and/or SNP scores would enable better assessment of an individual’s risk (as each SNP is considered in the context of other SNPs), allow alignment with clinically used HLA typing and therefore potential for clinical translation.
Combined role of inflammatory biomarkers and red blood cell distribution width in predicting in-hospital outcomes of acute ischemic stroke patients undergoing thrombolysis
Authors: Wang Yi , Zhu Yafang , Wang Xiaohong , Zhong Chongke , Qin Yan , Sun Yongrong , Cao Yongjun , Zhang Xia , Chen Dongqin 
Published: January 2023

Abstract
Background
To investigate the combined effect of red blood cell distribution width(RDW) and inflammatory biomarkers on in-hospital outcomes of acute ischemic stroke(AIS) patients with thrombolysis.
Methods and Results
417 AIS patients with thrombolysis were included. The participants were divided into four groups according to the cut-off of white blood cell (WBC) or C reactive protein(CRP) and RDW: LWLR, LWHR, HWLR, and HWHR; or LCLR, LCHR, HCLR, and HCHR(L-low, H-high, W-WBC, C-CRP, R-RDW). Logistic regression models were used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) of in-hospital pneumonia and functional outcome across the four subgroups. Patients with higher RDW and inflammatory biomarkers levels have the highest risk of in-hospital outcomes. Compared with patients in LWLR group, the ORs (95% CIs) of those in HWHR group were 12.16 (4.21–35.14) and 9.31 (3.19–27.17) for in-hospital pneumonia and functional outcome. The ORs (95% CIs) of those in HCHR group were 6.93 (2.70-17.78) and 3.38(1.10-10.39) for in-hospital pneumonia and functional outcome, compared with patients in LCLR group. Simultaneously adding RDW and WBC or CRP to the basic model with established risk factors significantly improved risk discrimination and reclassification for pneumonia and functional outcome (all P < 0.05).
Conclusions
Combined RDW and inflammatory biomarkers within 4.5 hours had a better predictive power for in-hospital outcomes of AIS patients with thrombolysis.
Development of a Multi-view Multi-level Artificial Intelligence System to Stratify Risk Assessment of Mammography
Authors: Tan Hongna , Wu Qingxia , Wu Yaping , Zheng Bingjie , Wang Bo , Chen Yan , Du Lijuan , Zhou Jing , Fu Fangfang , Guo Huihui , Fu Cong , Ma Lun , Dong Pei , Xue Zhong , Shen Dinggang , Wang Meiyun 
Published: January 2023

Abstract
Background:
Recent artificial intelligence has exhibited great potential in breast imaging, but its value in precise risk stratification of mammography still needs further investigation. This study is to develop an artificial intelligence system (AIS) for accurate malignancy diagnosis and supportive decision-making on mammographic risk stratification.
Methods:
In this retrospective study, 49732 mammograms of 24866 breasts from 12815 women from two Asian clinics between August 2012 and December 2018 were included. We developed an AIS using multi-view mammograms and multi-level convolutional neural network features to diagnosis malignancy and further assess the relative strengths of AIS versus current BI-RADS categorization. We further evaluate AIS by conducting a counterbalance-designed AI-assisted study, where ten radiologists read 1302 cases with/without AIS assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, F1 score were measured.
Results:
The AIS yielded AUC of 0.910 to 0.995 for malignancy diagnosis in the validation and testing sets. Within BI-RADS 3–4 subgroups with pathological results, AIS can downgrade 83.1% of false-positives into benign groups, and upgrade 54.1% of false-negatives into malignant groups. Compared with BI-RADS, AIS performed better sensitivity and specificity in dense and no-calcification subgroups. AIS also can successfully assist radiologists identify 7 out of 43 malignancies initially diagnosed with BI-RADS 0 with specificity of 96.7%. In the counterbalance-designed AI-assisted study, the average AUC across 10 readers was significantly improved with AIS assistance (P = 0.001).
Conclusion:
AIS can identify malignancy on mammography and further serve as a supportive tool for stratifying BI-RADS categorization.
The safety and efficacy of neoadjuvant chemotherapy based on our resectability criteria for locally advanced perihilar cholangiocarcinoma
Authors: Gyoten Kazuyuki , Kuriyama Naohisa , Maeda Koki , Ito Takahiro , Hayasaki Aoi , Fujii Takehiro , Iizawa Yusuke , Tanemura Akihiro , Murata Yasuhiro , Kishiwada Masashi , Mizuno Shugo 
Published: January 2023

Abstract
Background: Neoadjuvant chemotherapy (NAC) is not commonly used for perihilar cholangiocarcinoma (PHC). This study aimed to evaluate the safety and efficacy of NAC for PHC.
Patients and methods: Ninety-one PHC patients without metastases were treated at our department. They were classified as resectable (R), borderline resectable (BR), or locally advanced unresectable (LA). Upfront surgery (US) was performed for R-PHC without regional lymph node metastases (LNM). The NAC regimen consisted of two courses of gemcitabine-based chemotherapy for advanced PHC: R-PHC with LNM, BR, and LA.
Results: US and NAC were done on 32 and 59 patients, respectively. For US, 31 patients underwent resection (US-R); one with peritoneal-dissemination did not. NAC for locally advanced PHC was done in 56/59 (92%). NAC caused adverse effects in 10/59 (17%), allowed 36/59 (61%) to undergo resection (NAC-R) without impairing liver function, and spared 23/59 (39%) as un-resection (NAC-UR). Overall survival was better in the US-R and NAC-R groups than in NAC-UR (MST: 74 vs. 57 vs. 17 months, p<0.001). In 59 NAC patients, tumour size response occurred in 11/11 (100%) of R, 22/33 (66.7%) of BR, and 9/15 (60.0%) of LA patients. The un-resection rate was higher in the LA group (27% (3/11) in R, 30.3% (10/33) in BR, and 67% (10/15) in LA, p=0.039). Multivariate analyses revealed that LA and age were independent risk factors for un-resection after NAC.
Conclusion: NAC is safe, and contributes to curative resection for advanced PHC. LA remained a risk factor for non-resection through NAC, and required further interventions.
Evaluation of optimal methods and ancestries for calculating polygenic risk scores in East Asian population
Authors: Kim Dong Jun , Kang Joon Ho , Kim Ji-Woong , Cheon Myeong Jae , Kim Sun bin , Lee Young Kee , Lee Byung-Chul 
Published: January 2023

Abstract
Polygenic risk scores (PRSs) have been studied for predicting human diseases, and various methods for PRS calculation have been developed. Most PRS studies to date have focused on European ancestry, and the performance of PRS has not been sufficiently assessed in East Asia. Herein, we evaluated the best-performing PRSs for East Asian populations using data for seven diseases: asthma, breast cancer, coronary artery disease, glaucoma, hyperthyroidism, hypothyroidism, and type 2 diabetes (T2D). A total of 42 PRSs were generated for East Asian samples by applying three PRS methods [linkage disequilibrium (LD) pruning and P-value thresholding (P + T), PRSice, and PRS-CS] and genome-wide association study (GWAS) data from two biobank-scale datasets [European (UK Biobank) and East Asian (BioBank Japan)] to seven diseases. In most cases, PRS-CS showed better predictive performance for disease risk than the other methods and classified low- and high-risk groups more clearly. In addition, the East Asian GWAS data outperformed those from Europeans for T2D PRS, but neither of the two GWAS ancestries showed a dominant effect on PRS performance for other diseases. For East Asian populations, PRS-CS using large-sample GWAS data is likely to provide superior performance, and a PRS generated with GWAS from other ancestries may also perform well.
A fast and accurate kernel-based independence test with applications to high-dimensional and functional data
Authors: Zhang Jin-Ting , Zhu Tianming 
Published: January 2023

Abstract
Testing the dependency between two random variables is an important inference problem in statistics since many statistical procedures rely on the assumption that the two samples are independent. To test whether two samples are independent, a so-called HSIC (Hilbert--Schmidt Independence Criterion)-based test has been proposed. Its null distribution is approximated either by permutation or a Gamma approximation. In this paper, a new HSIC-based test is proposed. Its asymptotic null and alternative distributions are established. It is shown that the proposed test is root-n consistent. A three-cumulant matched chi-squared-approximation is adopted to approximate the null distribution of the test statistic. By choosing a proper reproducing kernel, the proposed test can be applied to many different types of data including multivariate, high-dimensional, and functional data. Three simulation studies and two real data applications show that in terms of level accuracy, power, and computational cost, the proposed test outperforms several existing tests for multivariate, high-dimensional, and functional data.
The value of peripheral blood cell ratios in primary membranous nephropathy
Authors: Zhang Ai-hua , Dai Guang-xia , Zhang Qi-dong , Huang Hong-dong , Liu Wen-hu 
Published: January 2023

AbstractBackgroundPrimary membranous nephropathy (PMN) is a common cause of nephrotic syndrome in adults. Forty percent of the patients still continue to progress and worsen and eventually develop into chronic renal failure. Although phospholipase A2 receptor (PLA2R) is the major antigen of PMN in adults, the clinical features don’t often parallel with the antibody titers. Therefore, it is significant to find relative credible markers to predict the treatment response in patients with PMN.MethodsIn this study, 118 patients with PMN were recruited. The response to treatment was defined as ALB≥30g/L at 6 months and complete remission (CR) or not at the end of the follow-up visit. Renal outcome endpoint was defined as 50% or more Cr increase at the end.ResultsThe patients with poor treatment effects had numerically higher platelet-lymphocytes ratio (PLR). Especially for patients with CR or not, the difference was near to statistic significant (P=0.095). It is noteworthy that when analyzing CR or not, the fitting of the binary logistic regression model including both PLA2R Ab titer and PLR (Hosmer-Lemeshow test: χ2=8.328,P=0.402; OR (PLA2R Ab titer) =1.002 (95% CI 1.000-1.004, P=0.042); OR (PLR) =1.006 (95% CI 0.999-1.013,P=0.098) was markedly better than that with only PLA2R Ab titer (Hosmer-Lemeshow test: χ2=13.885,P=0.016). The patients with renal function deterioration showed significantly higher monocyte-lymphocyte ratio (MLR) (0.26 (0.22-0.31)vs0.18 (0.13-0.22),P=0.012).ConclusionPMN patients with poor treatment response tended to have higher PLR at the time of renal biopsy, and a higher MLR was associated with poor renal outcomes. Our findings suggested that PLR and MLR might be used to predict treatment efficacy and prognosis for PMN patients, respectively.
Group based generalized parameters q-rung orthopairfuzzy Aczel- Alsina weighted average operator and anapplication over green industry development
Authors: ÖZLÜ Şerif 
Published: January 2023

Abstract
The generalized concepts matter in terms of providing more general structures. Therefore,in this paper a wider structure is obtained by being used together q- Rung Orthopair fuzzysets (q- ROFs) and Aczel- Alsina average operators. Q- ROFs are superior than several clusters as intuitionistic fuzzy sets (IFSs) and the Pythagorean fuzzy sets (PFSs) because of hostvariableness. Aczel- Alsina t- norm (AA-TN) and t- conorm (AA-TCN) structures were putforward by Aczel and Alsina in 1982. These operators have very useful structure due to having changeability parameters. The objective of this paper is to introduce q-rung orthopair fuzzy Aczel- Alsina weighted average operator (q-ROFAAWA) by using Aczel- Alsina Average opera-tors (AAAOs). Then, we give generalized q-rung orthopair fuzzy Aczel- Alsina weighted averageoperator (Gq-ROFAAWA) and introduce Group generalized based Q-rung orthopair fuzzy Aczel-Alsina weighted average operator (GGq-ROFAAWA) with helping to (Gq-ROFAAWA). Generalized parameter is essential to induce error margin while decision makers decide final options about a subject. Moreover, we order an algorithm of presented approach and give an example toindicate flexible construction of GGq-ROFAAWA. Immediately after, we introduce a comparative analysis with different methods which indicate the superiority of proposed concept thanexisting methods.
First documented case of Plasmodium knowlesi infection in Denmark in a traveller returning from Malaysian Borneo
Authors: Aftab Huma , Kemp Michael , Stensvold Christen R , Nielsen Henrik V , Jakobsen Marie M , Porskrog Anders , Dessau Ram B 
Published: January 2023

Abstract
Plasmodium knowlesi has been reported as an emerging infection throughout the Southeast Asian region, especially in the Malaysian state of Sabah, where it accounts for the majority of the malaria cases reported. We present a case of P. knowlesiinfection in a Danish woman returning from a short trip to Malaysian Borneo. The patient spent 14 days in forested areas of Sabah and fell ill after returning to Denmark in November 2022. Microscopy of blood smears revealed 0.8% infected erythrocytes, but due to the atypical morphological presentation, a conclusive species identification was made by molecular methods. The patient was treated successfully with artemisinin-based combination therapy. Plasmodium knowlesi is a potentially fatal infection, and taking the increasing travel activity into consideration after the coronavirus disease 2019 (COVID-19) pandemic, P. knowlesishould be a differential diagnosis in patients with travel-associated illness returning from highly endemic Southeast Asian areas.
Single-cell RNA sequencing of intestinal immune cells in neonatal necrotizing enterocolitis
Authors: Oshima Kazuo , Hinoki Akinari , Uchida Hiroo , Tanaka Yujiro , Okuno Yusuke , Go Yasuhiro , Shirota Chiyoe , Tainaka Takahisa , Sumida Wataru , Yokota Kazuki , Makita Satoshi , Takimoto Aitaro , Kano Yoko , Sawa Shinichiro 
Published: January 2023

Abstract
Purpose
Necrotizing enterocolitis (NEC) causes fatal intestinal necrosis in neonates, but its etiology is unknown. We analyzed the intestinal immune response to NEC.
Methods
Using single-cell RNA sequencing (scRNA-seq), we analyzed the gene-expression profiles of intestinal immune cells from four neonates with intestinal perforation (two with NEC and two without NEC). Target mononuclear cells were extracted from the lamina propria of the resected intestines.
Results
In all four cases, the major immune cells, such as T cells (15.1–47.7%), B cells (3.1–19.0%), monocytes (16.5–31.2%), macrophages (1.6–17.4%), dendritic cells (2.4–12.2%), and natural killer cells (7.5–12.8%), were present in similar proportions to those in the neonatal cord blood. Gene set enrichment analysis showed that the MTOR, TNF-α, and MYC signaling pathways were enriched in T cells of the NEC patients, suggesting upregulated immune responses related to inflammation and cell proliferation. In addition, all four cases exhibited a bias toward cell-mediated inflammation, based on the predominance of T helper 1 cells.
Conclusion
Intestinal immunity in NEC subjects exhibited stronger inflammatory responses compared to non-NEC subjects. Further scRNA-seq and cellular analysis may improve our understanding of the pathogenesis of NEC.