bluuebunny/crossref_metadata_2025_split huggingface dataset:
A low-dimensional cognitive-network space in Alzheimer’s disease and frontotemporal dementia
Authors: Pini Lorenzo , de Lange Siemon C , Pizzini Francesca Benedetta , Boscolo Galazzo Ilaria , Manenti Rosa , Cotelli Maria , Galluzzi Samantha , Cotelli Maria Sofia , Corbetta Maurizio , van den Heuvel Martijn P , Pievani Michela 
Published: December 2022

Abstract
Background
Alzheimer’s disease (AD) and frontotemporal dementia (FTD) show network dysfunctions linked with cognitive deficits. Within this framework, network abnormalities between AD and FTD show both convergent and divergent patterns. However, these functional patterns are far from being established and their relevance to cognitive processes remains to be elucidated.

Methods
We investigated the relationship between cognition and functional connectivity of major cognitive networks in these diseases. Twenty-three bvFTD (age: 71±10), 22 AD (age: 72±6), and 20 controls (age: 72±6) underwent cognitive evaluation and resting-state functional MRI. Principal component analysis was used to describe cognitive variance across participants. Brain network connectivity was estimated with connectome analysis. Connectivity matrices were created assessing correlations between parcels within each functional network. The following cognitive networks were considered: default mode (DMN), dorsal attention (DAN), ventral attention (VAN), and frontoparietal (FPN) networks. The relationship between cognition and connectivity was assessed using a bootstrapping correlation and interaction analyses.

Results
Three principal cognitive components explained more than 80% of the cognitive variance: the first component (cogPC1) loaded on memory, the second component (cogPC2) loaded on emotion and language, and the third component (cogPC3) loaded on the visuo-spatial and attentional domains. Compared to HC, AD and bvFTD showed impairment in all cogPCs (p<0.002), and bvFTD scored worse than AD in cogPC2 (p=0.031). At the network level, the DMN showed a significant association in the whole group with cogPC1 and cogPC2 and the VAN with cogPC2. By contrast, DAN and FPN showed a divergent pattern between diagnosis and connectivity for cogPC2. We confirmed these results by means of a multivariate analysis (canonical correlation).

Conclusions
A low-dimensional representation can account for a large variance in cognitive scores in the continuum from normal to pathological aging. Moreover, cognitive components showed both convergent and divergent patterns with connectivity across AD and bvFTD. The convergent pattern was observed across the networks primarily involved in these diseases (i.e., the DMN and VAN), while a divergent FC-cognitive pattern was mainly observed between attention/executive networks and the language/emotion cognitive component, suggesting the co-existence of compensatory and detrimental mechanisms underlying these components.
Investigation of the structure-odor relationship using a Transformer model
Authors: Zheng Xiaofan , Tomiura Yoichi , Hayashi Kenshi 
Published: December 2022

AbstractThe relationships between molecular structures and their properties are subtle and complex, and the properties of odor are no exception. Molecules with similar structures, such as a molecule and its optical isomer, may have completely different odors, whereas molecules with completely distinct structures may have similar odors. Many works have attempted to explain the molecular structure-odor relationship from chemical and data-driven perspectives. The Transformer model is widely used in natural language processing and computer vision, and the attention mechanism included in the Transformer model can identify relationships between inputs and outputs. In this paper, we describe the construction of a Transformer model for predicting molecular properties and interpreting the prediction results. The SMILES data of 100,000 molecules are collected and used to predict the existence of molecular substructures, and our proposed model achieves an F1 value of 0.98. The attention matrix is visualized to investigate the substructure annotation performance of the attention mechanism, and we find that certain atoms in the target substructures are accurately annotated. Finally, we collect 4462 molecules and their odor descriptors and use the proposed model to infer 98 odor descriptors, obtaining an average F1 value of 0.33. For the 19 odor descriptors that achieved F1 values greater than 0.45, we also attempt to summarize the relationship between the molecular substructures and odor quality through the attention matrix.
Deep learning and radiomics framework for PSMA-RADS classification of prostate cancer on PSMA PET
Authors: Leung Kevin H. , Rowe Steven P. , Leal Jeffrey P. , Ashrafinia Saeed , Sadaghiani Mohammad S. , Chung Hyun Woo , Dalaie Pejman , Tulbah Rima , Yin Yafu , VanDenBerg Ryan , Werner Rudolf A. , Pienta Kenneth J. , Gorin Michael A. , Du Yong , Pomper Martin G. 
Published: December 2022

Abstract
Background
Accurate classification of sites of interest on prostate-specific membrane antigen (PSMA) positron emission tomography (PET) images is an important diagnostic requirement for the differentiation of prostate cancer (PCa) from foci of physiologic uptake. We developed a deep learning and radiomics framework to perform lesion-level and patient-level classification on PSMA PET images of patients with PCa.

Methods
This was an IRB-approved, HIPAA-compliant, retrospective study. Lesions on [18F]DCFPyL PET/CT scans were assigned to PSMA reporting and data system (PSMA-RADS) categories and randomly partitioned into training, validation, and test sets. The framework extracted image features, radiomic features, and tissue type information from a cropped PET image slice containing a lesion and performed PSMA-RADS and PCa classification. Performance was evaluated by assessing the area under the receiver operating characteristic curve (AUROC). A t-distributed stochastic neighbor embedding (t-SNE) analysis was performed. Confidence and probability scores were measured. Statistical significance was determined using a two-tailed t test.

Results
PSMA PET scans from 267 men with PCa had 3794 lesions assigned to PSMA-RADS categories. The framework yielded AUROC values of 0.87 and 0.90 for lesion-level and patient-level PSMA-RADS classification, respectively, on the test set. The framework yielded AUROC values of 0.92 and 0.85 for lesion-level and patient-level PCa classification, respectively, on the test set. A t-SNE analysis revealed learned relationships between the PSMA-RADS categories and disease findings. Mean confidence scores reflected the expected accuracy and were significantly higher for correct predictions than for incorrect predictions (P < 0.05). Measured probability scores reflected the likelihood of PCa consistent with the PSMA-RADS framework.

Conclusion
The framework provided lesion-level and patient-level PSMA-RADS and PCa classification on PSMA PET images. The framework was interpretable and provided confidence and probability scores that may assist physicians in making more informed clinical decisions.
A new thinking: deciphering the aberrance and clinical implication of copper-death signatures in clear cell renal cell carcinoma
Authors: Jiang Aimin , Luo Peng , Chen Ming , Fang Yu , Liu Bing , Wu Zhenjie , Qu Le , Wang Anbang , Wang Linhui , Cai Chen 
Published: December 2022

Abstract
Rationale
Recent research has indicated that cuprotosis, or copper induced cell death, is a novel type of cell death that could be utilized as a new weapon for cancer management. However, the characteristics and implications of such signatures in cancers, especially in clear cell renal cell cancer (ccRCC), remain elusive.

Methods
Expression, methylation, mutation, clinical information, copy number variation, functional implication, and drug sensitivity data at the pan-cancer level were collected from The Cancer Genome Atlas. An unsupervised clustering algorithm was applied to decipher ccRCC heterogeneity. Immune microenvironment construction, immune therapy response, metabolic pattern, and cancer progression signature between subgroups were also investigated.

Results
Cuprotosis related genes were specifically downregulated in various cancer tissues compared with normal tissues and were correlated with hypermethylation and copy number variation. Cuprotosis scores were also dysregulated in tumor tissues, and we found that such a signature could positively regulate oxidative phosphorylation and Myc and negatively regulate epithelial mesenchymal translation and myogenesis pathways. CPCS1 (cuprotosis scores high) and CPCS2 (cuprotosis scores low) in ccRCC displayed distinctive clinical profiles and biological characteristics; the CPCS2 subtype had a higher clinical stage and a worse prognosis and might positively regulate cornification and epidermal cell differentiation to fuel cancer progression. CPCS2 also displayed a higher tumor mutation burden and low tumor stemness index, while it led to a low ICI therapy response and dysfunctional tumor immunity state. The genome-copy numbers of CPCS2, including arm- gain and arm- loss, were higher than those of CPCS1. The prognostic model constructed based on subgroup biomarkers exerted satisfactory performance in both the training and validation cohorts. In addition, overexpression of the copper death activator DLAT suppressed the malignant ability, including cell migration and proliferation, of renal cell lines in vitro and in vivo. Finally, activation of cuprotosis in tumors could enhance antitumor immunity through dsDNA-cGAS-STING signaling in ccRCC.

Conclusion
The activation of cuprotosis might function as a promising approach among multiple cancers. The cuprotosis related signatures could reshape tumor immunity in the ccRCC microenvironment via cGAS-STING signal, thus activating tumor antigen-presenting process. Upregulation of DLAT expression in ccRCC cell lines could reactivate the copper death pattern and be treated as a suitable target for ccRCC.
Points2Sound: from mono to binaural audio using 3D point cloud scenes
Authors: Lluís Francesc , Chatziioannou Vasileios , Hofmann Alex 
Published: December 2022

AbstractFor immersive applications, the generation of binaural sound that matches its visual counterpart is crucial to bring meaningful experiences to people in a virtual environment. Recent studies have shown the possibility of using neural networks for synthesizing binaural audio from mono audio by using 2D visual information as guidance. Extending this approach by guiding the audio with 3D visual information and operating in the waveform domain may allow for a more accurate auralization of a virtual audio scene. We propose Points2Sound, a multi-modal deep learning model which generates a binaural version from mono audio using 3D point cloud scenes. Specifically, Points2Sound consists of a vision network and an audio network. The vision network uses 3D sparse convolutions to extract a visual feature from the point cloud scene. Then, the visual feature conditions the audio network, which operates in the waveform domain, to synthesize the binaural version. Results show that 3D visual information can successfully guide multi-modal deep learning models for the task of binaural synthesis. We also investigate how 3D point cloud attributes, learning objectives, different reverberant conditions, and several types of mono mixture signals affect the binaural audio synthesis performance of Points2Sound for the different numbers of sound sources present in the scene.
Blockchained supply chain management based on IoT tracking and machine learning
Authors: Dong Zhongping , Liang Wei , Liang Yan , Gao Weibo , Lu Yi 
Published: December 2022

AbstractWhen it comes to running and managing modern supply chains, 6G Internet of things (IoT) is of utmost importance. To provide IoT with security and automation, blockchain and machine learning are two upper-layer technology that can help. First, we propose to utilize blockchain in modern supply chains to ensure efficient collaboration between all parties. Second, we adopt multi-head attention (MHA)-based gated recurrent unit (GRU) to do inbound logistics task prediction. Finally, numerical results justify that multi-head attention-based GRU model has better fitting efficiency and prediction accuracy than its counterparts.
Determinants of foreign direct investment inflows to COMESA member countries: an integration of institutional and socio-economic factors
Authors: Meressa Hayelom Abrha 
Published: December 2022

AbstractIn developing economies, stable foreign direct investment inflow is used as a means of realization of private sector growth and sustainable development goals. However, there is variability in inflows to African region in general and its economic bloc groupings in particular overtime across countries. In this regard, numerous empirical studies have been carried out on the determinants of investment inflow variability using different datasets on developing countries despite the studies have produced paradoxical findings. The aim of this study is, therefore, to empirically identify factors that determine variability of foreign direct investment inflows to COMESA member countries using panel data estimators. The study used explanatory research design with arrangement of secondary data, ex post control over variables, unbalanced short panel inclined with quantitative approach. The data were acquired from world development and governance indicators of World Bank for a period of 15 years ranging from 2002 to 2016 for 17 countries. Econometric model estimation procedures and diagnostic tests for classical linear regression model assumptions were carried out before making valid analysis. Accordingly, empirical evidence of the study revealed that infrastructure, government effectiveness, economic growth, control over corruption, trade openness, political stability, human capital and financial development have statistically positive effect on the inflow. However, external debt, inflation and regulatory quality failed to show significant effect. Therefore, member countries should take measures to narrow-up bottlenecks of financial development, improve infrastructure, scale-up trade integration, improve human capital quality, work to bring better political stability and to control corruption in order to boost-up stable inflows.
Sequential correction using satellite rod for the treatment of severe rigid spinal deformity: a retrospective study of 19 cases
Authors: Yin Huipeng , Wang Kun , Li Shuai , Song Yu , Feng Xiaobo , Hua Wenbin , Wu Xinghuo , Zhang Yukun , Yang Cao 
Published: December 2022

Abstract
Objectives
The purpose of this study was to evaluate the effectiveness of sequential correction using satellite rod in patients with severe rigid spinal deformity undergoing posterior-only PVCR.

Methods
19 patients with severe rigid spinal deformity who underwent PVCR at our center from January 2014 to December 2019 were reviewed. Radiographic measurements, including major coronal Cobb angle, kyphotic curve angle, coronal and sagittal balance were measured. Clinical results were noted, including the SRS-22 questionnaire, the Oswestry Disability Index score, and complications.

Results
Total 19 patients were followed at least 2 years. The mean coronal Cobb angle decreased from 122.7° ± 13.17° to 57.89° ± 8.65° postoperatively, and to 58.42° ± 8.98° at final follow-up. Correction rate is 52.8%. The kyphotic curve angle improved from 102.2° ± 17.05° preoperatively to 39.68° ± 13.67° postoperatively, and to 37.74° ± 12.14° at final follow-up. Correction rate is 61.2%. Compared to preoperative results, apex vertebral translation, ODI and SRS-22 were significantly improved at the final follow-up.

Conclusions
For patients with severe rigid spinal deformities, sequential correction with an auxiliary satellite rod can effectively reduce surgical difficulty and improve correction rate.
Using pseudo-absence models to test for environmental selection in marine movement ecology: the importance of sample size and selection strength
Authors: Pinti Jérôme , Shatley Matthew , Carlisle Aaron , Block Barbara A. , Oliver Matthew J. 
Published: December 2022

Abstract
Background
Understanding the selection of environmental conditions by animals requires knowledge of where they are, but also of where they could have been. Presence data can be accurately estimated by direct sampling, sightings, or through electronic tag deployments. However, absence data are harder to determine because absences are challenging to measure in an uncontrolled setting. To address this problem, ecologists have developed different methods for generating pseudo-absence data relying on theoretical movement models. These null models represent the movement of environmentally naive individuals, creating a set of locations that animals could have been if they were not exhibiting environmental selection.

Methods
Here, we use four different kinds of null animal movement models—Brownian motion, Lévy walks, Correlated random walks, and Joint correlated random walks to test the ability and power of each of these null movement models to serve as appropriate animal absence models. We use Kolmogorov-Smirnov tests to detect environmental selection using two data sets, one of simulated animal tracks biased towards warmer sea surface temperatures, and one of 57 observed blue shark tracks of unknown sea surface temperature selection.

Results
The four different types of movement models showed minimal difference in the ability to serve as appropriate null models for environmental selection studies. Selection strength and sample size were more important in detecting true environmental selection. We show that this method can suffer from high false positive rates, especially in the case where animals are not selecting for specific environments. We provide estimates of test accuracy at different sample sizes and selection strengths to avoid false positives when using this method.

Conclusion
We show how movement models can be used to generate pseudo-absences and test for habitat selection in marine organisms. While this approach efficiently detects environmental selection in marine organisms, it cannot detect the underlying mechanisms driving this selection.
Linking the Community Health Fund with Accredited Drug Dispensing Outlets in Tanzania: exploring potentials, pitfalls, and modalities
Authors: Dillip Angel , Kalolo Albino , Mayumana Iddy , Rutishauser Melina , Simon Vendelin T. , Obrist Brigit 
Published: December 2022

Abstract
Background
In low- and middle-income countries, too, public–private partnerships in health insurance schemes are crucial for improving access to health services. Problems in the public supply chain of medicines often lead to medicine stock-outs which then negatively influence enrolment in and satisfaction with health insurance schemes. To address this challenge, the government of Tanzania embarked on a redesign of the Community Health Fund (CHF) and established a Prime Vendor System (Jazia PVS). Informal and rural population groups, however, rely heavily on another public–private partnership, the Accredited Drug Dispensing Outlets (ADDOs). This study takes up this public demand and explores the potentials, pitfalls, and modalities for linking the improved CHF (iCHF) with ADDOs.

Methods
This was a qualitative exploratory study employing different methods of data collection: in-depth interviews, focus group discussions, and document reviews.

Results
Study participants saw a great potential for linking ADDOs with iCHF, following continuous community complaints about medicine stock-out challenges at public health facilities, a situation that also affects the healthcare staff’s working environment. The Jazia PVS was said to have improved the situation of medicine availability at public health facilities, although not fully measuring up to the challenge. Study participants thought linking ADDOs with the iCHF would not only improve access to medicine but also increase member enrolment in the scheme. The main pitfalls that may threaten this linkage include the high price of medicines at ADDOs that cannot be accommodated within the iCHF payment model and inadequate digital skills relevant for communication between iCHF and ADDOs. Participants recommended linking ADDOs with the iCHF by piloting the connection with a few ADDOs meeting the selected criteria, while applying similar modalities for linking private retail outlets with the National Health Insurance Fund (NHIF).

Conclusions
As the government of Tanzania is moving toward the Single National Health Insurance Fund, there is a great opportunity to link the iCHF with ADDOs, building on established connections between the NHIF and ADDOs and the lessons learnt from the Jazia PVS. This study provides insights into the relevance of expanding public–private partnership in health insurance schemes in low- and middle-income countries.
A lower starting point for the medial cut increases the posterior slope in opening-wedge high tibial osteotomy: a cadaveric study
Authors: Erquicia Juan Ignacio , Gil-Gonzalez Sergi , Ibañez Maximiliano , Leal-Blanquet Joan , Combalia Andrés , Monllau Juan Carlos , Pelfort Xavier 
Published: December 2022

Abstract
Purpose
The objective of this study was to evaluate the effects on the posterior tibial slope of different distances from the joint line to start the osteotomy and of varying the placement of the opening wedge in high tibial osteotomy.
Starting the osteotomy more distally and an incorrect location for the tibial opening wedge were hypothesized to increase the posterior tibial slope.

Methods
A cadaveric study was conducted using 12 knees divided into two groups based on the distance from the joint line to the start of the osteotomy: 3 and 4 cm. The preintervention posterior tibial slope was measured radiologically. Once the osteotomy was performed, the medial cortex of the tibia was divided into anteromedial, medial, and posteromedial thirds. A 10° opening wedge was sequentially placed in each third, and the effect on the posterior tibial slope was evaluated radiographically.
Results: Significant changes were observed only in the 3-cm group (p = 0.02) when the wedge was placed in the anteromedial zone. In contrast, in the 4-cm group, significant differences were observed when the opening wedge was placed at both the medial (p = 0.04) and anteromedial (p = 0.012) zones.

Conclusion
Correct control of the posterior tibial slope can be achieved by avoiding a low point when beginning the osteotomy and placing the opening wedge in the posteromedial third of the tibia when performing an opening-wedge high tibial osteotomy.

Level of evidence
Controlled laboratory study.