bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetically engineered human induced pluripotent stem cells for the production of brain-targeting extracellular vesicles
Authors: Tang Fan , Dong Tao , Zhou Chengqian , Deng Leon , Liu Hans B. , Wang Wenshen , Liu Guanshu , Ying Mingyao , Li Pan P. 
Published: October 2024

Abstract
Background
Extracellular vesicles (EVs) are cell-secreted membrane vesicles that have become a promising, natural nanoparticle system for delivering either naturally carried or exogenously loaded therapeutic molecules. Among reported cell sources for EV manufacture, human induced pluripotent stem cells (hiPSCs) offer numerous advantages. However, hiPSC-EVs only have a moderate ability for brain delivery. Herein, we sought to develop a stable hiPSC line for producing EVs with substantially enhanced brain targeting by genetic engineering to overexpress rabies viral glycoprotein (RVG) peptide fused to the N terminus of lysosomal associated membrane protein 2B (RVG-Lamp2B) which has been shown capable of boosting the brain delivery of EVs via the nicotinic acetylcholine receptor.

Methods
An RVG-Lamp2B-HA expression cassette was knocked into the AAVS1 safe harbor locus of a control hiPSC line using the CRISPR/Cas9-assisted homologous recombination. Western blot was used to detect the expression of RVG-Lamp2B-HA in RVG-edited hiPSCs as well as EVs derived from RVG-edited hiPSCs. Uptake of EVs by SH-SY5Y cells in the presence of various endocytic inhibitors was analyzed using flow cytometry. Biodistribution and brain delivery of intravenously injected control and RVG-modified EVs in wild-type mice were examined using ex vivo fluorescent imaging.

Results
Here we report that an RVG-Lamp2B-HA expression cassette was knocked into the AAVS1 safe harbor locus of a control hiPSC line using the CRISPR/Cas9-assisted homologous recombination. The RVG-edited iPSCs have normal karyotype, express pluripotency markers, and have differentiation potential. Expression of RVG-Lamp2B-HA was detected in total cell extracts as well as EVs derived from RVG-edited (vs. control) hiPSCs. The RVG-modified EVs enter neuronal cells via distinct endocytic pathways, compared with control EVs. The biodistribution study confirmed that EVs derived from RVG-edited hiPSCs possess higher brain delivery efficiency.

Conclusion
Taken together, we have established stable, genetically engineered hiPSCs for producing EVs with RVG expression, offering the improved ability for brain-targeted drug delivery.
Vasoactive intestinal peptide promotes secretory differentiation and mitigates radiation-induced intestinal injury
Authors: Agibalova Tatiana , Hempel Anneke , Maurer H. Carlo , Ragab Mohab , Ermolova Anastasia , Wieland Jessica , Waldherr Ávila de Melo Caroline , Heindl Fabian , Giller Maximilian , Fischer Julius Clemens , Tschurtschenthaler Markus , Kohnke-Ertel Birgit , Öllinger Rupert , Steiger Katja , Demir Ihsan Ekin , Saur Dieter , Quante Michael , Schmid Roland M. , Middelhoff Moritz 
Published: October 2024

Abstract
Background
Vasoactive intestinal peptide (VIP) is a neuronal peptide with prominent distribution along the enteric nervous system. While effects of VIP on intestinal motility, mucosal vasodilation, secretion, and mucosal immune cell function are well-studied, the direct impact of VIP on intestinal epithelial cell turnover and differentiation remains less understood. Intestinal stem and progenitor cells are essential for the maintenance of intestinal homeostasis and regeneration, and their functions can be modulated by factors of the stem cell niche, including neuronal mediators. Here, we investigated the role of VIP in regulating intestinal epithelial homeostasis and regeneration following irradiation-induced injury.

Methods
Jejunal organoids were derived from male and female C57Bl6/J, Lgr5-EGFP-IRES-CreERT2 or Lgr5-EGFP-IRES-CreERT2/R26R-LSL-TdTomato mice and treated with VIP prior to analysis. Injury conditions were induced by exposing organoids to 6 Gy of irradiation (IR). To investigate protective effects of VIP in vivo, mice received 12 Gy of abdominal IR followed by intraperitoneal injections of VIP.

Results
We observed that VIP promotes epithelial differentiation towards a secretory phenotype predominantly via the p38 MAPK pathway. Moreover, VIP prominently modulated epithelial proliferation as well as the number and proliferative activity of Lgr5-EGFP+ progenitor cells under homeostatic conditions. In the context of acute irradiation injury in vitro, we observed that IR injury renders Lgr5-EGFP+ progenitor cells more susceptible to VIP-induced modulations, which coincided with the strong promotion of epithelial regeneration by VIP. Finally, the observed effects translate into an in vivo model of abdominal irradiation, where VIP showed to prominently mitigate radiation-induced injury.

Conclusions
VIP prominently governs intestinal homeostasis by regulating epithelial progenitor cell proliferation and differentiation and promotes intestinal regeneration following acute irradiation injury.
[18F]TFB PET/CT misses intense [124I]iodine-avid metastases after redifferentiation therapy in metastatic thyroid cancer
Authors: Backhaus Philipp , Pentlow Keith S. , Ho Alan L , Mauguen Audrey , Fagin James A , Pillarsetty Naga Vara Kishore , Lyashchenko Serge K. , Burnazi Eva , Ghossein Ronald A. , Chhabra Shalini , Abusamra Murad , Larson Steven M. , Schöder Heiko , O’Donoghue Joseph , Weber Wolfgang , Grewal Ravinder K. 
Published: October 2024

Abstract
Background
Fluorine 18-labelled tetrafluoroborate ([18F]TFB) is a substrate for the sodium/iodide symporter. In thyroid cancer, [18F]TFB-PET/CT may be an alternative to iodine imaging to evaluate the extent of disease, eligibility for radioiodine treatment, and success of redifferentiation therapies. We report the results of a pilot study to determine tumor uptake of [18F]TFB and compare its properties to [124I]IodinePET/CT in patients with metastatic thyroid cancer.

Methods
Five patients were included in a prospective study. All patients received PET/CT 1 h after injection of 356 ± 12 MBq [18F]TFB and were given 230 ± 9 MBq [124I]Iodine orally on the same day, followed by PET/CT after 48 h. Before redifferentiation therapy, patients underwent an additional baseline [124I]Iodine PET/CT. Cases were analyzed by two board-certified specialists. Detection rates and Spearman correlation for [18F]TFB and [124I]Iodine were calculated.

Results
Three patients had poorly differentiated thyroid cancer and received trametinib in a redifferentiation trial. Two patients had papillary thyroid cancer and did not receive redifferentiation therapy. Of the 33 lesions seen before/without redifferentiation therapy, 19 (58%) were visible on [18F]TFB and 30 (91%) on [124I]Iodine imaging. In the patients who underwent redifferentiation therapy, 48 lesions were newly seen on [124I]Iodine PET/CT with a median SUVmax of 3.3 (range, 0.4–285.0). All of these lesions were [18F]TFB-negative.

Conclusion
[18F]TFB failed to predict radioactive iodine uptake in patients with poorly differentiated thyroid cancer who underwent redifferentiation therapy with trametinib. It is unclear whether such discrepancies may also occur in other redifferentiation therapies or may even be encountered in redifferentiation-naïve thyroid cancer.

Trial registration number
NCT03196518, registered on June 22, 2017.
Heparin does not improve myocardial glucose metabolism suppression in [18 F]FDG PET/CT in patients with low β-hydroxybutyrate level
Authors: Hartikainen Suvi , Vepsäläinen Ville , Laitinen Tiina , Hedman Marja , Laitinen Tomi , Tompuri Tuomo 
Published: October 2024

Abstract
Background
Inadequate myocardial glucose metabolism suppression (GMS) can hamper interpretation of cardiac [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET/CT). Use of β-hydroxybutyrate (BHB) measurement before [18F]FDG injection has been proposed for predicting adequate GMS. However, limited information is available on BHB measurement in guiding preparations for [18F]FDG-PET/CT. The purpose of this study was to evaluate if point-of-care measured BHB is useful in guiding heparin premedication for cardiac [18F]FDG-PET/CT.

Results
155 patients (82 male) had followed a high-fat, low-carbohydrate diet and fasted for at least twelve hours. For the first 63 patients, BHB was measured, but it was not used to guide premedication. For the subsequent 92 patients, heparin 50 IU/kg was injected intravenously 15–20 min before [18F]FDG injection if the BHB level was low (< 0.35 mmol/l). Cardiac [18F]FDG uptake pattern was evaluated visually and [18F]FDG uptake in the myocardium and blood pool were measured. Median BHB level was 0.4 (range 0.1–5.8) mmol/l. Eighty-eight patients (57%) reached a BHB level higher than 0.35 mmol/l. 112 patients (72%) had adequate GMS. In the high BHB group, 74 patients (84%) had adequate GMS, whereas of those with low BHB, only 38 (57%) had adequate GMS (p < 0.001). In the low BHB group, the prevalence of inadequate GMS was comparable in patients with and without heparin (44% vs. 42%, p = 0.875).

Conclusions
While high BHB predicts adequate GMS, unfractionated heparin does not improve GMS in patients with low BHB.
DOA-informed switching independent vector extraction and beamforming for speech enhancement in underdetermined situations
Authors: Ueda Tetsuya , Nakatani Tomohiro , Ikeshita Rintaro , Araki Shoko , Makino Shoji 
Published: October 2024

AbstractThis paper proposes novel methods for extracting a single Speech signal of Interest (SOI) from a multichannel observed signal in underdetermined situations, i.e., when the observed signal contains more speech signals than microphones. It focuses on extracting the SOI using prior knowledge of the SOI’s Direction of Arrival (DOA). Conventional beamformers (BFs) and Blind Source Separation (BSS) with spatial regularization struggle to suppress interference speech signals in such situations. Although Switching Minimum Power Distortionless Response BF (Sw-MPDR) can handle underdetermined situations using a switching mechanism, its estimation accuracy significantly decreases when it relies on a steering vector determined by the SOI’s DOA. Spatially-Regularized Independent Vector Extraction (SRIVE) can robustly enhance the SOI based solely on its DOA using spatial regularization, but its performance degrades in underdetermined situations. This paper extends these conventional methods to overcome their limitations. First, we introduce a time-varying Gaussian (TVG) source model to Sw-MPDR to effectively enhance the SOI based solely on the DOA. Second, we introduce the switching mechanism to SRIVE to improve its speech enhancement performance in underdetermined situations. These two proposed methods are called Switching weighted MPDR (Sw-wMPDR) and Switching SRIVE (Sw-SRIVE). We experimentally demonstrate that both surpass conventional methods in enhancing the SOI using the DOA in underdetermined situations.
Analysing the robustness of finger vein recognition: cross-dataset reliability and vein utility
Authors: Arican Tugce , Veldhuis Raymond , Spreeuwers Luuk 
Published: October 2024

AbstractFinger vein recognition is an emerging biometric trait known for its privacy features. Despite the remarkable performance of deep learning methods like convolutional neural networks on challenging finger vein datasets, their reliability and robustness need further examination. This study evaluates the robustness of three recognition methods—the traditional Miura Method, a supervised convolutional neural network, and an unsupervised convolutional auto-encoder—through the challenging and more realistic scenario of cross-dataset comparisons. We also analyse the reliability of these methods in terms of sample quality. We introduce a novel vein quality metric to measure vein clarity and complexity and compare it against an existing image quality metric, natural image quality evaluator. Our findings reveal differences in how these recognition methods utilise finger vein images for comparisons, highlighting the need for robust recognition techniques in more realistic scenarios. In addition, our vein quality metric effectively detects defective images, reducing the zero false-match rate from 34.98% to 8.18% on the SDUMLA-HMT dataset. These results indicate the need for metrics more focussing on finger vein image characteristics for effective quality assessment for finger vein images.
$$\text {CO}_2$$-based methane: an overlooked solution for the energy transition
Authors: Servin-Balderas Ivonne , Wetser Koen , ter Heijne Annemiek , Buisman Cees , Hamelers Bert 
Published: October 2024

Abstract
Background
Fossil fuels can be replaced with electricity and hydrogen. However, the implementation and use of these low-carbon energy carriers require a sociotechnical transition. This transition might not be completed in time.

Main text
$$\text {CO}_2$$

CO
2

-based methane is a substitute for natural gas that is less carbon-intensive. This methane is synthesized by capturing $$\text {CO}_2$$

CO
2

from air and by performing water electrolysis to produce hydrogen. $$\text {CO}_2$$

CO
2

-based methane is compatible with our current fossil-based society. An analysis of the substitution of natural gas with different energy carriers will be performed, and the results will be compared. The effects of $$\text {CO}_2$$

CO
2

-based methane, hydrogen, and electricity will be evaluated for energy storage, high-temperature level heat production, and residential heating. The multi-level perspective will be applied to assess these energy carriers in the context of our society.

Conclusions
$$\text {CO}_2$$

CO
2

-based methane is the least energy efficient energy carrier among those analyzed. Nevertheless, this type of methane supports the acceleration of the energy transition.

Highlights

CO2-based methane is a valuable, renewable, and carbon-neutral energy carrier that supports a timely energy transition.

The implementation of hydrogen and electricity requires more modifications to our current sociotechnical society than the implementation of CO2-based methane.

The urgency of reducing CO2 emissions is not being considered adequately in the current societal discussion, and a multi-level perspective analysis should provide valuable results that account for the temporal aspect.
Color restoration of mural images based on a reversible neural network: leveraging reversible residual networks for structure and texture preservation
Authors: Xu Zhigang , Geng Changpeng 
Published: October 2024

Abstract
The Mogao Grottoes in Dunhuang, a treasure of China's and the world's cultural heritage, contains rich historical and cultural deposits and has left precious relics of the history of human art. Over centuries, the Mogao Caves have been affected by natural and human factors, resulting in irreversible fading and discoloration of many murals. In recent years, deep learning technology has shown great potential in the field of virtual mural color restoration. Therefore, this paper proposes a mural image color restoration method based on a reversible neural network. The method first employs an automatic reference selection module based on structural and texture similarity to choose suitable reference mural images for the faded murals. Then, it utilizes a reversible residual network to extract deep features of the mural images without information loss. Next, a channel refinement module is used to eliminate redundant information in the network channels. Finally, an unbiased color transfer module restores the color of the faded mural images. Compared to other image color restoration methods, the proposed method achieves superior color restoration effects while effectively preserving the original structure and texture details of the mural images. Compared to baseline methods, the Structural Similarity Index (SSIM), Feature Similarity Index (FSIM), and Perception-based Image Quality Evaluator (PIQE) values are improved by 7.97%, 3.46%, and 13.98%, respectively. The color restoration of the Dunhuang Mural holds significant historical, artistic, cultural, and economic values, and plays a positive role in the preservation and inheritance of Chinese culture, as well as in the promotion of cultural exchange and mutual understanding.
Modeling unobserved geothermal structures using a physics-informed neural network with transfer learning of prior knowledge
Authors: Shima Akihiro , Ishitsuka Kazuya , Lin Weiren , Bjarkason Elvar K. , Suzuki Anna 
Published: October 2024

AbstractDeep learning has gained attention as a potentially powerful technique for modeling natural-state geothermal systems; however, its physical validity and prediction inaccuracy at extrapolation ranges are limiting. This study proposes the use of transfer learning in physics-informed neural networks to leverage prior expert knowledge at the target site and satisfy conservation laws for predicting natural-state quantities such as temperature, pressure, and permeability. A neural network pre-trained with multiple numerical datasets of natural-state geothermal systems was generated using numerical reservoir simulations based on uncertainties of the permeabilities, sizes, and locations of geological units. Observed well logs were then used for tuning by transfer learning of the network. Two synthetic datasets were examined using the proposed framework. Our results demonstrate that the use of transfer learning significantly improves the prediction accuracy in extrapolation regions with no observed wells.
Surgery for non-Meckel’s small-bowel diverticular perforation: two case reports and a literature review
Authors: Matsuya Naoki , Kuwabara Akifumi , Morioka Nobuhiro , Tanabe Tadashi , Musha Nobuyuki , Nishikura Ken , Tsubono Toshihiro 
Published: October 2024

Abstract
Background
Similar to colonic diverticula, small-intestinal diverticula are often asymptomatic, but may cause life-threatening acute complications. Non-Meckel’s small-bowel diverticular perforation is rare, and the rate of mortality is high. However, there is currently no consensus regarding its therapeutic management.

Case presentation
Case 1: A 73-year-old Japanese man with localized lower abdominal pain was referred to our hospital. Enhanced computed tomography (CT) revealed diverticulitis of the small intestine, which was managed conservatively. Four days after admission, abdominal pain worsened, and repeat CT revealed extraintestinal gas. Emergency surgery was performed for the segmental resection of the perforated jejunum with anastomosis. Case 2: A 73-year-old Japanese woman was transferred to our hospital with small-bowel perforation. CT revealed scattered diverticula in the small intestine and extraintestinal gas around the small-intestinal diverticula. Emergency surgery was performed for the segmental resection of the perforated jejunum with anastomosis.

Conclusions
Conservative treatment for small-bowel diverticular perforation may be attempted in mild cases; however, surgical intervention should not be delayed. Segmental resection of the affected intestinal tract with an anastomosis is the standard treatment. Residual diverticula should be documented because of the possibility of diverticulosis recurrence.
COVID-19 and its effects on food producers: panel data evidence from Burkina Faso
Authors: Druetz Thomas , Brenes-Garita Sara , Bicaba Frank , Tiendrebeogo Cheick , Bicaba Abel 
Published: October 2024

Abstract
Introduction
Burkina Faso implemented stringent measures in response to the COVID-19 pandemic that profoundly affected its economy and might have exacerbated food insecurity. While prior studies have assessed the impact of these measures on consumers, there is a dearth of evidence of its effects on food producers in Sub-Saharan Africa. This study aims (i) to evaluate the repercussions of COVID-19 on the possession of food production assets and on the number of livestock owned; and (ii) to determine the correlation between the food insecurity experience scale (FIES) score, ownership of these assets, and the number of livestock owned.

Methods
This study employs a pre-post comparison design in two panels of randomly selected households in Burkina Faso. While Panel A was constituted of 384 households predominantly (76%) living in rural areas, Panel B comprised 504 households, only half of which (51%) lived in rural areas. All households were visited twice: in July 2019 and February 2021, for Panel A, and in February 2020 and February 2021, for Panel B. Panel B was added to the study before the pandemic thanks to additional funding; the timing of the survey was harmonized in both panels for the second round. Regression models were used with fixed effects at the household level, controlling for potential time-invariant confounding variables, and correlation coefficients between possession of production assets or number of livestock and FIES score were measured.

Results
Our findings indicate that the possession of some assets in Panel A (cart, livestock, bicycle, watch) was significantly reduced during the pandemic, as was the herd sizes among livestock-owning households in both panels. Households with fewer production assets and number of livestock were more likely to experience food insecurity.

Conclusion
This study underscores the vulnerability of rural households in Burkina Faso to the economic disruptions caused by the COVID-19 pandemic. Addressing the challenges faced by farming and livestock-owning households is crucial for mitigating food insecurity and improving resilience in the face of ongoing crises.
Feature selection with annealing for forecasting financial time series
Authors: Pabuccu Hakan , Barbu Adrian 
Published: October 2024

AbstractStock market and cryptocurrency forecasting is very important to investors as they aspire to achieve even the slightest improvement to their buy-or-hold strategies so that they may increase profitability. However, obtaining accurate and reliable predictions is challenging, noting that accuracy does not equate to reliability, especially when financial time-series forecasting is applied owing to its complex and chaotic tendencies. To mitigate this complexity, this study provides a comprehensive method for forecasting financial time series based on tactical input–output feature mapping techniques using machine learning (ML) models. During the prediction process, selecting the relevant indicators is vital to obtaining the desired results. In the financial field, limited attention has been paid to this problem with ML solutions. We investigate the use of feature selection with annealing (FSA) for the first time in this field, and we apply the least absolute shrinkage and selection operator (Lasso) method to select the features from more than 1000 candidates obtained from 26 technical classifiers with different periods and lags. Boruta (BOR) feature selection, a wrapper method, is used as a baseline for comparison. Logistic regression (LR), extreme gradient boosting (XGBoost), and long short-term memory are then applied to the selected features for forecasting purposes using 10 different financial datasets containing cryptocurrencies and stocks. The dependent variables consisted of daily logarithmic returns and trends. The mean-squared error for regression, area under the receiver operating characteristic curve, and classification accuracy were used to evaluate model performance, and the statistical significance of the forecasting results was tested using paired t-tests. Experiments indicate that the FSA algorithm increased the performance of ML models, regardless of problem type. The FSA hybrid models showed better performance and outperformed the other BOR models on seven of the 10 datasets for regression and classification. FSA-based models also outperformed Lasso-based models on six of the 10 datasets for regression and four of the 10 datasets for classification. None of the hybrid BOR models outperformed the hybrid FSA models. Lasso-based models, excluding the LR type, were comparable to the best models for six of the 10 datasets for classification. Detailed experimental analysis indicates that the proposed methodology can forecast returns and their movements efficiently and accurately, providing the field with a useful tool for investors.