bluuebunny/crossref_metadata_2025_split huggingface dataset:
Safety outcomes and patients’ preferences for home-based intravenous enzyme replacement therapy (ERT) in pompe disease and mucopolysaccharidosis type I (MPS I) disorder: COVID-19 and beyond
Authors: Toscano Antonio , Musumeci Olimpia , Sacchini Michele , Ravaglia Sabrina , Siciliano Gabriele , Fiumara Agata , Verrecchia Elena , Maione Melania , Gentile Jennifer , Fischetto Rita , Crescimanno Grazia , Taurisano Roberta , Sechi Annalisa , Gasperini Serena , Cianci Vittoria , Maggi Lorenzo , Parini Rossella , Lupica Antonino , Scarpa Maurizio 
Published: October 2023

AbstractBackgroundThe Italian Medicines Agency (AIFA) demands precise information on benefit/risk profile of home-based enzyme replacement therapy (ERT) for the treatment of patients with Pompe disease and Mucopolysaccharidosis type I (MPS I). This passage is necessary to obtain the authorization for ERT home therapy, even after the coronavirus disease-19 (COVID-19) pandemic period. This research intends to evaluate the safety, treatment satisfaction, and compliance of MPS I patients treated with laronidase (Aldurazyme®) and Pompe Disease patients treated with alglucosidase alfa (Myozyme®) in a homecare setting.ResultsWe report herein an early interim analysis of the HomERT (Home infusions of ERT) study, a multicenter, non-interventional, double-cohort study that retrospectively analyzed 38 patients from 14 sites in Italy: cohort A (Pompe disease − 32 patients) and cohort B (MPS I − 6 patients). Among the selected patients who started home therapy before enrollment, the average number of missed home-based infusions was 0.7 (1.3) in cohort A and 3.8 (6.4) in cohort B with no return to the hospital setting. Irrespective of the treatment location, 3 prior ADRs per cohort were reported. The majority of patients preferred home-based infusions (cohort A: 96.9%; cohort B: 100%): the main reason was attributed to treatment convenience (cohort A: 81.3%; cohort B: 83.3%). Despite the underlying conditions, most patients self-evaluated their health as “good” (cohort A: 50%; cohort B: 83.3%).ConclusionsEvidence of favorable safety profile, improved treatment compliance and personal satisfaction validates the use of ERT with laronidase and alglucosidase alfa as a strong candidate for home therapy.
Construction of cascade circuits for dynamic temporal regulation and its application to PHB production
Authors: Li Xiaomeng , Qi Qingsheng , Liang Quanfeng 
Published: October 2023

Abstract
Background
To maximize the production capacity and yield of microbial cell factories, metabolic pathways are generally modified with dynamic regulatory strategies, which can effectively solve the problems of low biological yield, growth retardation and metabolic imbalance. However, the strategy of dynamic regulating multiple genes in different time and order is still not effectively solved. Based on the quorum-sensing (QS) system and the principle of cascade regulation, we studied the sequence and time interval of gene expression in metabolic pathways.

Results
We designed and constructed a self-induced dynamic temporal regulatory cascade circuit in Escherichia coli using the QS system and dual regulatory protein cascade and found that the time intervals of the cascade circuits based on the Tra, Las system and the Lux, Tra system reached 200 min and 150 min, respectively. Furthermore, a dynamic temporal regulatory cascade circuit library with time intervals ranging from 110 to 310 min was obtained based on this circuit using promoter engineering and ribosome binding site replacement, which can provide more selective synthetic biology universal components for metabolic applications. Finally, poly-β-hydroxybutyric acid (PHB) production was taken as an example to demonstrate the performance of the cascade circuit library. The content of PHB increased 1.5-fold. Moreover, circuits with different time intervals and different expression orders were found to have different potentials for application in PHB production, and the preferred time-interval circuit strain C2-max was identified by screening.

Conclusions
The self-induced dynamic temporal regulation cascade circuit library can enable the expression of target genes with sequential changes at different times, effectively solving the balance problem between cell growth and product synthesis in two-stage fermentation and expanding the application of dynamic regulatory strategies in the field of metabolic engineering.
First evidence of gonadal hybrid dysgenesis in Chagas disease vectors (Hemiptera, Triatominae): gonad atrophy prevents events of interspecific gene flow and introgression
Authors: Azevedo Luísa Martins Sensato , Cesaretto Natália Regina , de Oliveira Jader , Ravazi Amanda , dos Reis Yago Visinho , Tadini Samanta Cristina Antoniassi Fernand , da Silva Masarin Isabella , Borsatto Kelly Cristine , Galvão Cleber , da Rosa João Aristeu , de Azeredo-Oliveira Maria Tercília Vilela , Alevi Kaio Cesar Chaboli 
Published: October 2023

Abstract
Background
Hybridization events between Triatoma spp. have been observed under both natural and laboratory conditions. The ability to produce hybrids can influence different aspects of the parent species, and may even result in events of introgression, speciation and extinction. Hybrid sterility is caused by unviable gametes (due to errors in chromosomal pairing [meiosis]) or by gonadal dysgenesis (GD). All of the triatomine hybrids analyzed so far have not presented GD. We describe here for the first time GD events in triatomine hybrids and highlight these taxonomic and evolutionary implications of these events.

Methods
Reciprocal experimental crosses were performed between Triatoma longipennis and Triatoma mopan. Intercrosses were also performed between the hybrids, and backcrosses were performed between the hybrids and the parent species. In addition, morphological and cytological analyzes were performed on the atrophied gonads of the hybrids.

Results
Hybrids were obtained only for the crosses T. mopan♀ × T. longipennis♂. Intercrosses and backcrosses did not result in offspring. Morphological analyses of the male gonads of the hybrids confirmed that the phenomenon that resulted in sterility of the hybrid was bilateral GD (the gonads of the hybrids were completely atrophied). Cytological analyses of the testes of the hybrids also confirmed GD, with no germ cells observed (only somatic cells, which make up the peritoneal sheath).

Conclusions
The observations made during this study allowed us to characterize, for the first time, GD in triatomines and demonstrated that gametogenesis does not occur in atrophied gonads. The characterization of GD in male hybrids resulting from the crossing of T. mopan♀ × T. longipennis♂ highlights the importance of evaluating both the morphology and the cytology of the gonads to confirm which event resulted in the sterility of the hybrid: GD (which results in no gamete production) or meiotic errors (which results in non-viable gametes).

Graphical Abstract
A novel tetra-primer ARMS-PCR approach for the molecular karyotyping of chromosomal inversion 2Ru in the main malaria vectors Anopheles gambiae and Anopheles coluzzii
Authors: Pichler Verena , Sanou Antoine , Love R. Rebecca , Caputo Beniamino , Pombi Marco , Toe Kobie Hyacinth , Guelbeogo Moussa W. , Sagnon N’Fale , Ferguson Heather M. , Ranson Hilary , Torre Alessandra della , Besansky Nora J. 
Published: October 2023

Abstract
Background
Chromosomal inversion polymorphisms have been associated with adaptive behavioral, physiological, morphological and life history traits in the two main Afrotropical malaria vectors, Anopheles coluzzii and Anopheles gambiae. The understanding of the adaptive value of chromosomal inversion systems is constrained by the feasibility of cytological karyotyping. In recent years in silico and molecular approaches have been developed for the genotyping of most widespread inversions (2La, 2Rb and 2Rc). The 2Ru inversion, spanning roughly 8% of chromosome 2R, is commonly polymorphic in West African populations of An. coluzzii and An. gambiae and shows clear increases in frequency with increasing rainfall seasonally and geographically. The aim of this work was to overcome the constraints of currently available cytological and high-throughput molecular assays by developing a simple PCR assay for genotyping the 2Ru inversion in individual specimens of both mosquito species.

Methods
We designed tetra-primer amplification refractory mutation system (ARMS)-PCR assays based on five tag single-nucleotide polymorphisms (SNPs) previously shown to be strongly correlated with 2Ru inversion orientation. The most promising assay was validated against laboratory and field samples of An. coluzzii and An. gambiae karyotyped either cytogenetically or molecularly using a genotyping-in-thousands by sequencing (GT-seq) high-throughput approach that employs targeted sequencing of multiplexed PCR amplicons.

Results
A successful assay was designed based on the tag SNP at position 2R, 31710303, which is highly predictive of the 2Ru genotype. The assay, which requires only one PCR, and no additional post-PCR processing other than electrophoresis, produced a clear banding pattern for 98.5% of the 454 specimens tested, which is a 96.7% agreement with established karyotyping methods. Sequences were obtained for nine of the An. coluzzii specimens manifesting 2Ru genotype discrepancies with GT-seq. Possible sources of these discordances are discussed.

Conclusions
The tetra-primer ARMS-PCR assay represents an accurate, streamlined and cost-effective method for the molecular karyotyping of the 2Ru inversion in An. coluzzii and An. gambiae. Together with approaches already available for the other common polymorphic inversions, 2La, 2Rb and 2Rc, this assay will allow investigations of the adaptive value of the complex set of inversion systems observed in the two major malaria vectors in the Afrotropical region.

Graphical Abstract
Association of a history of gestational diabetes mellitus with osteoporosis, bone mineral density, and trabecular bone score in postmenopausal women
Authors: Lu Boqi , Zhang Liping 
Published: October 2023

Abstract
Background
Studies on the association of gestational diabetes mellitus (GDM) with osteoporosis, and bone mineral density (BMD) have been inconsistent. The aim of this study was to investigate the association of a history of GDM with osteoporosis, BMD, and trabecular bone score (TBS) in postmenopausal women.

Methods
Postmenopausal women from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2010, between 2013 and 2014, and between 2017 and 2018 were retrospectively included in this cross-sectional study. The logistic regression model was used to explore the relationship between GDM and osteoporosis, and a weighted linear regression model was applied to investigate the association between GDM and total femoral BMD, femoral neck BMD, and total TBS. Subgroup analysis of the association between GDM and osteoporosis was performed according to age, body mass index (BMI), and DM (yes or no).

Results
Of the 6732 women included, 253 women (3.76%) had GDM. No significant differences in total femoral BMD, femoral neck BMD, and total TBS were observed between postmenopausal women with and without a history of GDM. However, a history of GDM was associated with a higher risk of osteoporosis in postmenopausal women [odds ratio (OR): 11.18, 95% confidence intervals (CI): 3.64 to 34.27, P < 0.001]. There was no significant difference between a history of GDM and osteoporosis in postmenopausal women whom BMI is normal and overweight women. However, there was an association between a history of GDM and osteoporosis in postmenopausal obese women (OR: 26.57, 95% CI 10.23 to 68.98, P < 0.001).

Conclusion
A history of GDM was associated with a higher risk of osteoporosis in postmenopausal women, particularly in postmenopausal obese women.
DeepDelta: predicting ADMET improvements of molecular derivatives with deep learning
Authors: Fralish Zachary , Chen Ashley , Skaluba Paul , Reker Daniel 
Published: October 2023

AbstractEstablished molecular machine learning models process individual molecules as inputs to predict their biological, chemical, or physical properties. However, such algorithms require large datasets and have not been optimized to predict property differences between molecules, limiting their ability to learn from smaller datasets and to directly compare the anticipated properties of two molecules. Many drug and material development tasks would benefit from an algorithm that can directly compare two molecules to guide molecular optimization and prioritization, especially for tasks with limited available data. Here, we develop DeepDelta, a pairwise deep learning approach that processes two molecules simultaneously and learns to predict property differences between two molecules from small datasets. On 10 ADMET benchmark tasks, our DeepDelta approach significantly outperforms two established molecular machine learning algorithms, the directed message passing neural network (D-MPNN) ChemProp and Random Forest using radial fingerprints, for 70% of benchmarks in terms of Pearson’s r, 60% of benchmarks in terms of mean absolute error (MAE), and all external test sets for both Pearson’s r and MAE. We further analyze our performance and find that DeepDelta is particularly outperforming established approaches at predicting large differences in molecular properties and can perform scaffold hopping. Furthermore, we derive mathematically fundamental computational tests of our models based on mathematical invariants and show that compliance to these tests correlates with overall model performance — providing an innovative, unsupervised, and easily computable measure of expected model performance and applicability. Taken together, DeepDelta provides an accurate approach to predict molecular property differences by directly training on molecular pairs and their property differences to further support fidelity and transparency in molecular optimization for drug development and the chemical sciences.
A new fixed-time stability of neural network to solve split convex feasibility problems
Authors: Zheng Jinlan , Gan Rulan , Ju Xingxing , Ou Xiaoqing 
Published: October 2023

AbstractIn this paper, we propose a novel neural network that achieves stability within the fixed time (NFxNN) based on projection to solve the split convex feasibility problems. Under the bounded linear regularity assumption, the NFxNN admits a solution of the split convex feasibility problem. We introduce the relationships between NFxNN and the corresponding neural networks. Additionally, we also prove the fixed-time stability of the NFxNN. The convergence time of the NFxNN is independent of the initial states. The effectiveness and superiority of the NFxNN are also demonstrated by numerical experiments compared with the other methods.
Development and validation of an individualized gene expression-based signature to predict overall survival of patients with high-grade serous ovarian carcinoma
Authors: Yuan Dandan , Zhu Hong , Wang Ting , Zhang Yang , Zheng Xin , Qu Yanjun 
Published: October 2023

Abstract
Background
High-grade serious ovarian carcinoma (HGSOC) is a subtype of ovarian cancer with a different prognosis attributable to genetic heterogeneity. The prognosis of patients with advanced HGSOC requires prediction by genetic markers. This study systematically analyzed gene expression profile data to establish a genetic marker for predicting HGSOC prognosis.

Methods
The RNA-seq data set and information on clinical follow-up of HGSOC were retrieved from Gene Expression Omnibus (GEO) database, and the data were standardized by DESeq2 as a training set. On the other hand, HGSOC RNA sequence data and information on clinical follow-up were retrieved from The Cancer Genome Atlas (TCGA) as a test set. Additionally, ovarian cancer microarray data set was obtained from GEO as the external validation set. Prognostic genes were screened from the training set, and characteristic selection was performed using the least absolute shrinkage and selection operator (LASSO) with 80% re-sampling for 5000 times. Genes with a frequency of more than 2000 were selected as robust biomarkers. Finally, a gene-related prognostic model was validated in both the test and GEO validation sets.

Results
A total of 148 genes were found to be significantly correlated with HGSOC prognosis. The expression profile of these genes could stratify HGSOC prognosis and they were enriched to multiple tumor-related regulatory pathways such as tyrosine metabolism and AMPK signaling pathway. AKR1B10 and ANGPT4 were obtained after 5000-time re-sampling by LASSO regression. AKR1B10 was associated with the metastasis and progression of several tumors. In this study, Cox regression analysis was performed to create a 2-gene signature as an independent prognostic factor for HGSOC, which has the ability to stratify risk samples in all three data sets (p < 0.05). The Gene Set Enrichment Analysis (GSEA) discovered abnormally active REGULATION_OF_AUTOPHAGY and OLFACTORY_TRANSDUCTION pathways in the high-risk group samples.

Conclusion
This study resulted in the creation of a 2-gene molecular prognostic classifier that distinguished clinical features and was a promising novel prognostic tool for assessing the prognosis of HGSOC. RiskScore was a novel prognostic model which might be effective in guiding accurate prognosis of HGSOC.
Multipoint surface electromyography measurement using bull’s-eye electrodes for wide-area topographic analysis
Authors: Shimura Megumi , Mizumoto Akihiko , Xia Yali , Shimomura Yoshihiro 
Published: October 2023

Abstract
Background
Surface electromyography (sEMG) is primarily used to analyze individual and neighboring muscle activity. However, using a broader approach can enable simultaneous measurement of multiple muscles, which is essential for understanding muscular coordination. Using the “bull’s-eye electrode,” which allows bipolar derivation without directional dependence, enables wide-area multipoint sEMG measurements. This study aims to establish a multipoint measurement system and demonstrate its effectiveness and evaluates forearm fatigue and created topographic maps during a grasping task.

Methods
Nine healthy adults with no recent arm injuries or illnesses participated in this study. They performed grasping tasks using their dominant hand, while bull’s-eye electrodes recorded their muscle activity. To validate the effectiveness of the system, we calculated the root mean squares of muscle activity and entropy, an indicator of muscle activity distribution, and compared them over time.

Results
The entropy analysis demonstrated a significant time-course effect with increased entropy over time, suggesting increased forearm muscle uniformity, which is possibly indicative of fatigue. Topographic maps visually displayed muscle activity, revealing notable intersubject variations.

Discussion
Bull’s-eye electrodes facilitated the capture of nine homogeneous muscle activity points, enabling the creation of topographic images. The entropy increased progressively, suggesting an adaptive muscle coordination response to fatigue. Despite some limitations, such as inadequate measurement of the forearm muscles’ belly, the system is an unconventional measurement method.

Conclusion
This study established a robust system for wide-area multipoint sEMG measurements using a bull’s-eye electrode setup. This system effectively evaluates muscle fatigue and provides a comprehensive topographic view of muscle activity. These results mark a significant step towards developing a future multichannel sEMG system with enhanced measurement points and improved wearability.

Trial registration
This study was approved by the Ethics Committee of Chiba University Graduate School of Engineering (acceptance number: R4-12, Acceptance date: November 04, 2022).
Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem
Authors: Coclet Clement , Sorensen Patrick O. , Karaoz Ulas , Wang Shi , Brodie Eoin L. , Eloe-Fadrosh Emiley A. , Roux Simon 
Published: October 2023

AbstractBackgroundViruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics’ seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes.ResultsWe identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages (Leviviricetes), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a “seed-bank” viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: “Kill-The-Winner” which proposes that lytic phages are actively infecting abundant bacteria, and “Piggyback-The-Persistent” which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth.ConclusionTaken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry.