bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multicenter validation of synthetic FLAIR as a substitute for FLAIR sequence in acute ischemic stroke
Authors: Hamon Guillaume , Legrand Laurence , Hmeydia Ghazi , Turc Guillaume , Hassen Wagih Ben , Charron Sylvain , Debacker Clement , Naggara Olivier , Thirion Bertrand , Chen Bailiang , Lapergue Bertrand , Oppenheim Catherine , Benzakoun Joseph 
Published: August 2024

Purpose: To evaluate performance of synthetic and real FLAIR for identifying early stroke in a multicenter cohort. Methods: This retrospective study was conducted using DWI and FLAIR extracted from the Endovascular Treatment in Ischemic Stroke image registry (2017–2021). The database was partitioned into subsets according to MRI field strength and manufacturer, and randomly divided into training set (70%) used for model fine-tuning, validation set (15%), and test set (15%). In test set, five readers, blinded to FLAIR sequence type, assessed DWI-FLAIR mismatch using real and synthetic FLAIR. Interobserver agreement for DWI-FLAIR rating and concordance between synthetic and real FLAIR were evaluated with kappa statistics. Sensitivity and specificity for identification of ⩽4.5 h AIS were compared in patients with known onset-to-MRI delay using McNemar’s test. Results: 1454 complete MRI sets (1172 patients, median (IQR) age: 73 years (62–82); 762 women) acquired on 125 MRI units were analyzed. In test set (207 MRI), interobserver reproducibility for DWI-FLAIR mismatch labeling was substantial for real and synthetic FLAIR (Fleiss κ = 0.79 (95%CI: 0.73–0.84) and 0.77 (95%CI: 0.71–0.82), respectively). After consensus, concordance between real and synthetic FLAIR was excellent (κ = 0.85 (95%CI: 0.78–0.92)). In 141 MRI sets with known onset-to-MRI delay, diagnostic performances for ⩽4.5 h AIS identification did not differ between real and synthetic FLAIR (sensitivity: 60/71 (85%) vs 59/71 (83%), p = .56; specificity: 65/70 (93%) vs 65/70 (93%), p > 0.99). Conclusion: A deep-learning-based FLAIR fine-tuned on multicenter data can provide comparable performances to real FLAIR for early AIS identification. This approach may help reducing MR protocol duration and motion artifacts.
Review on the Fabrication of Surface Functional Structures for Enhancing Bioactivity of Titanium and Titanium Alloy Implants
Authors: Tang Heng , Xu Jiaxiang , Guo Bin , Xie Yansong , Sun Yalong , Lu Yanjun , Tang Yong 
Published: August 2024

AbstractTitanium and its alloys have been widely applied in many biomedical fields because of its excellent mechanical properties, corrosion resistance and good biocompatibility. However, problems such as rejection, shedding and infection will occur after titanium alloy implantation due to the low biological activity of titanium alloy surface. The structures with specific functions, which can enhance osseointegration and antibacterial properties, are fabricated on the surface of titanium implants to improve the biological activity between the titanium implants and human tissues. This paper presents a comprehensive review of recent developments and applications of surface functional structure in titanium and titanium alloy implants. The applications of surface functional structure on different titanium and titanium alloy implants are introduced, and their manufacturing technologies are summarized and compared. Furthermore, the fabrication of various surface functional structures used for titanium and titanium alloy implants is reviewed and analyzed in detail. Finally, the challenges affecting the development of surface functional structures applied in titanium and titanium alloy implants are outlined, and recommendations for future research are presented.
COI Barcodes combined with multilocus data for representative Aporia taxa shed light on speciation in the high altitude Irano-Turanian mountain plateaus (Lepidoptera: Pieridae)
Authors: Nazari Vazrick , Lukhtanov Vladimir , Naderi Alireza , Bruna Costantino Della , Zahiri Reza , Cesaroni Donatella , Sbordoni Valerio , Todisco Valentina 
Published: August 2024

AbstractEven though the high plateaus of Qinghai-Tibet and Iran share many faunal elements, the historical biogeography of the species present in this area are not very well understood. We present a complete COI barcode library for Aporia Hübner and a first comprehensive phylogeny for the genus including all known species and majority of subspecies using ten available genes (COI-COII, ND1, ND5, Cytb, EF-1a, Wg, 16S, 28S-D2/D3 and 28S-D8). We then focus on A. leucodice (Eversmann, 1843) and related taxa in order to resolve some long-standing taxonomic issues in this species-group. Based on DNA sequence data as well as morphology, we raise Aporia illumina (Grum-Grshimailo 1890) stat. nov. (= pseudoillumina Tshikolovets 2021 syn. nov.) as a distinct species and designate a lectotype; synonymize Aporia leucodice leucodice Eversmann, 1843 (= A. l. morosevitshae Sheljuzhko, 1908 syn. nov.); and describe a new species, Aporia ahura sp. nov., from the Central Alborz Mountains in northern Iran.
Combining distribution modelling and phylogeography to understand present, past and future of an endangered spider
Authors: Milano Filippo , Casazza Gabriele , Galimberti Andrea , Maggioni Davide , Isaia Marco 
Published: August 2024

Abstract
Background
Understanding how endangered species respond to climatic changes is fundamental for their conservation. Due to its restricted geographic range, its sensitivity to the ongoing global warming and its continuing decline, the Southwestern-Alpine endemic wolf spider Vesubia jugorum is currently classified as Endangered in the IUCN Red List. Here, we combined species distribution modelling (SDM) and phylogeographic inference to describe the present, the past and the future of this species in light of the mtDNA genetic structure of extant populations.

Results
Phylogenetic and network analyses show a high level of genetic differentiation and a strong genetic structure of the populations, likely explicable by a long history of isolation and survival in separate refugia. The SDM projection into past climatic conditions supports these results by showing a smaller distribution range compared to present, mostly restricted to the Maritime and Ligurian Alps, which possibly served as main refugium. Future forecast shows a significant shift in the bioclimatic range towards higher altitudes and latitudes, with a drastic decrease of habitat suitability in the central and south-eastern parts of the range, with consequent general loss of haplotype diversity.

Conclusion
SDM and phylogeographic inference support the hypothesis that the current distribution and the genetic structure of the extant populations mirror the survival in situ of Vesubia jugorum across repeated glacial and interglacial phases, in line with the ‘long-term stability hypothesis’. Future predictions show a significant shift in the bioclimatic range that V. jugorum will be likely unable to track, with profound impact on its long-term survival and its genetic diversity. Our considerations have implication for conservation genetics, highlighting the pivotal role of the transboundary protected areas of the SW-Alps in promoting conservation efforts for this species.
Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study
Authors: Andrikopoulos Dimitrios , Vassiliou Georgia , Fatouros Panagiotis , Tsirmpas Charalampos , Pehlivanidis Artemios , Papageorgiou Charalabos 
Published: August 2024

Abstract
Background
Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals’ functioning, relationships, productivity, and overall quality of life. However, the current diagnostic process exhibits limitations that can significantly affect its overall effectiveness. Notably, its face-to-face and time-consuming nature, coupled with the reliance on subjective recall of historical information and clinician subjectivity, stand out as key challenges. To address these limitations, objective measures such as neuropsychological evaluations, imaging techniques and physiological monitoring of the Autonomic Nervous System functioning, have been explored.

Methods
The main aim of this study was to investigate whether physiological data (i.e., Electrodermal Activity, Heart Rate Variability, and Skin Temperature) can serve as meaningful indicators of ADHD, evaluating its utility in distinguishing adult ADHD patients. This observational, case-control study included a total of 76 adult participants (32 ADHD patients and 44 healthy controls) who underwent a series of Stroop tests, while their physiological data was passively collected using a multi-sensor wearable device. Univariate feature analysis was employed to identify the tests that triggered significant signal responses, while the Informative k-Nearest Neighbors (KNN) algorithm was used to filter out less informative data points. Finally, a machine-learning decision pipeline incorporating various classification algorithms, including Logistic Regression, KNN, Random Forests, and Support Vector Machines (SVM), was utilized for ADHD patient detection.

Results
Results indicate that the SVM-based model yielded the optimal performance, achieving 81.6% accuracy, maintaining a balance between the experimental and control groups, with sensitivity and specificity of 81.4% and 81.9%, respectively. Additionally, integration of data from all physiological signals yielded the best results, suggesting that each modality captures unique aspects of ADHD.

Conclusions
This study underscores the potential of physiological signals as valuable diagnostic indicators of adult ADHD. For the first time, to the best of our knowledge, our findings demonstrate that multimodal physiological data collected via wearable devices can complement traditional diagnostic approaches. Further research is warranted to explore the clinical applications and long-term implications of utilizing physiological markers in ADHD diagnosis and management.
A dual methodology employing ion-pair chromatography and built-in UV spectrophotometry for quantifying recently approved combination of mometasone and indacaterol in a novel combined metered dose inhaler: assessing the greenness, carbon footprint, blueness, and whiteness
Authors: El-Masry Amal A. , Abbas Ahmed Emad F. , Salem Yomna A. 
Published: August 2024

AbstractDeveloping analytical techniques that align with green and sustainable chemistry principles is crucial in today's scientific landscape. This work introduces two innovative approaches for the simultaneous quantification of indacaterol (IND) and mometasone (MOM), a recently approved combination therapy for chronic obstructive pulmonary disease. These methods—rapid isocratic ion pair chromatography (IPC) and UV–visible spectrophotometry—demonstrate improved environmental sustainability, cost-effectiveness, and versatility compared to existing techniques. The optimized 4-min IPC method achieved excellent resolution (retention times 2.18 ± 0.1 min for IND and 3.95 ± 0.1 min for MOM), peak symmetry, and sensitivity. It utilizes a low-cost ion pair mobile phase of acetonitrile and acidified water containing 0.025% sodium dodecyl sulfate (50:50% v/v), making it suitable for laboratories with standard chromatographic instruments. The spectrophotometric approach offers two procedures: first derivative and ratio derivative methods. These serve as simplified, low-cost alternatives for resource-limited laboratories without access to advanced instruments. Both techniques feature simplified protocols that minimize extraction and fractionation steps. Comprehensive validation confirmed outstanding accuracy (98–102%) and precision (%2 <). Sustainability assessments using ComplexGAPI, AGREE, carbon footprint, BAGI, and RGB12 tools demonstrated enhanced environmental performance compared to existing methods. The IPC and spectrophotometry methods achieved greenness scores of 0.81 and 0.85, respectively, surpassing the 0.63–0.67 range of reported techniques. Additionally, they showed lower carbon footprints of 0.035 and 0.022 kg CO2 equivalent emissions per sample, compared to 0.079–0.092 kg for conventional procedures. The application of novel "blueness" and "whiteness" concepts using BAGI and RGB12 algorithms further confirmed superior sustainability, with scores of 87.5 & 90 for blueness and 88.1 & 89.8 for whiteness. Successfully applied to quantify IND and MOM in combined capsules, this work provides a model for eco-friendly pharmaceutical analysis that maintains high analytical reliability while improving sustainability metrics.
Efficiency of acetate-based isopropanol synthesis in Escherichia coli W is controlled by ATP demand
Authors: Kutscha Regina , Tomin Tamara , Birner-Gruenberger Ruth , Bekiaris Pavlos Stephanos , Klamt Steffen , Pflügl Stefan 
Published: August 2024

Abstract
Background
Due to increasing ecological concerns, microbial production of biochemicals from sustainable carbon sources like acetate is rapidly gaining importance. However, to successfully establish large-scale production scenarios, a solid understanding of metabolic driving forces is required to inform bioprocess design. To generate such knowledge, we constructed isopropanol-producing Escherichia coli W strains.

Results
Based on strain screening and metabolic considerations, a 2-stage process was designed, incorporating a growth phase followed by a nitrogen-starvation phase. This process design yielded the highest isopropanol titers on acetate to date (13.3 g L−1). Additionally, we performed shotgun and acetylated proteomics, and identified several stress conditions in the bioreactor scenarios, such as acid stress and impaired sulfur uptake. Metabolic modeling allowed for an in-depth characterization of intracellular flux distributions, uncovering cellular demand for ATP and acetyl-CoA as limiting factors for routing carbon toward the isopropanol pathway. Moreover, we asserted the importance of a balance between fluxes of the NADPH-providing isocitrate dehydrogenase (ICDH) and the product pathway.

Conclusions
Using the newly gained system-level understanding for isopropanol production from acetate, we assessed possible engineering approaches and propose process designs to maximize production. Collectively, our work contributes to the establishment and optimization of acetate-based bioproduction systems.

Graphical Abstract
A factor score clustering approach to analyze the biopharmaceutical sector in the Chinese market during COVID-19
Authors: Xi Jiahui , Wen Conghua , Tang Yifan , Zhao Feifan 
Published: August 2024

AbstractThe biopharmaceutical sector is of considerable interest during the COVID-19 pandemic. This study aims to investigate the biopharmaceutical sector using the Shenwan Industry Classification and provides insights into investment strategies. We combine factor and cluster analyses to reduce data dimensions and detect their latent similarities. Specifically, the biopharmaceutical sector is divided into six categories based on second-level industry classification. It is observed that medical devices, medical services, biological products, and chemical pharmaceuticals maintained their upward tendency, while Chinese medicine and pharmaceutical commerce declined slightly. We also develop optimal investment strategies using various metrics for different investor types.
Systematic review of methods used in prediction models with recurrent event data
Authors: Watson Victoria , Smith Catrin Tudur , Bonnett Laura J. 
Published: August 2024

Abstract
Background
Patients who suffer from chronic conditions or diseases are susceptible to experiencing repeated events of the same type (e.g. seizures), termed ‘recurrent events’. Prediction models can be used to predict the risk of recurrence so that intervention or management can be tailored accordingly, but statistical methodology can vary. The objective of this systematic review was to identify and describe statistical approaches that have been applied for the development and validation of multivariable prediction models with recurrent event data. A secondary objective was to informally assess the characteristics and quality of analysis approaches used in the development and validation of prediction models of recurrent event data.

Methods
Searches were run in MEDLINE using a search strategy in 2019 which included index terms and phrases related to recurrent events and prediction models. For studies to be included in the review they must have developed or validated a multivariable clinical prediction model for recurrent event outcome data, specifically modelling the recurrent events and the timing between them.
The statistical analysis methods used to analyse the recurrent event data in the clinical prediction model were extracted to answer the primary aim of the systematic review. In addition, items such as the event rate as well as any discrimination and calibration statistics that were used to assess the model performance were extracted for the secondary aim of the review.

Results
A total of 855 publications were identified using the developed search strategy and 301 of these are included in our systematic review. The Andersen-Gill method was identified as the most commonly applied method in the analysis of recurrent events, which was used in 152 (50.5%) studies. This was closely followed by frailty models which were used in 116 (38.5%) included studies. Of the 301 included studies, only 75 (24.9%) internally validated their model(s) and three (1.0%) validated their model(s) in an external dataset.

Conclusions
This review identified a variety of methods which are used in practice when developing or validating prediction models for recurrent events. The variability of the approaches identified is cause for concern as it indicates possible immaturity in the field and highlights the need for more methodological research to bring greater consistency in approach of recurrent event analysis. Further work is required to ensure publications report all required information and use robust statistical methods for model development and validation.

PROSPERO registration
CRD42019116031.
Comparative study of low-density versus high-density pedicular screw implantations in management of adolescent idiopathic scoliosis: a randomized clinical trial
Authors: Mostafa Hosam Eldin , Moustafa Abdelrhman Saber Sayed , El Zayat Hazem Hassan , Koheil Ahmed , Ragab Omar Abdel Aleem 
Published: August 2024

Abstract
Background
A number of studies have yielded disparate findings regarding the relationship between implant density and curve correction in adolescent idiopathic scoliosis (AIS) surgery. This study compared the efficacy and safety of low-density (LD) versus high-density (HD) pedicular screw implants in the correction of deformity in AIS regarding clinical, radiological, and quality of life outcomes.

Methods
This study was a single-blind, parallel, randomized trial that enrolled 20 adolescent patients with idiopathic scoliosis scheduled for posterior spinal fusion surgery with all pedicle screw constructs. Patients were randomized into two groups of 10 patients each. The LD group included patients in whom the number of screws per fused spinal level had a density of 1.5 or less, while the HD group had a density greater than 1.5. The primary outcomes were the radiological findings of curve correction. The secondary outcomes included the correlation between implant density and curve correction, the amount of blood loss, operation time, number of screws, fusion level, hospital stay duration, and quality of life assessed by the Scoliosis Research Society 22r questionnaire.

Results
Radiologically, the postoperative main curves Cobb angles and their changes were comparable between both approaches without statistical correlation with the implant density (p˃0.05). The LD approach significantly shortened the operative time (p=0.015), number of screws (p=0.011), implant density (p<0.001), and hospital stay (p<0.001). However, quality of life scores before surgery and at final follow-up did not differ between the two techniques (p˃0.05).

Conclusions
The use of a low-density approach is an effective and safe methodology for attaining satisfactory deformity correction in AIS patients. Furthermore, this approach confers the additional advantage of reduced operative time, number of screws, implant density, and hospital stay in comparison to the high-density approach.
Trial registration Pan African Clinical Trial Registry, PACTR202404611444119. Registered 28 March 2024-Retrospectively registered, https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=29382
Prognostic value of quality of life and functional status in patients with heart failure: a systematic review and meta-analysis
Authors: Ali Abraish , Siddiqui Asad Ali , Shahid Izza , Van Spall Harriette G. C. , Greene Stephen J. , Fudim Marat , Khan Muhammad Shahzeb 
Published: August 2024

Abstract
Background
Functional health status is increasingly being recognized as a viable endpoint in heart failure (HF) trials. We sought to assess its prognostic impact and relationship with traditional clinical outcomes in patients with HF.

Methods
MEDLINE and Cochrane central were searched up to January 2021 for post hoc analyses of trials or observational studies that assessed independent association between baseline health/functional status, and mortality and hospitalization in patients with HF across the range of left ventricular ejection fractions to evaluate the prognostic ability of NYHA class [II, III, IV], KCCQ, MLHFQ, and 6MWD. Hazard ratios (HR) with 95% confidence intervals were pooled.

Results
Twenty-two studies were included. Relative to NYHA I, NYHA class II (HR 1.54 [1.16–2.04]; p < 0.01), NYHA class III (HR 2.08 [1.57–2.77]; p < 0.01), and NYHA class IV (HR 2.53 [1.25–5.12]; p = 0.01) were independently associated with increased risk of mortality. 6MWD (per 10 m) was associated with decreased mortality (HR 0.98 [0.98–0.99]; p < 0.01). A 5-point increase in KCCQ-OSS (HR 0.94 [0.91–0.96]; p < 0.01) was associated with decreased mortality. A high MLHFQ score (> 45) was significantly associated with increased mortality (HR 1.30 [1.14–1.47]; p < 0.01). NHYA class, 6MWD (per 10 m), KCCQ-OSS, and MLHFQ all significantly associated with all-cause mortality in patients with HF.

Conclusion
Identifying such patients with poor health status using functional health assessment can offer a complementary assessment of disease burden and trajectory which carries a strong prognostic value.