bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hydrogen generation from sodium borohydride hydrolysis using a heterogeneous biocatalyst prepared with Zabrus tenebrionides Goeze 1777 (Coleoptera: Carabidae) chitin
Authors: Hoşgün Seda , Fidan Ebru Ceren , Hoşgün Emir Zafer , Şirin Davut Ümit 
Published: March 2024

AbstractCo–B/Chi, which is made up of highly distributed Co–B particles, was synthesized by impregnation and chemical reduction methods. Scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, Brunauer–Emmett–Teller adsorption and Fourier transform infrared spectroscopy analyses were used to describe the morphology and microstructure of Co–B/Chi. The synthesized catalyst showed high catalytic activity in the hydrolysis reaction of NaBH4. The unsupported Co–B samples were compared with the chitin-supported Co–B catalyst, and the result showed that higher catalytic activity and good cycling stability for NaBH4 hydrolysis were obtained with the chitin-supported catalyst. The reaction conditions were investigated to achieve high hydrogen production. The maximum rate of hydrogen production was obtained at 40 °C and 20 mg catalyst amount. At ideal conditions, the hydrolysis reaction’s activation energy was determined to be 51.65 kJ mol−1. It is indicate that Co–B/Chi is a viable low-cost catalyst for the hydrolysis of NaBH4 for hydrogen production.
Asymptomatic Dysphagia and Aspiration in Patients with Idiopathic Bronchiectasis
Authors: Perluk Tal , Abu Bandora Eiman , Freund Ophir , Jacob Tommy , Friedman Regev Inbal , Kleinhendler Eyal , Shteinberg Michal , Bar-Shai Amir , Oestriecher-Kedem Yael 
Published: March 2024

Abstract
Purpose
Although considered contributors to idiopathic bronchiectasis (IB), neither dysphagia nor silent aspiration have been systematically evaluated in IB patients. We aimed to explore the prevalence of asymptomatic dysphagia and silent aspiration in IB patients and to identify parameters predictive of their presence.

Methods
This prospective cohort study included IB patients from our Pulmonary Institute without prior history of dysphagia and without prior dysphagia workup. Swallowing function was assessed by the Eating Assessment Tool (EAT-10) questionnaire and by the Fiberoptic Endoscopic Evaluation of Swallowing (FEES) test.

Results
Forty-seven patients (31 females, mean age 67 ± 16 years) were recruited. An EAT-10 score ≥ 3 (risk for swallowing problems) was present in 21 patients (44.6%). Forty-two patients (89.3%) had at least one abnormal swallowing parameter in the FEES test. Six patients (12.7%) had a penetration aspiration score (PAS) in the FEES of at least 6, indicating aspiration. An EAT-10 score of 3 was found to be the ideal cutoff to predict aspiration in the FEES, with a good level of accuracy (area under the curve = 0.78, 95% CI 0.629–0.932, p = 0.03) and sensitivity of 83%. This cutoff also showed a trend towards a more severe disease using the FACED (forced expiratory volume, age, colonization with pseudomonas, extension of lung involvement, dyspnea) score (p = 0.05).

Conclusion
Dysphagia is prevalent in IB and may be undiagnosed if not specifically sought. We recommend screening all patients with IB for dysphagia by the EAT-10 questionnaire and referring all those with a score of ≥ 3 to formal swallowing assessment.
PD-(L)1 inhibitors plus bevacizumab and chemotherapy as first-line therapy in PD-L1-negative metastatic lung adenocarcinoma: a real-world data
Authors: Ge Yihui , Zhan Yujing , He Jie , Li Juan , Wang Jian , Wei Xiaojuan , Wang Chunni , Gao Aiqin , Sun Yuping 
Published: March 2024

Abstract
Background
Chemotherapy combined with immune checkpoint inhibitors (IC), bevacizumab (BC), or both (IBC) is the preferred first-line therapy for PD-L1-negative and oncogenic-driver wild-type metastatic lung adenocarcinoma. However, the optimal strategy is still undetermined.

Methods
This retrospective study enrolled PD-L1-negative metastatic lung adenocarcinoma patients from four cancer centers between January 1, 2018 and June 30, 2022. All the patients received IC, BC, or IBC as the first-line therapies. The efficacy and safety were evaluated.

Results
A total of 205 patients were included, with 60, 83, and 62 patients in IC, BC, and IBC groups, respectively. The baseline characteristics among three groups were well balanced. Patients treated with IBC had the highest objective response rate (ORR) (43.5%) and disease control rate (DCR) (100%) relative to those treated with IC (40.4%, 84.2%) or BC (40.5%, 96.2%) (ORR: P = 0.919, DCR: P < 0.01). Compared with the IC (6.74 m) or BC (8.28 m), IBC treatment significantly improved median progression-free survival (mPFS) (9.53 m, P = 0.005). However, no difference in overall survival (OS) was observed. When stratified by different clinical and molecular information, we found that male gender, ever smoking, wild-type genes mutations, and adrenal metastasis predict superior PFS benefit when treated with IBC. In patients with liver metastasis, IBC or BC treatment displayed better PFS compared with IC. No additional adverse reactions were observed in IBC group compared with other two groups.

Conclusion
Combined IBC treatment achieved superior DCR and PFS compared with IC or BC in patients with PD-L1-negative metastatic lung adenocarcinoma, while did not increase the adverse events.
Development strategy of non-GMO organism for increased hemoproteins in Corynebacterium glutamicum: a growth-acceleration-targeted evolution
Authors: Park Sehyeon , Lee Seungki , Kim Taeyeon , Choi Ahyoung , Lee Soyeon , Kim Pil 
Published: March 2024

AbstractHeme, found in hemoproteins, is a valuable source of iron, an essential mineral. The need for an alternative hemoprotein source has emerged due to the inherent risks of large-scale livestock farming and animal proteins. Corynebacterium glutamicum, regarded for Qualified Presumption of Safety or Generally Recognized as Safe, can biosynthesize hemoproteins. C. glutamicum single-cell protein (SCP) can be a valuable alternative hemoprotein for supplying heme iron without adversely affecting blood fat levels. We constructed the chemostat culture system to increase hemoprotein content in C. glutamicum SCP. Through adaptive evolution, hemoprotein levels could be naturally increased to address oxidative stress resulting from enhanced growth rate. In addition, we used several specific plasmids containing growth-accelerating genes and the hemA promoter to expedite the evolutionary process. Following chemostat culture for 15 days, the plasmid in selected descendants was cured. The evolved strains showed improved specific growth rates from 0.59 h−1 to 0.62 h−1, 20% enhanced resistance to oxidative stress, and increased heme concentration from 12.95 µg/g-DCW to 14.22–15.24 µg/g-DCW. Notably, the putative peptidyl-tRNA hydrolase-based evolved strain manifested the most significant increase (30%) of hemoproteins. This is the first report presenting the potential of a growth-acceleration-targeted evolution (GATE) strategy for developing non-GMO industrial strains with increased bio-product productivity.
Analysis of factors influencing pancreatic fistula after minimally invasive pancreaticoduodenectomy and establishment of a new prediction model for clinically relevant pancreatic fistula
Authors: Zhu Yuwen , Wu Di , Yang Hao , Lu Zekun , Wang Zhiliang , Zu Guangchen , Li Zheng , Xu Xiaowu , Zhang Yue , Chen Xuemin , Chen Weibo 
Published: March 2024

Abstract
Background
Postoperative pancreatic fistula (POPF) is the most prevalent complications following minimally invasive pancreaticoduodenectomy (MIPD). Only one model related to MIPD exists, and previous POPF scoring prediction methods are based on open pancreaticoduodenectomy patients. Our objectives are to determine the variables that may increase the probability of pancreatic fistula following MIPD and to develop and validate a POPF predictive risk model.

Methods
Data from 432 patients who underwent MIPD between July 2015 and May 2022 were retrospectively collected. A nomogram prediction model was created using multivariate logistic regression analysis to evaluate independent factors for POPF in patients undergoing MIPD in the modeling cohort. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) and the calibration curve were used to verify the nomogram prediction model internally and externally within the modeling cohort and the verification cohort.

Results
Multivariate logistic regression analysis showed that body mass index (BMI), albumin, triglycerides, pancreatic duct diameter, pathological diagnosis and intraoperative bleeding were independent variables for POPF. On the basis of this information, a model for the prediction of risks associated with POPF was developed. In accordance with the ROC analysis, the modeling cohort's AUC was 0.819 (95% CI 0.747–0.891), the internal validation cohort's AUC was 0.830 (95% CI 0.747–0.912), and the external validation cohort's AUC was 0.793 (95% CI 0.671–0.915). Based on the calibration curve, the estimated values of POPF have a high degree of concordance with the actual values that were measured.

Conclusions
This model for predicting the probability of pancreatic fistula following MIPD has strong predictive capacity and can provide a trustworthy predictive method for the early screening of high-risk patients with pancreatic fistula after MIPD and timely clinical intervention.
Comparing oncologic and surgical outcomes of robotic and laparoscopic pancreatoduodenectomy in patients with pancreatic cancer: a propensity-matched analysis
Authors: Wehrle Chase J. , Chang Jenny H. , Gross Abby R. , Woo Kimberly , Naples Robert , Stackhouse Kathryn A. , Dahdaleh Fadi , Augustin Toms , Joyce Daniel , Simon Robert , Walsh R. Matthew , Naffouje Samer A. 
Published: March 2024

Abstract
Introduction
Minimally invasive Pancreatoduodenectomy (MIPD), or the Whipple procedure, is increasingly utilized. No study has compared laparoscopic (LPD) and robotic (RPD) approaches, and the impact of the learning curve on oncologic, technical, and post-operative outcomes remains relatively understudied.

Methods
The National Cancer Database was queried for patients undergoing LPD or RPD from 2010 to 2020 with a diagnosis of pancreatic cancer. Outcomes were compared between approaches using propensity-score matching (PSM); the impact of annual center-level volume of MIPD was also assessed by dividing volume into quartiles.

Results
A total of 3,342 patients were included. Most (n = 2,716, 81.3%) underwent LPD versus RPD (n = 626, 18.7%). There was a high rate (20.2%, n = 719) of positive margins. Mean length-of-stay (LOS) was 10.4 ± 8.9 days. Thirty-day mortality was 2.8% (n = 92) and ninety-day mortality was 5.7% (n = 189).
PSM matched 625 pairs of patients receiving LPD or RPD. After PSM, there was no differences between groups based on age, sex, race, CCI, T-stage, neoadjuvant chemo/radiotherapy, or type of PD. After PSM, there was a higher rate of conversion to open (HR = 0.68, 95%CI = 0.50–0.92)., but there was no difference in LOS (HR = 1.00, 95%CI = 0.92–1.11), 30-day readmission (HR = 1.08, 95% CI = 0.68–1.71), 30-day (HR = 0.78, 95% CI = 0.39–1.56) or 90-day mortality (HR = 0.70, 95% CI = 0.42–1.16), ability to receive adjuvant therapy (HR = 1.15, 95% CI = 0.92–1.44), nodal harvest (HR = 1.01, 95%CI = 0.94–1.09) or positive margins (HR = 1.19, 95% CI = 0.89–1.59).
Centers in lower quartiles of annual volume of MIPD demonstrated reduced nodal harvest (p = 0.005) and a higher rate of conversion to open (p = 0.038). Higher-volume centers had a shorter LOS (p = 0.012), higher rate of initiation of adjuvant therapy (p = 0.042), and, most strikingly, a reduction in 90-day mortality (p = 0.033).

Conclusion
LPD and RPD have similar surgical and oncologic outcomes, with a lower rate of conversion to open in the robotic cohort. The robotic technique does not appear to eliminate the “learning curve”, with higher volume centers demonstrating improved outcomes, especially seen at minimum annual volume of 5 cases.
Grundzüge einer kritischen Medizinethik
Authors: Rubeis Giovanni 
Published: March 2024

ZusammenfassungDie Medizinethik sieht sich zunehmend mit Herausforderungen konfrontiert, die sich aus gesellschaftlichen Machtasymmetrien und epistemischen Ungerechtigkeiten ergeben. Dabei fehlen der Medizinethik die epistemischen Linsen, um diese gesellschaftlichen Kontextfaktoren ärztlichen Handelns analysieren zu können. Um diesen Herausforderungen zu begegnen, bedarf es daher einer theoretisch-konzeptuellen Neuausrichtung. In diesem Beitrag werden die Grundzüge einer kritischen Medizinethik diskutiert, welche Perspektiven und Erkenntniskategorien aus kritischen Theorien übernimmt. Dazu gehört die Kritische Theorie der Frankfurter Schule sowie diejenigen Ansätze aus den Sozial- und Kulturwissenschaften, die auf Machtasymmetrien reflektieren. Dadurch soll das epistemische Spektrum der Medizinethik erweitert werden, um reale Machtverhältnisse besser in normative Analysen einbeziehen zu können.In einem ersten Schritt wird der Beitrag der Sozialwissenschaften im Sinn einer empirischen Ethik diskutiert. Hierbei zeigt sich, dass eine empirische Ausrichtung alleine die epistemologische Lücke nicht schließen kann. In einem weiteren Schritt werden daher epistemische Linsen und Konzepte aus kritischen Theorien dargestellt. Dazu gehören einerseits die Kritische Theorie der Frankfurter Schule, andererseits feministische, postkoloniale, Queer- und Gender-Theorien sowie die Science and Technology Studies (STS). In einer Zusammenfassung werden die Grundzüge einer kritischen Medizinethik dargestellt und deren Limitierungen diskutiert.
Boolean Function Analysis on High-Dimensional Expanders
Authors: Dikstein Yotam , Dinur Irit , Filmus Yuval , Harsha Prahladh 
Published: March 2024

AbstractWe initiate the study of Boolean function analysis on high-dimensional expanders. We give a random-walk based definition of high-dimensional expansion, which coincides with the earlier definition in terms of two-sided link expanders. Using this definition, we describe an analog of the Fourier expansion and the Fourier levels of the Boolean hypercube for simplicial complexes. Our analog is a decomposition into approximate eigenspaces of random walks associated with the simplicial complexes. Our random-walk definition and the decomposition have the additional advantage that they extend to the more general setting of posets, encompassing both high-dimensional expanders and the Grassmann poset, which appears in recent work on the unique games conjecture. We then use this decomposition to extend the Friedgut–Kalai–Naor theorem to high-dimensional expanders. Our results demonstrate that a constant-degree high-dimensional expander can sometimes serve as a sparse model for the Boolean slice or hypercube, and quite possibly additional results from Boolean function analysis can be carried over to this sparse model. Therefore, this model can be viewed as a derandomization of the Boolean slice, containing only $$|X(k-1)|=O(n)$$

|
X
(
k
-
1
)
|
=
O
(
n
)

points in contrast to $$\left( {\begin{array}{c}n\\ k\end{array}}\right) $$

n

k

points in the (k)-slice (which consists of all n-bit strings with exactly k ones).
SHuffled Ant Lion Optimization approach with an exponentially weighted random walk strategy
Authors: Durgut Pinar G. , Tozak Mirac Bugse , Ayvaz M. Tamer 
Published: March 2024

AbstractAnt Lion Optimization (ALO) method is one of the population-based nature-inspired optimization algorithms which mimics the hunting strategy of antlions. ALO is successfully employed for solving many complicated optimization problems. However, it is reported in the literature that the original ALO has some limitations such as the requirement of high number of iterations and possibility of trapping to local optimum solutions, especially for complex or large-scale problems. For this purpose, the SHuffled Ant Lion Optimization (SHALO) approach is proposed by conducting two improvements in the original ALO. Performance of the proposed SHALO approach is evaluated by solving some unconstrained and constrained problems for different conditions. Furthermore, the identified results are statistically compared with the ones obtained by using the original ALO, two improved ALOs which are the self-adaptive ALO (saALO) and the exponentially weighted ALO (EALO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) approaches. Identified results indicated that the proposed SHALO approach significantly improves the solution accuracy with a mean success rate of 76% in terms of finding the global or near-global optimum solutions and provides better results than ALO (22%), saALO (25%), EALO (14%), GA (28%), and PSO (49%) approaches for the same conditions.
Effectiveness and safety of primary prophylaxis with G-CSF after induction therapy for acute myeloid leukemia: a systematic review and meta-analysis of the clinical practice guidelines for the use of G-CSF 2022 from the Japan society of clinical oncology
Authors: Maeda Tomoya , Najima Yuho , Kamiyama Yutaro , Nakao Shinji , Ozaki Yukinori , Nishio Hiroshi , Tsuchihashi Kenji , Ichihara Eiki , Miumra Yuji , Endo Makoto , Maruyama Dai , Yoshinami Tatsuhiro , Susumu Nobuyuki , Takekuma Munetaka , Motohashi Takashi , Ito Mamoru , Baba Eishi , Ochi Nobuaki , Kubo Toshio , Uchino Keita , Kimura Takahiro , Tamura Shinobu , Nishimoto Hitomi , Kato Yasuhisa , Sato Atsushi , Takano Toshimi , Yano Shingo 
Published: March 2024

AbstractAlthough granulocyte colony-stimulating factor (G-CSF) reduces the incidence, duration, and severity of neutropenia, its prophylactic use for acute myeloid leukemia (AML) remains controversial due to a theoretically increased risk of relapse. The present study investigated the effects of G-CSF as primary prophylaxis for AML with remission induction therapy. A detailed literature search for related studies was performed using PubMed, Ichushi-Web, and the Cochrane Library. Data were independently extracted and assessed by two reviewers. A qualitative analysis of pooled data was conducted, and the risk ratio with corresponding confidence intervals was calculated in the meta-analysis and summarized. Sixteen studies were included in the qualitative analysis, nine of which were examined in the meta-analysis. Although G-CSF significantly shortened the duration of neutropenia, primary prophylaxis with G-CSF did not correlate with infection-related mortality. Moreover, primary prophylaxis with G-CSF did not affect disease progression/recurrence, overall survival, or adverse events, such as musculoskeletal pain. However, evidence to support or discourage the use of G-CSF as primary prophylaxis for adult AML patients with induction therapy remains limited. Therefore, the use of G-CSF as primary prophylaxis can be considered for adult AML patients with remission induction therapy who are at a high risk of infectious complications.
Deep Learning Model for Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Chest Radiographs
Authors: Chou Hao-Yang , Lin Yung-Chieh , Hsieh Sun-Yuan , Chou Hsin-Hung , Lai Cheng-Shih , Wang Bow , Tsai Yi-Shan 
Published: March 2024

AbstractBronchopulmonary dysplasia (BPD) is common in preterm infants and may result in pulmonary vascular disease, compromising lung function. This study aimed to employ artificial intelligence (AI) techniques to help physicians accurately diagnose BPD in preterm infants in a timely and efficient manner. This retrospective study involves two datasets: a lung region segmentation dataset comprising 1491 chest radiographs of infants, and a BPD prediction dataset comprising 1021 chest radiographs of preterm infants. Transfer learning of a pre-trained machine learning model was employed for lung region segmentation and image fusion for BPD prediction to enhance the performance of the AI model. The lung segmentation model uses transfer learning to achieve a dice score of 0.960 for preterm infants with $$\le$$
≤
168 h postnatal age. The BPD prediction model exhibited superior diagnostic performance compared to that of experts and demonstrated consistent performance for chest radiographs obtained at $$\le$$
≤
24 h postnatal age, and those obtained at 25 to 168 h postnatal age. This study is the first to use deep learning on preterm chest radiographs for lung segmentation to develop a BPD prediction model with an early detection time of less than 24 h. Additionally, this study compared the model’s performance according to both NICHD and Jensen criteria for BPD. Results demonstrate that the AI model surpasses the diagnostic accuracy of experts in predicting lung development in preterm infants.
A review of predictive uncertainty estimation with machine learning
Authors: Tyralis Hristos , Papacharalampous Georgia 
Published: March 2024

AbstractPredictions and forecasts of machine learning models should take the form of probability distributions, aiming to increase the quantity of information communicated to end users. Although applications of probabilistic prediction and forecasting with machine learning models in academia and industry are becoming more frequent, related concepts and methods have not been formalized and structured under a holistic view of the entire field. Here, we review the topic of predictive uncertainty estimation with machine learning algorithms, as well as the related metrics (consistent scoring functions and proper scoring rules) for assessing probabilistic predictions. The review covers a time period spanning from the introduction of early statistical (linear regression and time series models, based on Bayesian statistics or quantile regression) to recent machine learning algorithms (including generalized additive models for location, scale and shape, random forests, boosting and deep learning algorithms) that are more flexible by nature. The review of the progress in the field, expedites our understanding on how to develop new algorithms tailored to users’ needs, since the latest advancements are based on some fundamental concepts applied to more complex algorithms. We conclude by classifying the material and discussing challenges that are becoming a hot topic of research.
The distribution of breast density in women aged 18 years and older
Authors: Perera Dilukshi , Pirikahu Sarah , Walter Jane , Cadby Gemma , Darcey Ellie , Lloyd Rachel , Hickey Martha , Saunders Christobel , Hackmann Michael , Sampson David D. , Shepherd John , Lilge Lothar , Stone Jennifer 
Published: March 2024

Abstract
Purpose
Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI.

Methods
Breast density measures were estimated for 1,961 Australian women aged 18–97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI.

Results
The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI.

Conclusion
This unique study describes the distribution of breast density measures for women aged 18–97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.