bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of adjuvant chemotherapy on survival in ypT0-2 N0 rectal cancer
Authors: Alorabi Mohamed Osama , Gouda Abdelrahman , Abdeen Mohammed , Said Ahmed , Abdelaal Moamen , Eid Reem , Yahia Maha 
Published: January 2025

Abstract
Purpose
The role of adjuvant chemotherapy in rectal cancer patients downstaged to ypT0-2 N0 after neoadjuvant chemoradiotherapy (CRT), and surgery is still debated. This study investigates the impact of adjuvant chemotherapy on survival outcomes in this patient population.

Methods
This retrospective study analyzed hospital records of rectal cancer cases from Shefa Al Orman Cancer Hospital between January 2016 and December 2020, focusing on patients downstaged to ypT0-2 N0 after neoadjuvant CRT and surgery. Patients were divided into two groups based on whether they received adjuvant chemotherapy. Baseline characteristics, DFS, and OS were compared, and survival factors were analyzed using univariate and multivariate Cox regression.

Results
Eighty-five patients met the inclusion criteria; 55 received adjuvant chemotherapy, and 30 did not. The median age was 52, but those receiving adjuvant therapy were younger (47 vs. 60 years, P = 0.006). No significant differences were observed in sex, tumor location, or pathology between groups. Although adjuvant chemotherapy showed a trend toward better 3-year DFS (89.5% vs. 81.9%, P = 0.153) and OS (88.1% vs. 84.6%, P = 0.654), these differences were not statistically significant. Univariate and multivariate analyses confirmed no significant effect of adjuvant chemotherapy on DFS or OS, nor were any other variables significantly associated with survival.

Conclusion
Adjuvant chemotherapy did not significantly improve DFS or OS in rectal cancer patients downstaged to ypT0-2 N0 following neoadjuvant CRT and surgery. Further studies are needed to define the role of adjuvant therapy in this group.
Local infiltration anesthesia with high dose ropivacaine and dexmedetomidine in major knee surgery is safe
Authors: Klasan Antonio , Rigaud Marcel , Hammer Sascha , Kammerlander Christian , Schittek Gregor 
Published: January 2025

Abstract
Background
The role of local infiltration anesthesia (LIA) in knee surgery is significant. LIA can be more potent than a nerve block, but without the downsides. A wide range of agents are used for LIA, including some off-label medications such as dexmedetomidine and ropivacaine. Dexmedetomidine has recently received attention for decreasing demand for anesthetic agents and prolonged effect of anesthesia. The purpose of this study was to demonstrate safety of dexmedetomidine and ropivacaine as LIA.

Methods
This is a retrospective analysis of 200 patients receiving 300 mg of ropivacaine, 100 µg of dexmedetomidine and 10 mL of saline solution as LIA. Both agents are off-label for this use. The LIA applied prior to skin closure as a pertiarticular block. Major knee surgery was defined as ligament reconstruction of at least one ligament, fracture of the femur and the tibia, knee replacement and osteotomy. We evaluated short-term major side-effects of these agents, and evaluated 30-day complications.

Results
Included were 77 arthroplasties, 10 fracture fixations, 19 osteotomies, 55 primary and revision ACL, 10 isolated medial patellar femoral ligament reconstructions, 2 ACLs combined with a partial knee arthroplasty, 4 cartilage transplantations and 23 multiligament knee reconstructions. We observed one transitory discoloration after an ACL reconstruction that disappeared by the 48 h mark. We had no 30-day superficial or deep infections. Cardiac or allergic reactions were not observed.

Conclusions
LIA in a combination of single high-dose ropivacaine and dexmedetomidine is safe in knee surgery. Further studies evaluating pain relief with this LIA combination are needed.
Robustness and Sensitivity of Gd(III)–Gd(III) Double Electron–Electron Resonance (DEER) Measurements: Comparative Study of High-Frequency EPR Spectrometer Designs and Spin Label Variants
Authors: Mocanu Elena M. , Ben-Ishay Yasmin , Topping Lydia , Fisher S. Ronan , Hunter Robert I. , Su Xun-Cheng , Butler Stephen J. , Smith Graham M. , Goldfarb Daniella , Lovett Janet E. 
Published: January 2025

AbstractIn this paper, we explore the robustness and sensitivity of Gd(III)-Gd(III) double electron–electron resonance (DEER) distance measurements in proteins for different spectrometer designs and three spin labels. To do this a protein was labeled at the same two positions with Gd(III) spin labels and measurements were performed on two home-built high-frequency (W-band, ~ 95 GHz) EPR spectrometers with different design approaches, and a commercial 150 W Q-band (34 GHz) spectrometer. The first W-band measurement approach uses a conventional, narrow band single mode cavity, while the second uses a broadband non-resonant induction mode sample holder. Both systems incorporate advanced arbitrary waveform generators (AWGs) that give flexibility over excitation bandwidth. We use three DOTA-like Gd(III) spin labels, Gd.C12, Gd.DO3A and Gd.L1, conjugated to the calmodulin protein. We compare measurements taken by including or excluding the Gd(III) central transition excitation. The advantages and disadvantages of the EPR spectrometers for the measurement of Gd(III)–Gd(III) DEER are discussed in terms of the robustness of the resulting distance distribution width, absolute and concentration sensitivity, sample handling, ease of use, and flexibility of measurement.
The effects of different vitamin E and selenium levels on growth performance, feed utilization, body composition, and intestinal bacterial load of European seabass (Dicentrarchus labrax) post-weaning fry
Authors: Kotit A. M. , Omar E. A. , Srour T. M. , Ibrahim H. A. H , El-Haroun Ehab , A.M.A.S.Goda  
Published: January 2025

Abstract
The current study investigates the combined effect of different dietary vitamins E and selenium (sodium selenite, Se) on the growth, survival, feed utilization, nutrients digestibility, body composition, activity test evaluation, intestinal bacterial load, and hematological indices of European seabass, Dicentrarchus labrax fry. A feeding experiment was conducted in D. labrax using five different diets with the same proximate composition. Introvit-ES100 oral® (ES) provides 50 mg/mL vitamin E and 0.5 mg/mL selenium, a source of VE and Se. The only distinction between the diets was the level of VE and SE. Each diet was fed to triplicate groups of fish (initial weight: 0.13 g) for 84 days. The control diet (ES0%) did not contain any added ES. Diets 2–5 included varying: 50: 0.5 mg/kg (ES1%), 100: 1.0 mg/kg (ES2%), 150: 1.5 mg/kg (ES3%), and 200: 2.0 mg/kg (ES4%). The water quality parameters were temperature 22, with a pH range of 7.9–8.2, the salinity range is 31.3–32.4 ppt, and the nitrogen concentrations are as follows: N at 0.54, NH3 at 0.73, and NH4 at 0.77. The results showed that seabass fry had the highest FBW, WG, SGR, FL, and K values when fed 150: 1.5 mg kg−1 of VE and Se, respectively (ES3%). Fish provided the ES4% diet had the highest survival (%) and showed inferior growth performance. Apparent digestibility coefficient analysis, which included protein, lipid, and carbohydrate digestibility, revealed that the highest values were recorded in fish fed the ES3% diets. The highest body protein was recorded in ES3%; the lowest lipid content value was recorded in ES4%. The highest white blood cell count, red blood cell count, and hematocrit values were recorded in ES3%. While the highest hemoglobin values were recorded in ES4%. The highest activity test value was recorded in ES2% and ES3% diets. The lowest Vibrio sp. count was recorded in ES3%. While the Aeromonas sp. was not detected in all experimental treatments. The results indicated that supplementing the diet with 150 mg kg−1 of VE and 1.5 mg kg−1 of Se improved growth performance, feed utilization, and survival rates, resulting in increased production of D. labrax fry after weaning in marine hatcheries.
Expanding towards contraction: the alternation of floods and droughts as a fundamental component in river ecology
Authors: Bernal S. , Ledesma J. L. J. , Peñarroya X. , Jativa C. , Catalán N. , Casamayor E. O. , Lupon A. , Marcé R. , Martí E. , Triadó-Margarit X. , Rocher-Ros G. 
Published: January 2025

AbstractClimate warming is causing more extreme weather conditions, with both larger and more intense precipitation events as well as extended periods of drought in many regions of the world. The consequence is an alteration of the hydrological regime of streams and rivers, with an increase in the probability of extreme hydrological conditions. Mediterranean-climate regions usually experience extreme hydrological events on a seasonal basis and thus, freshwater Mediterranean ecosystems can be used as natural laboratories for better understanding how climate warming will impact ecosystem structure and functioning elsewhere. In this paper, we revisited and contextualized historical and new datasets collected at Fuirosos, a well-studied Mediterranean intermittent stream naturally experiencing extreme hydrological events, to illustrate how the seasonal alternation of floods and droughts influence hydrology, microbial assemblages, water chemistry, and the potential for biogeochemical processing. Moreover, we revised some of the most influential conceptual and quantitative frameworks in river ecology to assess to what extent they incorporate the occurrence of extreme hydrological events. Based on this exercise, we identified knowledge gaps and challenges to guide future research on freshwater ecosystems under intensification of the hydrological cycle. Ultimately, we aimed to share the lessons learned from ecosystems naturally experiencing extreme hydrological events, which can help to better understand warming-induced impacts on hydrological transport and cycling of matter in fluvial ecosystems.
Drying and hornification of swollen cellulose
Authors: von Schreeb Antonia , Sjöstrand Björn , Ek Monica , Henriksson Gunnar 
Published: January 2025

AbstractChemical modification of cellulose can alter the properties of cellulose, creating endless application areas. Accessibility and reactivity are key to the successful modification of cellulose. However, its crystalline structure results in poor and uneven reactivity, which can be amplified during processing, such as hornification. In this work, we have dissolved cellulose in cold alkali and reprecipitated it with acid to form a highly swollen structure, herein called swollen cellulose. The swelled structure bound large amounts of water, and upon drying the cellulose became severely hornified. Hence, various drying methods to mitigate hornification were evaluated, including freeze-drying, acetone drying, and drying in the presence of glycerol. The degree of hornification was indirectly assessed by measuring the cellulose samples' water retention value (WRV), which reflects their ability to reswell in water. The alternative drying methods increased the WRV by 270–650%, demonstrating a significant reduction in hornification. In comparison, air-drying reduced the WRV by 30%. Electron microscopy evaluation showed that the structure of cellulose differed depending on the drying method and indicated that the remaining cell wall structures were lost by the swelling, and air-dried swollen cellulose appeared to have a more compact structure than freeze-dried or acetone-dried samples. Water retention value in the presence of the sodium sulfate indicated that hydrophobic surfaces play a role in cellulose and that swollen cellulose has more exposed hydrophobic surfaces compared to the crystalline reference material.
Evaluating and challenging the reasoning capabilities of generative artificial intelligence for technology-assisted chemistry education
Authors: Uçar Suna-Şeyma , Lopez-Gazpio Inigo , Lopez-Gazpio Josu 
Published: January 2025

AbstractRecent advancements in large language models (LLMs) have shown potential in enhancing educational practices, particularly in technology-assisted learning environments. This study critically evaluates the reasoning capabilities of LLMs, such as ChatGPT, within the context of chemistry education. We designed targeted adversarial prompts that challenge the models to solve complex chemistry problems and assessed their performance. By pushing the boundaries of LLM reasoning, we aim to identify their limitations and strengths in handling queries within the chemistry domain. Our findings expose inherent weaknesses in current AI systems, emphasizing the necessity of cautious AI deployment in teaching methodologies. We argue for a balanced approach, leveraging the benefits of LLMs while mitigating their limitations, to facilitate their seamless adoption in education.
Reconsidering Alterity of Ihde’s Garden: A Conceptual Critique
Authors: Penttilä Anna , Mertanen Mikko 
Published: January 2025

AbstractDon Ihde’s postphenomenological theory of technological relations has proven its value for understanding the role material artifacts play in our lives. However influential it may be, some of his key concepts have remained ambiguous. In this paper, we analyze and critically evaluate how Ihde describes one of these concepts, namely, alterity relation (Alterity). Alterity describes how technologies appear to subjects as humanlike others, or, as Ihde calls them, quasi-others. We identify and discuss three key problems with Ihde’s account of Alterity, namely, objectness, focality, and continuum. We argue that an overarching issue is prevalent in his account of Alterity: a subtle and possibly unintended emphasis on the subject’s role in constituting technological otherness. This emphasis runs counter to the interrelational ontological foundations of postphenomenology. Moreover, it hinders postphenomenological research from fully addressing the ethical and moral dimensions of its framework. By clarifying these problems, we aim to provide a fruitful groundwork for further reconsiderations of the framework’s key concepts and for the improvement of postphenomenological investigations concerning the nature of artifacts: our multifaceted engagements with, in and through them.
Addressing Methodological Challenges in Follow-Up RCTs During the COVID-19 Pandemic: The Impact of the Good Behavior Game and MyTeachingPartner™ on Teacher Burnout and Self-Efficacy
Authors: Budavari Alexa C. , McDaniel Heather L. , Morgan-López Antonio A. , Musci Rashelle J. , Downer Jason T. , Ialongo Nicholas S. , Bradshaw Catherine P. 
Published: January 2025

AbstractRetention of early career teachers is a critical issue in education, with burnout and self-efficacy serving as important precursors to teachers leaving the field. An integration of the PAX Good Behavior Game (GBG; Barrish et al., 1969) and MyTeachingPartner (MTP; Allen et al., 2015) was tested in a randomized controlled trial (RCT) to investigate whether the combined programs would improve long-term outcomes for early career teachers. However, due to the COVID-19 pandemic, there was a higher proportion of missing data and attrition in follow-up data collection than otherwise would have been expected. The current paper focused specifically on intervention impacts on teacher-reported burnout and self-efficacy through the COVID-19 pandemic and explored various approaches for addressing missing data as an illustrative example for other researchers who may similarly have faced missing data challenges due to the pandemic. Participants included in the original trial were N = 188 early career teachers (grades K-3) who were randomly assigned to either the intervention (i.e., GBG + MTP; n = 94 teachers) or control condition (n = 94) and provided baseline data. Specifically, teachers reported on their burnout and self-efficacy at pre-intervention (Fall), post-intervention (Spring), 1-year post intervention (in Fall and Spring), COVID Year 1 (Spring 2021), and COVID Year 2 (Spring 2022). We conducted a series of outcomes analyses under varying missing data assumptions (i.e., MCAR, MAR, NMAR). There were mixed findings (i.e., both null and beneficial) regarding GBG + MTP impacts on burnout, which varied across missing data assumptions; however, there were no GBG + MTP impacts on self-efficacy. This study may also provide insight for other researchers encountering similar challenges when analyzing follow-up data collected during the COVID-19 pandemic, as we highlight pros and cons of several different approaches for modeling missing data related to attrition due to the COVID-19 pandemic and related school closures.
Effect of in vitro exposure of first-line antiretrovirals on healthy human spermatozoa on kinematics and motility
Authors: Pinto Sohan Zane , Aneck-Hahn Natalie 
Published: January 2025

Abstract
Purpose
Contemporary antiretroviral (ARV) medications are used by millions of men for HIV treatment worldwide. Limited data exist on their direct effect on sperm motility. This pilot study hypothesizes that in vitro exposure to ARVs will reduce sperm kinematic and motility parameter values.

Methods
This laboratory-based experimental study analyzed sperm motility and kinematics after exposure to the ARVs Dolutegravir, Tenofovir, and Emtricitabine, individually and in combination. Each participant (n = 23) served as their experimental control. The Microptic SCA® Computer Assisted Sperm Analysis (CASA) system, Barcelona, Spain was used to generate quantitative data on sperm motility and the kinematics Straight-line velocity (VSL), Straightness index (STR), Linearity Index (LIN), Beat cross frequency (BCF), and the oscillation index (WOB).

Results
VSL, STR, LIN, and WOB of the non-progressive (grade c) spermatozoa were significantly decreased after ARV treatment. BCF of the medium velocity progressive sperm population (grade b) was significantly increased 90 min after exposure in the Tenofovir arm, and a significant decrease in the proportion of grade b spermatozoa was recorded at 90 min in all the antiretroviral arms when compared to the control arm. No impaired sperm motility was observed within the first 30 min of exposure.

Conclusion
Pharmacovigilance is a healthcare emergency as the fast-changing world of newer drugs leaves clinicians vulnerable. They must prescribe drugs whose long-term somatic and germline adverse effects are not fully understood. Guidelines and drugs are changing faster than we can monitor for side effects. Despite Dolutegravir being the only mainstream integrase inhibitor first-line ARV in South Africa for five years, its replacement, Cabotegravir, is already being launched. More research in this field is required, especially for commonly prescribed drugs. This preliminary pilot study concludes that the current first-line ARVs used by HIV patients and HIV-negative patients on pre-exposure prophylaxis (PrEP) can alter sperm motility and kinematics. Further research with a larger sample size is warranted to quantify its impact on human fertility, addressing the limitations of this study, before a comprehensive conclusion of the effects of ARVs on human male fertility can be drawn. Of particular importance would be to study the impact of ARVs on reactive oxygen species levels in semen and sperm DNA fragmentation.
Deep learning-based software engineering: progress, challenges, and opportunities
Authors: Chen Xiangping , Hu Xing , Huang Yuan , Jiang He , Ji Weixing , Jiang Yanjie , Jiang Yanyan , Liu Bo , Liu Hui , Li Xiaochen , Lian Xiaoli , Meng Guozhu , Peng Xin , Sun Hailong , Shi Lin , Wang Bo , Wang Chong , Wang Jiayi , Wang Tiantian , Xuan Jifeng , Xia Xin , Yang Yibiao , Yang Yixin , Zhang Li , Zhou Yuming , Zhang Lu 
Published: January 2025

AbstractResearchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However, although several surveys have provided overall pictures of the application of deep learning techniques in software engineering, they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas, we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets in such a subarea. We also discuss the challenges and opportunities concerning each of the surveyed software engineering subareas.
Modeling of Industrial Electric Arcs Using Different Plasma Gas Compositions
Authors: Haraldsson Hákon Valur , Reynolds Quinn , Tesfahunegn Yonatan A. , Saevarsdottir Gudrun 
Published: January 2025

AbstractElectric arcs are an important heat source in submerged arc furnaces that are used in the pyrometallurgical production of silicon. They are therefore of great interest to study so that the production process can be improved and made more efficient. Modeling of industrial arcs is a multiphysics problem that involves simultaneously solving several coupled physical phenomena, such as electromagnetics, fluid dynamics, and heat transfer, including radiative heat transfer from the plasma arc. Coupling fluid dynamics and electromagnetics is known as Magnetohydrodynamics (MHD). Two MHD model implementations developed by the authors are used to simulate alternating current arcs with different plasma gas compositions. The thermophysical properties of each composition are calculated using specialized code as well as gathered from literature. We investigate the dependence of the results on both the MHD model used and the input plasma data for three argon data sets and compare the results to data obtained from laboratory experiments. Finally, we investigate furnace conditions using different ratios of SiO to CO gases.