bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prostate neuroendocrine carcinoma successfully treated with etoposide and cisplatin
Authors: Ishizaki Masanori , Hasumi Masaru , Muramatsu Kazumichi , Shimizu Nobuaki 
Published: September 2024

IntroductionThe frequency of neuroendocrine carcinoma of the prostate is low, accounting for approximately 1%–5% of all prostate cancers. Herein, we report the case of a patient who was diagnosed with prostate neuroendocrine carcinoma and successfully treated with etoposide and cisplatin.Case presentationA 74‐year‐old man presented to the urology department with the chief complaint of urinary retention. After a thorough examination, he was diagnosed with neuroendocrine carcinoma of the prostate and treated with etoposide and cisplatin, called “EP therapy.” The patient remained in remission 1 year later.ConclusionA patient with neuroendocrine carcinoma of the prostate was successfully treated with etoposide and cisplatin, and the patient remained in remission. Prostate neuroendocrine carcinomas are rare and have poor prognoses. Therefore, information regarding treatments that can improve prognosis is needed.
iNAP 2.0: Harnessing metabolic complementarity in microbial network analysis
Authors: Peng Xi , Feng Kai , Yang Xingsheng , He Qing , Zhao Bo , Li Tong , Wang Shang , Deng Ye 
Published: September 2024

AbstractWith the widespread adoption of metagenomic sequencing, new perspectives have emerged for studying microbial ecological networks, yielding metabolic evidence of interspecies interactions that traditional co‐occurrence networks cannot infer. This protocol introduces the integrated Network Analysis Pipeline 2.0 (iNAP 2.0), which features an innovative metabolic complementarity network for microbial studies from metagenomics sequencing data. iNAP 2.0 sets up a four‐module process for metabolic interaction analysis, namely: (I) Prepare genome‐scale metabolic models; (II) Infer pairwise interactions of genome‐scale metabolic models; (III) Construct metabolic interaction networks; and (IV) Analyze metabolic interaction networks. Starting from metagenome‐assembled or complete genomes, iNAP 2.0 offers a variety of methods to quantify the potential and trends of metabolic complementarity between models, including the PhyloMint pipeline based on phylogenetic distance‐adjusted metabolic complementarity, the SMETANA (species metabolic interaction analysis) approach based on cross‐feeding substrate exchange prediction, and metabolic distance calculation based on parsimonious flux balance analysis (pFBA). Notably, iNAP 2.0 integrates the random matrix theory (RMT) approach to find the suitable threshold for metabolic interaction network construction. Finally, the metabolic interaction networks can proceed to analysis using topological feature analysis such as hub node determination. In addition, a key feature of iNAP 2.0 is the identification of potentially transferable metabolites between species, presented as intermediate nodes that connect microbial nodes in the metabolic complementarity network. To illustrate these new features, we use a set of metagenome‐assembled genomes as an example to comprehensively document the usage of the tools. iNAP 2.0 is available at https://inap.denglab.org.cn for all users to register and use for free.
Multi‐sensors edge computing for tennis stroke recognition in IoT environment
Authors: Zhang Yong 
Published: September 2024

AbstractThis paper proposes a multi‐sensors edge computing approach for tennis stroke recognition in an IoT environment. By applying the edge computing capabilities to this framework, we can ensure swift local processing of sensor data, thereby significantly reducing latency and enhancing system scalability for tennis stroke. In this way, we develop an advanced multi‐sensor based tennis stroke recognition mechanism, which employs dedicated measuring sensors mounted on the player's forearm to comprehensively capture intricate motion patterns and send the collected data to the edge computing center. Through rigorous analysis at the edge, we can determine the optimal actions in stroke detection with minimum delay, in which the optimal training datasets for stroke classification are also determined. Experimental results indicate that the proposed mechanism surpasses the state‐of‐the‐art methods and achieves effective adaptability and scalability for tennis stroke recognition in IoT‐driven environments, evidenced by their commendable performance even when applied to athletes not included in the training datasets.
Superb microvascular imaging for assessment of post‐cesarean myometrial blood flow from 1 to 4 weeks after operation: A preliminary study
Authors: Muto Megumi , Horinouchi Takashi , Kurokawa Yusuke , Yokomine Masato , Yoshizato Toshiyuki , Tsuda Naotake 
Published: September 2024

AbstractPurposeTo evaluate superb microvascular imaging for measuring puerperal myometrial microvascular blood flows at incisional sites following cesarean delivery.MethodsTwenty postpartum women (singleton births) were studied: 10 with cesarean and 10 with transvaginal deliveries. All cesarean cases were first operational delivery with lower uterine incision, repaired with double‐layer suture. At 1 and 4 weeks postpartum, the uterus was delineated using transvaginal ultrasonography with superb microvascular imaging. Separate regions of interest were created for anterior myometrium of the isthmus and the body. The microvascular flow profile in three circular sampling points placed in a region of interest was quantified and expressed as vascular density. The vascular density ratio of the uterine isthmus to the body was compared between one and four weeks for both groups. Wilcoxon's signed‐rank test was used to assess statistical significance (set at p < 0.05).ResultsIn cesarean deliveries, the vascular density ratio of the uterine isthmus to the body increased from 1 (median: 0.51, range: 0.30–0.68) to 4 weeks (0.99, 0.85–1.60), whereas no changes were noted in transvaginal deliveries.ConclusionSuperb microvascular imaging can effectively measure myometrial microvascular blood flow recovery at cesarean incision sites, indicating its potential as a tool for monitoring postpartum wound healing.
Evaluation of prognostic efficacy of liver immune status index in predicting postoperative outcomes in hepatocellular carcinoma patients: A multi‐institutional retrospective study
Authors: Imaoka Yuki , Ohira Masahiro , Kobayashi Tsuyoshi , Honmyo Naruhiko , Hamaoka Michinori , Onoe Takashi , Takei Daisuke , Oishi Koichi , Abe Tomoyuki , Nakayama Toshihiro , Akabane Miho , Sasaki Kazunari , Ohdan Hideki ,   Hiroshima Surgical Study Group of Clinical Oncology (HiSCO)
Published: September 2024

AbstractBackgroundHepatocellular carcinoma (HCC) ranks third in cancer‐related deaths globally. Despite treatment advances, high post‐hepatectomy recurrence rates (RR), especially with liver fibrosis and hepatitis C virus infection, remain challenging. Key prognostic factors include vascular invasion and perioperative blood loss, impacting extrahepatic recurrence. Natural killer (NK) cells are crucial in countering circulating tumor cells through TRAIL‐mediated pathways. The aim of this study was to validate the liver immune status index (LISI) as a predictive tool for liver NK cell antitumor efficiency, particularly in HCC patients with vascular invasion.MethodsA retrospective analysis of 1337 primary HCC hepatectomies was conducted by the Hiroshima Surgical Study Group of Clinical Oncology (HiSCO). Clinicodemographic data were extracted from electronic medical records. Prognostic indices (FIB‐4, ALBI, ALICE, GNRI, APRI, and LISI) were evaluated using area under the receiver operating characteristic curve values. Survival analyses employed Kaplan–Meier estimations and log‐rank tests.ResultsLISI significantly correlated with other prognostic markers and stratified patients into risk groups with distinct overall survival (OS) and RR. It showed superior predictive performance for 2‐year OS and RR, especially in patients with vascular invasion. Over longer periods, APRI and FIB‐4 index reliabilities improved. The HISCO‐HCC score, combining LISI, tumor burden score, and alpha‐fetoprotein levels, enhanced prognostic accuracy.ConclusionLISI outperformed existing models, particularly in HCC with vascular invasion. The HISCO‐HCC score offers improved prognostic precision, guiding immunotherapeutic strategies and individualized patient care in HCC.
Impact of COVID‐19 lockdown on sleep patterns and the related problems among nursing students
Authors: Elbilgahy Amal Ahmed , Alanazi Areej Musaad , Alrawili Badriah Mefrh , Alenezi Rawan Mamdouh , Alanazi Rawan Fahad , Alanazi Amal Khulaif , Fawzy Manal S. 
Published: September 2024

AbstractAimTo evaluate the impact of the COVID‐19 lockdown on sleep patterns and quality among nursing students in our college.DesignA cross‐sectional study was carried out.MethodsA total of 302 nursing students aged 18–25 years, representing both genders and various academic levels, participated in this study. A pre‐validated, self‐administered questionnaire was used to assess sleep quality during COVID‐19 and it was distributed through various social media platforms for data collection.ResultsFemale students comprised the majority (92.1%) of participants. Of 332 nursing students, 302 completed the questionnaire, yielding a 91% response rate. Statistically significant differences were observed before and during the COVID‐19 lockdown regarding the need to sleep after waking, feeling refreshed upon waking, satisfaction with individual sleep patterns and experiencing restless and troubled sleep (p = 0.001). Additionally, approximately one‐third of nursing students (32.9%) reported poor sleep quality during the COVID‐19 pandemic, with minimal impact on the total sleep hours among the studied cohorts.Public ContributionThe COVID‐19 pandemic has statistically significant impacted nursing students' sleep quality and levels. Acknowledging these challenges and planning for providing supporting measurements is essential to ensuring that nursing students can maintain their physical and mental health, which is critical for their ability to provide quality healthcare.
Exploring the factors affecting the readiness for hospital discharge after total knee arthroplasty: A structural equation model approach
Authors: Li Na , Guo Manjie , You Simeng , Ji Hong 
Published: September 2024

AbstractAimTo investigate the factors that influence readiness for hospital discharge in Chinese patients after total knee arthroplasty and to identify priorities for nursing interventions.DesignA cross‐sectional study.MethodsFrom January to August 2022, data were collected from 339 patients at two tertiary A‐level hospitals in Jinan, Shandong Province. SPSS 26.0 and Mplus 8.3 software were used for statistical analysis.ResultsResults from multiple linear regression showed that patients' age, residence status, education level, knee pain during sleep, quality of discharge teaching, self‐efficacy for rehabilitation, pain control knowledge, and social support were factors influencing their readiness for hospital discharge. The results of the structural equation model had shown that there were also indirect effects of the education level, knee pain during sleep, quality of discharge teaching, and pain control knowledge.ConclusionPatients' readiness for hospital discharge needs further improvement, hence physicians and nurses should judiciously allocate medical resources and concentrate their efforts on high‐risk groups characterized by low readiness for hospital discharge.Implications for the Profession and Patient CareThis study underscores the importance of physicians and nurses prioritizing key factors such as age, residency status, education level, and social support in total knee arthroplasty patients to enhance their readiness for hospital discharge. By implementing targeted discharge planning, effective pain management, and comprehensive rehabilitation education, healthcare providers can improve patient outcomes.ImpactThis study identified key factors influencing readiness for hospital discharge in total knee arthroplasty patients, guiding targeted nursing interventions to improve post‐operative care.Reporting MethodSTROBE.Patient or Public ContributionThe participants recruited for this study were actively engaged in the data collection process.
Obesity increases the risk of hepatic fibrosis in young adults with type 2 diabetes mellitus: the need to screen
Authors: Sharma Anu , Godinez Leiva Eddison , Kalavalapalli Srilaxmi , Lomonaco Romina , Marangi Stephen A. , Valdez Saenz Enrique , Gonzalez Maria A. , Ortiz Rocha Andrea , Cuervo Pardo Nathaly , Rosenberg Jens , Bedossa Pierre , Bril Fernando , Barb Diana , Cusi Kenneth 
Published: September 2024

AbstractObjectiveThe objective of this study was to determine the prevalence of metabolic dysfunction‐associated steatotic liver disease (MASLD) in young compared with older adults.MethodsIndividuals (n = 1420) with (63%) and without type 2 diabetes mellitus (T2D; 37%) who attended internal medicine clinics and did not have a known history of MASLD underwent laboratory evaluation and transient elastography to assess for hepatic steatosis and fibrosis. Magnetic resonance elastography and liver biopsy were recommended when indicated.ResultsA total of 243 participants were ages <45 years, and 1177 were ages ≥45 years. Obesity, T2D, and metabolic syndrome were highly prevalent in young adults. Frequencies of steatosis and fibrosis were high in young adults (50.2% and 7.5% vs. older adults 52.7% and 9.9%, respectively) and were significantly higher in those with both obesity and T2D (71.1% and 15.7%, respectively; p < 0.01). In young adults, T2D and obesity were the strongest risk factors for hepatic fibrosis (odds ratios 4.33 [95% CI: 1.37–13.68] and 1.16 [95% CI: 1.07–1.25], respectively; p < 0.05).ConclusionsThere is a high prevalence of clinically significant hepatic fibrosis in young adults with cardiometabolic risk factors. Up to one in seven young adults with obesity and T2D had clinically significant hepatic fibrosis on elastography. This highlights the need to screen young adults with cardiometabolic risk factors for MASLD for early detection and intervention.
Experimental study on the residual strength of butt adhesive joints subjected to systematic creep damage
Authors: Bidadi Jamal , Saeidi Googarchin Hamed 
Published: September 2024

AbstractUsing adhesively bonded joints is an effective strategy for achieving lightweight designs. However, understanding the long‐term performance of these bonded joints remains a critical concern. Creep is a time‐dependent phenomenon induced by sustained mechanical loads, which can lead to viscous strain in adhesive materials. This strain has the potential to cause cracking in bonded structures over time. This study aims to investigate the creep and post‐creep behaviors of adhesively bonded aluminum joints, focusing on two crucial parameters: creep load level and creep duration. Butt adhesive joint (BAJ) specimens were fabricated and exposed to varying creep loads and times. Subsequently, quasi‐static tensile tests were conducted to assess the residual mechanical properties. The results indicated that higher creep loads resulted in increased creep deformations at constant creep durations. Furthermore, a downward trend was observed in the residual tensile mechanical properties of BAJ specimens following creep. Specifically, higher creep load levels and longer times led to more pronounced reductions in joint strength, strain, and stiffness. These reductions in joint mechanical properties were corroborated through joint fracture surface analysis. Additionally, mathematical models were developed using response surface methodology (RSM) to predict the experimental joint residual mechanical properties under different creep loads and times.Highlights
Investigation of creep and post‐creep behaviors in adhesive joints.
Higher creep load levels result in greater joint permanent deformations.
Impact of higher creep load levels and durations on joint failure strength.
Decreasing in the joint deformability and stiffness after creep.
Changes in walking speed following resistance training in people with multiple sclerosis: A systematic review and meta‐analysis
Authors: McManaman Connor , Novak Brianna , Paul Lorna , Rooney Scott 
Published: September 2024

AbstractBackgroundReduced walking ability, especially decreased gait speed, is one of the most common and disabling impairments reported by people with multiple sclerosis (MS). Considering the impact of muscle strength on walking ability, resistance training may have the potential to improve walking speed in MS. Therefore, this systematic review and meta‐analysis aims to evaluate the effect of lower limb resistance training on walking speed in people with MS.MethodsSeven databases (CINAHL, MEDLINE, The Allied and Complimentary Medicine Database, Web of Science, Physiotherapy Evidence Database [PEDro], PsycINFO, and Sports Medicine and Education Index) were searched in March 2024 for studies that met the following eligibility criteria: randomized controlled trials investigating the effects of resistance training interventions on objective measures of walking speed in people with MS. Risk of bias was assessed using the PEDro scale. Meta‐analysis was performed to quantify intervention effect using a random effects model.ResultsTwelve randomized controlled trials were included, reporting data on 425 individuals with MS. Participants had mostly relapsing–remitting MS (85%) and a mild–moderate level of disability (Expanded Disability Status Score 1.0–6.0). Results of the meta‐analysis (based on 7 of the included studies) indicated a significant yet variable improvement in walking speed in favor of the intervention (0.10 m/s, 95% confidence interval 0.01–0.19, p < .05). Sensitivity analysis indicates that larger improvements in walking speed were found over tests covering shorter distances.ConclusionsResistance training was found to significantly improve walking speed in people with MS. However, variability in results were noted across studies; accordingly, future research should determine how variables—particularly related to resistance training prescription—influence the intervention effect.
Nonclassical Spin‐Multiplexing Metasurfaces Enabled Multifunctional Meta‐Scope
Authors: Sun Chuang , Wang Zixuan , Kiang Kian Shen , Buchnev Oleksandr , Tang Dawei , Yan Jize , Ou Jun‐Yu 
Published: September 2024

AbstractDielectric metasurfaces have emerged as attractive devices for advanced imaging systems because of their high efficiency, ability of wavefront manipulation, and lightweight. The classical spin‐multiplexing metasurfaces can only provide two orthogonal circular polarization channels and require high phase contrast which limits their applications. Here, metasurfaces with arbitrary three independent channels are demonstrated by proposing a nonclassical spin‐multiplexing approach exploring the low refractive index meta‐atoms. A zoom microscope with on‐axis tri‐foci and a synchronous achiral‐chiral microscope with in‐plane tri‐foci based on silicon nitride metasurfaces are experimentally demonstrated. Based on the on‐axis tri‐foci metasurface, singlet zoom imaging with three magnifications and a broadband response (blue to red) based on a single metasurface is first demonstrated. A compact microscope (meta‐scope) consisting of two metasurfaces with three magnifications of 9.5, 10, and 29X with diffraction‐limited resolutions is further constructed, respectively. Utilizing the in‐plane tri‐foci metasurface, a singlet microscope with three achiral‐chiral channels is demonstrated. It offers a magnification of 53X and a diffraction‐limited resolution, enabling simultaneous imaging of an object's achiral and chiral properties. Our multifunctional metasurfaces and meta‐scope approaches could boost the applications in biological imaging and machine vision.
Predictive modeling of compressive strength of geopolymer concrete before and after high temperature applying machine learning algorithms
Authors: Yang Haifeng , Li Hongrui , Jiang Jiasheng 
Published: September 2024

AbstractGeopolymer concrete (GPC) is regarded as a more environmentally friendly construction material compared to conventional cement concrete, and its exceptional environmental capabilities are highly favored by the contemporary construction sector. Studying the mechanical properties of GPC upon exposure to elevated temperatures is a crucial aspect of evaluating structural damage and enhancing fire safety measures. Nevertheless, properly predicting the compressive performance of GPC upon exposure to high temperatures remains a formidable task. This study employs various machine learning techniques, such as single models, integrated models, neural network models, and hybrid models, to predict the compressive strength of GPC from room temperature to 1000°C. The results of each model are summarized, and the significant factors influencing compressive strength are analyzed to evaluate the thermal behavior of GPC. These findings offer recommendations for future in‐depth machine learning applications in the GPC field. The K‐fold cross‐validation shows that the hybrid model genetic algorithm–random forest has the highest prediction accuracy, while the single model performs the worst. Other models also provide favorable prediction results. The feature importance analysis revealed that the compressive strength of GPC is primarily influenced by heating temperature (HT) and hydroxide ion concentration, with fly ash and ground granulated blast furnace slag content being secondary factors. The partial dependence plot‐2D analysis indicates that as HTs increase, the influence of other variables on GPC compressive strength decreases significantly. These findings can inform the design of GPC mixing ratios for high‐temperature exposure. The machine learning technique proposed in this study accurately predicts GPC compressive strength across various temperatures, reducing experimental time and costs while promoting the GPC sector.
Oberflächlich geschaltet
Authors: Gruber Manuel 
Published: September 2024

ZusammenfassungMolekulare Spinschalter sind seit fast hundert Jahren bekannt. Ihre Reaktion auf verschiedene Anregungen sowie die durch das Schalten veränderbaren physikalischen Eigenschaften machen sie für ein breites Spektrum von Anwendungen attraktiv. Vor kurzem gelang es, einzelne Moleküle kontrolliert zu manipulieren, um damit den Einfluss der lokalen Umgebung auf das Schalten zu verstehen. In der interdisziplinären Zusammenarbeit von Chemie und Physik lassen sich Spinschalter, die auf unterschiedlichen Mechanismen beruhen, entwerfen, synthetisieren und an Oberflächen erproben.
Large D gravity and low D string via α′ corrections
Authors: Ying Shuxuan 
Published: September 2024

Abstract
In this paper, we generalize the correspondence between large D gravity and low D string theory to the most general case, including its T-dual solutions. It is well-known that the large D limit of the Schwarzschild-Tangherlini black hole in gravity becomes a two-dimensional near-horizon geometry. Similarly, the large D limit of its T-dual solution, obtained by the Buscher rules, namely the string black hole with a naked singularity, reduces to a two-dimensional near-singularity geometry. Both of these geometries are described by the two-dimensional low-energy effective action of string theory and are related to each other by scale-factor duality. Secondly, we demonstrate that these near-horizon/singuglarity geometries, including complete α′ corrections, can be described by the two-dimensional Hohm-Zwiebach action. This approach allows for the derivation of non-perturbative and non-singular solutions. Furthermore, the Hohm-Zwiebach action provides a systematic way to investigate the α′-corrected near-horizon/singularity geometries of different kinds of black holes, which are difficult to achieve through the Wess-Zumino-Witten (WZW) model method.