bluuebunny/crossref_metadata_2025 huggingface dataset:
Relationships between Food Insecurity, Self-Efficacy, and Changes in Body Mass Index among the Youth in Taiwan: Analysis from a Longitudinal Cohort Survey
Authors: Huang Ya-Chi , Tan Chin Xuan , Lee Chih-Ting , Tsai Meng-Che
Published: May 2024

Background: Food insecurity is a heightened concern among economically disadvantaged youth, and it may contribute to the atypical body mass index (BMI) patterns frequently observed in this group. Self-efficacy seems to intervene in the negative impacts of contextual restraints. This study investigated the relationship between food insecurity, self-efficacy, and BMI trajectory among economically disadvantaged Taiwanese youth. Methods: We utilized three-wave longitudinal data from the Taiwan Database of Children and Youth in Poverty. The Food Insecurity Score (FIS) assessed food insecurity with a 4-item scale measuring reduced meal frequency, hunger, skipping meals, and economic constraints. Moreover, the General Self-Efficacy Scale (GSES) assessed self-efficacy, showcasing the ability to handle stress effectively and envision success scenarios, contributing to positive outcomes. By employing latent growth modeling, we were able to delineate the impacts of baseline food insecurity and self-efficacy on initial BMI and its subsequent growth trajectory. Results: Elevated baseline FIS significantly predicted higher initial BMI (coefficient = 0.420, p = 0.042). Baseline GSES was negatively associated with initial BMI (coefficient = −0.093, p < 0.001) but positively predicted the BMI growth rate (coefficient = 0.023, p = 0.011). Conclusion: Enhancing self-efficacy may be an effective multidisciplinary intervention to address psychosocial and socioeconomic factors when tackling weight problems in vulnerable youth groups.
Coincidence or Causality: Parathyroid Carcinoma in Chronic Kidney Disease—Case Report and Literature Review
Authors: Bilha Stefana Catalina , Matei Anca , Branisteanu Dumitru D. , Teodoriu Laura Claudia , Hristov Ioana , Bilha Stefan , Leustean Letitia , Ungureanu Maria-Christina , Apostol Ciobanu Delia Gabriela , Preda Cristina , Velicescu Cristian
Published: May 2024

Parathyroid carcinoma (PC) associated with primary hyperparathyroidism (PHPT) has been well investigated in recent years. Data regarding PC evolution in secondary hyperparathyroidism (SHPT) due to chronic kidney disease (CKD) are, however, scarce. Most features that raise the suspicion of PC in PHPT are part of the usual SHPT evolution in CKD, mirroring the natural changes undergone by the parathyroid glands. Therefore, pre-surgically establishing the malignant or benign character of the lesions is cumbersome. We present two cases of PC in end-stage renal disease, one of which was bilateral, diagnosed after total parathyroidectomy in a high-volume parathyroid surgery center. A literature review of the data was also performed. A systematic search of the PubMed/MEDLINE database until January 2024 identified 42 cases of PC associated with SHPT. Understanding the PC features in CKD might improve associated bone and mineral disease management, and reduce the risk of metastasis, parathyromatosis, or recurrence. Irradiation, prolonged immunosuppression, long dialysis vintage, and genotype may predispose to the malignant transformation of chronically stimulated parathyroids. Despite postsurgical diagnosis, favorable outcomes occurred when distant metastases were absent, even without “en bloc” resection. Further research is warranted to delineate specific diagnostic and therapeutic approaches tailored to this particular patient subpopulation.
A Dynamic Visual SLAM System Incorporating Object Tracking for UAVs
Authors: Li Minglei , Li Jia , Cao Yanan , Chen Guangyong
Published: May 2024

The capability of unmanned aerial vehicles (UAVs) to capture and utilize dynamic object information assumes critical significance for decision making and scene understanding. This paper presents a method for UAV relative positioning and target tracking based on a visual simultaneousocalization and mapping (SLAM) framework. By integrating an object detection neural network into the SLAM framework, this method can detect moving objects and effectively reconstruct the 3D map of the environment from image sequences. For multiple object tracking tasks, we combine the region matching of semantic detection boxes and the point matching of the optical flow method to perform dynamic object association. This joint association strategy can prevent trackingoss due to the small proportion of the object in the whole image sequence. To address the problem ofacking scale information in the visual SLAM system, we recover the altitude data based on a RANSAC-based plane estimation approach. The proposed method is tested on both the self-created UAV dataset and the KITTI dataset to evaluate its performance. The results demonstrate the robustness and effectiveness of the solution in facilitating UAV flights.
Use of Participatory sUAS in Resilient Socioecological Systems (SES) Research: A Review and Case Study from the Southern Great Plains, USA
Authors: Fagin Todd D. , Vadjunec Jacqueline M. , Boardman Austin L. , Hinsdale Lanah M.
Published: May 2024

Since the publication of the seminal work People and Pixels: Linking Remote Sensing and the Social Sciences, the call to “socialize the pixel” and “pixelize the social” has gone largely unheeded from a truly participatory research context. Instead, participatory remote sensing has primarily involved ground truthing to verify remote sensing observations and/or participatory mapping methods to complement remotely sensed data products. However, the recent proliferation of relatively low-cost, ready-to-fly small unoccupied aerial systems (sUAS), colloquially known as drones, may be changing this trajectory. sUAS may provide a means for community participation in all aspects of the photogrammetric/remote sensing process, from mission planning and data acquisition to data processing and analysis. We present an overview of the present state of so-called participatory sUAS through a comprehensive literature review of recent English-language journal articles. This is followed by an overview of our own experiences with the use of sUAS in a multi-year participatory research project in an agroecological system encompassing a tri-county/tri-state region in the Southern Great Plains, USA. We conclude with a discussion of opportunities and challenges associated with our experience.
FLsM: Fuzzy Localization of Image Scenes Based on Large Models
Authors: Chen Weiyi , Miao Lingjuan , Gui Jinchao , Wang Yuhao , Li Yiran
Published: May 2024

This article primarily focuses on the study of image-based localization technology. While traditional methods have made significant advancements in technology and applications, the emerging field of visual image-based localization technology demonstrates tremendous potential for research. Deep learning has exhibited a strong performance in image processing, particularly in developing visual navigation and localization techniques using large-scale visual models. This paper introduces a sophisticated scene image localization technique based on large models in a vast spatial sample environment. The study involved training convolutional neural networks using millions of geographically labeled images, extracting image position information using large model algorithms, and collecting sample data under various conditions in elastic scene space. Through visual computation, the shooting position of photos was inferred to obtain the approximate position information of users. This method utilizes geographic location information to classify images and combines it with landmarks, natural features, and architectural styles to determine their locations. The experimental results show variations in positioning accuracy among different models, with the most optimal model obtained through training on a large-scale dataset. They also indicate that the positioning error in urban street-based images is relatively small, whereas the positioning effect in outdoor and local scenes, especially in large-scale spatial environments, is limited. This suggests that the location information of users can be effectively determined through the utilization of geographic data, to classify images and incorporate landmarks, natural features, and architectural styles. The study’s experimentation indicates the variation in positioning accuracy among different models, highlighting the significance of training on a large-scale dataset for optimal results. Furthermore, it highlights the contrasting impact on urban street-based images versus outdoor and local scenes in large-scale spatial environments.
Development of Gold Inks for Inkjet Printing of Gas Sensors Electrodes on Plastic Support
Authors: Le Porcher Bastien , Rieu Mathilde , Viricelle Jean-Paul
Published: May 2024

Among the conventional inks used for inkjet printing, metals, oxides, or polymers have been deposited in order to form functional coatings. Gold is one of the most used metals for electrode fabrication in the gas sensor field due to its inert behavior when exposed to reactive gases and conductive properties. However, only a few commercial gold inks are commercially available, and the combination of excessive price, a high minimum purchase quantity, and an unknown composition renders the actual products unappealing. To meet these shortcomings, gold inks were formulated with different solvents in order to reach sufficient properties for the inkjet printing process, such as surface tension and viscosity. On the one hand, gold ink was developed using a gold nanoparticle (AuNP) solution as the metal. This ink was optimized from nanoparticle synthesis, with the ink formulation obtaining a 32 mN·m−1 surface tension and 11.2 mPa·s viscosity in order to be inkjet-printed onto polyimide foil. On the other hand, a particle-free ink, called a precursor based of ink, was also developed. In this case, ink was made by solubilizing gold salt in aqueous medium in order to reach jettable properties. Surface tension was measured at 32 mN·m−1 while viscosity was 14.0 mPa·s. Then, printing and deposition parameters were optimized in order to obtain a highly conductive gold coating. The measured resistivity was 2 × 10−7 Ω·m which is close to the bulk gold conductive value. These coatings could be used for the fabrication of various devices in different working fields.
A Novel Source Code Representation Approach Based on Multi-Head Attention
Authors: Xiao Lei , Zhong Hao , Liu Jianjian , Zhang Kaiyu , Xu Qizhen , Chang Le
Published: May 2024

Code classification and code clone detection are crucial for understanding and maintaining large software systems. Although deep learning surpasses traditional techniques in capturing the features of source code, existing models suffer from low processing power and high complexity. We propose a novel source code representation method based on the multi-head attention mechanism (SCRMHA). SCRMHA captures the vector representation of entire code segments, enabling it to focus on different positions of the input sequence, capture richer semantic information, and simultaneously process different aspects and relationships of the sequence. Moreover, it can calculate multiple attention heads in parallel, speeding up the computational process. We evaluate SCRMHA on both the standard dataset and an actual industrial dataset, and analyze the differences between these two datasets. Experiment results in code classification and clone detection tasks show that SCRMHA consumes less time and reduces complexity by about one-third compared with traditional source code feature representation methods. The results demonstrate that SCRMHA reduces the computational complexity and time consumption of the model while maintaining accuracy.
Detection of Dangerous Human Behavior by Using Optical Flow and Hybrid Deep Learning
Authors: Salim Laith Mohammed , Celik Yuksel
Published: May 2024

Dangerous human behavior in the driving sense may cause traffic accidents and even cause economic losses and casualties. Accurate identification of dangerous human behavior can prevent potential risks. To solve the problem of difficulty retaining the temporal characteristics of the existing data, this paper proposes a human behavior recognition model based on utilized optical flow and hybrid deep learning model-based 3D CNN-LSTM in stacked autoencoder and uses the abnormal behavior of humans in real traffic scenes to verify the proposed model. This model was tested using HMDB51 datasets and JAAD dataset and compared with the recent related works. For a quantitative test, the HMDB51 dataset was used to train and test models for human behavior. Experimental results show that the proposed model achieved good accuracy of about 86.86%, which outperforms recent works. For qualitative analysis, we depend on the initial annotations of walking movements in the JAAD dataset to streamline the annotating process to identify transitions, where we take into consideration flow direction, if it is cross-vehicle motion (to be dangerous) or if it is parallel to vehicle motion (to be of no danger). The results show that the model can effectively identify dangerous behaviors of humans and then test on the moving vehicle scene.
Does Renewable Energy Matter for Economic Growth and Happiness?
Authors: Ostrowska Aleksandra , Kotliński Kamil , Markowski Łukasz
Published: May 2024

This paper investigates whether renewable energy influences economic growth and happiness. Using panel data from 25 European Union countries for the period 2012–2022, this study employs a panel model for estimation with fixed and random effects, and robust HAC standard errors. According to the research results, in general, the growing share of renewable energy in the energy mix has a positive impact on economic growth and the happiness of citizens. However, detailed research has shown that this effect depends on the type of energy; a significant positive impact was recorded only in solar share energy, wind share energy and economic growth. However, almost all types of renewable energy were included, i.e., biofuel, hydro, solar and other renewable share energy, and all had a significantly positive impact on the level of happiness. The exception was wind share energy, which showed a significant negative impact. The research findings of this paper provide empirical support for promoting renewable energy, which is positive both for economies and the happiness of citizens. It is one of the main aspects of sustainable economic growth.
The Evaluation of the Phytochemical Profiles and Antioxidant and α-Glucosidase Inhibitory Activities of Four Herbal Teas Originating from China: A Comparative Analysis of Aqueous and Ethanol Infusions
Authors: Zhang Jin , Lv Jinling , Zhuang Guodong , Zhang Junjia , Hu Feng , Chen Yongsheng
Published: May 2024

Recent research has demonstrated the positive impact of herbal tea consumption on postprandial blood glucose regulation. This study conducts a comparative analysis of aqueous and ethanol extractions on four herbal teas (Mallotus, Cyclocarya, Rubus, and Vine) to assess their phytochemical profiles and functional attributes. Phytochemical contents, antioxidant activities, α-glucosidase inhibitory activities, and chemical compositions are investigated via colorimetric analyses and UPLC-Q-Orbitrap HRMS/MS, respectively. Results indicate that Vine, among the teas studied, exhibits the most pronounced glucose-regulating effects under both extraction methods. While ethanol extractions yield higher phytochemical content overall, the compositions vary. Conversely, aqueous extracts demonstrate unexpectedly potent antioxidant activities and comparable α-glucosidase inhibitory activities to ethanol extracts. Phytochemical contents correlate positively with antioxidant activities and α-glucosidase inhibitory activities. However, antioxidant activities exhibit a weak positive correlation with α-glucosidase inhibitory activities. These findings provide evidence that aqueous extracts from herbal teas contain valuable phytochemical compositions beneficial for antioxidants and individuals with hyperglycemia, suggesting their potential as functional ingredients to enhance the nutritional value of herbal food products.
Online System for Monitoring the Degree of Fermentation of Oolong Tea Using Integrated Visible–Near-Infrared Spectroscopy and Image-Processing Technologies
Authors: Zheng Pengfei , Solomon Adade Selorm Yao-Say , Rong Yanna , Zhao Songguang , Han Zhang , Gong Yuting , Chen Xuanyu , Yu Jinghao , Huang Chunchi , Lin Hao
Published: May 2024

During the fermentation process of Oolong tea, significant changes occur in both its external characteristics and its internal components. This study aims to determine the fermentation degree of Oolong tea using visible–near–infrared spectroscopy (vis-VIS-NIR) and image processing. The preprocessed vis-VIS-NIR spectral data are fused with image features after sequential projection algorithm (SPA) feature selection. Subsequently, traditional machine learning and deep learning classification models are compared, with the support vector machine (SVM) and convolutional neural network (CNN) models yielding the highest prediction rates among traditional machine learning models and deep learning models with 97.14% and 95.15% in the prediction set, respectively. The results indicate that VIS-NIR combined with image processing possesses the capability for rapid non-destructive online determination of the fermentation degree of Oolong tea. Additionally, the predictive rate of traditional machine learning models exceeds that of deep learning models in this study. This study provides a theoretical basis for the fermentation of Oolong tea.
PC Gene Affects Milk Production Traits in Dairy Cattle
Authors: Du Aixia , Guo Zijiao , Chen Ao , Xu Lingna , Sun Dongxiao , Han Bo
Published: May 2024

In previous work, we found that PC was differentially expressed in cows at different lactation stages. Thus, we deemed that PC may be a candidate gene affecting milk production traits in dairy cattle. In this study, we found the polymorphisms of PC by resequencing and verified their genetic associations with milk production traits by using an animal model in a cattle population. In total, we detected six single-nucleotide polymorphisms (SNPs) in PC. The single marker association analysis showed that all SNPs were significantly associated with the five milk production traits (p < 0.05). Additionally, we predicted that allele G of 29:g.44965658 in the 5′ regulatory region created binding sites for TF GATA1 and verified that this allele inhibited the transcriptional activity of PC by the dual-luciferase reporter assay. In conclusion, we proved that PC had a prominent genetic effect on milk production traits, and six SNPs with prominent genetic effects could be used as markers for genomic selection (GS) in dairy cattle, which is beneficial for accelerating the improvement in milk yield and quality in Chinese Holstein cows.
Usefulness of the Sympto-Thermal Method with Standardized Cervical Mucus Assessment (InVivo Method) for Evaluating the Monthly Cycle in Women with Polycystic Ovary Syndrome (PCOS)
Authors: Stachowska Aneta , Kicińska Aleksandra M. , Kotulak-Chrząszcz Anna , Babińska Anna
Published: May 2024

(1) Background: FABMs (fertility awareness-based methods) are methods that rely on the observation of clinical signs related to fertility found in women, the so-called fertility bioindicators. They can be a valuable tool for diagnosing monthly cycle disorders and infertility, for example, among patients with PCOS (polycystic ovary syndrome). Until now, it has been difficult for women with PCOS to use FABM, due to the difficulty of describing fertility bioindicators and their disorders due to the biology of the syndrome. The new InVivo sympto-thermal method with standardized cervical mucus assessment may provide a valuable diagnostic and therapeutic tool for observing the monthly cycle in this group of women. (2) Methods: The monthly cycle was evaluated in a group of 32 women of reproductive age. A total of 108 monthly cycle observation cards were analyzed: 35 monthly cycle cards were collected from 18 women with PCOS, and 73 monthly cycle cards collected from 14 healthy women. In addition, 32 pairs of macroscopic and microscopic images were evaluated: 17 pairs from the study group (four subjects) and 15 pairs from women in the control group (six subjects). (3) Results: We showed that in the group of patients with PCOS, menstruation was longer (p = 0.000814), the number of mucus peaks was statistically higher (p = 0.040747), and the interquartile range (IQR) of the duration of the follicular phase (calculated according to the BBT) was significantly higher (8 days) compared to women in the control group. We also observed that among all the women studied, the microscopic image of cervical mucus correlated with the cycle phase described in the observation card, as determined by reference to the BBT chart, provided that it showed the correct features. (4) Conclusions: Systematic maintenance of monthly cycle observation charts using the InVivo method can be an important supplement to the medical history, as it allows for a thorough assessment of, among others, the timing of monthly bleeding, cervical mucus symptoms, BBT changes, and the duration of the follicular and luteal phases among both healthy and PCOS women.
Virtual Reality Simulation-Based Clinical Procedure Skills Training for Nursing College Students: A Quasi-Experimental Study
Authors: Yoon Hyeongyeong , Lee Eunwha , Kim Chung-Jong , Shin Yoonhee
Published: May 2024

Core nursing skills are emphasized in nursing education, given their vital role in nurses’ competence; however, invasive nursing procedures like catheterization and enemas are infrequently performed in actual clinical practice, primarily being observed rather than executed. Virtual reality simulation training involves performing core nursing skills on virtual patients in a three-dimensional virtual reality environment, following the correct procedures. The purpose of this study is to examine the effects of VR simulation on nursing students’ confidence, proficiency, task engagement, and satisfaction. The study participants included 76 second-year nursing students, with 37 in the VR group and 39 in the control group. The VR group engaged in immersive VR (IVR) training sessions including enemas, nasogastric feeding, and nelaton catheterization. Conversely, the control group practiced these skills using mannequins. Assessments evaluated confidence, proficiency, learning satisfaction, and task engagement before and after the intervention. The average age of the study participants was 21.07 years, with 78.95% being female and 21.05% being male. The study findings revealed no significant differences between the VR and control groups regarding confidence (F = 3.878, p = 0.053), task engagement (F = 0.164, p = 0.687), and learning satisfaction (F = 0.668, p = 0.416). However, the VR group demonstrated significantly higher proficiency in the overall assessment of nasogastric feeding (F = 5.389, p = 0.023) and core components of nelaton catheterization (F = 4.046, p = 0.048). The IVR program emerged as an effective and valuable teaching tool, particularly well-suited for second-year nursing students, significantly enhancing proficiency.
Can ‘What Is Known’ about Social Isolation and Loneliness Interventions Sufficiently Inform the Clinical Practice of Health Care and Social Service Professionals Who Work with Older Adults? Exploring Knowledge-to-Practice Gaps
Authors: Horgan Salinda , Prorok Jeanette , Conn David , Checkland Claire , Saunders John , Watson-Borg Bette , Tinley Lisa
Published: May 2024

Establishing intervention effectiveness is an important component of a broader knowledge translation (KT) process. However, mobilizing the implementation of these interventions into practice is perhaps the most important aspect of the KT cycle. The purpose of the current study was to conduct an umbrella review to (a) identify promising interventions for SI&L in older adults, (b) interpret (translate) the findings to inform clinical knowledge and practice interventions in different settings and contexts, and (c) highlight research gaps that may hinder the uptake of these interventions in practice. The broader purpose of this study was to inform evidence-based clinical practice guidelines on SI&L for HCSSPs. In line with other reviews, our study noted variations in methods and intervention designs that prohibit definitive statements about intervention effectiveness. Perhaps, the most significant contribution of the current review was in identifying knowledge-to-practice gaps that inhibit the implementation of interventions into practice-based realities.
Cartography and Neural Networks: A Scientometric Analysis Based on CiteSpace
Authors: Cheng Shiyuan , Zhang Jianchen , Wang Guangxia , Zhou Zheng , Du Jin , Wang Lijun , Li Ning , Wang Jiayao
Published: May 2024

Propelled by emerging technologies such as artificial intelligence and deep learning, the essence and scope of cartography have significantly expanded. The rapid progress in neuroscience has raised high expectations for related disciplines, furnishing theoretical support for revealing and deepening the essence of maps. In this study, CiteSpace was used to examine the confluence of cartography and neural networks over the past decade (2013–2023), thus revealing the prevailing research trends and cutting-edge investigations in the field of machine learning and its application in mapping. In addition, this analysis included the systematic categorization of knowledge clusters arising from the fusion of cartography and neural networks, which was followed by the discernment of pivotal clusters in the field of knowledge mapping. Crucially, this study diligently identified the critical studies (milestones) that have made significant contributions to the development of these elucidated clusters. Timeline analysis was used to track these studies’ origins, evolution, and current status. Finally, we constructed collaborative networks among the contributing authors, journals, institutions, and countries. This mapping aids in identifying and visualizing the primary contributing factors of the evolution of knowledge mapping encompassing cartography and neural networks, thus facilitating interdisciplinary and multidisciplinary research and investigations.
Comparing the HER2 Status of the Primary Tumor to That of Disseminated Tumor Cells in Early Breast Cancer
Authors: Volmer Léa Louise , Dannehl Dominik , Matovina Sabine , Taran Florin-Andrei , Walter Christina Barbara , Wallwiener Markus , Brucker Sara Yvonne , Hartkopf Andreas Daniel , Engler Tobias
Published: May 2024

Breast cancer remains a leading cause of cancer mortality in women globally. Despite advancements in systemic therapy, the risk of distant recurrence persists even after such treatment and may be linked to disseminated tumor cells (DTCs). Variability in molecular characteristics between primary tumors (PTs) and distant metastases underscores the need to comprehensively understand metastatic pathways. This retrospective study investigated discrepancies between HER2 expression in PTs and DTCs and their implications for survival outcomes in 201 early breast cancer (EBC) patients. We found a significant association between HER2 expression in PTs and DTCs when classifying tumors as HER2-high/low/negative. Patients whose HER2 status was discordant between PTs and DTCs exhibited worse distant disease-free survival than those with concordant status. Multivariate analysis confirmed the HER2 status of DTCs as an independent prognostic factor for distant DFS. These findings emphasize the importance of assessing HER2 expression in DTCs and its potential implications for tailored therapy strategies in EBC. Furthermore, prospective trials are needed to validate these findings and explore targeted therapies based on the molecular characteristics of DTCs.
Safety of Human–Artificial Intelligence Systems: Applying Safety Science to Analyze Loopholes in Interactions between Human Organizations, Artificial Intelligence, and Individual People
Authors: Fox Stephen , Victores Juan G.
Published: May 2024

Loopholes involve misalignments between rules about what should be done and what is actually done in practice. The focus of this paper is loopholes in interactions between human organizations’ implementations of task-specific artificial intelligence and individual people. The importance of identifying and addressing loopholes is recognized in safety science and in applications of AI. Here, an examination is provided of loophole sources in interactions between human organizations and individual people. Then, it is explained how the introduction of task-specific AI applications can introduce new sources of loopholes. Next, an analytical framework, which is well-established in safety science, is applied to analyses of loopholes in interactions between human organizations, artificial intelligence, and individual people. The example used in the analysis is human–artificial intelligence systems in gig economy delivery driving work.
Systematics Review and Phylogeny of Cyrtophyllitinae Zeuner, 1935 sensu Gorochov, Jarzembowski & Coram, 2006 (Ensifera, Haglidae), with Description of Two New Species
Authors: Gu Jun-Jie , Yuan Wei , Huang Rong , Ren Dong , Chen Hong-Xing
Published: May 2024

A phylogeny of Cyrtophyllitinae Zeuner, 1935 sensu Gorochov, Jarzembowski & Coram, 2006, based on wing morphology, is presented including all genera. Cyrtophillitinae is found to be paraphyletic. Except for Cyrtophyllites rogeri Oppenheim, 1888, all other species were moved from the subfamily Cyrtophyllitinae (Hagloidea, Haglidae). Consequently, a new subfamily Archaboilinae subfam. nov. was erected and accommodates most of the previous cyrtophillitine taxa, except Cyrtophyllites rogeri. The type genus Archaboilus Martynov, 1937 of the new subfamily was designated; a new genus, Pararchaboilus gen. nov., was erected with the designation of type species Pararchaboilus cretaceus comb. nov. From the Middle Jurassic deposits of China, two new species, Archaboilus ornatus sp. nov. and Vitimoilus gigantus sp. nov., are described.
Comprehensive Approach to Phenotype Varroa destructor Reproduction in Honey Bee Drone Brood and Its Correlation with Decreased Mite Reproduction (DMR)
Authors: Lefebre Regis , Claeys Bouuaert David , Bossuyt Emma , De Smet Lina , Brunain Marleen , Danneels Ellen , de Graaf Dirk C.
Published: May 2024

The mechanisms of action behind decreased mite reproduction (DMR) are still unknown, but current hypotheses state that DMR is the result of brood-intrinsic and/or external disturbances in the V. destructor—honey bee pupa signal interactions. For accurate and precise DMR phenotyping, sufficient single infested honey bee brood cells are required (e.g., 35), which requires extensive labor and time and may exclude many samples not reaching the threshold. We defined a new comprehensive trait called the ‘mean V. destructor reproduction rate’ (mVR), which describes the mean number of offspring mites per infested cell in the sample while compensating for the reduced number of offspring with increasing multiple infested cells. We found a significant correlation between mVR and DMR, allowing for an estimation of DMR based on the mVR only. When the mVR was calculated with 10 infested cells, we found an average variation in mVR of 16.8%. For the same variation in DMR determination, 40 single infested cells are required. This broader look at V. destructor resistance phenotyping can improve the applicability and effectiveness of traits related to V. destructor reproduction in honey bee breeding programs.
Current Practices of Medication Plans in Austrian Patients Undergoing Coronary Angiography: An In-Depth Analysis
Authors: Vogel Johannes B. , Neyer Magdalena , Elsner Pascal , Vonbank Alexander , Plattner Thomas , Saely Christoph H. , Leiherer Andreas , Drexel Heinz
Published: May 2024

A complete medication plan (MPlan) increases medication safety and adherence and is crucial in care transitions. Countries that implemented a standardized MPlan reported benefits on patients’ understanding and handling of their medication. Austria lacks such a standardization, with no available data on the issue. Objective: This study aimed to investigate the current state of all medication documentations (MDocs) at hospital admission in a population at high risk for polypharmacy in Austria. Methods: We enrolled 512 consecutive patients undergoing elective coronary angiography. Their MDocs and medications were recorded at admission. MDocs were categorized, whereby a MPlan was defined as a tabular list including medication name, dose, route, frequency and patient name. Results: Out of 485 patients, 55.1% had an MDoc (median number of drugs: 6, range 2–17), of whom 24.7% had unstructured documentation, 18.0% physicians’ letters and 54.3% MPlans. Polypharmacy patients did not have a MDoc in 31.3%. Crucial information as the patients’s name or the originator of the MDoc was missing in 31.1% and 20.4%, respectively. Patients with MDoc provided more comprehensive medication information (p = 0.019), although over-the-counter-medication was missing in 94.5% of MDocs. A discrepancy between the MPlan and current medication at admission existed in 64.4%. In total, only 10.7% of our patient cohort presented an MPlan that was in accordance with their current medication. Conclusion: The situation in Austria is far from a standardized MPlan generated in daily routine. Numerous MPlans do not represent the current medication and could pose a potential risk for the effectiveness and safety of pharmacotherapy.
Incidence and Risk Factors of Cholestasis in Newborns with Hemolytic Disease—A Case-Control Study
Authors: Drozdowska-Szymczak Agnieszka , Mazanowska Natalia , Pomianek Tomasz , Ludwin Artur , Krajewski Paweł
Published: May 2024

Background/Objectives: One of the rare causes of cholestasis may be hemolytic disease of the fetus and newborn (HDFN). Methods: We retrospectively analyzed 88 medical records of HDFN newborns with cholestasis and 186 records of children with HDFN without cholestasis and conducted an observational, case-control, retrospective study. Results: Factors influencing the risk of cholestasis were lower gestational age at birth (36.83 ± 1.9 vs. 37.57 ± 1.8, p = 0.002), Rh or Kidd HDFN (80.7% vs. 53.2%), and the need for intrauterine transfusion (27.3 vs. 11.8%). The subjects had lower hemoglobin concentrations at birth (14.01 ± 3.8 vs. 16.39 ± 2.8 g/dL) and during whole hospital stay, higher cord blood total bilirubin concentration (4.26 ± 1.8 vs. 2.39 ± 1.4 mg/dL), higher maximum bilirubin concentration (15.27 ± 5.8 vs. 10.24 ± 3.4 mg/dL), and more frequent liver ultrasound abnormalities (19.9 vs. 6.3%). They also required more extended hospitalization due to higher rates of postnatal blood transfusion (33 vs. 3.8%), more frequent need for exchange transfusion (8.8% vs. 2.2%), more extended time and higher risk of phototherapy (94.3 vs. 59.1%), and higher usage of immunoglobulins (55.7 vs. 8.1%), parenteral nutrition (45.5 vs. 12.9%), and antibiotics (14.8 vs. 4.8%). Conclusions: The risk factors for cholestasis in children with HDFN are lower gestational age at delivery, Rh and Kidd serological type of HDFN, and the need for intrauterine transfusions.
Evaluating Mental Health Outcomes in COVID-19 ICU Survivors: A Scoping Review of Measurement Tools
Authors: T’ng Kimberly , Kenardy Justin , Hartanto Andree
Published: May 2024

Objective: The objective of this scoping review was to map the range of measurement tools used to study the prevalence of common mental health conditions in COVID-19 ICU survivors. Introduction: Increased rates of admission to and survivorship from intensive care units (ICUs) have been observed in recent years, particularly during the global pandemic. ICU patients are at a higher risk of developing depressive, anxiety, and PTSD symptoms. Due to the high burden of disease, an accurate understanding of long-term mental health challenges for this population is key. Unfortunately, there is significant variability in reported prevalence rates. Heterogeneity in measurement tools potentially contribute to this. Inclusion criteria: Studies were eligible if they (a) reported mental health outcomes of adult patients diagnosed with COVID-19 and admitted to an ICU, (b) used standardised mental health outcome measures, and (3) were peer-reviewed. Methods: Searches were conducted in PubMed, PsycInfo, and Scopus. The initial search retrieved 1234 publications. After de-duplication and title and abstract screening, 72 full-text articles were examined for eligibility and 44 articles were excluded, leaving 28 eligible studies. Reference lists of the eligible studies were screened, and four other studies were added. 32 studies were ultimately included in this review. Results: Significant heterogeneity of measurement tools and clinical thresholds were observed. Only 6.25% of the studies compared changes in mental health outcomes to baseline measurements. Between five and nine unique measurement tools were used to study depression, anxiety, and PTSD, respectively. Studies were also observed to use up to 19 different thresholds to establish the prevalence of PTSD. Conclusions: The heterogeneity of measurement tools and thresholds continues to confound prevalence rate estimations of mental health complications post-ICU admission. Future research will benefit from consistency in the use of recommended outcome measures and the use of psychometrically comparable cut-off points between key measures.
The Impact of the Withdrawal of SGLT2 Inhibitors on Clinical Outcomes in Patients with Heart Failure
Authors: Nakagaito Masaki , Imamura Teruhiko , Ushijima Ryuichi , Nakamura Makiko , Kinugawa Koichiro
Published: May 2024

Background: The clinical impact of the withdrawal of sodium–glucose cotransporter 2 inhibitors (SGLT2i) on all-cause readmission in patients with heart failure remains unknown. Methods: We enrolled a total of 212 consecutive patients who were hospitalized for heart failure and received SGLT2i during their index hospitalization between February 2016 and July 2022. Of these patients, 51 terminated SGLT2i during or after their index hospitalization. We evaluated the prognostic impact of the withdrawal of SGLT2i on the primary outcome, which was defined as the all-cause readmission rate/times. Results: Over a median of 23.2 months, all-cause readmission occurred in 38 out of 51 patients (74.5%) withdrawn from SGLT2i and 93 out of 161 patients (57.8%) with continuation of SGLT2i (p = 0.099). The incidence of all-cause readmissions per year was 0.97 [0–1.50] in patients withdrawn from SGLT2i and 0.50 [0–1.03] in patients with continuation of SGLT2i (p = 0.030). There was no significant difference in total medical costs (62,906 [502–187,246] versus 29,236 [7920–180,305] JPY per month, p = 0.866) between both patient groups. Conclusions: Termination of SGLT2i may be associated with incremental all-cause readmission and no benefit in reducing total medical costs.
Multi-Parametric Methodology for the Feasibility Assessment of Alternative-Fuelled Ships
Authors: Adami Giorgia , Figari Massimo
Published: May 2024

The shipping industry significantly influences global greenhouse gas emissions through a predominant fossil fuel-based fleet. Regulating bodies are continuously developing rules to reduce the shipping carbon footprint. Adopting low-carbon fuels is considered a step toward achieving the Paris Agreement’s goals; however, it represents a significant paradigm shift in ship design. This work aims to illustrate a methodology for the feasibility assessment of alternative-fuelled vessels considering technical, environmental, and economic perspectives. The technical feasibility focuses on ship propulsion, fuel system safety, and design parameters. The environmental impact evaluation is based on the Tank-to-Wake and the Well-to-Wake approaches. The cost assessment is performed by estimating capital and operational expenditures, considering only the modifications required by the new fuel. The methodology addresses new-building and retrofit solutions, and can be used as a decision support tool for selecting the best strategy. A key output of the methodology is the cargo emission footprint, expressed in equivalent carbon dioxide per cargo unit. Using a handysize bulk carrier as a case study, this work points out the effects of using methanol as an alternative fuel, highlighting its impact on market and transport strategies in a sector evolving towards Eco-Delivery services.
DNA Damage Checkpoints Govern Global Gene Transcription and Exhibit Species-Specific Regulation on HOF1 in Candida albicans
Authors: Zhang Yan , Cai Huaxin , Chen Runlu , Feng Jinrong
Published: May 2024

DNA damage checkpoints are essential for coordinating cell cycle arrest and gene transcription during DNA damage response. Exploring the targets of checkpoint kinases in Saccharomyces cerevisiae and other fungi has expanded our comprehension of the downstream pathways involved in DNA damage response. While the function of checkpoint kinases, specifically Rad53, is well documented in the fungal pathogen Candida albicans, their targets remain poorly understood. In this study, we explored the impact of deleting RAD53 on the global transcription profiles and observed alterations in genes associated with ribosome biogenesis, DNA replication, and cell cycle. However, the deletion of RAD53 only affected a limited number of known DNA damage-responsive genes, including MRV6 and HMX1. Unlike S. cerevisiae, the downregulation of HOF1 transcription in C. albicans under the influence of Methyl Methanesulfonate (MMS) did not depend on Dun1 but still relied on Rad53 and Rad9. In addition, the transcription factor Mcm1 was identified as a regulator of HOF1 transcription, with evidence of dynamic binding to its promoter region; however, this dynamic binding was interrupted following the deletion of RAD53. Furthermore, Rad53 was observed to directly interact with the promoter region of HOF1, thus suggesting a potential role in governing its transcription. Overall, checkpoints regulate global gene transcription in C. albicans and show species-specific regulation on HOF1; these discoveries improve our understanding of the signaling pathway related to checkpoints in this pathogen.
Community Diversity of Fungi Carried by Four Common Woodpeckers in Heilongjiang Province, China
Authors: Shi Wenhui , Maqsood Iram , Liu Keying , Yu Meichen , Si Yuhui , Rong Ke
Published: May 2024

Woodpeckers exhibit selectivity when choosing tree cavities for nest development in forest ecosystems, and fungi play a significant and important role in this ecological process. Therefore, there is a complex and intricate relationship between the various behaviors of woodpeckers and the occurrence of fungal species. Research into the complex bond between fungi and woodpeckers was undertaken to provide more information about this remarkable ecological relationship. Through the process of line transect sampling, woodpecker traces were searched for, and mist nets were set up to capture them. A total of 21 woodpeckers belonging to four species were captured. High-throughput sequencing of the ITS region was performed on fungal-conserved samples to enable an in-depth analysis of the fungal communities linked to the woodpeckers’ nests. Members of Ascomycota were the most abundant in the samples, accounting for 91.96% of the total, demonstrating the importance of this group in the forest ecosystem of this station. The statistical results indicate significant differences in the fungal diversity carried by woodpeckers among the different groups. Species of Cladosporium were found to be the most prevalent of all the detected fungal genera, accounting for 49.3%. The top 15 most abundant genera were Cladosporium, Trichoderma, Beauveria, Epicococcum, Hypoxylon, Penicillium, Nigrospora, Aspergillus, Oidiodendron, Cercospora, Talaromyces, Phialemo-nium, Petriella, Cordyceps, and Sistotrema. The standard Bray–Curtis statistical technique was used in a hierarchical clustering analysis to compute inter-sample distances, allowing for the identification of patterns and correlations within the dataset. We discovered that in the grouped samples from woodpeckers, there were differences in the diversity of fungal communities carried by four woodpecker species, but the less dominant fungal species were still similar. The findings highlight the need to consider these diverse ecological linkages in woodpecker research and conservation efforts.
The Immunomodulatory Potential of Concurrent High-Dose Radiotherapy and Immune Checkpoint Inhibitor Cemiplimab in Advanced Cutaneous Squamous Cell Carcinoma: Initial Results
Authors: Lo Greco Maria Chiara , Marano Giorgia , Milazzotto Roberto , Liardo Rocco Luca Emanuele , Finocchiaro Irene , La Rocca Madalina , Basile Antonio , Foti Pietro Valerio , Palmucci Stefano , David Emanuele , Pergolizzi Stefano , Spatola Corrado
Published: May 2024

In this retrospective case series, we investigate the synergistic effect and the immunomodulatory potential of combination radiotherapy and immunotherapy on 11 patients affected by locally advanced or metastatic cutaneous squamous cell carcinoma (CSCC), treated at our institution between 2020 and 2023. The primary endpoints of this study are objective tumor response, assessed by Immunotherapy Response Evaluation Criteria in Solid Tumors (iRECIST), and time to treatment failure (disease progression). In all patients, surgery was deemed not amenable, due to its potential functional and aesthetic impact. Therefore, upon multidisciplinary agreement, radiotherapy and immunotherapy with cemiplimab were alternatively administered. After 6 months, an early objective tumor response was observed in 9/11 patients, with 17/20 cutaneous lesions (85%) presenting either a complete or partial response. Only 2/11 patients, with a total of 3/20 cutaneous lesions (15%), had stable disease. These benefits persisted at a longer follow-up (21.4 ± 9.7 months), with no patients presenting disease progression. Despite the retrospective nature of this study and small sample size, our experience highlights the ability of concomitant radiotherapy and cemiplimab to promote an early objective response in patients with advanced CSCC. Moreover, in our population, the clinical benefits were also related to a longer progression-free survival, without any safety alert reported.
Prediction of the Hamstring Graft Size for ACL Reconstruction Using Different Axial Layers in Preoperative MRI
Authors: Mayr Moritz Florian , Siegel Markus , Taghizadeh Elham , Obid Peter , Schmal Hagen , Izadpanah Kaywan
Published: May 2024

Background: In ACL reconstruction, it is desirable to assess preoperatively whether a sufficient graft diameter can be achieved with the planned tendon graft. The present study investigated the effect of the location of the cross-sectional area (CSA) measurement of the hamstring tendons in preoperative MRI on the correlation of the CSA with the intraoperative graft diameter. In addition, we analyzed whether the measurement results of examiners with different skill levels were comparable. Methods: A total of 32 subjects undergoing a single bundle ACL reconstruction using an autologous ipsilateral quadrupled hamstring graft (STGT) were included. The CSA of the semitendinosus and gracilis tendon was determined in preoperative MRI on six defined levels by three examiners. The intraclass correlation coefficient between the measurements of these observers was determined. The correlation between the sum of the CSA of both tendons (CSA STGT) and the graft diameter was investigated. Results: The interrater reliability was excellent on most of the investigated levels. A significant correlation between CSA STGT and the graft diameter was seen on all levels. The strongest correlation was found on the level 10 mm above the joint line. Conclusions: The measurement of the CSA STGT in the preoperative MRI 10 mm above the joint line enabled a good assessment of the achievable graft diameter in ACL reconstruction, independent of the examiners’ training level.