bluuebunny/crossref_metadata_2025 huggingface dataset:
The effect of exercise and disease status on mobilization of anti-tumorigenic and pro-tumorigenic immune cells in women with breast cancer
Authors: Koivula Tiia , Lempiäinen Salla , Neuvonen Joona , Norha Jooa , Hollmén Maija , Sundberg Carl Johan , Rundqvist Helene , Minn Heikki , Rinne Petteri , Heinonen Ilkka
Published: June 2024

Background

Mobilization of certain immune cells may improve the ability of the immune system to combat tumor cells, but the effect of acute exercise on mobilizing immune cells has been sparsely investigated in cancer patients. Therefore, we examined how acute exercise influences circulating immune cells in breast cancer patients.

Methods

Nineteen newly diagnosed breast cancer patients aged 36–68 performed 30 minutes of moderate-intensity exercise with a cycle ergometer. Blood samples were collected at various time points: at rest, at 15 (E15) and 30 minutes (E30) after onset of the exercise, and at 30 and 60 minutes post-exercise. We analyzed several immune cell subsets using flow cytometry.

Results

Acute exercise increased the number of total leukocytes, neutrophils, lymphocytes, monocytes, basophils, total T-cells, CD4+ T-cells, T helper (Th) 2-cells, Th 17-cells, CD8+ T-cells, CD4-CD8- T-cells, CD56+ natural killer (NK) cells, and CD14-CD16+ monocytes. Many of the changes were transient. Proportions of NK-cells and CD8+ T-cells increased, while the proportion of myeloid derived suppressor cells (MDSCs) reduced, and proportion of regulatory T-cells remained unchanged by exercise. Several associations were detected between cell mobilizations and disease state. For instance, tumor size correlated negatively with NK cell mobilization at E15, and progesterone receptor positivity correlated negatively with CD8+ T-cell mobilization.

Conclusion

The findings show that the proportions of CD8+ T-cells and NK cells increased and the proportion of MDSCs proportion decreased in breast cancer patients after 30-minute exercise, suggesting a change in the profile of circulating immune cells towards more cytotoxic/anti-tumorigenic. The mobilization of some immune cells also appears to be related to the disease state.
Impaired arginine/ornithine metabolism drives severe HFMD by promoting cytokine storm
Authors: Zhang Yaozhong , Yang Qingqing , Peng Qi , Tian Zhihua , Lv Fen , Zeng Xiaomei , Jiang Zaixue , Cheng Qingqiu , Yang Lijun , Zhong Baimao , Lu Xiaomei , Zhu Yinghua
Published: June 2024

Introduction

The Hand, Foot and Mouth Disease (HFMD), caused by enterovirus 71 infection, is a global public health emergency. Severe HFMD poses a significant threat to the life and well-being of children. Numerous studies have indicated that the occurrence of severe HFMD is associated with cytokine storm. However, the precise molecular mechanism underlying cytokine storm development remains elusive, and there are currently no safe and effective treatments available for severe HFMD in children.

Methods

In this study, we established a mouse model of severe HFMD to investigate the molecular mechanisms driving cytokine storm. We specifically analyzed metabolic disturbances, focusing on arginine/ornithine metabolism, and assessed the potential therapeutic effects of spermine, an ornithine metabolite.

Results

Our results identified disturbances in arginine/ornithine metabolism as a pivotal factor driving cytokine storm onset in severe HFMD cases. Additionally, we discovered that spermine effectively mitigated the inflammatory injury phenotype observed in mice with severe HFMD.

Discussion

In conclusion, our findings provide novel insights into the molecular mechanisms underlying severe HFMD from a metabolic perspective while offering a promising new strategy for its safe and effective treatment.
Optimal dosage ranges of various exercise types for enhancing timed up and go performance in Parkinson’s disease patients: a systematic review and Bayesian network meta-analysis
Authors: Yuan Yuan , Wang JunYu , Wang GuoTuan , Wang Tao , Zhang HaoYang , Fu XueYing , Wu LiHua , Chen XiaoTian , Xia Rui , Zhang Lin , Lin Shu-Cheng , Yang Yong
Published: June 2024

Objective

To examine the dose–response relationship between specific types of exercise for alleviating Timed up and Go (TUG) in Parkinson’s disease PD.

Design

Systematic review and Bayesian network meta-analysis.

Data sources

PubMed, Medline, Embase, PsycINFO, Cochrane Library, and Web of Science were searched from inception until February 5th, 2024.

Study analysis

Data analysis was conducted using R software with the MBNMA package. Effect sizes of outcome indicators were expressed as mean deviation (MD) and 95% confidence intervals (95% CrI). The risk of bias in the network was evaluated independently by two reviewers using ROB2.

Results

A total of 73 studies involving 3,354 PD patients. The text discusses dose–response relationships in improving TUG performance among PD patients across various exercise types. Notably, Aquatic (AQE), Mix Exercise (Mul_C), Sensory Exercise (SE), and Resistance Training (RT) demonstrate effective dose ranges, with AQE optimal at 1500 METs-min/week (MD: −8.359, 95% CI: −1.398 to −2.648), Mul_C at 1000 METs-min/week (MD: −4.551, 95% CI: −8.083 to −0.946), SE at 1200 METs-min/week (MD: −5.145, 95% CI: −9.643 to −0.472), and RT at 610 METs-min/week (MD: −2.187, 95% CI: −3.161 to −1.278), respectively. However, no effective doses are found for Aerobic Exercise (AE), Balance Gait Training (BGT), Dance, and Treadmill Training (TT). Mind–body exercise (MBE) shows promise with an effective range of 130 to 750 METs-min/week and an optimal dose of 750 METs-min/week (MD: −2.822, 95% CI: −4.604 to −0.996). According to the GRADE system, the included studies’ overall quality of the evidence was identified moderate level.

Conclusion

This study identifies specific exercise modalities and dosages that significantly enhance TUG performance in PD patients. AQE emerges as the most effective modality, with an optimal dosage of 1,500 METs-min/week. MBE shows significant benefits at lower dosages, catering to patients with varying exercise capacities. RT exhibits a nuanced “U-shaped” dose–response relationship, suggesting an optimal range balancing efficacy and the risk of overtraining. These findings advocate for tailored exercise programs in PD management, emphasizing personalized prescriptions to maximize outcomes.

Systematic Review Registration: International Prospective Register of Systematic Reviews (PROSPERO) (CRD42024506968).
Comparison of immunochemotherapy and chemotherapy alone in conversion therapy for locally advanced unresectable esophageal squamous cell carcinoma
Authors: Xu Zhiyun , You Zhenbing , Chen Mengzhou , Zhang Mingzhi , Shen Cheng , Xu Dafu , Xu Keping , Tian Wenze
Published: June 2024

Background

The clinical value of preoperative immunochemotherapy and simple chemotherapy induction regimen in the conversion therapy of locally advanced unresectable esophageal squamous cell carcinoma (ESCC) is still unclear.

Method

Retrospective analysis was conducted on patients with unresectable cT4b stage ESCC who underwent conversion surgery in our hospital from January 2020 to December 2022. According to the preoperative induction treatment plan, they were divided into induction immunochemotherapy group (iICT group) and induction chemotherapy group (iCT group). The conversion surgery rate, R0 resection rate, radiological and pathological tumor responses, safety, and short-term survival outcomes were analyzed.

Results

The results showed that a total of 199 patients with cT4b locally advanced unresectable ESCC who underwent preoperative induction therapy were included in this study. Among them, there were 64 cases (32.2%) in the iICT group, 135 cases (67.8%) in the iCT group. There was a statistically significant difference in objective response rate (73.5% vs 48.9%) and conversion surgery rate (81.3% vs 66.7%), between the iICT and iCT groups (P=0.001 and P=0.019). Among the two groups of patients who underwent surgery, there were statistically significant differences in R0 resection rate (94.2% vs 82.2%) and pathological complete remission rate (23.1% vs 6.7%) between the iICT and iCT groups (P=0.043 and P=0.004). And there was no statistically significant difference in the incidence of grade 3 and above between two groups (P=0.928). The 2-year EFS of the iICT group and iCT group were 76.4% and 42.4%, respectively, with statistically significant differences (P=0.006).

Conclusions

Compared with simple chemotherapy, the combination of PD-1 inhibitors and chemotherapy can achieve better conversion surgery rate, tumor response and event-free survival in the conversion therapy of locally advanced unresectable ESCC.
Immune microenvironment and immunotherapy for chordoma
Authors: Chen Yujia , Zhang Hongwei
Published: June 2024

Chordoma, as a rare, low-grade malignant tumor that tends to occur in the midline of the body, grows slowly but often severely invades surrounding tissues and bones. Due to the severe invasion and damage to the surrounding tissues, chordoma is difficult to be gross totally resected in surgery, and the progression of the residual tumor is often unavoidable. Besides, the tumor is insensitive to conventional radiotherapy and chemotherapy, thus finding effective treatment methods for chordoma is urgent. Nowadays, immunotherapy has made a series of breakthroughs and shown good therapeutic effects in kinds of tumors, which brings new insights into tumors without effective treatment strategies. With the deepening of research on immunotherapy, some studies focused on the immune microenvironment of chordoma have been published, most of them concentrated on the infiltration of immune cells, the expression of tumor-specific antigen or the immune checkpoint expression. On this basis, a series of immunotherapy studies of chordoma are under way, some of which have shown encouraging results. In this review, we reviewed the research about immune microenvironment and immunotherapy for chordoma, combined with the existing clinical trials data, hoping to clarify the frontiers and limitations of chordoma immune research, and provide reference for follow-up immunotherapy research on chordoma.
Exploring the lutein therapeutic potential in steatotic liver disease: mechanistic insights and future directions
Authors: Balboa Elisa , Saud Faride , Parra-Ruiz Claudia , de la Fuente Marjorie , Landskron Glauben , Zanlungo Silvana
Published: June 2024

The global prevalence of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is increasing, now affecting 25%–30% of the population worldwide. MASLD, characterized by hepatic steatosis, results from an imbalance in lipid metabolism, leading to oxidative stress, lipoperoxidation, and inflammation. The activation of autophagy, particularly lipophagy, alleviates hepatic steatosis by regulating intracellular lipid levels. Lutein, a carotenoid with antioxidant and anti-inflammatory properties, protects against liver damage, and individuals who consume high amounts of lutein have a lower risk of developing MASLD. Evidence suggests that lutein could modulate autophagy-related signaling pathways, such as the transcription factor EB (TFEB). TFEB plays a crucial role in regulating lipid homeostasis by linking autophagy to energy metabolism at the transcriptional level, making TFEB a potential target against MASLD. STARD3, a transmembrane protein that binds and transports cholesterol and sphingosine from lysosomes to the endoplasmic reticulum and mitochondria, has been shown to transport and bind lutein with high affinity. This protein may play a crucial role in the uptake and transport of lutein in the liver, contributing to the decrease in hepatic steatosis and the regulation of oxidative stress and inflammation. This review summarizes current knowledge on the role of lutein in lipophagy, the pathways it is involved in, its relationship with STARD3, and its potential as a pharmacological strategy to treat hepatic steatosis.
Quantum magnetism in Fe2Cu2 polymeric branched chains: insights from exactly solved Ising-Heisenberg model
Authors: Sivý Dávid , Karl’ová Katarína , Strečka Jozef
Published: June 2024

The spin-1/2 Ising-Heisenberg branched chain, inspired by the magnetic structure of three isostructural polymeric coordination compounds [(Tp)2Fe2(CN)6X (bdmap)Cu2(H2O)] ⋅ H2O to be further denoted as Fe2Cu2 (Tp = tris(pyrazolyl)hydroborate, bdmapH = 1,3-bis(dimethylamino)-2-propanol, HX = acetic acid, propionic acid or trifluoroacetic acid), is rigorously studied using the transfer-matrix method. The overall ground-state phase diagram reveals three distinct phases: a quantum antiferromagnetic phase, a quantum ferrimagnetic phase and a classical ferromagnetic phase. In the zero-temperature magnetization curve, two quantum ground states are manifested as intermediate plateaus at zero and half of the saturation magnetization, while the magnetization reaches its saturated value within the classical ferromagnetic phase. The bipartite entanglement between nearest-neighbor Heisenberg spins is more pronounced in the quantum ferrimagnetic phase compared to the quantum antiferromagnetic phase due to a fully polarized nature of the Ising spins. A reasonable agreement between theoretical predictions for the spin-1/2 Ising-Heisenberg branched chain and experimental data measured for a temperature dependence of the magnetic susceptibility and a low-temperature magnetization curve suggests strong antiferromagnetic coupling between nearest-neighbor Cu2+-Cu2+ magnetic ions and moderately strong ferromagnetic coupling between nearest-neighbor Cu2+-Fe3+ magnetic ions in the polymeric compounds Fe2Cu2. A thermal entanglement between nearest-neighbor Cu2+-Cu2+ magnetic ions persists up to a relatively high threshold temperature T ≈ 224 K and undergoes a transient magnetic-field-driven strengthening.
Social wellbeing profiles: associations with trust in managers and colleagues, job satisfaction, and intention to leave
Authors: Hennicks Eugeny C. , Heyns Marita M. , Rothmann Sebastiaan
Published: June 2024

Introduction

This study aimed to determine latent social wellbeing profiles and investigate differences between the profiles in terms of trust in managers and colleagues, job satisfaction, intention to leave, and demographic variables (age and service years).

Methods

Permanently employed individuals of a South African utility organization participated in the study (N = 403). The Social Well-being Scale, Workplace Trust Survey, Job Satisfaction Scale, and Turnover Intention Scale were administered.

Results

Four social wellbeing profiles were identified: socially disconnected (19.11%), socially challenged (31.27%), socially adequate (22.30%), and socially thriving (27.33%). Individuals in the socially thriving profile were significantly more inclined to experience job satisfaction and had lower intentions to leave than individuals in the other social wellbeing profiles. Two demographic variables, namely, age and service years, were associated with profile membership.

Discussion

This study provided a nuanced understanding of social wellbeing by identifying patterns in which social contribution, social integration, social actualization, social coherence, and social acceptance interacted within individuals in a population, which might otherwise not have been evident. The differing levels of social wellbeing among these profiles have substantial implications for job satisfaction and staff retention.
Emotional intelligence training for pre-service primary school teachers: a mixed methods research
Authors: Özdemir Cihan Meryem , Dilekmen Mücahit
Published: June 2024

Introduction

This research devises a training program for developing emotional intelligence focused on social and emotional learning and integrates it into teaching to improve pre-service teachers’ emotional intelligence.

Methods

The study used a embedded mixed design. The quantitative dimension of the study used a controlled quasi-experimental design with pre-test/post-test, and the qualitative dimension used an evaluative case study design. The study was conducted with 73 prospective primary school teachers studying at the faculty of education of a Turkish state university. The study group was formed using purposive random sampling. The sample for the quantitative dimension was composed using probability random sampling, whereas the sample for the qualitative dimension was composed using purposive sampling. The program was administered to the experimental group for 10 weeks. Quantitative data were obtained using the Bar-On EQ-i, and qualitative data were obtained using a semi-structured interview questionnaire and participant diaries. Quantitative data were analyzed using normality analysis and one-factor analysis of covariance, whereas qualitative data were analyzed using descriptive and content analysis.

Results

The results found the developed training program to be an effective approach to improve emotional intelligence among pre-service teachers. Moreover, data obtained from documentary sources and focus group interviews during and after the application of the program confirmed and adequately explained the quantitative results.

Discussion

In line with the purpose of the study, the findings obtained from the quantitative part of the study showed that the implementation of the training program for the development of emotional intelligence focused on SEL was an effective approach in increasing the emotional intelligence levels of the pre-service teachers in the experimental group. Similar research results also support that pre-service teachers’ emotional intelligence can be improved with additional intervention practices without affecting their curriculum.
Effects of mindfulness on test anxiety: a meta-analysis
Authors: Yılmazer Eda , Hamamci Zeynep , Türk Fulya
Published: June 2024

Objective

This meta-analysis evaluated the effectiveness of mindfulness-based interventions (MBIs) on test anxiety across diverse age groups and intervention modalities.

Methods

Rigorous inclusion criteria were applied to select studies focusing on MBIs as the independent variable, with test anxiety as the outcome. A comprehensive search across multiple databases yielded 18 primary studies, contributing 20 comparisons. Data were extracted on study characteristics, sample sizes, and intervention details, and were analyzed using a random-effects model.

Results

The analyses incorporated 1,275 participants, with MBIs demonstrating a moderate to large negative effect on test anxiety (effect size = −0.716; 95% CI: −1.383 to −0.049). Moderation analysis indicated that mean age, number of sessions, and intervention delivery mode did not significantly influence effect sizes. Publication bias assessment suggested the presence of bias via Egger’s regression (p = 0.025), though Begg and Mazumdar’s test and Duval and Tweedie’s trim and fill method indicated no missing studies.

Conclusion

MBIs are effective in reducing test anxiety, though results should be interpreted with caution due to potential publication bias and unexplained heterogeneity. The impact of MBIs did not vary significantly with participant age, number of sessions, or delivery mode.
Sensory Phenomenon Assessment Scale: a new tool for assessment of tic-associated sensations
Authors: Wang Xianbin , Li Yanlin , Yu Liping , Xu Hui , Zhang Anyi , Zhang Wenyan , Jiang Zhongliang , Cui Yonghua , Li Ying
Published: June 2024

Background

Sensory symptoms linked to tic disorder (TD) are challenging to quantify via self- or parent-reported measures. The current study aimed to develop a novel observer-rated semi-structured interview, namely, the Sensory Phenomenon Assessment Scale (SPAS), to aid clinical evaluation on symptoms of TD among children.

Methods

To test its psychometric properties, tic, premonitory urge (PU), and obsessive–compulsive symptoms (OCS) were also assessed in 223 children via the Yale Global Tic Severity Scale (YGTSS), the Premonitory Urge for Tic Scale (PUTS), and the Children’s Yale–Brown Obsessive–Compulsive Scale (CY-BOCS). Factor analysis and internal consistency test were carried out using data from TD-diagnosed individuals.

Results

Good internal consistency and test–retest reliability were observed. Criterion validity was established by significant correlations between the PUTS, the YGTSS, the CY-BOCS, and scores of the SPAS. Factor analyses supported a single-factor model of the SPAS, in which the five items each showed a factor loading above 0.6.

Conclusion

This study demonstrated that the SPAS is reliable and valid and, thus, can serve as a good and concise measure of clinical symptoms among children and adolescents with TD.
Impact of COVID-19 on individual mental health and maternal health services in Ethiopia: systematic review and meta-analysis
Authors: Alie Melsew Setegn , Girma Desalegn , Negesse Yilkal , Adugna Amanuel , Abebe Gossa Fetene
Published: June 2024

Background

The COVID-19 pandemic has caused a major outbreak in the 21st century and has led to significant mental health hazards worldwide. To address this issue, a systematic review has been conducted to analyze existing literature on the impact of COVID-19 on the psychological well-being of the general population, as well as the associated risk factors.

Methods

A comprehensive search was carried out on PubMed, Embase, Medline, Web of Science, and Scopus databases, covering all available literature up until February 20, 2024. This search was conducted in accordance with the PRISMA guidelines, ensuring a systematic approach. The selection of articles was based on predetermined eligibility criteria, ensuring the inclusion of appropriate and suitable research. In the final analysis, a total of 15 articles focusing on depression and anxiety, 11 articles on stress, and 7 articles on psychological problems were included. These articles specifically examined the outcome variables within the context of English language and specific areas. For the meta-analysis on maternal health services, 11 articles were included for family planning, 25 articles for postnatal care services, 16 articles for institutional delivery, and 14 articles for safe abortion services. These articles were carefully selected for the final pooled analysis.

Result

According to a recent systematic review, anxiety, depression, stress, and psychological distress have been prevalent in Ethiopia during the COVID-19 pandemic, with rates of 40, 41, 23, and 41%, respectively. The review also identified various sociodemographic factors that have impacted the country’s response to the pandemic, including female gender, age, marital status, incarceration, low income, and lack of social support. Furthermore, the review found that maternal health services have experienced significant reductions during the pandemic.

Conclusion

The COVID-19 pandemic has led to a significant increase in psychological distress, which in some cases, is severe enough to require clinical treatment. It is crucial to prioritize efforts to address the negative impact of COVID-19 on mental health as a global public health priority. Additionally, it is important to pay attention to maternal health services during COVID-19 mitigation programs.
The benefits of socioemotional learning strategies and video formats for older digital immigrants learning a novel smartphone application
Authors: Ford Jaclyn H. , Daley Ryan T. , Kensinger Elizabeth A.
Published: June 2024

The need to continually learn and adjust to new technology can be an arduous demand, particularly for older adults who did not grow up with digital technology (“older digital immigrants” or ODIs). This study tests the efficacy of socioemotional learning strategies (i.e., encoding information in a socially- or emotionally-meaningful way) for ODIs learning a new software application from an instructional video (Experiment 1) or a written manual (Experiment 2). An experiment-by-condition effect was identified, where memory was greatest for participants engaging socioemotional learning strategies while learning from a video, suggesting a synergistic effect of these manipulations. These findings serve as a first step toward identifying and implementing an optimal learning context for ODIs to learn new technologies in everyday life.
Mastering Migraines
Authors: Atkisson Mary , Fowler Lauren
Published: June 2024

On a scale of 1–10, imagine a headache turned up to 10. That is a migraine, caused by intricate changes in the brain’s nerves and chemicals. Despite affecting 15% of the population, the exact cause of migraines remains a puzzle, with genetic, environmental, and hormonal factors all at play. Migraines unfold in four phases: prodrome, aura, headache, and postdrome, each with its distinct symptoms and challenges. Delving into the brain’s workings during a migraine, scientists have discovered a complex interplay between various aspects of the nervous system. Far beyond mere headaches, migraines are an intense experience. For people grappling with migraines, treatment options can range from medications to lifestyle adjustments. Treatment options depend on the person and the type of migraine they have. Fortunately, migraine treatments are constantly improving. So, the next time your headache feels like it might be more than a “regular” headache, consider the possibility of a migraine.
Recompression after percutaneous transforaminal endoscopic decompression for degenerative lumbar spinal stenosis: risk factors and outcomes of two different reoperation procedures
Authors: Yuan Shuo , Wang Aobo , Fan Ning , Du Peng , Wang Tianyi , Li Jian , Zhu Wenyi , Zang Lei
Published: June 2024

Purpose

To determine the risk factors for recompression after percutaneous transforaminal endoscopic decompression (PTED) for the treatment of degenerative lumbar spinal stenosis (DLSS) and compare the outcomes of PTED and posterior lumbar interbody fusion (PLIF) as revision surgery.

Methods

We retrospectively evaluated 820 consecutive DLSS patients who underwent PTED at our institution. 26 patients developed postoperative recompression and underwent reoperation. In total, 208 patients with satisfactory clinical outcomes were enrolled in the control group. The demographic and imaging data of each patient were recorded. Univariate and multivariate analyses were performed to assess risk factors for recompression. Additionally, patients with recompression were divided into PTED and PLIF groups according to the reoperation procedure. The clinical outcomes of the two groups were compared using independent-sample t-tests.

Results

The grade of surgical-level disc degeneration [odds ratio (OR): 2.551, p = 0.045] and the number of disc degeneration levels (OR: 11.985, p < 0.001) were independent risk factors for recompression after PTED. There was no significant difference in the visual analog score (VAS) and Oswestry disability index (ODI) two weeks postoperatively between the PTED and PLIF groups for surgical treatment. However, the mean VAS of back pain (14.1 vs. 20.5, p = 0.016) and ODI (16.0 vs. 21.8, p = 0.016) of patients in the PLIF group were smaller than those in the PTED group at the final follow-up.

Conclusion

More severe degeneration and degenerated levels indicate a higher recompression rate after PTED. Although both PTED and PLIF could achieve immediate relief postoperatively in the treatment of recompression, the final follow-up results showed that the outcome of PLIF appeared better than that of PTED.
Supervised Dynamic Correlated Topic Model for Classifying Categorical Time Series
Authors: Pais Namitha , Ravishanker Nalini , Rajasekaran Sanguthevar
Published: June 2024

In this paper, we describe the supervised dynamic correlated topic model (sDCTM) for classifying categorical time series. This model extends the correlated topic model used for analyzing textual documents to a supervised framework that features dynamic modeling of latent topics. sDCTM treats each time series as a document and each categorical value in the time series as a word in the document. We assume that the observed time series is generated by an underlying latent stochastic process. We develop a state-space framework to model the dynamic evolution of the latent process, i.e., the hidden thematic structure of the time series. Our model provides a Bayesian supervised learning (classification) framework using a variational Kalman filter EM algorithm. The E-step and M-step, respectively, approximate the posterior distribution of the latent variables and estimate the model parameters. The fitted model is then used for the classification of new time series and for information retrieval that is useful for practitioners. We assess our method using simulated data. As an illustration to real data, we apply our method to promoter sequence identification data to classify E. coli DNA sub-sequences by uncovering hidden patterns or motifs that can serve as markers for promoter presence.
Current State, Needs, and Opportunities for Wearable Robots in Military Medical Rehabilitation and Force Protection
Authors: Cooper Rory A. , Smolinski George , Candiotti Jorge L. , Satpute Shantanu , Grindle Garrett G. , Sparling Tawnee L. , Nordstrom Michelle J. , Yuan Xiaoning , Symsack Allison , Lee Chang Dae , Vitiello Nicola , Knezevic Steven , Sugar Thomas G. , Schneider Urs , Kopp Verena , Holl Mirjam , Gaunaurd Ignacio , Gailey Robert , Bonato Paolo , Poropatich Ron , Adet David J. , Clemente Francesco , Abbas James , Pasquina Paul F.
Published: June 2024

Despite advances in wearable robots across various fields, there is no consensus definition or design framework for the application of this technology in rehabilitation or musculoskeletal (MSK) injury prevention. This paper aims to define wearable robots and explore their applications and challenges for military rehabilitation and force protection for MSK injury prevention. We conducted a modified Delphi method, including a steering group and 14 panelists with 10+ years of expertise in wearable robots. Panelists presented current wearable robots currently in use or in development for rehabilitation or assistance use in the military workforce and healthcare. The steering group and panelists met to obtain a consensus on the wearable robot definition applicable for rehabilitation or primary injury prevention. Panelists unanimously agreed that wearable robots can be grouped into three main applications, as follows: (1) primary and secondary MSK injury prevention, (2) enhancement of military activities and tasks, and (3) rehabilitation and reintegration. Each application was presented within the context of its target population and state-of-the-art technology currently in use or under development. Capturing expert opinions, this study defines wearable robots for military rehabilitation and MSK injury prevention, identifies health outcomes and assessment tools, and outlines design requirements for future advancements.
Tracing the Evolution of E-Government: A Visual Bibliometric Analysis from 2000 to 2023
Authors: Song Yifan , Natori Takashi , Yu Xintao
Published: June 2024

In the continuously evolving field of E-government, understanding the breadth and depth of academic research is crucial for advancing governmental digital transformation and policy development. This study employs visual bibliometric analysis, using the Web of Science database to map the evolution trajectory of E-government research from 2000 to 2023. By utilizing CiteSpace for a comprehensive examination of 4536 academic articles, this paper outlines the growth patterns and thematic evolution within the field. The development of the E-government field is delineated into four distinct phases: the budding period (2000–2003), the bottleneck period (2004–2014), the development period (2015–2018), and the growth period (2019–2023), which are each marked by unique thematic shifts and technological advancements. The research results reveal the transformation of research focus in different periods, from the initial focus on the technological means and the electronic transformation of government services, moving on to more complex issues such as E-government acceptance and government transparency and corruption, and ultimately to the current focus on innovation and smart cities. In addition, the paper also clarifies that the research boom that began in 2019 is driven by technological innovation opportunities, the improvement in infrastructure, and multidisciplinary research. By depicting these developmental stages and emerging trends, this study not only unveils past academic efforts but also forecasts future research directions, thereby providing valuable insights for researchers and policymakers aiming to understand and implement effective E-government strategies.
SpaceLight: A Framework for Enhanced On-Orbit Navigation Imagery
Authors: Zhang Zhang , Feng Jiaqi , Chang Liang , Deng Lei , Li Dong , Si Chaoming
Published: June 2024

In the domain of space rendezvous and docking, visual navigation plays a crucial role. However, practical applications frequently encounter issues with poor image quality. Factors such as lighting uncertainties, spacecraft motion, uneven illumination, and excessively dark environments collectively pose significant challenges, rendering recognition and measurement tasks during visual navigation nearly infeasible. The existing image enhancement methods, while visually appealing, compromise the authenticity of the original images. In the specific context of visual navigation, space image enhancement’s primary aim is the faithful restoration of the spacecraft’s mechanical structure with high-quality outcomes. To address these issues, our study introduces, for the first time, a dedicated unsupervised framework named SpaceLight for enhancing on-orbit navigation images. The framework integrates a spacecraft semantic parsing network, utilizing it to generate attention maps that pinpoint structural elements of spacecraft in poorly illuminated regions for subsequent enhancement. To more effectively recover fine structural details within these dark areas, we propose the definition of a global structure loss and the incorporation of a pre-enhancement module. The proposed SpaceLight framework adeptly restores structural details in extremely dark areas while distinguishing spacecraft structures from the deep-space background, demonstrating practical viability when applied to visual navigation. This paper is grounded in space on-orbit servicing engineering projects, aiming to address visual navigation practical issues. It pioneers the utilization of authentic on-orbit navigation images in the research, resulting in highly promising and unprecedented outcomes. Comprehensive experiments demonstrate SpaceLight’s superiority over state-of-the-art low-light enhancement algorithms, facilitating enhanced on-orbit navigation image quality. This advancement offers robust support for subsequent visual navigation.
A Rapid Modeling Method for Airborne FSS Radomes Based on Dynamic Customizable Primitives
Authors: Qiu Cunai , Li Shen , Zhang Wenwu , Song Liwei , Li Xiang , Yan Zhongen , Chen Yue , Suo Saisai
Published: June 2024

The digital model of airborne frequency selective surface radomes (AFSSRs) is the basis of design, simulation analysis, manufacturing, and other related research on AFSSRs. This paper proposes a rapid modeling method for AFSSRs based on dynamic customizable primitives. Firstly, a layered digital model construction scheme for AFSSRs is presented based on the typical radome wall structure. Then, according to the characteristics of various surface configurations and the complex wireframe information of AFSSRs, the dynamic primitives are raised to express the boundary and contour information of all kinds of radomes. Focusing on the undevelopable characteristics of the aerodynamic shape surface of the AFSSR, the arrangement solution and mapping method for frequency-selective elements on undevelopable surfaces are proposed. Furthermore, the implementation logic of this method for the creation of each layer model and the assembly of the whole machine model is introduced. Finally, a rapid modeling system (RMS) is established based on this method, enabling the automated creation of digital models of AFSSRs. Utilizing this system resulted in modeling time savings ranging from 20% to 97.5% compared to traditional methods, which verifies the feasibility and effectiveness of this method.
Research on Nondestructive Inspection of Fruits Based on Spectroscopy Techniques: Experimental Scenarios, ROI, Number of Samples, and Number of Features
Authors: Wang Qi , Lu Jinzhu , Wang Yuanhong , Gao Junfeng
Published: June 2024

Spectral technology is a scientific method used to study and analyze substances. In recent years, the role of spectral technology in the non-destructive testing (NDT) of fruits has become increasingly important, and it is expected that its application in the NDT of fruits will be promoted in the coming years. However, there are still challenges in terms of dataset collection methods. This article aims to enhance the effectiveness of spectral technology in NDT of citrus and other fruits and to apply this technology in orchard environments. Firstly, the principles of spectral imaging systems and chemometric methods in spectral analysis are summarized. In addition, while collecting fruit samples, selecting an experimental environment is crucial for the study of maturity classification and pest detection. Subsequently, this article elaborates on the methods for selecting regions of interest (ROIs) for fruits in this field, considering both quantitative and qualitative perspectives. Finally, the impact of sample size and feature size selection on the experimental process is discussed, and the advantages and limitations of the current research are analyzed. Therefore, future research should focus on addressing the challenges of spectroscopy techniques in the non-destructive inspection of citrus and other fruits to improve the accuracy and stability of the inspection process. At the same time, achieving the collection of spectral data of citrus samples in orchard environments, efficiently selecting regions of interest, scientifically selecting sample and feature quantities, and optimizing the entire dataset collection process are critical future research directions. Such efforts will help to improve the application efficiency of spectral technology in the fruit industry and provide broad opportunities for further research.
Exploring Gene Action Underlying Post-Harvest Water Loss in Fresh Market Peppers
Authors: Rêgo Elizanilda Ramalho do , Finger Fernando Luiz , Pessoa Angela Maria dos Santos , da Silva Anderson Rodrigo , Azevedo Aristéa Alves , Meira Renata Maria Strozi Alves , da Silva André Luiz Biscaia Ribeiro , Silva Ruan dos Santos , Rêgo Mailson Monteiro do
Published: June 2024

The objective of this study was to evaluate the genetic effects involved in post-harvest water loss of C. baccatum fruits and to correlate fruit morphological characteristics. Fruits of eight landraces of C. baccatum and their twenty-eight hybrids were evaluated in a randomized, complete block design. Analysis of variance, diallel analysis, phenotypic and genotypic correlation, and path analysis for eight fruit traits were performed. Fruit width, fruit length, dry matter content, and fruit wall thickness were determined by additive gene effects. On the other hand, the non-additive effects played more important role than additive ones, including water loss, cuticle thickness, exocarp thickness, and total soluble solids. The relationship of fruit traits suggested that indirect selection can be carried out from field experiments under different environmental conditions. Overall, genitors 4, 24, 50, and 56 should be selected to form new populations to improve these traits. The Brazilian pepper landraces of C. baccatum species are a source of genetic variability for plant breeders, and the new segregating populations emerging through the crossing of pepper lines with reduced water loss should be developed, opening new ways for conventional breeding.
Design and Testing of Vehicle-Mounted Crop Growth Monitoring System
Authors: Yu Shanshan , Cao Qiang , Tian Yongchao , Zhu Yan , Liu Xiaojun , Ni Jun , Zhang Wenyi , Cao Weixing
Published: June 2024

The aim of this study was to overcome the impact of vibration generated by agricultural machinery on the monitoring accuracy and performance of vehicle-mounted crop growth monitoring systems during field operation. This paper developed a vehicle-mounted crop growth monitoring system with vibration damping capability to achieve this goal. The system consists of a multispectral crop growth sensor, signal conditioning module, and truss-type sensor bracket with self-vibration damping capability. The commercial finite element analysis software ABAQUS 6.10 was used to conduct modal and dynamic simulation analyses of the sensor bracket, which indicate that the truss-type sensor bracket can damp vibrations effectively. The p-values (least significant differences) of crop canopy DNRE (red edge normalized difference vegetation index) under different operating speeds (1.5, 3, and 4.5 km/h) are 0.454, 0.703, 0.81, and 0.838, respectively, for four different crop growth stages. In a comparative experiment between the proposed monitoring system and two similar vehicle-mounted sensors (CropSpec and GreenSeeker RT 200) for measuring agronomic parameters at different stages of crop growth, the proposed monitoring system yielded R2 values of 0.8757, 0.7194, and 0.795, respectively, and RMSE values of 0.7157, 2.2341, and 2.0952, respectively, in the tillering stage, jointing stage, and tillering and jointing stage, outperforming the other two sensors.
Clinical Evidence on Expansion of Essential Oil-Based Formulation’s Pharmacological Activity in Bovine Mastitis Treatment: Antifungal Potential as Added Value
Authors: Tomanić Dragana , Božić Dragana D. , Kladar Nebojša , Samardžija Marko , Apić Jelena , Baljak Jovan , Kovačević Zorana
Published: June 2024

Bovine mastitis, as a significant and prevalent health problem in dairy herds, is primarily attributed to bacterial infections. Yeasts, although considered relatively rare causative agents, have also been associated with mastitis in dairy cattle. Current mastitis treatment predominantly relies on antibiotics, with limited emphasis on antifungal treatment. However, mycotic mastitis is challenging to treat, since these fungi are often resistant to antibiotics and may even utilize them for energy. In the current research, the in vivo antimicrobial activity of the essential oil-based formulation (Phyto-Bomat), as a possible alternative mastitis treatment associated with yeasts, was studied. This study involved a total of 68 animals from two dairy farms with diagnosed mastitis, and three treatment groups were established: conventional antibiotic treatment, Phyto-Bomat treatment, and the combination of both. The findings suggest significant variations in the presence of Candida samples based on the treatment administered, and the most significant difference was noted in cows treated with the combination (Phyto-Bomat and antibiotics). Yet, it is important to note that the results reveal that, regardless of the treatment type, there are statistically significant differences in the presence of Candida samples across the examined time points. These results aim to provide valuable insights into the potential of EOs as an alternative therapy in bovine mastitis, specifically targeting yeasts. Such findings could offer new strategies in the mycotic mastitis control and reducing the occurrence of secondary infections following antibiotic treatment.
Knowledge, Attitudes, and Practices of Antibiotic Use among Small-, Medium-, and Large-Scale Fish Farmers of the Stratum II of the Volta Lake of Ghana
Authors: Dandi Samuel O. , Abarike Emmanuel D. , Abobi Seth M. , Doke Dzigbodi A. , Lyche Jan L. , Addo Samuel , Edziyie Regina E. , Obiakara-Amaechi Amii I. , Øystein Evensen , Mutoloki Stephen , Cudjoe Kofitsyo S.
Published: June 2024

Background: Antibiotic residue in food products and the resulting antibiotic-resistant bacteria represent a significant global public health threat. The misuse of antibiotics is a primary contributor to this issue. This study investigated the knowledge, attitudes, and practices (KAP) regarding antibiotic use among cage fish farmers on Ghana’s Volta Lake. Method: We conducted a cross-sectional survey with 91 cage fish farmers across three scales: small, medium, and large. A semi-structured questionnaire complemented by personal observations provided comprehensive data. We used several statistical methods for analysis: Pearson Chi-Square and Spearman correlation tests to examine relationships and trends among variables, logistic regression to analyze variable interactions, and Cronbach’s alpha to check internal consistency. Additionally, Kendall’s coefficient was used to rank challenges, utilizing STATA and SPSS for these calculations. Results: The survey revealed that 58.55% of cage fish farmers earn an average of 10,000 USD annually, with 35.16% having over 16 years of experience. From the survey, all sampled populations admitted to antibiotic applications in their farming operation. Knowledge of antibiotic types was mainly influenced by peers (46.15%), with tetracycline being the most recognized and used. There was a significant reliance on the empirical use of antibiotics, with 52.75% of farmers using them based on personal experience and 40.66% without a prescription. When initial treatments failed, 41.76% of the farmers would change or combine drugs. Older farmers (over 51 years) and those with tertiary education demonstrated significantly better KAP scores regarding antibiotic use. Strong correlations were also found among knowledge, attitudes, and practices in antibiotic usage. Conclusions: The findings indicate a need for improved education on antibiotic use among fish farmers to reduce misuse and enhance awareness of the potential consequences. This study provides foundational data for designing interventions to address these issues in the context of cage fish farming on Volta Lake.
Open DGML: Intrusion Detection Based on Open-Domain Generation Meta-Learning
Authors: Jiang Kaida , Zou Futai , Huang Hongjun , Zheng Liwen , Zhai Haochen
Published: June 2024

Network security is crucial for national infrastructure, but the increasing number of network intrusions poses significant challenges. To address this issue, we propose Open DGML, a framework based on open-domain generalization meta-learning for intrusion detection. Our approach incorporates flow imaging, data augmentation, and open-domain generalization meta-learning algorithms. Experimental results on the ISCX2012, NDSec-1, CICIDS2017, and CICIDS2018 datasets demonstrate the effectiveness of Open DGML. Compared to state-of-the-art models (HAST-IDS, CLAIRE, FC-Net), Open DGML achieves higher accuracy and detection rates. In closed-domain settings, it achieves an average accuracy of 96.52% and a detection rate of 97.04%. In open-domain settings, it achieves an average accuracy of 68.73% and a detection rate of 61.49%. These results highlight the superior performance of Open DGML, particularly in open-domain scenarios, for effective identification of various network attacks.