bluuebunny/crossref_metadata_2025 huggingface dataset:
Migration, invasion, and metastasis are mediated by P-Rex1 in neuroblastoma
Authors: Jacobson Jillian C. , Qiao Jingbo , Cochran Elizabeth D. , McCreery Sullivan , Chung Dai H.
Published: May 2024

Neuroblastoma accounts for approximately 15% of pediatric cancer-related deaths despite intensive multimodal therapy. This is due, in part, to high rates of metastatic disease at diagnosis and disease relapse. A better understanding of tumor biology of aggressive, pro-metastatic phenotypes is necessary to develop novel, more effective therapeutics against neuroblastoma. Phosphatidylinositol 3,4,5-trisphosphate-dependent Rac exchanger 1 (P-Rex1) has been found to stimulate migration, invasion, and metastasis in several adult malignancies. However, its role in neuroblastoma is currently unknown. In the present study, we found that P-Rex1 is upregulated in pro-metastatic murine models of neuroblastoma, as well as human neuroblastoma metastases. Correspondingly, silencing of P-Rex1 was associated with decreased migration and invasion in vitro. This was associated with decreased AKT-mTOR and ERK2 activity, dysregulation of Rac, and diminished secretion of matrix metalloproteinases. Furthermore, increased P-Rex1 expression was associated with inferior relapse-free and overall survival via tissue microarray and Kaplan-Meier survival analysis of a publicly available clinical database. Together, these findings suggest that P-Rex1 may be a novel therapeutic target and potential prognostic factor in neuroblastoma.
Combined treatment for a rare malignant glomus tumor of the esophagus with pulmonary and liver metastases: a case report and review of literature
Authors: Liu Yanan , Mao Jingjing , Shen Dongfeng , Jin Baoli , Wu Xueqin , Song Congcong , Du Wenjing
Published: May 2024

Background

Glomus tumors are typically benign soft tissue tumors that occur at the extremities; malignant and viscerally occurring cases are extremely rare.

Case presentation

We report a 49-year old male patient with a malignant esophageal glomus tumor that was complicated by lung and liver metastases. Genetic test results guided the patient’s individualized treatment. Consequently, treatment with Anlotinib combined with Tislelizumab achieved significant clinical benefits.

Conclusion

Our case report demonstrates that immunotherapy combined with anti-angiogenic therapy in patients with malignant esophageal glomus tumors can achieve significant efficacy and suggests the potential value of next-generation sequencing (NGS) detection in guiding personalized treatments in patients with malignant esophageal glomus tumors.
Synchronous neuroendocine liver metastases in comparison to primary pancreatic neuroendocrine tumors on MRI and SSR-PET/CT
Authors: Horng Annie , Ingenerf Maria , Berger Frank , Steffinger Denise , Rübenthaler Johannes , Zacherl Matthias , Wenter Vera , Ricke Jens , Schmid-Tannwald Christine
Published: May 2024

Background

The study aimed to compare and correlate morphological and functional parameters in pancreatic neuroendocrine tumors (pNET) and their synchronous liver metastases (NELM), while also assessing prognostic imaging parameters.

Methods

Patients with G1/G2 pNET and synchronous NELM underwent pretherapeutic abdominal MRI with DWI and 68Ga-DOTATATE/TOC PET/CT were included. ADC (mean, min), SNR_art and SNT_T2 (SNR on arterial phase and on T2) and SUV (max, mean) for three target NELM and pNET, as well as tumor-free liver and spleen (only in PET/CT) were measured. Morphological parameters including size, location, arterial enhancement, cystic components, T2-hyperintensity, ductal dilatation, pancreatic atrophy, and vessel involvement were noted. Response evaluation used progression-free survival (PFS) with responders (R;PFS>24 months) and non-responders (NR;PFS ≤ 24 months).

Results

33 patients with 33 pNETs and 95 target NELM were included. There were no significant differences in ADC and SUV values between NELM and pNET. 70% of NELM were categorized as hyperenhancing lesions, whereas the pNETs exhibited significantly lower rate (51%) of hyperenhancement (p<0.01) and significant lower SNR_art. NELM were qualitatively and quantitatively (SNR_T2) significantly more hyperintense on T2 compared to pNET (p=0.01 and p<0.001). NELM of R displayed significantly lower ADCmean value in comparison to the ADC mean value of pNET (0.898 versus 1.037x10-3mm²/s,p=0.036). In NR, T2-hyperintensity was notably higher in NELM compared to pNET (p=0.017). The hepatic tumor burden was significantly lower in the R compared to the NR (10% versus 30%).

Conclusions

Arterial hyperenhancement and T2-hyperintensity differ between synchronous NELM and pNET. These findings emphasize the importance of a multifaceted approach to imaging and treatment planning in patients with these tumors as well as in predicting treatment responses.
Computed tomography guided electromagnetic navigation system in percutaneous laser ablation for treating primary lung cancer: a case report
Authors: Liu Xiaodan , Zhang Shusen , Li Honglin , Ren Xuezhu , Xu Xiaolan , Wang Xuejing , Ye Liyun , Cai Zhigang
Published: May 2024

Background

The majority of patients of lung cancer have already lost the chance of surgery at the time of diagnosis. Percutaneous local thermal ablation is a precise minimally invasive technique and a viable alternative to surgical treatment. Compared with radiofrequency ablation and microwave ablation, percutaneous laser ablation for the treatment of lung tumors is less commonly used and reported, especially for primary lung cancer.

Case presentation

A 63-year-old male patient with mixed pulmonary nodules selected computed tomography-guided electromagnetic navigation system for percutaneous biopsy and laser ablation therapy. The puncture point was determined through Computed tomography scanning, along with the placement of the electromagnetic navigation system locators. After rapid on-site evaluation and pathological examination of the puncture tissue specimen, the diagnosis of lung adenocarcinoma was confirmed. A 980-nanometer wavelength semiconductor laser fiber was inserted into the appropriate position guided by the electromagnetic navigation system. Subsequently, a power of 7 watt was applied to ablate the tumor for 30 seconds, then pause for 60 seconds before repeating the procedure. Positron emission tomography-Computed tomography examination was performed 1 month after operation, suggesting complete response of the tumor.

Conclusion

Here, we present a case of percutaneous laser ablation treatment for primary lung cancer guided by computed tomography-electromagnetic navigation system. As a more precise, shorter duration, impedance-independent, safe and effective minimally invasive thermal ablation method, it is expected to gain wider application and become a novel alternative for surgical treatment.
The role of metabolic reprogramming in kidney cancer
Authors: Chen Ziyi , Zhang Xiaohong
Published: May 2024

Metabolic reprogramming is a cellular process in which cells modify their metabolic patterns to meet energy requirements, promote proliferation, and enhance resistance to external stressors. This process also introduces new functionalities to the cells. The ‘Warburg effect’ is a well-studied example of metabolic reprogramming observed during tumorigenesis. Recent studies have shown that kidney cells undergo various forms of metabolic reprogramming following injury. Moreover, metabolic reprogramming plays a crucial role in the progression, prognosis, and treatment of kidney cancer. This review offers a comprehensive examination of renal cancer, metabolic reprogramming, and its implications in kidney cancer. It also discusses recent advancements in the diagnosis and treatment of renal cancer.
Value of catecholamine levels in the differential diagnosis of vasovagal syncope and psychogenic pseudosyncope in children
Authors: Wang Hua , Ma Wandong , Jin Mei , Li Bo , Sun Suzhen
Published: May 2024

Background and purpose

Vasovagal syncope (VVS) and psychogenic pseudosyncope (PPS) can be difficult to distinguish, given their similar clinical presentations. This study was conducted to explore the clinical value of catecholamine levels in the differential diagnosis of VVS and PPS in children.

Methods

This retrospective case-control study was conducted with data from children with VVS and PPS who underwent head-up tilt tests (HUTTs) at the Children's Hospital of Hebei Province between March 2021 and March 2023. The data collected were baseline clinical characteristics, HUTT results, serum catecholamine levels in the supine and upright positions, and 24 h urinary catecholamine concentrations. These variables were compared between the VVS and PPS groups.

Results

From 328 potentially eligible cases, 54 (16.46%) cases of VVS and 24 (7.32%) cases of PPS were included in the analysis. No significant difference in age, sex, body mass index, or syncope frequency was observed between the VVS and PPS groups. The main predisposing factors for syncope were body position changes in the VSS group (83.33%) and emotional changes in the PPS group (41.67%). The episode duration was significantly shorter in the VSS group than in the PPS group (4.01 ± 1.20 vs. 24.06 ± 5.56 min, p < 0.05). The recovery time was also shorter in the VVS group than in the PPS group (1.91 ± 0.85 vs. 8.62 ± 2.55 min, p < 0.05). Relative to patients with PPS, those with VVS had significantly higher serum epinephrine (EP) levels in the upright position [199.35 (102.88, 575.00) vs. 147.40 (103.55, 227.25), p < 0.05] and lower serum epinephrine levels in the supine position [72.70 (42.92, 122.85) vs. 114.50 (66.57, 227.50), p < 0.05].

Conclusions

Serum EP levels have potential value in the differential diagnosis of VVS and PPS.
Cynanchum paniculatum (Bunge) Kitag. ex H.Hara inhibits pancreatic cancer progression by inducing caspase-dependent apoptosis and suppressing TGF-β-mediated epithelial-mesenchymal transition
Authors: Cheng Chien-Shan , Wu Yuan , Jin Jia-Bin , Xu Jia-Yue , Yang Pei-Wen , Zhu Wen-Hua , Zheng Lan , Chen Jing-Xian
Published: May 2024

Background:Cynanchum paniculatum (Bunge) Kitag. ex H.Hara, a member of the Asclepiadaceae family, has a rich history as a traditional Chinese medicinal plant used to treat digestive disorders. However, its potential anti-cancer effects in pancreatic cancer remain largely unexplored.

Aim: This study delves into the intricate anti-pancreatic cancer mechanisms of C. paniculatum (Bunge) Kitag. ex H.Hara aqueous extract (CPAE) by elucidating its role in apoptosis induction and the inhibition of invasion and migration.

Methods: A comprehensive set of methodologies was employed to assess CPAE’s impact, including cell viability analyses using MTT and colony formation assays, flow cytometry for cell cycle distribution and apoptosis assessment, scratch-wound and Matrigel invasion assays for migration and invasion capabilities, and immunoblotting to measure the expression levels of key proteins involved in apoptosis and metastasis. Additionally, a murine xenograft model was established to investigate CPAE’s in vivo anti-cancer potential.

Results: CPAE exhibited time- and dose-dependent suppression of proliferation and colony formation in pancreatic cancer cells. Notably, CPAE induced apoptosis and G2/M phase arrest, effectively activating the caspase-dependent PARP pathway. At non-cytotoxic doses, CPAE significantly curtailed the metastatic abilities of pancreatic cells, effectively suppressing epithelial-mesenchymal transition (EMT) and downregulating the TGF-β1/Smad2/3 pathway. In vivo experiments underscored CPAE’s ability to inhibit tumor proliferation.

Conclusion: This study illuminates the multifaceted anti-proliferative, pro-apoptotic, anti-invasive, and anti-migratory effects of CPAE, both in vitro and in vivo. CPAE emerges as a promising herbal medicine for pancreatic cancer treatment, with its potential mediated through apoptosis induction via the caspase-dependent PARP pathway and MET suppression via the TGF-β1/Smad2/3 signaling pathway at non-cytotoxic doses. These findings advocate for further exploration of CPAE’s therapeutic potential in pancreatic cancer.
Proteomic profiling and biomarker discovery for predicting the response to PD-1 inhibitor immunotherapy in gastric cancer patients
Authors: Sun Jiangang , Li Xiaojing , Wang Qian , Chen Peng , Zhao Longfei , Gao Yongshun
Published: May 2024

Background: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment; however, a significant proportion of gastric cancer (GC) patients do not respond to this therapy. Consequently, there is an urgent need to elucidate the mechanisms underlying resistance to ICIs and identify robust biomarkers capable of predicting the response to ICIs at treatment initiation.

Methods: In this study, we collected GC tissues from 28 patients prior to the administration of anti-programmed death 1 (PD-1) immunotherapy and conducted protein quantification using high-resolution mass spectrometry (MS). Subsequently, we analyzed differences in protein expression, pathways, and the tumor microenvironment (TME) between responders and non-responders. Furthermore, we explored the potential of these differences as predictive indicators. Finally, using machine learning algorithms, we screened for biomarkers and constructed a predictive model.

Results: Our proteomics-based analysis revealed that low activity in the complement and coagulation cascades pathway (CCCP) and a high abundance of activated CD8 T cells are positive signals corresponding to ICIs. By using machine learning, we successfully identified a set of 10 protein biomarkers, and the constructed model demonstrated excellent performance in predicting the response in an independent validation set (N = 14; area under the curve [AUC] = 0.959).

Conclusion: In summary, our proteomic analyses unveiled unique potential biomarkers for predicting the response to PD-1 inhibitor immunotherapy in GC patients, which may provide the impetus for precision immunotherapy.
Risk of dyslipidemia and major adverse cardiac events with tofacitinib versus adalimumab in rheumatoid arthritis: a real-world cohort study from 7580 patients
Authors: Ma Xiao-Na , Shi Mei-Feng , Wang Shiow-Ing , Feng Wei , Chen Shu-Lin , Zhong Xiao-Qin , Liu Qing-Ping , Cheng-Chung Wei James , Lin Chang-Song , Xu Qiang
Published: May 2024

Objective

To compare the effects of tofacitinib and adalimumab on the risk of adverse lipidaemia outcomes in patients with newly diagnosed rheumatoid arthritis (RA).

Methods

Data of adult patients newly diagnosed with RA who were treated with tofacitinib or adalimumab at least twice during a 3-year period from 1 January 2018 to 31 December 2020, were enrolled in the TriNetX US Collaborative Network. Patient demographics, comorbidities, medications, and laboratory data were matched by propensity score at baseline. Outcome measurements include incidental risk of dyslipidemia, major adverse cardiac events (MACE) and all-cause mortality.

Results

A total of 7,580 newly diagnosed patients with RA (1998 receiving tofacitinib, 5,582 receiving adalimumab) were screened. After propensity score matching, the risk of dyslipidaemia outcomes were higher in the tofacitinib cohort, compared with adalimumab cohort (hazard ratio [HR] with 95% confidence interval [CI], 1.250 [1.076–1.453]). However, there is no statistically significant differences between two cohorts on MACE (HR, 0.995 [0.760–1.303]) and all-cause mortality (HR, 1.402 [0.887–2.215]).

Conclusion

Tofacitinib use in patients with RA may increase the risk of dyslipidaemia to some extent compared to adalimumab. However, there is no differences on MACE and all-cause mortality.
Copper homeostasis dysregulation in respiratory diseases: a review of current knowledge
Authors: Song Wei , Yue Yuanyi , Zhang Qiang , Wang Xueqing
Published: May 2024

Cu is an essential micronutrient for various physiological processes in almost all human cell types. Given the critical role of Cu in a wide range of cellular processes, the local concentrations of Cu and the cellular distribution of Cu transporter proteins in the lung are essential for maintaining a steady-state internal environment. Dysfunctional Cu metabolism or regulatory pathways can lead to an imbalance in Cu homeostasis in the lungs, affecting both acute and chronic pathological processes. Recent studies have identified a new form of Cu-dependent cell death called cuproptosis, which has generated renewed interest in the role of Cu homeostasis in diseases. Cuproptosis differs from other known cell death pathways. This occurs through the direct binding of Cu ions to lipoylated components of the tricarboxylic acid cycle during mitochondrial respiration, leading to the aggregation of lipoylated proteins and the subsequent downregulation of Fe-S cluster proteins, which causes toxic stress to the proteins and ultimately leads to cell death. Here, we discuss the impact of dysregulated Cu homeostasis on the pathogenesis of various respiratory diseases, including asthma, chronic obstructive pulmonary disease, idiopathic interstitial fibrosis, and lung cancer. We also discuss the therapeutic potential of targeting Cu. This study highlights the intricate interplay between copper, cellular processes, and respiratory health. Copper, while essential, must be carefully regulated to maintain the delicate balance between necessity and toxicity in living organisms. This review highlights the need to further investigate the precise mechanisms of copper interactions with infections and immune inflammation in the context of respiratory diseases and explore the potential of therapeutic strategies for copper, cuproptosis, and other related effects.
Visible/near-infrared hyperspectral imaging combined with machine learning for identification of ten Dalbergia species
Authors: Chen Zhenan , Xue Xiaoming , Wu Haoqi , Gao Handong , Wang Guangyu , Ni Geyi , Cao Tianyi
Published: May 2024

Introduction

This study addresses the urgent need for non-destructive identification of commercially valuable Dalbergia species, which are threatened by illegal logging. Effective identification methods are crucial for ecological conservation, biodiversity preservation, and the regulation of the timber trade.

Methods

We integrate Visible/Near-Infrared (Vis/NIR) Hyperspectral Imaging (HSI) with advanced machine learning techniques to enhance the precision and efficiency of wood species identification. Our methodology employs various modeling approaches, including Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), and Convolutional Neural Networks (CNN). These models analyze spectral data across Vis (383–982 nm), NIR (982–2386 nm), and full spectral ranges (383 nm to 2386 nm). We also assess the impact of preprocessing techniques such as Standard Normal Variate (SNV), Savitzky-Golay (SG) smoothing, normalization, and Multiplicative Scatter Correction (MSC) on model performance.

Results

With optimal preprocessing, both SVM and CNN models achieve 100% accuracy across NIR and full spectral ranges. The selection of an appropriate wavelength range is critical; utilizing the full spectrum captures a broader array of the wood's chemical and physical properties, significantly enhancing model accuracy and predictive power.

Discussion

These findings underscore the effectiveness of Vis/NIR HSI in wood species identification. They also highlight the importance of precise wavelength selection and preprocessing techniques to maximize both accuracy and cost-efficiency. This research contributes substantially to ecological conservation and the regulation of the timber trade by providing a reliable, non-destructive method for identifying threatened wood species.
Digital natives of the labor market: Generation Z as future leaders and their perspectives on leadership
Authors: Yılmaz Betül , Dinler Kısaçtutan Elvin , Gürün Karatepe Seçil
Published: May 2024

Introduction

Today’s labor market is comprised of different generations and in the near future, the majority of it will consist of Generation Z. In this respect, it is of great importance to know the perspective of Generation Z, which will take its place in leadership positions in organizations, on leadership and what kind of leader they will be. The present study probes to investigate how Generation Z will become a leader and their perspective on leadership. In this regard, the study aims to offer suggestions and guidance to the literature and organizations by providing information on what kind of leaders they will be as well as knowing the characteristics of Generation Z leaders.

Methods

In the study conducted Generation Z, employed in the IT sector, semi-structured interviews were held with 13 participants. While analyzing the data obtained from the interviews, the MAXQDA 2020 program was utilized and the thematic analysis method was applied.

Results

In our findings about how Generation Z will be leaders in the future, two themes were identified, which include intra-organizational communication and working conditions. In the light of findings on the leadership of Generation Z, the sub-themes of being supportive, empathetic, egoless, managing people well and managing with love and respect were reached on the theme of intra-organizational communication. On the other hand, on the theme of working conditions, sub-themes such as providing training, offering payment according to output, preferring flexible working hours, being friendly, assigning appropriate work to the employee, being fun and not giving importance to gender were identified.

Discussion

The results revealed that Generation Z prefers managing their team with a people-oriented approach when they take leadership positions. From their perspective, the leader should understand and value his employees. Leaders who know the expectations of Generation Z will contribute to their organizations. In addition, organizations should improve their leadership skills by providing leadership training for Generation Z, who will be leaders in the future. In this way, they will make investment both in their leaders and their organizations.
Balancing the equation: assessing the impact of management practices on staff and faculty wellbeing in Chinese higher education institutions
Authors: Hu Tingting
Published: May 2024

Introduction

The intersection of work-family dynamics and job contentment has become a pivotal area of investigation within the higher education landscape, drawing scholarly attention, especially in the Chinese context. This study delves into the intricate relationship between work-family culture and job satisfaction, with a particular spotlight on the mediating influence of perceptions of organizational fairness. The impetus behind this emphasis lies in the burgeoning acknowledgment of organizational justice as a pivotal force shaping employee attitudes and conduct within academic establishments.

Method

This research was conducted using two distinct groups. The first group consisted of 1,075 faculty members at Chinese universities, while the second group comprised 972 administrative and technical employees at these institutions.

Results

The mediational analyses provided in this study offer an enhanced comprehension of the intricate relationships under discussion. Significantly, the findings reveal that Work-Family Culture plays a crucial predictive role in influencing perceptions of Organizational Justice among both faculty and administrative staff. More importantly, the study uncovers that Work-Family Culture indirectly affects Job Satisfaction through its impact on Organizational Justice.

Discussion

This insight underscores the importance of harmonious work-family interactions as a determinant of job-related attitudes and satisfaction levels.
The impact of online classes on sleep, physical activity, and cognition functioning among physical education students
Authors: Haddad Monoem , Abbes Zied , Abdel-Salam Abdel-Salam G.
Published: May 2024

Introduction

Online education has become a crucial component of teachers’ professional development, and universities incorporate innovative pedagogical approaches to enhance teachers’ training. These approaches have proven invaluable, particularly during the COVID-19 pandemic. This study investigates the impact of online versus face-to-face learning environments on sleep quality, physical activity, and cognitive functioning among physical education students.

Methods

Utilizing a unique methodological approach that combines wrist actigraphy, the Pittsburgh Sleep Quality Index, and the Cambridge Neuropsychological Test Automated Battery, we provide a comprehensive assessment of these variables. Over 4 weeks, 19 male students participated in alternating online and face-to-face class formats.

Results

Our results reveal no significant differences in sleep quality or cognitive function between learning environments. However, notable findings include significant differences in Paired Associates Learning and weekday step counts in the face-to-face setting.

Discussion

These insights suggest that while online learning environments may not adversely affect sleep or cognitive functions, they could impact certain aspects of physical activity and specific cognitive tasks. These findings contribute to the nuanced understanding of online learning’s implications and can inform the design of educational strategies that promote student well-being.
TanhReLU -based convolutional neural networks for MDD classification
Authors: Zhou Qiao , Sun Sheng , Wang Shuo , Jiang Ping
Published: May 2024

Major Depression Disorder (MDD), a complex mental health disorder, poses significant challenges in accurate diagnosis. In addressing the issue of gradient vanishing in the classification of MDD using current data-driven electroencephalogram (EEG) data, this study introduces a TanhReLU-based Convolutional Neural Network (CNN). By integrating the TanhReLU activation function, which combines the characteristics of the hyperbolic tangent (Tanh) and rectified linear unit (ReLU) activations, the model aims to improve performance in identifying patterns associated with MDD while alleviating the issue of model overfitting and gradient vanishing. Experimental results demonstrate promising outcomes in the task of MDD classification upon the publicly available EEG data, suggesting potential clinical applications.
Geographical patterns of implementing a government subsidy program: implications for health outcomes and nutrient intake in Iran
Authors: Pakravan-Charvadeh Mohammad Reza
Published: May 2024

Introduction

The lack of access to a diverse and nutritious diet has significant health consequences worldwide. Governments have employed various policy mechanisms to ensure access, but their success varies.

Method

In this study, the impact of changes in food assistance policy on food prices and nutrient security in different provinces of Iran, a sanctioned country, was investigated using statistical and econometric models.

Results

Both the old and new policies were broad in scope, providing subsidized food or cash payments to the entire population. However, the implementation of these policies led to an increase in the market price of food items, resulting in a decline in the intake of essential nutrients. Particularly, the policy that shifted food assistance from commodity subsidies to direct cash payments reduced the price sensitivity of consumers. Consequently, the intake of key nutrients such as Vitamin C and Vitamin A, which are often constrained by their high prices, decreased. To improve the diets of marginalized populations, it is more effective to target subsidies towards specific nutrient groups and disadvantaged populations, with a particular focus on food groups that provide essential nutrients like Vitamin A and Vitamin C in rural areas of Iran.

Discussion

More targeted food assistance policies, tailored to the specific context of each province and income level, are more likely to yield positive nutritional outcomes with minimal impact on food prices.
Enhancing neurosurgical navigation operation flow management through personal digital assistant technology: a prospective cohort study
Authors: Quan YaQin , Zhang ManHong , Ji HongMing , Cheng Rui
Published: May 2024

Purpose

This prospective cohort study aims to evaluate the impact of digital health technology especially Personal Digital Assistants (PDA) in neurosurgical procedure management, focusing on surgical safety check accuracy, efficiency, and patient satisfaction.

Methods

The study included 211 neurosurgical cases from January to December 2022. The control group of 106 patients followed traditional verification methods, while the experimental group of 105 patients used PDA. The PDA system facilitated real-time data collection, verification, and transmission. The study compared both groups in terms of check times, accuracy rates, and patient satisfaction, and used multivariate regression to assess the impact of baseline parameters on these outcomes.

Results

The study found that the experimental group using the PDA system reduced the average verification time by approximately 8 min, achieving 100.0% accuracy in preoperative and postoperative checks, significantly better than the control group (91.5% pre- and post-operation). Multivariate regression confirmed a 48.1% reduction in postoperative verification time due to the PDA system (p < 0.001), with the model showing high explanatory power (R2 = 0.911). Other examined factors, including patient age and nurse experience, had no significant effects. Similarly, the PDA’s introduction markedly improved verification accuracy, with no significant impact from other variables (p = 0.010).

Conclusion

The application of the PDA system in neurosurgical operations significantly enhanced the accuracy and efficiency of surgical safety checks, reduced nursing errors, optimized nursing workflows, and improved patient satisfaction. These results provide valuable insights for the application of PDA technology in high-risk medical fields, demonstrating potential of digital health tools in enhancing surgical safety and efficiency.
Long non-coding RNAs: emerging functional players in the pathobiology and progression of myeloid leukemia
Authors: Dutta Sangeeta , Akhade Vijay Suresh , Choudhury Subhendu Roy , Rao Manchanahalli Rangaswamy Satyanarayana
Published: May 2024

Advancements and innovations in transcriptomics and computational biology have revealed long non-coding RNAs (lncRNAs) as some of the major regulators of essential biological processes. Their restricted spatial and temporal expressions as well as ability to interact with nucleic acids (DNA and RNA) and proteins make them key players in chromosome integrity, genomic architecture, and transcriptional and post-transcriptional regulation. Their dysregulation has been associated with numerous diseases and pathological conditions, including cancers. Myeloid leukemia is a malignancy of the hematopoietic system, and its pathobiology has been found to have increasing number of lncRNAs with functional significance. This comprehensive review summarizes a majority of the reported lncRNAs in acute myeloid leukemia (AML) and chronic myeloid leukemia (CML), focusing on the regulatory mechanisms by which they modulate the disease progression and pathogenesis, their potential as diagnostics and prognostic markers, and their feasibility as novel therapeutic targets. We also highlight our recent work on the significance of the lncRNA Hmrhl in CML, which has been found to regulate gene transcription at the chromatin level.
Changes in plasma metabolite concentrations and enzyme activities in aging riding horses
Authors: Asahi Yukari , Arai Toshiro , Tanaka Yoshikazu
Published: May 2024

In older horses, basal metabolic rate decreases, and plasma metabolite and hormone concentrations related to energy metabolism change. The occurrence of age-related diseases, which increases in old animals, may enhance inflammatory reactivity (inflammaging). Finding the appropriate treatment for inflammaging at an early stage may prevent various age-related diseases. Changes in metabolite and hormone concentrations and enzyme activities involved in energy metabolism in the plasma of clinically healthy riding horses of various ages were measured to identify biomarkers of inflammaging (persistent low-grade inflammation that occurs with aging). All horses were clinically healthy, and their body condition scores (BCSs) were 4 or 5 (9-point scale). Plasma triglyceride (TG), total cholesterol (T-Cho), blood urea nitrogen (BUN), insulin concentrations, malondialdehyde (MDA), and serum amyloid A (SAA) concentrations generally increased with age. Adiponectin concentrations, plasma superoxide dismutase (SOD), and leukocyte AMP-activated protein kinase (AMPK) activities decreased, while plasma aspartate aminotransferase (AST), alanine aminotransferase (ALT), and glutathione peroxidase (GPx) remained unchanged as horses aged. Although riding horses that partake in continuous exercise seems to be less likely to develop inflammaging, horses over 17 years of age tend to show proinflammatory signs with disordered lipid metabolism. In riding horses, SAA, in combination with other markers, may be a useful biomarker for inflammaging and dysregulated lipid metabolism in aging horses.
Assessment and Implementation of WOAH Day 1 Competencies (AID-1C): a cyclical methodology for curriculum harmonization with international standards
Authors: Hoet Armando E. , Swisher Samantha , Berrian Amanda M. , Bessler Andrea L. , Grozdic Ivana
Published: May 2024

Introduction

The World Organisation for Animal Health (WOAH) Day 1 Competencies for Graduating Veterinarians provide a standard framework to guide Veterinary Educational Establishments (VEEs) in improving their veterinary public health and population medicine curricula. However, pursuing a curriculum revision to incorporate these standards may be daunting, especially for institutions with limited resources or experience. This manuscript describes a methodology for targeted curriculum revision specifically focused on the WOAH Day 1 Competencies.

Phases of the AID-1 process

The Assessment and Implementation of WOAH Day 1 Competencies (AID-1C) is a six-step, cyclical, collaborative methodology that encompasses a series of tools and processes that help a VEE to evaluate their curriculum, identify and prioritize gaps, and develop and implement an action plan based on the results. The six phases of the AID-1C process include: (1) Assessment of the proficiency of the VEE’s graduates in Day 1 Competencies using a structured Evaluation Tool; (2) A systematic curricular review and evaluation; (3) Identification and prioritization of interventions through a group problem-solving and prioritization exercise called Focus Forward; (4) Design and development of interventions to address identified gaps; (5) Curricular implementation; and (6) Monitoring and evaluation. The AID-1C methodology relies upon active involvement of senior students, recent graduates, faculty, instructional staff, and employers throughout the process.

Conclusion

The AID-1C methodology provides a systematic, participatory, collaborative approach that simplifies the planning and execution of the curricular revision, making a complex process more manageable. This enables VEEs to improve their curricula, while moving toward harmonization with WOAH standards. The result is a curriculum that allows a VEE to train well-rounded and competent veterinarians, with the requisite skills to support the veterinary services in their country.
A Zero-Watermarking Algorithm Based on Scale-Invariant Feature Reconstruction Transform
Authors: Li Fan , Wang Zhong-Xun
Published: May 2024

In order to effectively protect and verify the copyright information of multimedia digital works, this paper proposes a zero-watermarking algorithm based on carrier image feature point descriptors. The constructed feature matrix of this algorithm consists of two parts: the feature descriptor vector calculated from scale-invariant feature reconstruction transform (SIFRT) and the multi-radius local binary pattern (MrLBP) descriptor vector. The algorithm performs a standardization, feature decomposition, and redundancy reduction on the traditional keypoint descriptor matrix, combines it with the texture feature matrix, and achieves the dimensional matching of copyright information. The advantage of this algorithm lies in its non-modification of the original data. Compared to computing global features, the local features computed from a subset of key points reduce the amount of attack interference introduced during copyright verification, thereby reducing the number of erroneous pixel values that are introduced. The algorithm introduces a timestamp mechanism when uploading the generated zero-watermarking image to a third-party copyright center, preventing subsequent tampering. Experimental data analysis demonstrates that the algorithm exhibits good discriminability, security, and robustness.
FOT Technique Applied for Monitoring of COVID-19 Pneumonia Reveals Small Airways Involvement
Authors: Taivans Immanuels , Grima Laura , Jurka Normunds , Zvaigzne Ligita , Gordjušina Valentina , Strazda Gunta
Published: May 2024

The fact that some SARS-CoV-2 pneumonia patients benefit from changing body position, and some from continuous positive airways pressure (CPAP), indicates the functional character of hypoxia. We hypothesize that such effects could be explained by the closure of small airways. To prove the hypothesis, we evaluated the patency of small airways in 30 oxygen-dependent, spontaneously breathing patients with SARS-CoV-2 pneumonia during their hospital stay using the FOT method and then compared the results with data obtained three months later. During the acute period, total resistance (R5) and peripheral resistance (R5-20) rose above the upper limit of normal (ULN) in 28% and 50% of all patients, respectively. Reactance indices X5, AX and Fres exceeded ULN in 55%, 68% and 66% of cases. Significant correlations were observed between PaO2/FiO2, the time spent in the hospital and R5, X5, AX and Fres. After 3 months, 18 patients were re-examined. During the hospital stay, 11 of them had risen above the upper limit of normal (ULN), for both resistance (R5-20) and reactance (X5, AX) values. Three months later, ULN for R5-20 was exceeded in only four individuals, but ULN for X5 and AX was exceeded in five individuals. Lung function examination revealed a combined restrictive/obstructive ventilatory failure and reduced CO transfer factor. We interpret these changes as lung tissue remodeling due to the process of fibrosis. We conclude that during acute period of SARS-CoV-2 pneumonia, dilated pulmonary blood vessels and parenchymal oedema induce functional closure of small airways, which in turn induce atelectasis with pulmonary right-to-left shunting, followed by the resulting hypoxemia.
SF-Transformer: A Mutual Information-Enhanced Transformer Model with Spot-Forward Parity for Forecasting Long-Term Chinese Stock Index Futures Prices
Authors: Mao Weifang , Liu Pin , Huang Jixian
Published: May 2024

The complexity in stock index futures markets, influenced by the intricate interplay of human behavior, is characterized as nonlinearity and dynamism, contributing to significant uncertainty in long-term price forecasting. While machine learning models have demonstrated their efficacy in stock price forecasting, they rely solely on historical price data, which, given the inherent volatility and dynamic nature of financial markets, are insufficient to address the complexity and uncertainty in long-term forecasting due to the limited connection between historical and forecasting prices. This paper introduces a pioneering approach that integrates financial theory with advanced deep learning methods to enhance predictive accuracy and risk management in China’s stock index futures market. The SF-Transformer model, combining spot-forward parity and the Transformer model, is proposed to improve forecasting accuracy across short and long-term horizons. Formulated upon the arbitrage-free futures pricing model, the spot-forward parity model offers variables such as stock index price, risk-free rate, and stock index dividend yield for forecasting. Our insight is that the mutual information generated by these variables has the potential to significantly reduce uncertainty in long-term forecasting. A case study on predicting major stock index futures prices in China demonstrates the superiority of the SF-Transformer model over models based on LSTM, MLP, and the stock index futures arbitrage-free pricing model, covering both short and long-term forecasting up to 28 days. Unlike existing machine learning models, the Transformer processes entire time series concurrently, leveraging its attention mechanism to discern intricate dependencies and capture long-range relationships, thereby offering a holistic understanding of time series data. An enhancement of mutual information is observed after introducing spot-forward parity in the forecasting. The variation of mutual information and ablation study results highlights the significant contributions of spot-forward parity, particularly to the long-term forecasting. Overall, these findings highlight the SF-Transformer model’s efficacy in leveraging spot-forward parity for reducing uncertainty and advancing robust and comprehensive approaches in long-term stock index futures price forecasting.
Generation of Face Privacy-Protected Images Based on the Diffusion Model
Authors: You Xingyi , Zhao Xiaohu , Wang Yue , Sun Weiqing
Published: May 2024

In light of growing concerns about the misuse of personal data resulting from the widespread use of artificial intelligence technology, it is necessary to implement robust privacy-protection methods. However, existing methods for protecting facial privacy suffer from issues such as poor visual quality, distortion and limited reusability. To tackle this challenge, we propose a novel approach called Diffusion Models for Face Privacy Protection (DIFP). Our method utilizes a face generator that is conditionally controlled and reality-guided to produce high-resolution encrypted faces that are photorealistic while preserving the naturalness and recoverability of the original facial information. We employ a two-stage training strategy to generate protected faces with guidance on identity and style, followed by an iterative technique for improving latent variables to enhance realism. Additionally, we introduce diffusion model denoising for identity recovery, which facilitates the removal of encryption and restoration of the original face when required. Experimental results demonstrate the effectiveness of our method in qualitative privacy protection, achieving high success rates in evading face-recognition tools and enabling near-perfect restoration of occluded faces.
Application of C-InGAN Model in Interpretable Feature of Bearing Fault Diagnosis
Authors: Yang Wanyi , Liang Tao , Tan Jianxin , Jing Yanwei , Lv Liangnian
Published: May 2024

Although traditional fault diagnosis methods are proficient in extracting signal features, their diagnostic interpretability remains challenging. Consequently, this article proposes a conditionally interpretable generative adversarial network (C-InGAN) model for the interpretable feature fault diagnosis of bearings. Initially, the vibration signal is denoised and transformed into a frequency domain signal. The model consists of the two primary networks, each employing a convolutional layer and an attention module, generator (G) and discriminator (D), respectively. Latent code was incorporated into G to constrain the generated samples, and a discriminant layer was added to D to identify the interpretable features. During training, the two networks were alternately trained, and the feature mapping relationship of the pre-normalized encoder was learned by maximizing the information from the latent code and the discriminative result. The encoding that represents specific features in the vibration signal was extracted from the random noise. Ultimately, after completing adversarial learning, G is capable of generating a simulated signal of the specified feature, and D can assess the interpretable features in the vibration signal. The effectiveness of the model is validated through three typical experimental cases. This method effectively separates the discrete and continuous feature coding in the signal.
DAFT-Net: Dual Attention and Fast Tongue Contour Extraction Using Enhanced U-Net Architecture
Authors: Wang Xinqiang , Lu Wenhuan , Liu Hengxin , Zhang Wei , Li Qiang
Published: May 2024

In most silent speech research, continuously observing tongue movements is crucial, thus requiring the use of ultrasound to extract tongue contours. Precisely and in real-time extracting ultrasonic tongue contours presents a major challenge. To tackle this challenge, the novel end-to-end lightweight network DAFT-Net is introduced for ultrasonic tongue contour extraction. Integrating the Convolutional Block Attention Module (CBAM) and Attention Gate (AG) module with entropy-based optimization strategies, DAFT-Net establishes a comprehensive attention mechanism with dual functionality. This innovative approach enhances feature representation by replacing traditional skip connection architecture, thus leveraging entropy and information-theoretic measures to ensure efficient and precise feature selection. Additionally, the U-Net’s encoder and decoder layers have been streamlined to reduce computational demands. This process is further supported by information theory, thus guiding the reduction without compromising the network’s ability to capture and utilize critical information. Ablation studies confirm the efficacy of the integrated attention module and its components. The comparative analysis of the NS, TGU, and TIMIT datasets shows that DAFT-Net efficiently extracts relevant features, and it significantly reduces extraction time. These findings demonstrate the practical advantages of applying entropy and information theory principles. This approach improves the performance of medical image segmentation networks, thus paving the way for real-world applications.
Research on Virtual Energy Storage Scheduling Strategy for Air Conditioning Based on Adaptive Thermal Comfort Model
Authors: Lv Ran , Wu Enqi , Lan Li , Fu Chen , Guo Mingxing , Chen Feier , Wang Min , Zou Jie
Published: May 2024

With the rapid development of a social economy, the yearly increase in air conditioning load in the winter and summer seasons may bring serious challenges to the safe and economic operation of the power grid during the peak period of electricity consumption. So, how we reasonably adjust the set temperature of air conditioning so as to cut down the load during peak periods is very important. In this paper, considering the thermal inertia of air-conditioned buildings and the adaptability of human thermal comfort to temperature changes, the air conditioning load is regarded as virtual energy storage, the air conditioning temperature adjustment range for different users is determined based on the adaptive thermal comfort model of different geographic locations and climatic conditions, and a compensation mechanism is set up based on air conditioning users’ level of participation. Then, an optimal scheduling strategy for a microgrid was constructed with the objectives of user satisfaction, carbon emissions, and microgrid operation benefits, as well as regulating the users’ electricity consumption behavior, and the strategy was solved by using a multi-objective JAYA algorithm. Finally, winter and summer are used as case studies to analyze the results, which demonstrate that regulating the virtual energy storage of air conditioning can effectively improve the economy and environmental friendliness of a microgrid operation and reduce the cost of electricity consumption for the users, taking into account the comfort of the users.