bluuebunny/crossref_metadata_2025 huggingface dataset:
Involvement of the Gut Microbiome in the Local and Systemic Immune Response to Pancreatic Ductal Adenocarcinoma
Authors: Halle-Smith James M. , Pearce Hayden , Nicol Samantha , Hall Lewis A. , Powell-Brett Sarah F. , Beggs Andrew D. , Iqbal Tariq , Moss Paul , Roberts Keith J.
Published: February 2024

The systemic and local immunosuppression exhibited by pancreatic ductal adenocarcinoma (PDAC) contributes significantly to its aggressive nature. There is a need for a greater understanding of the mechanisms behind this profound immune evasion, which makes it one of the most challenging malignancies to treat and thus one of the leading causes of cancer death worldwide. The gut microbiome is now thought to be the largest immune organ in the body and has been shown to play an important role in multiple immune-mediated diseases. By summarizing the current literature, this review examines the mechanisms by which the gut microbiome may modulate the immune response to PDAC. Evidence suggests that the gut microbiome can alter immune cell populations both in the peripheral blood and within the tumour itself in PDAC patients. In addition, evidence suggests that the gut microbiome influences the composition of the PDAC tumour microbiome, which exerts a local effect on PDAC tumour immune infiltration. Put together, this promotes the gut microbiome as a promising route for future therapies to improve immune responses in PDAC patients.
Jun Dimerization Protein 2 (JDP2) Increases p53 Transactivation by Decreasing MDM2
Authors: Price Kasey , Yang William H. , Cardoso Leticia , Wang Chiung-Min , Yang Richard H. , Yang Wei-Hsiung
Published: February 2024

The AP-1 protein complex primarily consists of several proteins from the c-Fos, c-Jun, activating transcription factor (ATF), and Jun dimerization protein (JDP) families. JDP2 has been shown to interact with the cAMP response element (CRE) site present in many cis-elements of downstream target genes. JDP2 has also demonstrates important roles in cell-cycle regulation, cancer development and progression, inhibition of adipocyte differentiation, and the regulation of antibacterial immunity and bone homeostasis. JDP2 and ATF3 exhibit significant similarity in their C-terminal domains, sharing 60–65% identities. Previous studies have demonstrated that ATF3 is able to influence both the transcriptional activity and p53 stability via a p53-ATF3 interaction. While some studies have shown that JDP2 suppresses p53 transcriptional activity and in turn, p53 represses JDP2 promoter activity, the direct interaction between JDP2 and p53 and the regulatory role of JDP2 in p53 transactivation have not been explored. In the current study, we provide evidence, for the first time, that JDP2 interacts with p53 and regulates p53 transactivation. First, we demonstrated that JDP2 binds to p53 and the C-terminal domain of JDP2 is crucial for the interaction. Second, in p53-null H1299 cells, JDP2 shows a robust increase of p53 transactivation in the presence of p53 using p53 (14X)RE-Luc. Furthermore, JDP2 and ATF3 together additively enhance p53 transactivation in the presence of p53. While JDP2 can increase p53 transactivation in the presence of WT p53, JDP2 fails to enhance transactivation of hotspot mutant p53. Moreover, in CHX chase experiments, we showed that JDP2 slightly enhances p53 stability. Finally, our findings indicate that JDP2 has the ability to reverse MDM2-induced p53 repression, likely due to decreased levels of MDM2 by JDP2. In summary, our results provide evidence that JDP2 directly interacts with p53 and decreases MDM2 levels to enhance p53 transactivation, suggesting that JDP2 is a novel regulator of p53 and MDM2.
Induction of Multiple Alternative Mitogenic Signaling Pathways Accompanies the Emergence of Drug-Tolerant Cancer Cells
Authors: Celeste Frank V. , Powers Scott
Published: February 2024

Drug resistance can evolve from a subpopulation of cancer cells that initially survive drug treatment and then gradually form a pool of drug-tolerant cells. Several studies have pinpointed the activation of a specific bypass pathway that appears to provide the critical therapeutic target for preventing drug tolerance. Here, we take a systems-biology approach, using proteomics and genomics to examine the development of drug tolerance to EGFR inhibitors in EGFR-mutant lung adenocarcinoma cells and BRAF inhibitors in BRAF-mutant melanoma cells. We found that there are numerous alternative mitogenic pathways that become activated in both cases, including YAP, STAT3, IGFR1, and phospholipase C (PLC)/protein kinase C (PKC) pathways. Our results suggest that an effective therapeutic strategy to prevent drug tolerance will need to take multiple alternative mitogenic pathways into account rather than focusing on one specific pathway.
Overcoming Understaging and Undergrading in Upper Tract Urothelial Carcinoma. Comment on Ghoreifi et al. Modern Kidney-Sparing Management of Upper Tract Urothelial Carcinoma. Cancers 2023, 15, 4495
Authors: Jue Joshua S. , Alameddine Mahmoud , Armenakas Noel A.
Published: February 2024

Kidney-sparing management for upper tract urothelial carcinoma (UTUC) has become more common but is still most limited by inaccurate histopathologic diagnosis [...]
It Looks Like a Spinal Cord Tumor but It Is Not
Authors: Fournel Julien , Hermier Marc , Martin Anna , Gamondès Delphine , Tommasino Emanuele , Broussolle Théo , Morgado Alexis , Baassiri Wassim , Cotton Francois , Berthezène Yves , Bani-Sadr Alexandre
Published: February 2024

Differentiating neoplastic from non-neoplastic spinal cord pathologies may be challenging due to overlapping clinical and radiological features. Spinal cord tumors, which comprise only 2–4% of central nervous system tumors, are rarer than non-tumoral myelopathies of inflammatory, vascular, or infectious origins. The risk of neurological deterioration and the high rate of false negatives or misdiagnoses associated with spinal cord biopsies require a cautious approach. Facing a spinal cord lesion, prioritizing more common non-surgical myelopathies in differential diagnoses is essential. A comprehensive radiological diagnostic approach is mandatory to identify spinal cord tumor mimics. The diagnostic process involves a multi-step approach: detecting lesions primarily using MRI techniques, precise localization of lesions, assessing lesion signal intensity characteristics, and searching for potentially associated anomalies at spinal cord and cerebral MRI. This review aims to delineate the radiological diagnostic approach for spinal cord lesions that may mimic tumors and briefly highlight the primary pathologies behind these lesions.
Continuous Intraoperative Nerve Monitoring of a Non-Recurrent Laryngeal Nerve: Real-Life Data of a High-Volume Thyroid Surgery Center
Authors: Lederer Ann-Kathrin , Staubitz-Vernazza Julia I. , Margies Rabea , Wild Florian , Musholt Thomas J.
Published: February 2024

Thyroid surgery is associated with a risk of injury to the recurrent laryngeal nerve, especially in the presence of anatomical variants such as a non-recurrent laryngeal nerve (NRLN). Injury to the nerve leads to transient or permanent vocal cord palsy (VCP). A novel method to prevent VCP is continuous intraoperative nerve monitoring (cIONM), but less is known about the applicability of this method in patients with NRLN. The aim of this study was to evaluate our own data regarding feasibility and detailed characteristics of cIONM in NRLN patients. We performed a monocentric retrospective cohort analysis including clinical data and intraoperative nerve monitoring data (measured by Inomed Medizintechnik GmbH, Emmendingen, ‘C2’ and ‘C2 Xplore’ device) of all thyroid surgery patients, showing NRLN between 2014 and 2022. Of 1406 patients who underwent thyroid surgery with cIONM between 2014 and 2022, 12 patients (0.9%) showed NRLN intraoperatively. Notably, cIONM was feasible in eight patients (67%). In all cases the onset latency of the right vagus nerve was shorter (<3.0 ms) than usually expected, suggesting that a short latency might be suitable to distinguish NRLN. None of the patients had a post-operative VCP. Overall, cIONM appears to be feasible and safe in NRLN patients and provides helpful information to prevent VCP.
Liquid Biopsy for Glioma Using Cell-Free DNA in Cerebrospinal Fluid
Authors: Otsuji Ryosuke , Fujioka Yutaka , Hata Nobuhiro , Kuga Daisuke , Hatae Ryusuke , Sangatsuda Yuhei , Nakamizo Akira , Mizoguchi Masahiro , Yoshimoto Koji
Published: February 2024

Glioma is one of the most common primary central nervous system (CNS) tumors, and its molecular diagnosis is crucial. However, surgical resection or biopsy is risky when the tumor is located deep in the brain or brainstem. In such cases, a minimally invasive approach to liquid biopsy is beneficial. Cell-free DNA (cfDNA), which directly reflects tumor-specific genetic changes, has attracted attention as a target for liquid biopsy, and blood-based cfDNA monitoring has been demonstrated for other extra-cranial cancers. However, it is still challenging to fully detect CNS tumors derived from cfDNA in the blood, including gliomas, because of the unique structure of the blood–brain barrier. Alternatively, cerebrospinal fluid (CSF) is an ideal source of cfDNA and is expected to contribute significantly to the liquid biopsy of gliomas. Several successful studies have been conducted to detect tumor-specific genetic alterations in cfDNA from CSF using digital PCR and/or next-generation sequencing. This review summarizes the current status of CSF-based cfDNA-targeted liquid biopsy for gliomas. It highlights how the approaches differ from liquid biopsies of other extra-cranial cancers and discusses the current issues and prospects.
Current Insights into Tissue Injury of Giant Cell Arteritis: From Acute Inflammatory Responses towards Inappropriate Tissue Remodeling
Authors: Palamidas Dimitris Anastasios , Chatzis Loukas , Papadaki Maria , Gissis Ilias , Kambas Konstantinos , Andreakos Evangelos , Goules Andreas V. , Tzioufas Athanasios G.
Published: February 2024

Giant cell arteritis (GCA) is an autoimmune disease affecting large vessels in patients over 50 years old. It is an exemplary model of a classic inflammatory disorder with IL-6 playing the leading role. The main comorbidities that may appear acutely or chronically are vascular occlusion leading to blindness and thoracic aorta aneurysm formation, respectively. The tissue inflammatory bulk is expressed as acute or chronic delayed-type hypersensitivity reactions, the latter being apparent by giant cell formation. The activated monocytes/macrophages are associated with pronounced Th1 and Th17 responses. B-cells and neutrophils also participate in the inflammatory lesion. However, the exact order of appearance and mechanistic interactions between cells are hindered by the lack of cellular and molecular information from early disease stages and accurate experimental models. Recently, senescent cells and neutrophil extracellular traps have been described in tissue lesions. These structures can remain in tissues for a prolonged period, potentially favoring inflammatory responses and tissue remodeling. In this review, current advances in GCA pathogenesis are discussed in different inflammatory phases. Through the description of these—often overlapping—phases, cells, molecules, and small lipid mediators with pathogenetic potential are described.
Numerical Modelling and Simulation for Sliding Wear Effect with Microstructural Evolution of Sputtered Titanium Carbide Thin Film on Metallic Materials
Authors: Ogunlana Musibau Olalekan , Muchie Mammo , Swanepoel Jan , Adenuga Olukorede Tijani , Oladijo Oluseyi Philip
Published: February 2024

Titanium carbide materials are introduced into manufacturing industries for the reinforcement and surface protection of base materials due to their substantial ability to withstand severe environments, which include sliding wear, corrosion, and mechanical failures. A thin film of titanium carbide (TiC) is coated onto brass and copper substrates using the radio frequency magnetron sputtering (RFMS) deposition method. The coating process is carried out at constant processing parameters, which include a sputtering power of 200 W, a temperature of 80 °C, a deposition time of 180 min, and an argon (Ar) gas flow rate at 10 standard cubic centimetres per minute (SCCM). The coating, together with the base materials, is modelled and its behaviours are simulated using ANSYS Workbench R19.2 Academic, supported by Mechanical APDL solver for nonlinear finite element analysis (FEA). The deformation, equivalent stress–strain characteristics, and elastic–plastic properties of the coating are determined at applied loads of 60 N and 25 N and coefficients of friction (CoF) of 0.25 and 0.38 for the thin film deposition on brass and copper substrates. The sliding distance and the speed of the alloy steel ball used during the sliding wear operation are found to be 3 mm and 4 mm/s, respectively. The sliding wear modelling and simulation process are, however, designed for the ball-on-flat (BoF) wear technique with a dry sliding approach. Therefore, BoF wear simulations are also performed on titanium carbide–brass (TiC-Br) and titanium carbide–copper (TiC-Cu) conjugates for the evaluation of surface engineering applications such as cutting tools and in automotive, aerospace, thermomechanical, and biomedical fields. The ball used for the FEA wear simulation is made from alloy steel material (AISI 52100) with a radius of 3.175 mm.
Predicting the RUL of Li-Ion Batteries in UAVs Using Machine Learning Techniques
Authors: Andrioaia Dragos , Gaitan Vasile , Culea George , Banu Ioan
Published: February 2024

Over the past decade, Unmanned Aerial Vehicles (UAVs) have begun to be increasingly used due to their untapped potential. Li-ion batteries are the most used to power electrically operated UAVs for their advantages, such as high energy density and the high number of operating cycles. Therefore, it is necessary to estimate the Remaining Useful Life (RUL) and the prediction of the Li-ion batteries’ capacity to prevent the UAVs’ loss of autonomy, which can cause accidents or material losses. In this paper, the authors propose a method of prediction of the RUL for Li-ion batteries using a data-driven approach. To maximize the performance of the process, the performance of three machine learning models, Support Vector Machine for Regression (SVMR), Multiple Linear Regression (MLR), and Random Forest (RF), were compared to estimate the RUL of Li-ion batteries. The method can be implemented within UAVs’ Predictive Maintenance (PdM) systems.
Potentials and Limits of PMN-PT and PIN-PMN-PT Single Crystals for Pyroelectric Energy Harvesting
Authors: Es-Souni Mohammed
Published: February 2024

Waste heat is inherent to industrial activities, IT services (e.g., data centers and microprocessors), human mobility, and many other common processes. The power lost each year in this way has been estimated in the 1000 TWh in the EU which, owing to skyrocketing energy prices and not least the urgent need for decarbonizing the economy, has engendered tremendous research efforts among scientists and engineers to recover/recycle this waste energy. Beyond established thermal engineering solutions for waste heat, advances in multifunctional materials open new paradigms for waste heat harvesting. Two smart material types are of particular focus and interest at present; these are thermoelectric and pyroelectric materials, which can both transform heat to electrical power, though via different effects. The present paper summarizes our research work on a new class of pyroelectric materials, namely <111> oriented (1 − x)(Pb(Mg1/3Nb2/3)O3–xPbTiO3 (PMN-PT) and x-Pb(In1/2 Nb1/2)O3-y-Pb(Mg1/3 Nb2/3)O3-(1 − x − y)-PbTiO3 (PIN-PMN-PT) single crystals that exhibit some of the highest pyroelectric properties ever measured. First, a figure of merit for pyroelectric energy harvesting is derived, followed by a detailed assessment of the properties of the said crystals and how they depend on structure, poling, thickness, and temperature. The properties are further contrasted with those of conventional pyroelectric crystals. It is concluded that the PMN-PT-base single crystals are best suited for harvesting devices with a working temperature range from 40 to 100 °C, which encompasses waste heat generated by data centers and some chemical and industrial processes, affording the highest figure of merit among pyroelectric materials.
Effects of Ultrasonic Treatment on Grain Refinement and Gas Removal in Magnesium Alloys
Authors: Hu Wenyi , Le Qichi , Liao Qiyu , Wang Tong
Published: February 2024

The effects of ultrasonic treatment on grain refinement and hydrogen removal in three kinds of magnesium alloys—Mg-3Ca, Mg-6Zn-1Ca, and AZ80 alloys—were investigated in this study. After ultrasonic treatment, the grains of the magnesium alloys were refined to varying degrees. The degassing effect was characterized by measuring the densities and hydrogen content of ingots. The results indicated that the application of ultrasonic treatment in these magnesium alloys was able to remove hydrogen and obviously refine the microstructure. In this experiment, both the measurement of the density of the ingots and the solid-state hydrogen measurement reflected the degree of degassing. The highest degassing efficiencies were 53.8%, 67.5%, and 34.9% for the Mg-3Ca, Mg-6Zn-1Ca, and AZ80 alloys, respectively. The lowest hydrogen content of the AZ80 alloy reached 8.2 cm3/100 g, and the corresponding tensile strengths were 174 Mpa, 79 Mpa, and 6.2%, which represented increases of 41.5%, 38.6%, and 87.9%, respectively. The cavitation effect and acoustic streaming effect with an appropriate ultrasonic treatment duration resulted in grain refinement, degassing, and the uniform dispersion of second phases. This can significantly improve mechanical properties and provide a basis for industrial production.
Strain-Modulated Electronic Transport Properties in Two-Dimensional Green Phosphorene with Different Edge Morphologies
Authors: Li Shuo , Yang Hai
Published: February 2024

Based on two-dimensional green phosphorene, we designed two molecular electronic devices with zigzag (Type 1) and whisker-like (Type 2) configurations. By combining density functional theory (DFT) and non-equilibrium Green’s function (NEGF), we investigated the electronic properties of Types 1 and 2. Type 1 exhibits an interesting negative differential resistance (NDR), while the current characteristics of Type 2 show linear growth in the current–voltage curve. We studied the electronic transport properties of Type 1 under uniaxial strain modulation and find that strained devices also exhibit a NDR effect, and the peak-to-valley ratio of device could be controlled by varying the strain intensity. These results show that the transport properties of green phosphorene with different edge configuration are different, and the zigzag edge have adjustable negative differential resistance properties.
Analysis of OCT Scanning Parameters in AMD and RVO
Authors: Burchard Claus von der , Roider Johann , Kepp Timo
Published: February 2024

Optical coherence tomography (OCT) is an extensively used imaging tool for disease monitoring in both age-related macular degeneration (AMD) and retinal vein occlusion (RVO). However, there is limited literature on minimum requirements of OCT settings for reliable biomarker detection. This study systematically investigates both the influence of scan size and interscan distance (ISD) on disease activity detection. We analyzed 80 OCT volumes of AMD patients and 12 OCT volumes of RVO patients for the presence of subretinal fluid (SRF), intraretinal fluid (IRF), and pigment epithelium detachment (PED). All volume scans had a scan size of 6 × 6 mm and an ISD of 125 µm. We analyzed both general fluid distribution and how biomarker detection sensitivity decreases when reducing scan size or density. We found that in AMD patients, all fluids were nearly normally distributed, with most occurrences in the foveal center and concentric decrease towards the periphery. When reducing the scan size to 3 × 3 and 2 × 2 mm, disease activity detection was still high (0.98 and 0.96). Increasing ISD only slightly can already compromise biomarker detection sensitivity (0.9 for 250 µm ISD against 125 µm ISD).
Intrinsic Factors Influencing Career Choice of Music Graduates in Fujian, China
Authors: Wang Xiaolu , Poon Chiew Hwa , Cheong Ku Wing
Published: February 2024

Career choice has received significant attention in recent years, with research indicating a strong correlation between individual intrinsic motivations and career decisions. This study investigated the intrinsic factors influencing music graduates’ decisions to pursue a professional career in music in Fujian, China, using the Exploratory Design research method. This research design involved two phases. In phase one, the influencing factors were explored through interviews seeking to obtain qualitative information (N = 18). In phase two, the codes derived from the qualitative study were utilized to build a Likert scale for the quantitative questionnaire (N = 221). The qualitative results revealed that music graduates’ professional career choices were intrinsically influenced by their commitment to the music profession, sense of self-worth derived from successful performing and teaching experiences, self-purpose in sharing and teaching music, interest in music playing and music teaching, confidence in music-playing skills, and working relationship between teacher and student. These variables were confirmed by the quantitative study to have an impact on career choice. Commitment to the music profession was the most influential variable, followed by a sense of self-worth. Confidence in music-playing skills was the least influential variable. These findings deepen our understanding of the variables impacting music majors’ job choices. Understanding these determinants can help educational institutions, policymakers, and career counselors better understand music majors’ particular needs and concerns, leading to more supportive career pathways for aspiring musicians in the region.
A Novel Framework for Forest Above-Ground Biomass Inversion Using Multi-Source Remote Sensing and Deep Learning
Authors: Zhang Junxiang , Zhou Cui , Zhang Gui , Yang Zhigao , Pang Ziheng , Luo Yongfeng
Published: February 2024

The estimation of forest above-ground biomass (AGB) can be significantly improved by leveraging remote sensing (RS) and deep learning (DL) techniques. In this process, it is crucial to obtain appropriate RS features and develop a suitable model. However, traditional methods such as random forest (RF) feature selection often fail to adequately consider the complex relationships within high-dimensional RS feature spaces. Moreover, challenges related to parameter selection and overfitting inherent in DL models may compromise the accuracy of AGB estimation. Therefore, this study proposes a novel framework based on freely available Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical data. Firstly, we designed new indices through the formula analogous with vegetation index calculation to integrate multidimensional spectral and structural information. Then, leveraging the simplicity of computational principles, a pigeon-inspired optimization algorithm (PIO) was introduced into a bi-directional long short-term memory neural network (PIO-BiLSTM), which achieved the set objective function through repeated iteration and validation to obtain the optimal model parameters. Finally, to verify the framework’s effect, we conducted experiments in two different tree species and compared another seven classical optimization algorithms and machine learning models. The results indicated that the new indices significantly improved the inversion accuracy of all models in both categories, and the PIO-BiLSTM model achieved the highest accuracy (Category-1: R2 = 0.8055, MAE = 8.8475 Mg·ha−1, RMSE = 12.2876 Mg·ha−1, relative RMSE = 18.1715%; Category-2: R2 = 0.7956, MAE = 1.7103 Mg·ha−1, RMSE = 2.2887 Mg·ha−1, relative RMSE = 9.3000%). Compared with existing methods, the proposed framework greatly reduced the labor costs in parameter selection, and its potential uncertainty also decreased by up to 9.0%. Furthermore, the proposed method has a strong generalization ability and is independent of tree species, indicating its great potential for future forest AGB inversion in wider regions with diverse forest types.
Simultaneous Analysis of Nicarbazin, Diclazuril, Toltrazuril, and Its Two Metabolites in Chicken Muscle and Eggs by In-Syringe Dispersive Solid-Phase Filter Clean-Up Followed by Liquid Chromatography–Tandem Mass Spectrometry
Authors: An Yuxin , Pan Xiaodong , Cai Zengxuan , Xu Meijia , Jiang Dingguo , Xu Xiaomin
Published: February 2024

Nicarbazin (NICA) and triazine anticoccidial drugs (diclazuril (DIZ) and toltrazuril (TOZ)) are the primary strategy for preventing and treating coccidiosis. To prevent the development of drug resistance and mitigate the potential chronic toxicity to humans resulting from prolonged exposure, a liquid chromatography–tandem mass spectrometry method with high reliability and sensitivity was developed to determine NICA, DIZ, TOZ, and its two metabolites in chicken muscle and eggs. Upon establishing the extraction conditions involving 10 mL of acetonitrile and 10 min of sonication, in-syringe dispersive solid-phase extraction with silica was performed in combination with n-hexane clean-up. The selection of isotope peaks of precursor ions and low-mass range scanning allowed the two transitions for the quantification of all compounds. The limits of detection for DIZ and NICA were both 0.1 μg/kg, and for TOZ and metabolites, they were 0.3 μg/kg; the limits of quantitation were 0.3 and 1 μg/kg, respectively. The linear range was 0.25–50 ng/mL with a correlation coefficient r > 0.999. The average recoveries at three spiking levels in muscle and eggs were 90.1–105.2% and 94.0–103.7% with the relative standard deviations of 3.0–8.1% and 3.1–14.4%, respectively. The precision, accuracy, and stability were evaluated by three quality control samples.
The Added Value of Advanced Echocardiography for the Morpho-Functional and Prognostic Evaluation of the Right Heart in Dilated Cardiomyopathy: Do Not Forget about the Right Atrium
Authors: Hădăreanu Călin-Dinu , Hădăreanu Diana-Ruxandra , Stoiculescu Flavia-Mihaela , Raicea Victor-Cornel , Târtea Georgică-Costinel , Florescu Cristina , Radu Răzvan Ilie , Donoiu Ionuț
Published: February 2024

(1) Introduction and Aims: Right ventricular (RV) remodeling significantly impacts the prognosis of dilated cardiomyopathy (DCM) patients, and right atrial (RA) size and function are still often neglected in DCM patients. Accordingly, our aims were to (i) evaluate right heart subclinical changes and (ii) the prognostic value of RA compared to left atrial (LA) size and function in patients with DCM by advanced echocardiography. (2) Materials and Methods: Sixty-eight patients with DCM (with a mean age of 60 years; 35 men) were evaluated by comprehensive transthoracic echocardiography, compared to 62 age- and sex-matched healthy controls (with a mean age of 61 years; 32 men), and followed up for 12.4 ± 5 months. (3) Results: DCM patients have RV and RA global longitudinal dysfunction by 2DSTE, higher RA minimum volumes and tricuspid annulus areas despite having normal RV volumes, ejection fractions, and RA maximum volumes by 3DE compared to the controls. The RA strain and RV strain are correlated with each other. The RA reservoir strain (with an AUC = 0.769) has an increased value for outcome prediction compared to that of the LA strain. (4) Conclusion: Patients with DCM have RV longitudinal dysfunction and decreased RA function, in the absence of clinical RV involvement or atrial arrhythmias, and the RA strain is associated with an increased risk of hospitalization and cardiac death.
Cognitive Impairment and Brain Atrophy in Patients with Chronic Kidney Disease
Authors: Tsuruya Kazuhiko , Yoshida Hisako
Published: February 2024

In Japan, the aging of the population is rapidly accelerating, with an increase in patients with chronic kidney disease (CKD) and those undergoing dialysis. As a result, the number of individuals with cognitive impairment (CI) is rising, and addressing this issue has become an urgent problem. A notable feature of dementia in CKD patients is the high frequency of vascular dementia, making its prevention through the management of classical risk factors such as hypertension, diabetes mellitus, dyslipidemia, smoking, etc., associated with atherosclerosis and arteriosclerosis. Other effective measures, including the use of renin–angiotensin system inhibitors, addressing anemia, exercise therapy, and lifestyle improvements, have been reported. The incidence and progression of CI may also be influenced by the type of kidney replacement therapy, with reports suggesting that long-duration dialysis, low-temperature hemodialysis, peritoneal dialysis, and kidney transplantation can have a preferable effect on the preservation of cognitive function. In conclusion, patients with CKD are at a higher risk of developing CI, with brain atrophy being a contributing factor. Despite the identification of various preventive measures, the evidence substantiating their efficacy remains limited across all studies. Future expectations lie in large-scale randomized controlled trials.
Identifying Proteins and Amino Acids Associated with Liver Cancer Risk: A Study Utilizing Mendelian Randomization and Bulk RNA Sequencing Analysis
Authors: Ma Chi , Tang Ling , Yao Jiaqi , Tan Guang
Published: February 2024

Background: Primary liver cancer (PLC) ranks third in terms of fatality rate among all malignant tumors worldwide. Proteomics and metabolomics have become widely utilized in identifying causes and diagnostic indicators of PLC. Nevertheless, in studies aiming to identify proteins/metabolites that experienced significant changes before PLC, the potential impact of reverse causation and confounding variables still needs to be fully addressed. Methods: This study thoroughly investigated the causal relationship between 4719 blood proteins, 21 amino acids, and the risk of PLC using the Mendelian randomization (MR) method. In addition, through a comprehensive analysis of the TCGA-LIHC cohort and GEO databases, we evaluated the differentially expressed genes (DEGs) related to serine metabolism in diagnosing and predicting the prognosis of patients with PLC. Results: A total of 63 proteins have been identified as connected to the risk of PLC. Additionally, there has been confirmation of a positive cause–effect between PLC and the concentration of serine. The integration of findings from both MR analyses determined that the protein associated with PLC risk exhibited a significant correlation with serine metabolism. Upon careful analysis of the TCGA-LIHC cohort, it was found that eight DEGs are linked to serine metabolism. After thoroughly validating the GEO database, two DEGs, TDO2 and MICB, emerged as potential biomarkers for diagnosing PLC. Conclusions: Two proteins involved in serine metabolism, MICB and TDO2, are causally linked to the risk of PLC and could potentially be used as diagnostic indicators.
The Impact on Survival of Neoadjuvant Treatment Interruptions in Locally Advanced Rectal Cancer Patients
Authors: Lișcu Horia-Dan , Antone-Iordache Ionut-Lucian , Atasiei Dimitrie-Ionuț , Anghel Ioana Valentina , Ilie Andreea-Teodora , Emamgholivand Taraneh , Ionescu Andreea-Iuliana , Șandru Florica , Pavel Christopher , Ultimescu Flavia
Published: February 2024

The standard oncologic treatment of locally advanced rectal cancer is long-course radio-chemotherapy followed by surgery and adjuvant chemotherapy. This can result in a lengthy total treatment duration, sometimes up to one year from the diagnosis. Interruptions to neoadjuvant treatment can occur for a variety of reasons, forced or unforced. The main purpose of this study is to analyze the survival data of locally advanced rectal cancer patients who received neoadjuvant treatment and to find a cut-off point showing exactly how many days of interruption of neoadjuvant treatment the risk of death or disease relapse increases. We conducted a retrospective study on 299 patients with locally advanced rectal cancer using survival analysis (Kaplan–Meier curve and Cox regression) to determine survival probabilities for overall survival, local control, and disease-free survival. Patients with 0 to 3 days of neoadjuvant therapy interruption had a higher overall survival probability compared to patients with 4 or more days (90.2% compared to 57.9%, p-value < 0.001), hazard ratio 5.89 (p < 0.001). Local control and disease-free survival had a higher probability in patients with 0–2 days of interruption compared to people with 3 or more days (94% vs. 75.4%, and 82.2% vs. 50.5%, respectively, both p-values < 0.001). Patients with tumoral or nodal downstaging experienced fewer days of interruption than patients with no downstage. These findings reinforce the need for radiation oncologists to be well-organized when starting neoadjuvant treatment for rectal cancer, in order to anticipate and prevent potential treatment interruptions and achieve the best therapeutic results.
Sexual Functioning and Sexual Health in Female Patients following Stroke: A Scoping Review with Implications for Rehabilitation
Authors: Latella Desirèe , Grimaldi Alessandro , Calabrò Rocco Salvatore
Published: February 2024

The impact of stroke on the sexual functioning of female survivors can arise from direct neurological effects or be triggered indirectly through various psychophysiological processes. Although an increasing number of publications exist, the topic of sexuality remains seldom discussed in the stroke literature, even though patients have expressed a need for sexual rehabilitation services. A literature review on sexual functioning in post-stroke females examining existing rehabilitation programs addressing patients’ sexuality and exploring the perspectives of nurses and caregivers on sexual issues constitutes a novel approach. Therefore, we conducted a scoping review to better investigate this hot topic. Studies were identified by searching Scopus, PubMed, Web of Science, Cochrane Library, PsychINFO, and Embase databases. Current data indicates substantial connections between stroke and female sexual dysfunction (SD), including factors like desire/libido, sexual satisfaction, and sexual intercourse. Some intervention programs have been created to provide specific guidance to healthcare professionals in addressing patients’ requirements for sexual recovery, although their adequacy remains uncertain. However, to date, there are neither specific rehabilitation programs for post-stroke female SD nor healthcare personnel trained to deal with post-stroke sexual issues adequately and efficiently. The incorporation of sexual rehabilitation into the overall rehabilitation process for stroke patients is crucial, ideally within an interdisciplinary framework. Despite being a fundamental aspect of post-stroke women’s lives, sexuality remains taboo.
Using Super-Resolution for Enhancing Visual Perception and Segmentation Performance in Veterinary Cytology
Authors: Caputa Jakub , Wielgosz Maciej , Łukasik Daria , Russek Paweł , Grzeszczyk Jakub , Karwatowski Michał , Mazurek Szymon , Frączek Rafał , Śmiech Anna , Jamro Ernest , Koryciak Sebastian , Dąbrowska-Boruch Agnieszka , Pietroń Marcin , Wiatr Kazimierz
Published: February 2024

The primary objective of this research was to enhance the quality of semantic segmentation in cytology images by incorporating super-resolution (SR) architectures. An additional contribution was the development of a novel dataset aimed at improving imaging quality in the presence of inaccurate focus. Our experimental results demonstrate that the integration of SR techniques into the segmentation pipeline can lead to a significant improvement of up to 25% in the mean average precision (mAP) metric. These findings suggest that leveraging SR architectures holds great promise for advancing the state-of-the-art in cytology image analysis.
A Multi-Objective Learning Whale Optimization Algorithm for Open Vehicle Routing Problem with Two-Dimensional Loading Constraints
Authors: Zhang Yutong , Li Hongwei , Wang Zhaotu , Wang Huajian
Published: February 2024

With the rapid development of the sharing economy, the distribution in third-party logistics (3PL) can be modeled as a variant of the open vehicle routing problem (OVRP). However, very few papers have studied 3PL with loading constraints. In this work, a two-dimensional loading open vehicle routing problem with time windows (2L-OVRPTW) is described, and a multi-objective learning whale optimization algorithm (MLWOA) is proposed to solve it. As the 2L-OVRPTW is integrated by the routing subproblem and the loading subproblem, the MLWOA is designed as a two-phase algorithm to deal with these subproblems. In the routing phase, the exploration mechanisms and learning strategy in the MLWOA are used to search the population globally. Then, a local search method based on four neighborhood operations is designed for the exploitation of the non-dominant solutions. In the loading phase, in order to avoid discarding non-dominant solutions due to loading failure, a skyline-based loading strategy with a scoring method is designed to reasonably adjust the loading scheme. From the simulation analysis of different instances, it can be seen that the MLWOA algorithm has an absolute advantage in comparison with the standard WOA and other heuristic algorithms, regardless of the running results at the scale of 25, 50, or 100 datasets.
Effects of Contaminations on Electric Arc Behavior and Occurrence of Defects in Wire Arc Additive Manufacturing of 316L-Si Stainless Steel
Authors: Souto Joyce Ingrid Venceslau de , Lima Jefferson Segundo de , Castro Walman Benício de , Santana Renato Alexandre Costa de , Silva Antonio Almeida , Abreu Santos Tiago Felipe de , Tavares João Manuel R. S.
Published: February 2024

Additive Manufacturing is a manufacturing process that consists of obtaining a three-dimensional object from the deposition of material layer by layer, unlike conventional subtractive manufacturing methods. Wire Arc Additive Manufacturing stands out for its high productivity among the Additive Manufacturing technologies for manufacturing metal parts. On the other hand, the excessive heat input promotes increased residual stress levels and the occurrence of defects, such as pores, voids, a lack of fusion, and delamination. These defects result in abnormalities during the process, such as disturbances in electrical responses. Therefore, process monitoring and the detection of defects and failures in manufactured items are of fundamental importance to ensure product quality and certify the high productivity characteristic of this process. Thus, this work aimed to characterize the effects of different contaminations on the electric arc behavior of the Wire Arc Additive Manufacturing process and the occurrence of microscopic defects in thin walls manufactured by this process. To investigate the presence of defects in the metal preforms, experimental conditions were used to promote the appearance of defects, such as the insertion of contaminants. To accomplish the electric arc behavior analysis, voltage and current temporal data were represented through histograms and cyclograms, and the arc stability was assessed based on the Vilarinho index for a short circuit. Effectively, the introduction of contaminants caused electric arc disturbances that led to the appearance of manufacturing defects, such as inclusions and porosities, observed through metallographic characterization. The results confirm that the introduction of contaminations could be identified early in the Wire Arc Additive Manufacturing process through electric arc data analysis.
Mechanical Properties and In Vitro Corrosion Behaviors of Biodegradable Magnesium Alloy Suture Anchors
Authors: Mao Lin , Dai Zhiwei , Cai Xue , Hu Zhongxin , Zhang Jian , Song Chengli
Published: February 2024

Biodegradable suture anchors based on Mg-Nd-Zn-Zr alloy were developed for ligament-to-bone fixation in rotator cuff surgeries. The Mg alloy anchors were designed with structural features of narrow tooth and wide tooth, and simulated through finite element analysis (FEA). Meanwhile, the corrosion behaviors of the Mg alloy anchors were studied by immersion test and the mechanical properties were investigated by measuring the maximum torque and pull-out force. The simulation result showed that the wide-tooth anchor exhibited more a uniform stress distribution and lower shear stress in the torsion process, suggesting a satisfactory torsional resistance of this structure. Meanwhile, the wide-tooth anchor exhibited a lower Von-Mises stress after applying the same pull-out force in the simulation, indicating a higher resistance to pull-out failure of the anchor. The result of the immersion test indicated that the wide-tooth anchor exhibited a slightly slower corrosion rate in Hank’s solution after 14-day immersion, which was beneficial to enhance the structural and mechanical stability of the biodegradable suture anchor. Furthermore, the results of the mechanical properties test demonstrated that the wide-tooth anchor showed superior performance with higher maximum torques and axial pull-out forces before and after corrosion. More importantly, the axial pull-out force and maximum torque for the wide-tooth anchor decreased by 5.86% and 8.64% after corrosion, which were significantly less than those for the narrow-tooth anchor. Therefore, the wide-tooth suture anchor with lower corrosion rate, higher mechanical properties and structural stability is a promising candidate for ligament-bone fixation in the repair of rotator cuff injuries.
Advancing Personalized Medicine by Analytical Means: Selection of Three Metabolites That Allows Discrimination between Glaucoma, Diabetes, and Controls
Authors: Bernal-Casas David , Serrano-Marín Joan , Sánchez-Navés Juan , Oller Josep M. , Franco Rafael
Published: February 2024

This paper aimed at devising an intelligence-based method to select compounds that can distinguish between open-angle glaucoma patients, type 2 diabetes patients, and healthy controls. Taking the concentration of 188 compounds measured in the aqueous humour (AH) of patients and controls, linear discriminant analysis (LDA) was used to identify the right combination of compounds that could lead to accurate diagnosis. All possibilities, using the leave-one-out approach, were considered through ad hoc programming and in silico massive data production and statistical analysis. Our proof of concept led to the selection of four molecules: acetyl-ornithine (Ac-Orn), C3 acyl-carnitine (C3), diacyl C42:6 phosphatidylcholine (PC aa C42:6), and C3-DC (C4-OH) acyl-carnitine (C3-DC (C4-OH)) that, taken in combination, would lead to a 95% discriminative success. 100% success was obtained with a non-linear combination of the concentration of three of these four compounds. By discarding younger controls to adjust by age, results were similar although one control was misclassified as a diabetes patient. Methods based on the consideration of individual clinical chemical parameters have limitations in the ability to make a reliable diagnosis, stratify patients, and assess disease progression. Leveraging human AH metabolomic data, we developed a procedure that selects a minimal number of metabolites (3–5) and designs algorithms that maximize the overall accuracy evaluating both positive predictive (PPV) and negative predictive (NPV) values. Our approach of simultaneously considering the levels of a few metabolites can be extended to any other body fluid and has potential to advance precision medicine. Artificial intelligence is expected to use algorithms that use the concentration of three to five molecules to correctly diagnose diseases, also allowing stratification of patients and evaluation of disease progression. In addition, this significant advance shifts focus from a single-molecule biomarker approach to that of an appropriate combination of metabolites.
Recent Progress in Droplet Structure Machining for Advanced Optics
Authors: Guo Jin-Kun , Sandaruwan W.D.N. , Li Jinwei , Ling Jinzhong , Yuan Ying , Liu Xin , Li Qiang , Wang Xiaorui
Published: February 2024

The development of optical and photonic applications using soft-matter droplets holds great scientific and application importance. The machining of droplet structures is expected to drive breakthroughs in advancing frontier applications. This review highlights recent advancements in micro–nanofabrication techniques for soft-matter droplets, encompassing microfluidics, laser injection, and microfluidic 3D printing. The principles, advantages, and weaknesses of these technologies are thoroughly discussed. The review introduces the utilization of a phase separation strategy in microfluidics to assemble complex emulsion droplets and control droplet geometries by adjusting interfacial tension. Additionally, laser injection can take full advantage of the self-assembly properties of soft matter to control the spontaneous organization of internal substructures within droplets, thus providing the possibility of high-precision customized assembly of droplets. Microfluidic 3D printing demonstrates a 3D printing-based method for machining droplet structures. Its programmable nature holds promise for developing device-level applications utilizing droplet arrays. Finally, the review presents novel applications of soft-matter droplets in optics and photonics. The integration of processing concepts from microfluidics, laser micro–nano-machining, and 3D printing into droplet processing, combined with the self-assembly properties of soft materials, may offer novel opportunities for processing and application development.
Numerical Simulations of Combined Dielectrophoresis and Alternating Current Electrothermal Flow for High-Efficient Separation of (Bio)Microparticles
Authors: Jiang Hao , Li Yalin , Du Fei , Nie Zhaoguang , Wei Gang , Wang Yan , Liu Xiaomin
Published: February 2024

High-efficient separation of (bio)microparticles has important applications in chemical analysis, environmental monitoring, drug screening, and disease diagnosis and treatment. As a label-free and high-precision separation scheme, dielectrophoresis (DEP) has become a research hotspot in microparticle separation, especially for biological cells. When processing cells with DEP, relatively high electric conductivities of suspending media are sometimes required to maintain the biological activities of the biosample, which results in high temperature rises within the system caused by Joule heating. The induced temperature gradient generates a localized alternating current electrothermal (ACET) flow disturbance, which seriously impacts the DEP manipulation of cells. Based on this, we propose a novel design of the (bio)microparticle separator by combining DEP with ACET flow to intensify the separation process. A coupling model that incorporates electric, fluid flow, and temperature fields as well as particle tracking is established to predict (bio)microparticle trajectories within the separator. Numerical simulations reveal that both ACET flow and DEP motion act in the same plane but in different directions to achieve high-precision separation between particles. This work provides new design ideas for solving the very tricky Joule heating interference in the DEP separation process, which paves the way for further improving the throughput of the DEP-based (bio)microparticle separation system.