bluuebunny/crossref_metadata_2025 huggingface dataset:
Adjuvant FOLFIRINOX in Patients with Resectable Pancreatic Cancer Is Effective but Rarely Feasible in Real Life: Is Neoadjuvant FOLFIRINOX a Better Option?
Authors: Maman Yossi , Goykhman Yaacov , Yakir Oz , Barenboim Alex , Geva Ravit , Peles-Avraham Sharon , Wolf Ido , Klausner Joseph M. , Lahat Guy , Lubezky Nir
Published: June 2023

Background: The recommended treatment for resectable pancreatic cancer (PC) is resection followed by adjuvant FOLFIRINOX. We assessed the proportion of patients that managed to complete the 12 courses of adjuvant FOLFIRINOX and compared their outcome with that of patients with borderline resectable pancreatic cancer (BRPC) who underwent resection after neoadjuvant FOLFIRINOX. Methods: A retrospective analysis was performed on a prospectively maintained database of all PC patients who underwent resection with (2/2015–12/2021) or without (1/2018–12/2021) neoadjuvant therapy. Results: A total of 100 patients underwent upfront resection, and 51 patients with BRPC received neoadjuvant treatment. Only 46 resection patients started adjuvant FOLFIRINOX, and only 23 completed 12 courses. The main reasons for not starting/completing adjuvant therapy were poor tolerance and rapid recurrence. Significantly more patients in the neoadjuvant group received at least six FOLFIRINOX courses (80.4% vs. 31%, p < 0.001). Patients who completed at least 6 courses, either pre- or postoperatively, had better overall survival (p = 0.025) than those who did not. In spite of having more advanced disease, the neoadjuvant group had comparable overall survival (p = 0.062) regardless of the number of treatment courses. Conclusion: Only a minority of patients (23%) undergoing upfront pancreatic resection completed the planned 12 courses of FOLFIRINOX. Patients who received neoadjuvant treatment were significantly more likely to receive at least six treatment courses. Patients receiving at least six courses had better overall survival than those who received fewer than six courses, regardless of the timing of treatment relative to surgery. Potential ways to increase chemotherapy adherence, such as administering treatment before surgery, should be considered.
Metronomic Photodynamic Therapy with Conjugated Polymer Nanoparticles in Glioblastoma Tumor Microenvironment
Authors: Caverzán Matías Daniel , Oliveda Paula Martina , Beaugé Lucía , Palacios Rodrigo Emiliano , Chesta Carlos Alberto , Ibarra Luis Exequiel
Published: June 2023

Alternative therapies such as photodynamic therapy (PDT) that combine light, oxygen and photosensitizers (PSs) have been proposed for glioblastoma (GBM) management to overcome conventional treatment issues. An important disadvantage of PDT using a high light irradiance (fluence rate) (cPDT) is the abrupt oxygen consumption that leads to resistance to the treatment. PDT metronomic regimens (mPDT) involving administering light at a low irradiation intensity over a relatively long period of time could be an alternative to circumvent the limitations of conventional PDT protocols. The main objective of the present work was to compare the effectiveness of PDT with an advanced PS based on conjugated polymer nanoparticles (CPN) developed by our group in two irradiation modalities: cPDT and mPDT. The in vitro evaluation was carried out based on cell viability, the impact on the macrophage population of the tumor microenvironment in co-culture conditions and the modulation of HIF-1α as an indirect indicator of oxygen consumption. mPDT regimens with CPNs resulted in more effective cell death, a lower activation of molecular pathways of therapeutic resistance and macrophage polarization towards an antitumoral phenotype. Additionally, mPDT was tested in a GBM heterotopic mouse model, confirming its good performance with promising tumor growth inhibition and apoptotic cell death induction.
Modulation of NRF2/KEAP1 Signaling in Preeclampsia
Authors: Tossetta Giovanni , Fantone Sonia , Piani Federica , Crescimanno Caterina , Ciavattini Andrea , Giannubilo Stefano Raffaele , Marzioni Daniela
Published: June 2023

Placentation is a key and tightly regulated process that ensures the normal development of the placenta and fetal growth. Preeclampsia (PE) is a hypertensive pregnancy-related disorder involving about 5–8% of all pregnancies and clinically characterized by de novo maternal hypertension and proteinuria. In addition, PE pregnancies are also characterized by increased oxidative stress and inflammation. The NRF2/KEAP1 signaling pathway plays an important role in protecting cells against oxidative damage due to increased reactive oxygen species (ROS) levels. ROS activate NRF2, allowing its binding to the antioxidant response element (ARE) region present in the promoter of several antioxidant genes such as heme oxygenase, catalase, glutathione peroxidase and superoxide dismutase that neutralize ROS, protecting cells against oxidative stress damages. In this review, we analyze the current literature regarding the role of the NRF2/KEAP1 pathway in preeclamptic pregnancies, discussing the main cellular modulators of this pathway. Moreover, we also discuss the main natural and synthetic compounds that can regulate this pathway in in vivo and in vitro models.
SNARE Protein Snc1 Is Essential for Vesicle Trafficking, Membrane Fusion and Protein Secretion in Fungi
Authors: Adnan Muhammad , Islam Waqar , Waheed Abdul , Hussain Quaid , Shen Ling , Wang Juan , Liu Gang
Published: June 2023

Fungi are an important group of microorganisms that play crucial roles in a variety of ecological and biotechnological processes. Fungi depend on intracellular protein trafficking, which involves moving proteins from their site of synthesis to the final destination within or outside the cell. The soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNARE) proteins are vital components of vesicle trafficking and membrane fusion, ultimately leading to the release of cargos to the target destination. The v-SNARE (vesicle-associated SNARE) Snc1 is responsible for anterograde and retrograde vesicle trafficking between the plasma membrane (PM) and Golgi. It allows for the fusion of exocytic vesicles to the PM and the subsequent recycling of Golgi-localized proteins back to the Golgi via three distinct and parallel recycling pathways. This recycling process requires several components, including a phospholipid flippase (Drs2-Cdc50), an F-box protein (Rcy1), a sorting nexin (Snx4-Atg20), a retromer submit, and the COPI coat complex. Snc1 interacts with exocytic SNAREs (Sso1/2, Sec9) and the exocytic complex to complete the process of exocytosis. It also interacts with endocytic SNAREs (Tlg1 and Tlg2) during endocytic trafficking. Snc1 has been extensively investigated in fungi and has been found to play crucial roles in various aspects of intracellular protein trafficking. When Snc1 is overexpressed alone or in combination with some key secretory components, it results in enhanced protein production. This article will cover the role of Snc1 in the anterograde and retrograde trafficking of fungi and its interactions with other proteins for efficient cellular transportation.
Multi-Drug Cocktail Therapy Improves Survival and Neurological Function after Asphyxial Cardiac Arrest in Rodents
Authors: Choudhary Rishabh C. , Shoaib Muhammad , Hayashida Kei , Yin Tai , Miyara Santiago J. , d’Abramo Cristina , Heuser William G. , Shinozaki Koichiro , Kim Nancy , Takegawa Ryosuke , Nishikimi Mitsuaki , Li Timmy , Owens Casey , Molmenti Ernesto P. , He Mingzhu , Vanpatten Sonya , Al-Abed Yousef , Kim Junhwan , Becker Lance B.
Published: June 2023

Background: Cardiac arrest (CA) can lead to neuronal degeneration and death through various pathways, including oxidative, inflammatory, and metabolic stress. However, current neuroprotective drug therapies will typically target only one of these pathways, and most single drug attempts to correct the multiple dysregulated metabolic pathways elicited following cardiac arrest have failed to demonstrate clear benefit. Many scientists have opined on the need for novel, multidimensional approaches to the multiple metabolic disturbances after cardiac arrest. In the current study, we have developed a therapeutic cocktail that includes ten drugs capable of targeting multiple pathways of ischemia–reperfusion injury after CA. We then evaluated its effectiveness in improving neurologically favorable survival through a randomized, blind, and placebo-controlled study in rats subjected to 12 min of asphyxial CA, a severe injury model. Results: 14 rats were given the cocktail and 14 received the vehicle after resuscitation. At 72 h post-resuscitation, the survival rate was 78.6% among cocktail-treated rats, which was significantly higher than the 28.6% survival rate among vehicle-treated rats (log-rank test; p = 0.006). Moreover, in cocktail-treated rats, neurological deficit scores were also improved. These survival and neurological function data suggest that our multi-drug cocktail may be a potential post-CA therapy that deserves clinical translation. Conclusions: Our findings demonstrate that, with its ability to target multiple damaging pathways, a multi-drug therapeutic cocktail offers promise both as a conceptual advance and as a specific multi-drug formulation capable of combatting neuronal degeneration and death following cardiac arrest. Clinical implementation of this therapy may improve neurologically favorable survival rates and neurological deficits in patients suffering from cardiac arrest.
Comparative Study of Physicochemical Properties of Finely Dispersed Powders and Ceramics in the Systems CeO2–Sm2O3 and CeO2–Nd2O3 as Electrolyte Materials for Medium Temperature Fuel Cells
Authors: Kalinina Marina V. , Dyuskina Daria A. , Mjakin Sergey V. , Kruchinina Irina Yu. , Shilova Olga A.
Published: June 2023

Finely dispersed (CeO2)1−x(Sm2O3)x (x = 0.05, 0.10, 0.20) and (CeO2)1−x(Nd2O3)x (x = 0.05, 0.10, 0.15, 0.20, 0.25) powders were synthesized via liquid-phase techniques based on the co-precipitation of hydroxides and were used to obtain ceramic materials comprising fluorite-like solid solutions with CSR in the range 69–88 nm (upon annealing at 1300 °C) and open porosity in the range 0.6–6.2%. The physicochemical properties of the synthesized materials were comparatively characterized. In general, the prepared materials were found to possess a mixed type of electrical conductivity, but in the medium-temperature range, the ionic component was predominant (ion transfer numbers ti = 0.93–0.73 at 300–700 °C). The highest ionic conductivity was observed for CeO2-based samples containing 20 mol.% Sm2O3 (σ700°C = 3.3 × 10−2 S/cm) and 15 mol.% Nd2O3 (σ700°C = 0.48 × 10−2 S/cm) was in the temperature range 500–700 °C. The physicochemical properties (density, open porosity, type and mechanism of electrical conductivity) of the obtained ceramic materials make them promising as solid oxide electrolytes for medium temperature fuel cells.
Development of Sensitive Electrochemical Sensor Based on Chitosan/MWCNTs-AuPtPd Nanocomposites for Detection of Bisphenol A
Authors: Han En , Pan Yingying , Li Lei , Liu Yuan , Gu Yuan , Cai Jianrong
Published: June 2023

An electrochemical sensor based on AuPtPd trimetallic nanoparticles functionalized multi-walled carbon nanotubes coupled with chitosan modified glassy carbon electrode (GCE/CS/MWCNTs-AuPtPd) was proposed for the rapid detection of bisphenol A (BPA). AuPtPd trimetallic nanoparticles were first assembled on MWCNTs to obtain MWCNTs-AuPtPd nanocomposite. Then, the MWCNTs-AuPtPd was further dispersed on the chitosan-modified electrode surface to fabricate the GCE/CS/MWCNTs-AuPtPd sensor. Due to the superior catalytic properties of MWCNTs-AuPtPd and the good film formation of chitosan, the constructed sensor displayed good performances for BPA detection. The structural morphology of CS/MWCNTs-AuPtPd was characterized in many ways, such as SEM, TEM and UV-vis. The designed sensor showed a linear relationship in concentration range from 0.05 to 100 µM for BPA detecting, and the detection limit was 1.4 nM. The GCE/CS/MWCNTs-AuPtPd was further used to realize the detection of BPA in food samples, and the recovery was between 94.4% and 103.6%. Those results reflected that the electrochemical sensor designed by CS/MWCNTs-AuPtPd nanocomposites was available, which could be used for the monitoring of food safety.
Metabolic Deregulation in Pulmonary Hypertension
Authors: Mathew Rajamma , Iacobas Sanda , Huang Jing , Iacobas Dumitru Andrei
Published: June 2023

The high morbidity and mortality rate of pulmonary arterial hypertension (PAH) is partially explained by metabolic deregulation. The present study complements our previous publication in “Genes” by identifying significant increases of the glucose transporter solute carrier family 2 (Slc2a1), beta nerve growth factor (Ngf), and nuclear factor erythroid-derived 2-like 2 (Nfe2l2) in three standard PAH rat models. PAH was induced by subjecting the animals to hypoxia (HO), or by injecting with monocrotaline in either normal (CM) or hypoxic (HM) atmospheric conditions. The Western blot and double immunofluorescent experiments were complemented with novel analyses of previously published transcriptomic datasets of the animal lungs from the perspective of the Genomic Fabric Paradigm. We found substantial remodeling of the citrate cycle, pyruvate metabolism, glycolysis/gluconeogenesis, and fructose and mannose pathways. According to the transcriptomic distance, glycolysis/gluconeogenesis was the most affected functional pathway in all three PAH models. PAH decoupled the coordinated expression of many metabolic genes, and replaced phosphomannomutase 2 (Pmm2) with phosphomannomutase 1 (Pmm1) in the center of the fructose and mannose metabolism. We also found significant regulation of key genes involved in PAH channelopathies. In conclusion, our data show that metabolic dysregulation is a major PAH pathogenic factor.
Magnolia kobus Extract Suppresses Porphyromonas gingivalis LPS-Induced Proinflammatory Cytokine and MMP Expression in HGF-1 Cells and Regulates Osteoclastogenesis in RANKL-Stimulated RAW264.7 Cells
Authors: Lee Hae Jin , Lee So Jung , Lee Sung Kwon , Choi Bong Keun , Lee Dong Ryung , Park Ju-Hyoung , Oh Joa Sub
Published: June 2023

Clinical prevention is of utmost importance for the management of periodontal diseases. Periodontal disease starts with an inflammatory response in the gingival tissue, and results in alveolar bone destruction and subsequent tooth loss. This study aimed to confirm the anti-periodontitis effects of MKE. To confirm this, we studied its mechanism of action using qPCR and WB in LPS-treated HGF-1 cells and RANKL-induced osteoclasts. We found that MKE suppressed proinflammatory cytokine protein expression by inhibiting the TLR4/NF-κB pathway in LPS-PG-induced HGF-1 cells and blocking ECM degradation by regulating the expression of TIMPs and MMPs. We also confirmed that TRAP activity and multinucleated cell formation were reduced in RANKL-stimulated osteoclasts after exposure to MKE. These results were confirmed by inhibiting TRAF6/MAPK expression, which led to the suppression of NFATc1, CTSK, TRAP, and MMP expression at the gene and protein levels. Our results confirmed that MKE is a promising candidate for the management of periodontal disease based on its anti-inflammatory effects and inhibition of ECM degradation and osteoclastogenesis.
An Evaluation of the Anti-Inflammatory Effects of a Thai Traditional Polyherbal Recipe TPDM6315 in LPS-Induced RAW264.7 Macrophages and TNF-α-Induced 3T3-L1 Adipocytes
Authors: Subin Phetpawi , Sabuhom Pattraporn , Naladta Alisa , Luecha Prathan , Nualkaew Somsak , Nualkaew Natsajee
Published: June 2023

TPDM6315 is an antipyretic Thai herbal recipe that contains several herbs with anti-inflammatory and anti-obesity activities. This study aimed to investigate the anti-inflammatory effects of TPDM6315 extracts in lipopolysaccharide (LPS)-induced RAW264.7 macrophages and TNF-α-induced 3T3-L1 adipocytes, and the effects of TPDM6315 extracts on lipid accumulation in 3T3-L1 adipocytes. The results showed that the TPDM6315 extracts reduced the nitric oxide production and downregulated the iNOS, IL-6, PGE2, and TNF-α genes regulating fever in LPS-stimulated RAW264.7 macrophages. The treatment of 3T3-L1 pre-adipocytes with TPDM6315 extracts during a differentiation to the adipocytes resulted in the decreasing of the cellular lipid accumulation in adipocytes. The ethanolic extract (10 µg/mL) increased the mRNA level of adiponectin (the anti-inflammatory adipokine) and upregulated the PPAR-γ in the TNF-α induced adipocytes. These findings provide evidence-based support for the traditional use of TPDM6315 as an anti-pyretic for fever originating from inflammation. The anti-obesity and anti-inflammatory actions of TPDM6315 in TNF-α induced adipocytes suggest that this herbal recipe could be useful for the treatment of metabolic syndrome disorders caused by obesity. Further investigations into the modes of action of TPDM6315 are needed for developing health products to prevent or regulate disorders resulting from inflammation.
Effects of Laser Remelting on Microstructure, Wear Resistance, and Impact Resistance of Laser-Clad Inconel625-Ni/WC Composite Coating on Cr12MoV Steel
Authors: Wei Yacheng , Feng Aixin , Chen Chunlun , Shang Dazhi , Pan Xiaoming , Xue Jianjun
Published: June 2023

In this study, an Inconel625-Ni60-Ni60/25%WC (Inconel625-Ni/WC) composite coating was fabricated on Cr12MoV steel by first-stage laser cladding, followed by second-stage laser remelting with various laser powers, and the better laser energy density of 25.0 J/mm2 for laser remelting test was obtained by macroscopic morphology and microhardness analysis. The effects of laser remelting on the microstructure, microhardness, wear resistance, and impact resistance of the composite coating was systematically investigated by combining various characterization methods. The results showed that laser remelting did not cause the composite coating to produce new phases. The microstructure of the Ni/WC layer in the remelted composite coating was denser and finer, and the average grain size of the surface layer was reduced by 11.69%. The impact depth of laser remelting was about 2.0 mm. The average microhardness of the Ni/WC layer in the remelted composite coating increased by 5.9%, and the average wear rate of the surface was reduced by 50.12% compared with that before laser remelting. The wear surface of remelted composite coating exhibited abrasive wear, and the wear resistance was significantly improved. In addition, the impact toughness value of the remelted composite coating reached 5.15 J/cm2, which increased by 87.96% compared with that before laser remelting. The impact resistance of the composite coating was further improved.
Study of Electrodeposition and Properties of Composite Nickel Coatings Modified with Ti3C2TX MXene
Authors: Tseluikin Vitaly , Dzhumieva Asel , Tribis Alena , Tikhonov Denis , Tsyganov Alexey , Gorshkov Nikolay , Lopukhova Marina
Published: June 2023

In this work we have synthesized Ti3C2TX MXene powder and studied its structure. Composite electrochemical coatings (CECs) of Ni-Ti3C2TX MXene were obtained from a sulfate– chloride bath in the galvanostatic regime. The microstructure of CEC was researched using X-ray phase analysis and scanning electron microscopy methods. It has been established that a Ni–Ti3C2TX MXene CEC microhardness rises by about 1.80 times compared with electrolytic Ni without a dispersed phase. For corrosion research, different corrosive media is applied. The corrosion–electrochemical behavior of Ni–Ti3C2TX MXene CECs by the chronovoltamperometry method in 0.5 M H2SO4 solution has been investigated. Trials in 3.5% NaCl have shown that Ti3C2TX MXene inclusion into the matrix of the electrochemical Ni results in a decrease in the corrosion rate by 1.60–1.75 times. These effects are due to the addition of Ti3C2TX MXene into the nickel matrix and the formation of CECs with a strengthening fine-grained structure.
Advances in the Field of Graphene-Based Composites for Energy–Storage Applications
Authors: Du Yining , Wang Mingyang , Ye Xiaoling , Liu Benqing , Han Lei , Jafri Syed Hassan Mujtaba , Liu Wencheng , Zheng Xiaoxiao , Ning Yafei , Li Hu
Published: June 2023

To meet the growing demand in energy, great efforts have been devoted to improving the performances of energy–storages. Graphene, a remarkable two-dimensional (2D) material, holds immense potential for improving energy–storage performance owing to its exceptional properties, such as a large-specific surface area, remarkable thermal conductivity, excellent mechanical strength, and high-electronic mobility. This review provides a comprehensive summary of recent research advancements in the application of graphene for energy–storage. Initially, the fundamental properties of graphene are introduced. Subsequently, the latest developments in graphene-based energy–storage, encompassing lithium-ion batteries, sodium-ion batteries, supercapacitors, potassium-ion batteries and aluminum-ion batteries, are summarized. Finally, the challenges associated with graphene-based energy–storage applications are discussed, and the development prospects for this field are outlined.
Microstructural Evaluation and Tensile Properties of Al-Mg-Sc-Zr Alloys Prepared by LPBF
Authors: Lu Yuxian , Zhang Hao , Xue Peng , Wu Lihui , Liu Fengchao , Jia Luanluan , Ni Dingrui , Xiao Bolv , Ma Zongyi
Published: June 2023

Laser powder bed fusion (LPBF) is a typical additive manufacturing technology that offers significant advantages in the production of complex components. With the rapid heating and cooling characteristics of LPBF, a large amount of solid solution of alloying elements in the matrix can be achieved to form supersaturated solid solutions, thus enhancing the properties of LPBF alloys. For the unique microstructure, the heat treatment process needs to be adjusted accordingly. In this work, a Zr/Sc-modified Al-Mg alloy processed by laser powder bed fusion (LPBF) with relatively low cost and good mechanical properties was investigated. The fine microstructure was obtained under rapid solidification conditions. The nanoscale Al3(Sc,Zr) particles precipitated at the molten pool boundary during solidification. These particles, as effective heterogeneous nucleators, further refined the α-Al grains and improved the mechanical properties of the alloy. As a result, the alloy exhibited a heterogeneous microstructure consisting of columnar grains in the center of the molten pool and equiaxed grains at the boundaries. The rapid solidification resulted in the supersaturation of solute atoms in the α-Al matrix, which significantly enhanced the solid solution strengthening effect. With the LPBF processing parameters of a combination of a laser power of 250 W, a laser scanning speed of 833 mm/s, and stripe scanning mode, the tensile strength of the alloy reached 401.4 ± 5.7 MPa, which was significantly higher than that of the cast alloys with aging treatment (281.1 ± 1.3 MPa). The heat treatment promoted the formation of secondary Al3(Sc,Zr), Mn/Mg-rich phases. The ultimate tensile strength and elongation at fracture after aging at 325 °C for 2 h were 536.0 ± 1.7 MPa and 14.8 ± 0.8%, respectively. The results provide insight into the preparation of aluminum alloys with relatively low cost and excellent mechanical properties.
Investigating Rare and Endangered Species: When a Single Methodology Is Not Enough—The Mediterranean Monk Seal Monachus monachus along the Coast of Salento (South Apulia, Italy)
Authors: Bundone Luigi , Rizzo Lucia , Fai Sergio , Hernandez-Milian Gema , Guerzoni Stefano , Molinaroli Emanuela
Published: June 2023

Several factors contributed, over time, to the Mediterranean monk seal’s sharp population decline. Despite the relative disappearance of documented breeding sub-populations, sightings have been collected, in recent decades, from most of the species’ former habitat. The conservation of this endangered marine mammal should also encompass those areas. We conducted our research along the coast of Salento (South Apulia, Italy) as a case study. To collect data on monk seal presence in the area, expected to be characterized by low numbers, we combined three different methodologies: a questionnaire to fishermen, interviews with witnesses of sightings, and a historical review of the species’ presence. The different methodologies allowed us to collect 11 records of recent sightings (after 2000) and 30 records of historical encounters (before 2000), highlighting that the species was already rare in Salento over the last century. Most of the historical information was concentrated between 1956 and 1988 (28 records), suggesting discontinuous occurrence in the area, possibly depending on the lack of monitoring efforts. Furthermore, a broad regional approach should be considered as a more effective path to aid the monk seal recovery, better comprehend the species’ abundance and movements, and eventually contribute to the overall health of ecosystems.
Alternatives to Polysomnography for the Diagnosis of Pediatric Obstructive Sleep Apnea
Authors: Teplitzky Taylor B. , Zauher Audrey J. , Isaiah Amal
Published: June 2023

Diagnosis of obstructive sleep apnea (OSA) in children with sleep-disordered breathing (SDB) requires hospital-based, overnight level I polysomnography (PSG). Obtaining a level I PSG can be challenging for children and their caregivers due to the costs, barriers to access, and associated discomfort. Less burdensome methods that approximate pediatric PSG data are needed. The goal of this review is to evaluate and discuss alternatives for evaluating pediatric SDB. To date, wearable devices, single-channel recordings, and home-based PSG have not been validated as suitable replacements for PSG. However, they may play a role in risk stratification or as screening tools for pediatric OSA. Further studies are needed to determine if the combined use of these metrics could predict OSA.
A Comparison of Clinical Outcomes in Rotator Cuff Re-Tear Patients Who Had Either an Arthroscopic Primary Repair or Arthroscopic Patch Augmentation for Large-to-Massive Rotator Cuff Tears
Authors: Kim Ki-Tae , Kim Gwan-Ho , Cha Dong-Heon , Lee Jae-Hoo , Lee Yong-Beom
Published: June 2023

Background and Purpose: Despite the prevalent incidence of re-tear following rotator cuff repair, there is a notable lack of comparative studies investigating the outcomes between patients with re-tear who underwent primary repair versus those who received patch augmentation for large-to-massive tears. We assessed clinical outcomes of these techniques through a retrospective, randomized controlled trial. Methods: 134 patients diagnosed with large-to-massive rotator cuff tears from 2018 to 2021 underwent surgery; 65 had primary repair and 69 had patch augmentation. A total of 31 patients with re-tears were included, split into two groups; Group A (primary repair, 12 patients) and Group B (patch augmentation, 19 patients). Outcomes were evaluated using several clinical scales and MRI imaging. Results: Most clinical scores improved postoperatively in both groups. No significant difference in clinical outcomes was observed between groups, except for pain visual analog scale (P-VAS) scores. P-VAS scores showed greater decrease in the patch-augmentation group, a statistically significant difference. Conclusions: for large-to-massive rotator cuff tears, patch augmentation led to greater decreases in pain than primary repair, despite similar radiographic and clinical results. Greater tuberosity coverage of the supraspinatus tendon footprint may impact P-VAS scores.
Federated Machine Learning for Skin Lesion Diagnosis: An Asynchronous and Weighted Approach
Authors: Yaqoob Muhammad Mateen , Alsulami Musleh , Khan Muhammad Amir , Alsadie Deafallah , Saudagar Abdul Khader Jilani , AlKhathami Mohammed
Published: June 2023

The accurate and timely diagnosis of skin cancer is crucial as it can be a life-threatening disease. However, the implementation of traditional machine learning algorithms in healthcare settings is faced with significant challenges due to data privacy concerns. To tackle this issue, we propose a privacy-aware machine learning approach for skin cancer detection that utilizes asynchronous federated learning and convolutional neural networks (CNNs). Our method optimizes communication rounds by dividing the CNN layers into shallow and deep layers, with the shallow layers being updated more frequently. In order to enhance the accuracy and convergence of the central model, we introduce a temporally weighted aggregation approach that takes advantage of previously trained local models. Our approach is evaluated on a skin cancer dataset, and the results show that it outperforms existing methods in terms of accuracy and communication cost. Specifically, our approach achieves a higher accuracy rate while requiring fewer communication rounds. The results suggest that our proposed method can be a promising solution for improving skin cancer diagnosis while also addressing data privacy concerns in healthcare settings.
The Caries-Arrest Effectiveness of Silver Diamine Fluoride Treatment with Different Post-Treatment Instructions in Preschool Children: A Study Protocol for a Randomized Controlled Trial
Authors: Sun Ivy Guofang , Duangthip Duangporn , Lo Edward Chin Man , Chu Chun Hung
Published: June 2023

In this 12-month randomized active-controlled clinical trial, we compare two post-treatment instructions for silver diamine fluoride (SDF) therapy in arresting dentine caries. The trial will include at least 254 kindergarten children with active dentine caries. The children will be randomized into two groups and receive a 38% SDF solution applied topically to their carious lesions. Children in Group A will rinse immediately, whereas those in Group B will refrain from rinsing, eating, and drinking for 30 min. One trained examiner will perform the dental examination at baseline and every six months. The primary outcome measurement will be the proportion of caries lesions that become arrested at the 12-month examination. Potential confounding factors and parents’ satisfaction with SDF therapy at baseline and after 12 months will be collected using parental questionnaires. This trial will provide evidence-based information for clinical practitioners to give post-treatment instructions for SDF therapy. This study is registered at ClinicalTrial.gov (USA) (registration number: NCT05655286).
Deep Reinforcement Learning for the Visual Servoing Control of UAVs with FOV Constraint
Authors: Fu Gui , Chu Hongyu , Liu Liwen , Fang Linyi , Zhu Xinyu
Published: June 2023

Visual servoing is a control method that utilizes image feedback to control robot motion, and it has been widely applied in unmanned aerial vehicle (UAV) motion control. However, due to field-of-view (FOV) constraints, visual servoing still faces challenges, such as easy target loss and low control efficiency. To address these issues, visual servoing control for UAVs based on the deep reinforcement learning (DRL) method is proposed, which dynamically adjusts the servo gain in real time to avoid target loss and improve control efficiency. Firstly, a Markov model of visual servoing control for a UAV under field-of-view constraints is established, which consists ofquintuplet and considers the improvement of the control efficiency. Secondly, an improved deep Q-network (DQN) algorithm with a target network and experience replay is designed to solve the Markov model. In addition, two independent agents are designed to adjust the linear and angular velocity servo gains in order to enhance the control performance, respectively. In the simulation environment, the effectiveness of the proposed method was verified using a monocular camera.
A Deep Learning Approach for Wireless Network Performance Classification Based on UAV Mobility Features
Authors: Bai Yijie , Yu Daojie , Zhang Xia , Chai Mengjuan , Liu Guangyi , Du Jianping , Wang Linyu
Published: June 2023

The unmanned aerial vehicle (UAV) has drawn attention from the military and researchers worldwide, which has advantages such as robust survivability and execution ability. Mobility models are usually used to describe the movement of nodes in drone networks. Different mobility models have been proposed for different application scenarios; currently, there is no unified mobility model that can be adapted to all scenarios. The mobility of nodes is an essential characteristic of mobile ad hoc networks (MANETs), and the motion state of nodes significantly impacts the network’s performance. Currently, most related studies focus on the establishment of mathematical models that describe the motion and connectivity characteristics of the mobility models with limited universality. In this study, we use a backpropagation neural network (BPNN) to explore the relationship between the motion characteristics of mobile nodes and the performance of routing protocols. The neural network is trained by extracting five indicators that describe the relationship between nodes and the global features of nodes. Our model shows good performance and accuracy of classification on new datasets with different motion features, verifying the correctness of the proposed idea, which can help the selection of mobility models and routing protocols in different application scenarios having the ability to avoid repeated experiments to obtain relevant network performance. This will help in the selection of mobility models for drone networks and the setting and optimization of routing protocols in future practical application scenarios.
Cycas micronesica Megastrobilus Traits Respond to Chronic Herbivory by Aulacaspis yasumatsui
Authors: Marler Thomas E. , Terry L. Irene
Published: June 2023

Aulacaspis yasumatsui Takagi invaded Guam in 2003 and caused the widespread mortality of the indigenous Cycas micronesica K.D. Hill population. The regeneration of the surviving tree population continues to be constrained 20 years later, and a look at the changes in megastrobili traits may inform future conservation management decisions concerning regeneration. We quantified megastrobilus reproductive effort and output from 2001 to 2022 to address this need. The reproductive effort of each megastrobilus was immediately reduced by the invasion, as the number of megasporophylls declined by 29%, and the number of ovules declined by 73% in 2006. Reproductive output was also damaged, as the percent seed set declined by 56% and the number of seeds per strobilus declined by 88%. These fecundity metrics have shown few signs of recovery through 2022. Our results reveal that chronic A. yasumatsui infestations, combined with other invasive herbivore threats, have damaged the host C. micronesica population through a sustained reduction in ovule production and the percent seed set for each megastrobilus, thereby impairing regeneration. This plant response to the biotic threats is distinct from the ongoing mortality of mature trees and emerging seedlings. Conservation interventions may be required to foster a return to adequate regeneration during future attempts to aid C. micronesica recovery.
A Novel Strategic Approach to Evaluating Higher Education Quality Standards in University Colleges Using Multi-Criteria Decision-Making
Authors: Makki Anas A. , Alqahtani Ammar Y. , Abdulaal Reda M. S. , Madbouly Ayman I.
Published: June 2023

Universities worldwide strive to achieve excellence in research, learning, teaching, and community services, which are the pillars of their strategic plans. However, satisfying international ranking criteria might not directly result in achieving their strategic objectives. This paper proposes a new approach to rank university colleges by evaluating their educational quality. Standard sets of criteria from multiple international university ranking systems and a university’s strategic plan’s Balanced Scorecard perspectives were cross-mapped for the evaluation. A new multi-criteria decision-making-based framework was applied to six colleges of a non-profit university in the Middle East. It revealed their performance rankings and contributions to the university’s educational quality objectives. This paper offers a novel approach for universities to develop strategies that satisfy multiple international ranking systems while achieving their strategic goals concurrently and as per their priorities. Implications include informing university leaders on the most contributing colleges and assisting in pinpointing quality shortcomings and their causes. This helps universities design better performance indicators and allocate resources to achieve educational excellence. This paper puts forward a new approach for universities to unify their efforts in satisfying the requirements of multiple international ranking systems while achieving their strategic goals.
The Impact of the COVID-19 Pandemic on Sense of Belonging and Science Outcomes among Biomedical Science Students: A Longitudinal Study
Authors: Escobedo Patricia , Moon Sungmin , Moreno Kyle , Lin Judith C. P. , Kwan Patchareeya P. , Flores Gilberto E. , Chavira Gabriela
Published: June 2023

To understand how COVID-19 impacted undergraduate research experiences (URE), the current study examined how student outcomes changed over time among biomedical science majors. In addition, this study describes how a Building Infrastructure Leading to Diversity (BUILD) Promoting Opportunities for Diversity in Education and Research (PODER) URE program shifted entirely online in response to COVID-19. Biomedical science majors at a university in Southern California completed surveys in 2019 and 2020 and rated their science identity, science self-efficacy, and academic self-concept. We examined how scores changed over time by comparing: (1) BUILD and non-BUILD students and (2) students from underrepresented groups (URG) and non-URG students. Sense of belonging scores from 2020 were also compared among BUILD and non-BUILD students. BUILD students reported a significant increase in science self-efficacy scores, unlike non-BUILD participants. BUILD students also increased their science identity scores, unlike non-BUILD participants. Differences in sense of belonging were not significant, and differences between URG and non-URG students were not significant. Given the importance of science self-efficacy and science identity in a student’s academic trajectory, our results indicate that UREs such as BUILD PODER were able to improve or maintain critical student outcomes during a pandemic. These results highlight the importance of URE participation among biomedical science majors.
Neural Network-Based Robust Bipartite Consensus Tracking Control of Multi-Agent System with Compound Uncertainties and Actuator Faults
Authors: Li Tong , Qin Kaiyu , Jiang Bing , Huang Qian , Liu Hui , Lin Boxian , Shi Mengji
Published: June 2023

This paper addresses the challenging problem of bipartite consensus tracking of multi-agent systems that are subject to compound uncertainties and actuator faults. Specifically, the study considers a leader agent with fractional-order nonlinear dynamics unknown to the followers. In addition, both cooperative and competitive interactions among agents are taken into account. To tackle these issues, the proposed approach employs a fully distributed robust bipartite consensus tracking controller, which integrates a neural network approximator to estimate the uncertainties of the leader and the followers. The adaptive laws of neural network parameters are continuously updated online based on the bipartite consensus tracking error. Furthermore, an adaptive control technique is utilized to generate the fault-tolerant component to mitigate the partial loss caused by actuator effectiveness faults. Compared with the existing works on nonlinear multi-agent systems, we consider the compound uncertainties, actuator faults and cooperative–competition interactions simultaneously. By implementing the proposed control scheme, the robustness of the closed-loop system can be significantly improved. Finally, numerical simulations are performed to validate the effectiveness of the control scheme.
A Multi-View Face Expression Recognition Method Based on DenseNet and GAN
Authors: Dong Jingwei , Zhang Yushun , Fan Lingye
Published: June 2023

Facial expression recognition (FER) techniques can be widely used in human-computer interaction, intelligent robots, intelligent monitoring, and other domains. Currently, FER methods based on deep learning have become the mainstream schemes. However, these methods have some problems, such as a large number of parameters, difficulty in being applied to embedded processors, and the fact that recognition accuracy is affected by facial deflection. To solve the problem of a large number of parameters, we propose a DSC-DenseNet model, which improves the standard convolution in DenseNet to depthwise separable convolution (DSC). To solve the problem wherein face deflection affects the recognition effect, we propose a posture normalization model based on GAN: a GAN with two local discriminators (LD-GAN) that strengthen the discriminatory abilities of the expression-related local parts, such as the parts related to the eyes, eyebrows, mouth, and nose. These discriminators improve the model’s ability to retain facial expressions and evidently benefits FER. Quantitative and qualitative experimental results on the Fer2013 and KDEF datasets have consistently shown the superiority of our FER method when working with multi-pose face images.
Study on the Selection Method of Federated Learning Clients for Smart Manufacturing
Authors: Yang Chi , Zhao Xiaoli
Published: June 2023

Artificial intelligence technology in the context of smart manufacturing uses manufacturing data to enable the automatic detection, classification, and identification of products in the production process, reducing production costs and human consumption, thereby improving production efficiency and product quality. Federated learning enables the distributed implementation of AI technologies, keeping data local to avoid privacy leaks. However, data heterogeneity factors have an impact on federated learning in a manufacturing context, and this paper proposes a customer degree selection method based on model parameter variation. The method relies on transmitting the local model changes in the participants to reflect the data characteristics, calculates the model similarity of the participants using graph theory and similarity, and uses the Top-K mechanism to filter the original participant set through the similarity scores of graph nodes to reduce the influence of heterogeneity factors in the participant set and maximize the training effect and accuracy of federated learning. The effectiveness of this method was verified by using the Dirichlet distribution to perform non-IID data partitioning on the power system attack dataset and the hard disk fault detection dataset.
Research on Offloading Strategy for Mobile Edge Computing Based on Improved Grey Wolf Optimization Algorithm
Authors: Zhang Wenzhu , Tuo Kaihang
Published: June 2023

With the development of intelligent transportation and the rapid growth of application data, the tasks of offloading vehicles in vehicle-to-vehicle communication technology are continuously increasing. To further improve the service efficiency of the computing platform, energy-efficient and low-latency mobile-edge-computing (MEC) offloading methods are urgently needed, which can solve the insufficient computing capacity of vehicle terminals. Based on an improved gray-wolf algorithm designed, an adaptive joint offloading strategy for vehicular edge computing is proposed, which does not require cloud-computing support. This strategy first establishes an offloading computing model, which takes task computing delays, computing energy consumption, and MEC server computing resources as constraints; secondly, a system-utility function is designed to transform the offloading problem into a constrained system-utility optimization problem; finally, the optimal solution to the computation offloading problem is obtained based on an improved gray-wolf optimization algorithm. The simulation results show that the proposed strategy can effectively reduce the system delay and the total energy consumption.
Lightweight Transmission Behavior Audit Scheme for NDN Industrial Internet Identity Resolution and Transmission Based on Blockchain
Authors: He Yunhua , Ma Yuliang , Hu Qing , Zhou Zhihao , Xiao Ke , Wang Chao
Published: June 2023

The Named Data Network (NDN) enables efficient content dissemination through interest-based retrieval, name-based routing, and content caching. In the industrial Internet architecture based on NDN, device identity distribution, identification, resolution, and routing rely on identification resolution technology. However, this approach presents challenges such as cache poisoning, interest packet flood attacks, and black hole attacks. Existing security schemes primarily focused on routing forwarding and verification fail to address critical concerns, including routing environment credibility and data leakage, while exhibiting poor time and space efficiency. To address these challenges, this paper proposes a lightweight behavior auditing scheme using blockchain technology. The scheme utilizes an improved Bloom filter to compress behavioral information like interest and data packets during the identification transmission process. The compressed data are subsequently uploaded to a blockchain for auditing, achieving efficient space and time utilization while maintaining feasibility.
A Nonintrusive Load Identification Method Based on Improved Gramian Angular Field and ResNet18
Authors: Wang Jingqin , Wu Yufeng , Shu Liang
Published: June 2023

Image classification methods based on deep learning have been widely used in the study of nonintrusive load identification. However, in the process of encoding the load electrical signals into images, how to fully retain features of the raw data and thus increase the recognizability of loads carried with very similar current signals are still challenging, and the loss of load features will cause the overall accuracy of load identification to decrease. To deal with this problem, this paper proposes a nonintrusive load identification method based on the improved Gramian angular field (iGAF) and ResNet18. In the proposed method, fast Fourier transform is used to calculate the amplitude spectrum and the phase spectrum to reconstruct the pixel matrices of the B channel, G channel, and R channel of generated GAF images so that the color image fused by the three channels contains more information. This improvement to the GAF method enables generated images to retain the amplitude feature and phase feature of the raw data that are usually missed in the general GAF image. ResNet18 is trained with iGAF images for nonintrusive load identification. Experiments are conducted on two private datasets, ESEAD and EMCAD, and two public datasets, PLAID and WHITED. Experimental results suggest that the proposed method performs well on both private and public datasets, achieving overall identification accuracies of 99.545%, 99.375%, 98.964%, and 100% on the four datasets, respectively. In particular, the method demonstrates significant identification effects for loads with similar current waveforms in private datasets.