bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Extracellular Heat Shock Proteins in Cardiovascular Diseases
Authors: Patnaik Soumya , Nathan Sriram , Kar Biswajit , Gregoric Igor D. , Li Yi-Ping
Published: May 2023

In the early 1960s, heat shock proteins (HSPs) were first identified as vital intracellular proteinaceous components that help in stress physiology and reprogram the cellular responses to enable the organism’s survival. By the early 1990s, HSPs were detected in extracellular spaces and found to activate gamma-delta T-lymphocytes. Subsequent investigations identified their association with varied disease conditions, including autoimmune disorders, diabetes, cancer, hepatic, pancreatic, and renal disorders, and cachexia. In cardiology, extracellular HSPs play a definite, but still unclear, role in atherosclerosis, acute coronary syndromes, and heart failure. The possibility of HSP-targeted novel molecular therapeutics has generated much interest and hope in recent years. In this review, we discuss the role of Extracellular Heat Shock Proteins (Ec-HSPs) in various disease states, with a particular focus on cardiovascular diseases.
Diversity of Mycogenic Oxide and Chalcogenide Nanoparticles: A Review
Authors: Loshchinina Ekaterina A. , Vetchinkina Elena P. , Kupryashina Maria A.
Published: May 2023

Oxide and chalcogenide nanoparticles have great potential for use in biomedicine, engineering, agriculture, environmental protection, and other research fields. The myco-synthesis of nanoparticles with fungal cultures, their metabolites, culture liquids, and mycelial and fruit body extracts is simple, cheap and environmentally friendly. The characteristics of nanoparticles, including their size, shape, homogeneity, stability, physical properties and biological activity, can be tuned by changing the myco-synthesis conditions. This review summarizes the data on the diversity of oxide and chalcogenide nanoparticles produced by various fungal species under different experimental conditions.
Biomechanical Analysis of Hip Braces after Hip Arthroscopic Surgery for Femoroacetabular Impingement Syndrome: An Observational Study
Authors: Hirata Kai , Murata Yoichi , Hatakeyama Akihisa , Takahashi Makoto , Quinn Patrick M. , Uchida Soshi
Published: May 2023

Currently, hip braces are recommended and typically worn by femoroacetabular impingement (FAI) patients after hip arthroscopic surgery. However, there is currently a lack of literature regarding the biomechanical effectiveness of hip braces. The purpose of this study was to investigate the biomechanical effect of hip braces after hip arthroscopic surgery for FAI. Overall, 11 patients who underwent arthroscopic FAI correction and labral preservation surgery were included in the study. Standing-up and walking tasks in unbraced and braced conditions were performed at 3 weeks postoperatively. For the standing-up task, videotaped images of the hip’s sagittal plane were recorded while patients stood from a seated position. After each motion, the hip flexion-extension angle was calculated. For the walking task, acceleration of the greater trochanter was measured using a triaxial accelerometer. For the standing-up motion, the mean peak hip flexion angle was found to be significantly lower in the braced condition than in the unbraced condition. Furthermore, the mean peak acceleration of the greater trochanter was significantly lower in the braced condition than in the unbraced condition. Patients undergoing arthroscopic FAI correction surgery would benefit from usage of a hip brace in terms of protecting repaired tissues during early postoperative recovery.
Chitosan Cryogels Cross-Linked with 1,1,3-Triglycidyloxypropane: Mechanical Properties and Cytotoxicity for Cancer Cell 3D Cultures
Authors: Privar Yuliya , Boroda Andrey , Pestov Alexandr , Kazantsev Daniil , Malyshev Daniil , Skatova Anna , Bratskaya Svetlana
Published: May 2023

Here, we have presented a new method of 1,1,3-triglycidyloxypropane (TGP) synthesis and investigated how cross-linker branching affects mechanical properties and cytotoxicity of chitosan scaffolds in comparison with those cross-linked using diglycidyl ethers of 1,4-butandiol (BDDGE) and poly(ethylene glycol) (PEGDGE). We have demonstrated that TGP is an efficient cross-linker for chitosan at a subzero temperature at TGP:chitosan molar ratios from 1:1 to 1:20. Although the elasticity of chitosan scaffolds increased in the following order of the cross-linkers PEGDGE > TGP > BDDGE, TGP provided cryogels with the highest compressive strength. Chitosan-TGP cryogels have shown low cytotoxicity for colorectal cancer HCT 116 cell line and supported the formation of 3D multicellular structures of the spherical shape and size up to 200 µm, while in more brittle chitosan-BDDGE cryogel this cell culture formed epithelia-like sheets. Hence, the selection of the cross-linker type and concentration for chitosan scaffold fabrication can be used to mimic the solid tumor microenvironment of certain human tissue, control matrix-driven changes in the morphology of cancer cell aggregates, and facilitate long-term experiments with 3D tumor cell cultures.
Graphene-Based Sensors for the Detection of Microorganisms in Food: A Review
Authors: Gao Jingrong , Chakraborthy Aniket , He Shan , Yang Song , Afsarimanesh Nasrin , Nag Anindya , Deng Shanggui
Published: May 2023

There is a constant need to maintain the quality of consumed food. In retrospect to the recent pandemic and other food-related problems, scientists have focused on the numbers of microorganisms that are present in different food items. As a result of changes in certain environmental factors such as temperature and humidity, there is a constant risk for the growth of harmful microorganisms, such as bacteria and fungi, in consumed food. This questions the edibility of the food items, and constant monitoring to avoid food poisoning-related diseases is required. Among the different nanomaterials used to develop sensors to detect microorganisms, graphene has been one of the primary materials due to its exceptional electromechanical properties. Graphene sensors are able to detect microorganisms in both a composite and non-composite manner, due to their excellent electrochemical characteristics such as their high aspect ratios, excellent charge transfer capacity and high electron mobility. The paper depicts the fabrication of some of these graphene-based sensors, and their utilization to detect bacteria, fungi and other microorganisms that are present in very small amounts in different food items. In addition to the classified manner of the graphene-based sensors, this paper also depicts some of the challenges that exist in current scenarios, and their possible remedies.
Persistence Is Multi-Trait: Persistence Scale Development and Persistence Perseveration and Perfectionism Questionnaire into Polish Translation
Authors: Styk Wojciech , Zmorzynski Szymon , Samardakiewicz Marzena
Published: May 2023

Persistence is defined as, among other ways, the need to achieve the goals and strive for the goal. Persistence can also be considered from the perspective of the resource concept, as a positive factor related to an individual’s adaptive behaviour, psychological resilience, and normal self-regulation. In contrast, tendencies behaviourally similar to perseverance, but which may have psychopathological features, are persistence and perfectionism. The main goal of our study was to: (I) Build non-clinical Persistence Scale (PS) in Polish and English; (II) translate in Polish and validate the Persistence, Perfectionism and Perseveration Questionnaire (PPPQ); (III) analyse properties of both scales. Methods: The study was conducted on a non-clinical group of 306 subjects. The mean age was 27.6 and ranged from 18 to 58 years. The properties of both scales were analysed using the NEO-FFI personality inventory, PSS-10 Perceived stress level scale, The UPPS-P Impulsive Behaviour Scale, the SPSRQ Sensitivity to Punishment and Reward scale, Grit scale and NAS-50 Self-Control Scale. Results: The psychometric features of the scales fulfil the requirements for psychometric tools. The factorial structure of both versions of the PS-20 scale proved to be unifactorial. Openness was the only variable to co-occur with the persistence scales of both the PS-20 and the PPPQ-10, and did not co-occur with scales intended to indicate psychopathology (Perseveration, Perfectionism). Negative correlations occurred with variables describing Persistence with levels of perceived stress, anxiety and depressive symptoms. Impulsivity measured by the SUPPS scale also showed negative correlations with the study variables. Conclusions: In the present work, we postulate that persistence is an umbrella construct that gathers and integrates many other traits to form a multi-trait persistence. Perseveration should be regarded as an undesirable trait characterising psychopathological behaviour. Desirable and indicative traits of an individual’s good functioning are persistence and, to some extent, perfectionism. Individuals with low persistence and high perseveration may be characterised by a repertoire of psychopathological behaviours.
Melatonin in Combination with Albendazole or Albendazole Sulfoxide Produces a Synergistic Cytotoxicity against Malignant Glioma Cells through Autophagy and Apoptosis
Authors: Hernández-Cerón Miguel , Chavarria Víctor , Ríos Camilo , Pineda Benjamin , Palomares-Alonso Francisca , Rojas-Tomé Irma Susana , Jung-Cook Helgi
Published: May 2023

Glioblastoma is the most aggressive and lethal brain tumor in adults, presenting diffuse brain infiltration, necrosis, and drug resistance. Although new drugs have been approved for recurrent patients, the median survival rate is two years; therefore, new alternatives to treat these patients are required. Previous studies have reported the anticancer activity of albendazole, its active metabolite albendazole sulfoxide, and melatonin; therefore, the present study was performed to evaluate if the combination of melatonin with albendazole or with albendazole sulfoxide induces an additive or synergistic cytotoxic effect on C6 and RG2 rat glioma cells, as well as on U87 human glioblastoma cells. Drug interaction was determined by the Chou–Talalay method. We evaluated the mechanism of cell death by flow cytometry, immunofluorescence, and crystal violet staining. The cytotoxicity of the combinations was mainly synergistic. The combined treatments induced significantly more apoptotic and autophagic cell death on the glioma cell lines. Additionally, albendazole and albendazole sulfoxide inhibited proliferation independently of melatonin. Our data justify continuing with the evaluation of this proposal since the combinations could be a potential strategy to aid in the treatment of glioblastoma.
Direct Burr Hole Access for Transverse–Sigmoid Junction DAVF Embolization: A Case Report
Authors: Withers James , Regenhardt Robert , Dmytriw Adam , Vranic Justin , Marciano Rudolph , Stapleton Christopher , Patel Aman
Published: May 2023

Dural arteriovenous fistulas (DAVFs) are rare intracranial vascular malformations that present with a variety of clinical signs and symptoms. Among these, intracranial hemorrhage is a severe complication. A 72-year-old male presented with headache and pulsatile tinnitus. Cerebral angiography revealed a Borden II/Cognard IIa+b DAVF. He underwent stage 1 transarterial embolization of the occipital artery which reduced shunting by 30%. Several attempts were made to access the fistula during stage 2 transvenous embolization, but it was not possible to access the left transverse sinus fistula site since there was no communication across the torcula from the right transverse sinus and the left inferior sigmoid–jugular bulb was occluded. Therefore, a single burr hole was drilled and direct access to the DAVF was achieved with a micropuncture needle under neuronavigational guidance. The left transverse–sigmoid sinus junction was then embolized with coils. After the procedure, angiography revealed that the DAVF was cured with no residual shunting. This case demonstrates how minimally invasive surgery provides an alternative method to access a DVAF when conventional transarterial and/or transvenous embolization treatment options are not possible. Each DAVF case has unique anatomy and physiology, and creative multi-disciplinary strategies can often yield the best results.
Parameter Selection for the Dehumidification System of the Main Cable of Suspension Bridge Based on Ventilation Experiments
Authors: Guo Zhihang , Sui Wenhao , Guan Hua , Peng Pei , Liu Qun , Shi Jianzhong
Published: May 2023

Moisture in the main cable is the main cause of steel wire corrosion. Modern suspension bridges utilize main cable dehumidification systems to prevent corrosion. The main cable ventilation experiment can help the selection of the system parameters. This research is based on the ventilation experiment of the main cable of Xihoumen Bridge to obtain the design parameters of the dehumidification system. According to the experiment, the suitable dehumidification distance is 150–180 m; the pressure loss of the main cable with a length of 150 m is 200–300 Pa, so the inlet pressure should be higher than 300 Pa; increasing the outlet clamp can increase the dehumidification efficiency; Under single inlet and double outlet situation, every 100% increase in air volume increases the dehumidification capacity is about 35%. The water content of the main cable of Xihoumen Bridge is 5.74 kg/m3, and 1 m3 of dry air can remove 5.5 g of water under experimental conditions, and the minimum air volume is 30 m3/h. The main factors affecting the dehumidification time are air volume and leakage rate. Input these parameters into the dehumidification system for the dehumidification experiment, and the water content of the outlet clamp will drop by about 37.5% within ten days.
Enhancing the Vulnerability Assessment of Rainwater Pipe Networks: An Advanced Fuzzy Borda Combination Evaluation Approach
Authors: He Fang , Cheng Shuliang , Zhu Jing
Published: May 2023

A vulnerability assessment system for rainwater pipe networks, comprising 13 indexes, was developed to facilitate the rational allocation and timely updating of urban storm drainage systems. An enhanced Borda combination evaluation method, which considers both the optimal and worst solutions, was proposed, accompanied by the operation procedure and numerical calculation method. Five stormwater systems in Central China were selected as case studies, and their vulnerability was evaluated and compared using five distinct evaluation methods: the entropy weight method, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), the efficacy coefficient method, the fuzzy comprehensive evaluation method, and the improved fuzzy Borda combination evaluation method. The results demonstrated that the correlation coefficients between the fuzzy Borda combination evaluation method and the four individual evaluation methods were equal to or greater than 0.88, indicating strong agreement. Additionally, the compatibility of the combination evaluation method was found to be 0.96. This study holds both theoretical significance and practical value for preventing urban waterlogging and contributes to the development of more resilient urban storm drainage systems.
Inverse Propensity Score-Weighted Analysis of Entecavir and Tenofovir Disoproxil Fumarate in Patients with Chronic Hepatitis B: A Large-Scale Multicenter Study
Authors: Kim Jihye , Hur Moon Haeng , Kim Seung Up , Kim Jin-Wook , Sinn Dong Hyun , Lee Hyun Woong , Kim Moon Young , Cheong Jae Youn , Jung Yong Jin , Lee Han Ah , Jin Young-Joo , Yoon Jun Sik , Park Sung-Jae , Lee Chang Hun , Kim In Hee , Lee June Sung , Cho Young Youn , Kim Hyung Joon , Park Soo Young , Seo Yeon Seok , Oh Hyunwoo , Jun Dae Won , Kim Mi Na , Chang Young , Jang Jae Young , Hwang Sang Youn , Kim Yoon Jun
Published: May 2023

Tenofovir disoproxil fumarate (TDF) is reportedly superior or at least comparable to entecavir (ETV) in preventing hepatocellular carcinoma (HCC) among chronic hepatitis B (CHB) patients; however, it remains controversial. This study aimed to conduct comprehensive comparisons between the two antivirals. CHB patients initially treated with ETV or TDF between 2012 and 2015 at 20 referral centers in Korea were included. The primary outcome was the cumulative incidence of HCC. The secondary outcomes included death or liver transplantation, liver-related outcome, extrahepatic malignancy, development of cirrhosis, decompensation events, complete virologic response (CVR), seroconversion rate, and safety. Baseline characteristics were balanced using the inverse probability of treatment weighting (IPTW). Overall, 4210 patients were enrolled: 1019 received ETV and 3191 received TDF. During the median follow-ups of 5.6 and 5.5 years, 86 and 232 cases of HCC were confirmed in the ETV and TDF groups, respectively. There was no difference in HCC incidence between the groups both before (p = 0.36) and after IPTW was applied (p = 0.81). Although the incidence of extrahepatic malignancy was significantly higher in the ETV group than in the TDF group before weighting (p = 0.02), no difference was confirmed after IPTW (p = 0.29). The cumulative incidence rates of death or liver transplantation, liver-related outcome, new cirrhosis development, and decompensation events were also comparable in the crude population (p = 0.24–0.91) and in the IPTW-adjusted population (p = 0.39–0.80). Both groups exhibited similar rates of CVR (ETV vs. TDF: 95.1% vs. 95.8%, p = 0.38), and negative conversion of hepatitis B e antigen (41.6% vs. 37.2%, p = 0.09) or surface antigen (2.8% vs. 1.9%, p = 0.10). Compared to the ETV group, more patients in the TDF group changed initial antivirals due to side effects, including decreased kidney function (n = 17), hypophosphatemia (n = 20), and osteoporosis (n = 18). In this large-scale multicenter study, ETV and TDF demonstrated comparable effectiveness across a broad range of outcomes in patients with treatment-naïve CHB during similar follow-up periods.
Novel NUP98::ASH1L Gene Fusion in Acute Myeloid Leukemia Detected by Optical Genome Mapping
Authors: Tembrink Marco , Gerding Wanda Maria , Wieczorek Stefan , Mika Thomas , Schroers Roland , Nguyen Huu Phuc , Vangala Deepak Ben , Nilius-Eliliwi Verena
Published: May 2023

Optical genome mapping (OGM) recently has demonstrated the potential to improve genetic diagnostics in acute myeloid leukemia (AML). In this study, OGM was utilized as a tool for the detection of genome-wide structural variants and disease monitoring. A previously unrecognized NUP98::ASH1L fusion was detected in an adult patient with secondary AML. OGM identified the fusion of NUP98 to Absent, Small, or Homeotic-Like Histone Lysine Methyltransferase (ASH1L) as result of a complex structural rearrangement between chromosomes 1 and 11. A pipeline for the measurement of rare structural variants (Rare Variant Pipeline, Bionano Genomics, San Diego, CA, USA) was used for detection. As NUP98 and other fusions are relevant for disease classification, this demonstrates the necessity for methods such as OGM for cytogenetic diagnostics in AML. Furthermore, other structural variants showed discordant variant allele frequencies at different time points over the course of the disease and treatment pressure, indicating clonal evolution. These results support OGM to be a valuable tool for primary diagnostics in AML as well as longitudinal testing for disease monitoring and deepening our understanding of genetically heterogenous diseases.
Adherence to Opioid Patient Prescriber Agreements at a Safety Net Hospital
Authors: Pacheco Soraira , Nguyen Linh M. T. , Halphen John M. , Samy Nikitha N. , Wilson Nathaniel R. , Sattler Gregory , Wing Shane E. , Feng Christine , Paulino Rex A. D. , Shah Pulin , Addimulam Supriyanka , Patel Riddhi , Wray Curtis J. , Arthur Joseph A. , Hui David
Published: May 2023

Patient prescriber agreements, also known as opioid contracts or opioid treatment agreements, have been recommended as a strategy for mitigating non-medical opioid use (NMOU). The purpose of our study was to characterize the proportion of patients with PPAs, the rate of non-adherence, and clinical predictors for PPA completion and non-adherence. This retrospective study covered consecutive cancer patients seen at a palliative care clinic at a safety net hospital between 1 September 2015 and 31 December 2019. We included patients 18 years or older with cancer diagnoses who received opioids. We collected patient characteristics at consultation and information regarding PPA. The primary purpose was to determine the frequency and predictors of patients with a PPA and non-adherence to PPAs. Descriptive statistics and multivariable logistic regression models were used for the analysis. The survey covered 905 patients having a mean age of 55 (range 18–93), of whom 474 (52%) were female, 423 (47%) were Hispanic, 603 (67%) were single, and 814 (90%) had advanced cancer. Of patients surveyed, 484 (54%) had a PPA, and 50 (10%) of these did not adhere to their PPA. In multivariable analysis, PPAs were associated with younger age (odds ratio [OR] 1.44; p = 0.02) and alcohol use (OR 1.72; p = 0.01). Non-adherence was associated with males (OR 3.66; p = 0.007), being single (OR 12.23; p = 0.003), tobacco (OR 3.34; p = 0.03) and alcohol use (OR 0.29; p = 0.02), contact with persons involved in criminal activity (OR 9.87; p < 0.001), use for non-malignant pain (OR 7.45; p = 0.006), and higher pain score (OR 1.2; p = 0.01). In summary, we found that PPA non-adherence occurred in a substantial minority of patients and was more likely in patients with known NMOU risk factors. These findings underscore the potential role of universal PPAs and systematic screening of NMOU risk factors to streamline care.
CAR-T Cells Immunotherapies for the Treatment of Acute Myeloid Leukemia—Recent Advances
Authors: Zarychta Julia , Kowalczyk Adrian , Krawczyk Milena , Lejman Monika , Zawitkowska Joanna
Published: May 2023

In order to increase the effectiveness of cancer therapies and extend the long-term survival of patients, more and more often, in addition to standard treatment, oncological patients receive also targeted therapy, i.e., CAR-T cells. These cells express a chimeric receptor (CAR) that specifically binds an antigen present on tumor cells, resulting in tumor cell lysis. The use of CAR-T cells in the therapy of relapsed and refractory B-type acute lymphoblastic leukemia (ALL) resulted in complete remission in many patients, which prompted researchers to conduct tests on the use of CAR-T cells in the treatment of other hematological malignancies, including acute myeloid leukemia (AML). AML is associated with a poorer prognosis compared to ALL due to a higher risk of relapse caused by the development of resistance to standard treatment. The 5-year relative survival rate in AML patients was estimated at 31.7%. The objective of the following review is to present the mechanism of action of CAR-T cells, and discuss the latest findings on the results of anti-CD33, -CD123, -FLT3 and -CLL-1 CAR-T cell therapy, the emerging challenges as well as the prospects for the future.
Amplification of SERS Signal of Methotrexate Using Beta-Cyclodextrin Modified Silver Nanoparticles
Authors: Markina Natalia E. , Goryacheva Irina Yu. , Markin Alexey V.
Published: May 2023

The paper describes the use of native β-cyclodextrin (CD) for the modification of silver nanoparticles (AgNPs) in order to improve the determination of the anticancer drug methotrexate (MTX) using surface-enhanced Raman spectroscopy (SERS). A control experiment with unmodified AgNPs showed that the strong SERS signal of MTX can only be achieved in alkaline media. However, competitive interactions and the strong background signal of human body fluid components significantly challenge MTX determination in real samples. While previous reports propose the use of thorough sample pretreatment (e.g., solid phase extraction), the application of CD-modified AgNPs increases the SERS signal of MTX in neutral media by seven times which enables simplifying the analysis and improving its accuracy by reducing the influence of endogenous components of body fluids. A detailed study of the synthesis conditions (CD concentration and reaction time) and SERS registration conditions (pH, NaCl concentration, dilution of urine samples) was performed to maximize the analytical signal and signal-to-noise ratio. The final assay was tested for MTX determination in artificially spiked samples of real human urine. The results demonstrated that MTX can be determined within the concentration range suitable for therapeutic drug monitoring (20–300 μg mL−1) with satisfactory precision (6–15% RSD), accuracy (95–111% apparent recovery), and limit of detection (0.3 μg mL−1).
Prototype of a Recommendation Model with Artificial Intelligence for Computational Thinking Improvement of Secondary Education Students
Authors: Hijón-Neira Raquel , Connolly Cornelia , Pizarro Celeste , Pérez-Marín Diana
Published: May 2023

There is a growing interest in finding new ways to address the difficult task of introducing programming to secondary students for the first time to improve students’ computational thinking (CT) skills. Therefore, extensive research is required in this field. Worldwide, new ways to address this difficult task have been developed: visual execution environments and approaches by text programming or visual programming are among the most popular. This paper addresses the complex task by using a visual execution environment (VEE) to introduce the first programming concepts that should be covered in any introductory programming course. These concepts include variables, input and output, conditionals, loops, arrays, functions, and files. This study explores two approaches to achieve this goal: visual programming (using Scratch) and text programming (using Java) to improve CT. Additionally, it proposes an AI recommendation model into the VEE to further improve the effectiveness of developing CT among secondary education students. This integrated model combines the capabilities of an AI learning system module and a personalized learning module to better address the task at hand. To pursue this task, an experiment has been carried out among 23 preservice secondary teachers’ students in two universities, one in Madrid, Spain, and the other in Galway, Ireland. The overall results showed a significant improvement in the Scratch group. However, when analyzing the results based on specific programming concepts, significance was observed only in the Scratch group, specifically for the Loop concept.
Narrowband Filters Designed from Hybrid One-Dimensional Periodic/Quasiperiodic Photonic Crystals with a Single Defect Layer
Authors: Murillo-García Waira , Gómez-Urrea Hernán A. , Mora-Ramos Miguel E. , Duque Carlos A.
Published: May 2023

We report the transmission spectra and electric field amplitudes of electromagnetic modes propagating in hybrid periodic/quasiperiodic multilayer photonic structures in one dimension (1D). We consider the case of the combination of biperiodic Bragg mirror and triperiodic Bragg mirrors with quasiregular (FB, Fibonacci) layered components. The corresponding hybrid structure (HB) is formed by concatenating BM(N)-FB(M)-BM(N), where N (M) means the number of periods (sequence order) used for the Bragg mirrors (FB) structure. A single defect layer (D) is considered in the middle of two HBs (HB-D-HB). Optimizing the parameters (the order of sequence, number of Bragg mirror layers, thickness, and the refractive index of D) allows us to obtain narrowband filters. The manipulation of these parameters fixes the number of photonic band gaps as well as the position of transmission peaks. The existence of the selectively localized behavior of some optical modes in the structures is discussed.
Machine Learning Assisting the Prediction of Clinical Outcomes following Nucleoplasty for Lumbar Degenerative Disc Disease
Authors: Chiu Po-Fan , Chang Robert Chen-Hao , Lai Yung-Chi , Wu Kuo-Chen , Wang Kuan-Pin , Chiu You-Pen , Ji Hui-Ru , Kao Chia-Hung , Chiu Cheng-Di
Published: May 2023

Background: Lumbar degenerative disc disease (LDDD) is a leading cause of chronic lower back pain; however, a lack of clear diagnostic criteria and solid LDDD interventional therapies have made predicting the benefits of therapeutic strategies challenging. Our goal is to develop machine learning (ML)–based radiomic models based on pre-treatment imaging for predicting the outcomes of lumbar nucleoplasty (LNP), which is one of the interventional therapies for LDDD. Methods: The input data included general patient characteristics, perioperative medical and surgical details, and pre-operative magnetic resonance imaging (MRI) results from 181 LDDD patients receiving lumbar nucleoplasty. Post-treatment pain improvements were categorized as clinically significant (defined as a ≥80% decrease in the visual analog scale) or non-significant. To develop the ML models, T2-weighted MRI images were subjected to radiomic feature extraction, which was combined with physiological clinical parameters. After data processing, we developed five ML models: support vector machine, light gradient boosting machine, extreme gradient boosting, extreme gradient boosting random forest, and improved random forest. Model performance was measured by evaluating indicators, such as the confusion matrix, accuracy, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC), which were acquired using an 8:2 allocation of training to testing sequences. Results: Among the five ML models, the improved random forest algorithm had the best performance, with an accuracy of 0.76, a sensitivity of 0.69, a specificity of 0.83, an F1 score of 0.73, and an AUC of 0.77. The most influential clinical features included in the ML models were pre-operative VAS and age. In contrast, the most influential radiomic features had the correlation coefficient and gray-scale co-occurrence matrix. Conclusions: We developed an ML-based model for predicting pain improvement after LNP for patients with LDDD. We hope this tool will provide both doctors and patients with better information for therapeutic planning and decision-making.
Diagnostic and Prognostic Roles of Procalcitonin and Other Tools in Community-Acquired Pneumonia: A Narrative Review
Authors: Ozbay Sedat , Ayan Mustafa , Ozsoy Orhan , Akman Canan , Karcioglu Ozgur
Published: May 2023

Community-acquired pneumonia (CAP) is among the most common causes of death and one of the leading healthcare concerns worldwide. It can evolve into sepsis and septic shock, which have a high mortality rate, especially in critical patients and comorbidities. The definitions of sepsis were revised in the last decade as “life-threatening organ dysfunction caused by a dysregulated host response to infection”. Procalcitonin (PCT), C-reactive protein (CRP), and complete blood count, including white blood cells, are among the most commonly analyzed sepsis-specific biomarkers also used in pneumonia in a broad range of studies. It appears to be a reliable diagnostic tool to expedite care of these patients with severe infections in the acute setting. PCT was found to be superior to most other acute phase reactants and indicators, including CRP as a predictor of pneumonia, bacteremia, sepsis, and poor outcome, although conflicting results exist. In addition, PCT use is beneficial to judge timing for the cessation of antibiotic treatment in most severe infectious states. The clinicians should be aware of strengths and weaknesses of known and potential biomarkers in expedient recognition and management of severe infections. This manuscript is intended to present an overview of the definitions, complications, and outcomes of CAP and sepsis in adults, with special regard to PCT and other important markers.
Availability of Third Molars as Donor Teeth for Autotransplantation to Replace Congenitally Absent Second Premolars in Children and Young Adults
Authors: Bilińska Małgorzata , Burzykowski Tomasz , Plakwicz Paweł , Zadurska Małgorzata , Czochrowska Ewa Monika
Published: May 2023

The aim of the study was to assess the presence and distribution of third molars (M3) regarding their autotransplantation in patients with congenital absence of second premolars (PM2). Additionally, M3 development in relation to patients’ age and gender was investigated. Panoramic radiographs of non-syndromic patients with at least one congenitally absent PM2 were used to assess the localization and number of missing PM2 and the presence or absence of M3 (minimum age 10 years). The alternate logistic regression model was applied to analyze associations between the presence of PM2 and M3. A total of 131 patients with PM2 agenesis were identified (82 females, 49 males). At least one M3 was present in 75.6% and all M3 were present in 42.7% of patients. A statistically significant association between the number of PM2 and M3 agenesis was found; the effects of age and gender were not significant. More than half of M3 in patients between 14–17 years old had completed ¼ of their root development. The congenital absence of maxillary PM2 was associated with the absence of maxillary PM2, M3, and no correlation was found in the mandible. In patients with PM2 agenesis, at least one M3 is often present and can be considered as a donor tooth for autotransplantation.
Complications during CT-Guided Lung Nodule Localization: Impact of Needle Insertion Depth and Patient Characteristics
Authors: Chiang Hua , Chen Liang-Kuang , Hsieh Wen-Pei , Tang Yun-Xuan , Lo Chun-Yu
Published: May 2023

Although widely used, CT-guided lung nodule localization is associated with a significant risk of complications, including pneumothorax and pulmonary hemorrhage. This study identified potential risk factors affecting the complications associated with CT-guided lung nodule localization. Data from patients with lung nodules who underwent preoperative CT-guided localization with patent blue vital (PBV) dye at Shin Kong Wu Ho-Su Memorial Hospital, Taiwan, were retrospectively collected. Logistic regression analysis, the chi-square test, and the Mann–Whitney test were used to analyze the potential risk factors for procedure-related complications. We included 101 patients with a single nodule (49 with pneumothorax and 28 with pulmonary hemorrhage). The results revealed that men were more susceptible to pneumothorax during CT-guided localization (odds ratio: 2.48, p = 0.04). Both deeper needle insertion depth (odds ratio: 1.84, p = 0.02) and nodules localized in the left lung lobe (odds ratio: 4.19, p = 0.03) were associated with an increased risk of pulmonary hemorrhage during CT-guided localization. In conclusion, for patients with a single nodule, considering the needle insertion depth and patient characteristics during CT-guided localization procedures is probably important for reducing the risk of complications.
The Fixed-Time Observer-Based Adaptive Tracking Control for Aerial Flexible-Joint Robot with Input Saturation and Output Constraint
Authors: Li Tandong , Li Shaobo , Sun Hang , Lv Dongchao
Published: May 2023

The aerial flexible-joint robot (AFJR) manipulation system has been widely used in recent years. To handle uncertainty, the input saturation and the output constraint existing in the system, a fixed-time observer-based adaptive control scheme (FTOAC) is proposed. First, to estimate the input saturation and disturbances from the internal force between the robot and the flight platform, a fixed-time observer is designed. Second, a tangent-barrier Lyapunov function is introduced to implement the output constraint. Third, adaptive neural networks are introduced for the online identification of nonlinear unknown dynamics in the system. In addition, a fixed-time compensator is designed in this paper to eliminate the adverse effects caused by filtering errors. The stability analysis shows that all the signals of the closed-loop system are bounded, and the system satisfies the condition of fixed-time convergence. Finally, the simulation results prove the superiority of the proposed control strategy by comparing it with the previous schemes.
Robust Flight-Path Angle Consensus Tracking Control for Non-Minimum Phase Unmanned Fixed-Wing Aircraft Formation in the Presence of Measurement Errors
Authors: Zhu Yang , Qin Kaiyu
Published: May 2023

The robust flight-path angle consensus tracking control problem for multiple unmanned fixed-wing aircrafts is investigated in this paper, where the non-minimum phase properties and the presence of measurement errors are systematically addressed. A three-module control scheme is proposed for each aircraft: a Distributed Observer that obtains the available information from the reference system and the neighbor aircraft to provide the estimates of the reference states; a Casual Stable Inversion that calculates the bounded estimates of the desired input, desired external states, and most importantly, desired internal states to resolve the divergence issues caused by the non-minimum phase properties; and a Local Measurement Error Rejection Controller that includes a measurement error estimator (MEE) to actively compensate for the adverse effect of measurement errors to achieve robust consensus tracking control. Stability, convergence, and robustness of the proposed control are analyzed, showing that (1) the non-minimum phase issue can be systematically resolved by the designed Casual Stable Inversion to ensure aircraft internal stability and flight safety, and (2) the consensus tracking accuracy can be improved by tuning a single MEE parameter, which is favorable in practical applications to large-scale unmanned aircraft formations. Comparative simulation results with classic PID-based consensus control demonstrate the advantage of the proposed control in transient oscillations, steady-state tracking accuracy, and robustness against measurement errors.
A Robust Pedestrian Re-Identification and Out-Of-Distribution Detection Framework
Authors: Bouzid Abdelhamid , Sierra-Sosa Daniel , Elmaghraby Adel
Published: May 2023

Pedestrian re-identification is an important field due to its applications in security and safety. Most current solutions for this problem use CNN-based feature extraction and assume that only the identities that are in the training data can be recognized. On the one hand, the pedestrians in the training data are called In-Distribution (ID). On the other hand, in real-world scenarios, new pedestrians and objects can appear in the scene, and the model should detect them as Out-Of-Distribution (OOD). In our previous study, we proposed a pedestrian re-identification based on von Mises–Fisher (vMF) distribution. Each identity is embedded in the unit sphere as a compact vMF distribution far from other identity distributions. Recently, a framework called Virtual Outlier Synthetic (VOS) was proposed, which detects OOD based on synthesizing virtual outliers in the embedding space in an online manner. Their approach assumes that the samples from the same object map to a compact space, which aligns with the vMF-based approach. Therefore, in this paper, we revisited the vMF approach and merged it with VOS to detect OOD data points. Experiment results showed that our framework was able to detect new pedestrians that do not exist in the training data in the inference phase. Furthermore, this framework improved the re-identification performance and holds a significant potential in real-world scenarios.
Operational Mapping of Salinization Areas in Agricultural Fields Using Machine Learning Models Based on Low-Altitude Multispectral Images
Authors: Mukhamediev Ravil , Amirgaliyev Yedilkhan , Kuchin Yan , Aubakirov Margulan , Terekhov Alexei , Merembayev Timur , Yelis Marina , Zaitseva Elena , Levashenko Vitaly , Popova Yelena , Symagulov Adilkhan , Tabynbayeva Laila
Published: May 2023

Salinization of cultivated soil is an important negative factor that reduces crop yields. Obtaining accurate and timely data on the salinity of soil horizons allows for planning the agrotechnical measures to reduce this negative impact. The method of soil salinity mapping of the 0–30 cm layer on irrigated arable land with the help of multispectral data received from the UAV is described in this article. The research was carried out in the south of the Almaty region of Kazakhstan. In May 2022, 80 soil samples were taken from the ground survey, and overflight of two adjacent fields was performed. The flight was carried out using a UAV equipped with a multispectral camera. The data preprocessing method is proposed herein, and several machine learning algorithms are compared (XGBoost, LightGBM, random forest, support vector machines, ridge regression, elastic net, etc.). Machine learning methods provided regression reconstruction to predict the electrical conductivity of the 0–30 cm soil layer based on an optimized list of spectral indices. The XGB regressor model showed the best quality results: the coefficient of determination was 0.701, the mean-squared error was 0.508, and the mean absolute error was 0.514. A comparison with the results obtained based on Landsat 8 data using a similar model was performed. Soil salinity mapping using UAVs provides much better spatial detailing than satellite data and has the possibility of an arbitrary selection of the survey time, less dependence on the conditions of cloud cover, and a comparable degree of accuracy of estimates.
Transformer-Based Detection for Highly Mobile Coded OFDM Systems
Authors: Wang Leijun , Zhou Wenbo , Tong Zian , Zeng Xianxian , Zhan Jin , Li Jiawen , Chen Rongjun
Published: May 2023

This paper is concerned with mobile coded orthogonal frequency division multiplexing (OFDM) systems. In the high-speed railway wireless communication system, an equalizer or detector should be used to mitigate the intercarrier interference (ICI) and deliver the soft message to the decoder with the soft demapper. In this paper, a Transformer-based detector/demapper is proposed to improve the error performance of the mobile coded OFDM system. The soft modulated symbol probabilities are computed by the Transformer network, and are then used to calculate the mutual information to allocate the code rate. Then, the network computes the codeword soft bit probabilities, which are delivered to the classical belief propagation (BP) decoder. For comparison, a deep neural network (DNN)-based system is also presented. Numerical results show that the Transformer-based coded OFDM system outperforms both the DNN-based and the conventional system.
Delay Minimization in RIS-Assisted URLLC Systems under Reliability Constraints
Authors: Song Xiaoyang , Zhao Yingxin , Zhao Wannan , Wu Hong , Liu Zhiyang
Published: May 2023

The ultra-reliable and low-latency communication (URLLC) systems are expected to support the stringent quality of service (QoS) demands in the Internet of Things (IoT) networks. In order to support the strict latency and reliability constraints, it is preferable to deploy a reconfigurable intelligent surface (RIS) in the URLLC systems to improve the link quality. In this paper, we focus on the uplink of an RIS-assisted URLLC system, and we propose to minimize the transmission latency under the reliability constraints. To solve the non-convex problem, a low-complexity algorithm is proposed by using the Alternating Direction Method of Multipliers (ADMM) technique. The RIS phase shifts optimization, which is typically non-convex, is efficiently solved by formulating as a Quadratically Constrained Quadratic Programming (QCQP) problem. Simulation results verify that our proposed ADMM-based method is able to achieve better performance than the conventional semi-definite relaxation (SDR)-based method with lower computational complexity. Our proposed RIS-assisted URLLC system is able to significantly reduce the transmission latency, which highlights the great potential in deploying RIS in the IoT networks with strict reliability requirements.
Optimizing Quantum Classification Algorithms on Classical Benchmark Datasets
Authors: John Manuel , Schuhmacher Julian , Barkoutsos Panagiotis , Tavernelli Ivano , Tacchino Francesco
Published: May 2023

The discovery of quantum algorithms offering provable advantages over the best known classical alternatives, together with the parallel ongoing revolution brought about by classical artificial intelligence, motivates a search for applications of quantum information processing methods to machine learning. Among several proposals in this domain, quantum kernel methods have emerged as particularly promising candidates. However, while some rigorous speedups on certain highly specific problems have been formally proven, only empirical proof-of-principle results have been reported so far for real-world datasets. Moreover, no systematic procedure is known, in general, to fine tune and optimize the performances of kernel-based quantum classification algorithms. At the same time, certain limitations such as kernel concentration effects—hindering the trainability of quantum classifiers—have also been recently pointed out. In this work, we propose several general-purpose optimization methods and best practices designed to enhance the practical usefulness of fidelity-based quantum classification algorithms. Specifically, we first describe a data pre-processing strategy that, by preserving the relevant relationships between data points when processed through quantum feature maps, substantially alleviates the effect of kernel concentration on structured datasets. We also introduce a classical post-processing method that, based on standard fidelity measures estimated on a quantum processor, yields non-linear decision boundaries in the feature Hilbert space, thus achieving the quantum counterpart of the radial basis functions technique that is widely employed in classical kernel methods. Finally, we apply the so-called quantum metric learning protocol to engineer and adjust trainable quantum embeddings, demonstrating substantial performance improvements on several paradigmatic real-world classification tasks.
Quantum Image Encryption Based on Quantum DNA Codec and Pixel-Level Scrambling
Authors: Gao Jie , Wang Yinuo , Song Zhaoyang , Wang Shumei
Published: May 2023

In order to increase the security and robustness of quantum images, this study combined the quantum DNA codec with quantum Hilbert scrambling to offer an enhanced quantum image encryption technique. Initially, to accomplish pixel-level diffusion and create enough key space for the picture, a quantum DNA codec was created to encode and decode the pixel color information of the quantum image using its special biological properties. Second, we used quantum Hilbert scrambling to muddle the image position data in order to double the encryption effect. In order to enhance the encryption effect, the altered picture was then employed as a key matrix in a quantum XOR operation with the original image. The inverse transformation of the encryption procedure may be used to decrypt the picture since all the quantum operations employed in this research are reversible. The two-dimensional optical image encryption technique presented in this study may significantly strengthen the anti-attack of quantum picture, according to experimental simulation and result analysis. The correlation chart demonstrates that the average information entropy of the RGB three channels is more than 7.999, the average NPCR and UACI are respectively 99.61% and 33.42%, and the peak value of the ciphertext picture histogram is uniform. It offers more security and robustness than earlier algorithms and can withstand statistical analysis and differential assaults.
Introduction to the Special Issue “Emergency Remote Teaching during the COVID-19 Lockdown and Its Implications for Higher Education Institutions: An International Perspective”
Authors: Göbel Kerstin , Makarova Elena
Published: May 2023

In spring 2020, the proliferation of the COVID-19 virus and the imposition of subsequent lockdowns across the globe demanded that university institutions undertake an emergency transition toward online teaching [...]