bluuebunny/crossref_metadata_2025 huggingface dataset:
Esophageal Self-Expandable Metal Stents Can Fracture in the Distal Third When Used for Post-Bariatric Surgery Complications: A Single Center Experience and Review of the Literature with Video
Authors: Abboud Yazan , El Helou Mohamad Othman , Meza Joseph , Samaan Jamil S. , Bancila Liliana , Randhawa Navkiran , Park Kenneth H. , Mehdizadeh Shahab , Gaddam Srinivas , Lo Simon K.
Published: June 2024

Background: Esophageal self-expandable metal stents (SEMS) are an important endoscopic tool. These stents have now been adapted successfully to manage post-bariatric surgery complications such as anastomotic leaks and strictures. In centers of expertise, this has become the primary standard-of-care treatment given its minimally invasive nature, and that it results in early oral feeding, decreased hospitalization, and overall favorable outcomes. Self-expandable metal stents (SEMS) fractures are a rare complication of unknown etiology. We aimed to investigate possible causes of SEMS fractures and highlight a unique endoscopic approach utilized to manage a fractured and impaled SEMS. Methods: This is a retrospective study of consecutive patients who underwent esophageal SEMS placement between 2015–2021 at a tertiary referral center to identify fractured SEMS. Patient demographics, stent characteristics, and possible etiologies of fractured SEMS were identified. A comprehensive literature review was also conducted to evaluate all prior cases of fractured SEMS and to hypothesize fracture theories. Results: There were seven fractured esophageal SEMS, of which six were used to manage post-bariatric surgery complications. Five SEMS were deployed with their distal ends in the gastric antrum and proximal ends in the distal esophagus. All stents fractured within 9 weeks of deployment. Most stents (5/7) were at least 10 cm in length with fractures commonly occurring in the distal third of the stents (6/7). The wires of a fractured SEMS were embedded within the esophagogastric junction in one case, prompting the use of an overtube that was synchronously advanced while steadily extracting the stent. Discussion: We suggest the following four etiologies of SEMS fractures: anatomical, physiological, mechanical, and chemical. Stent curvature at the stomach incisura can lead to strain- and stress-related fatigue due to mechanical bending with exacerbation from respiratory movements. Physiologic factors (gastric body contractions) can result in repetitive squeezing of the stent, adding to metal fatigue. Intrinsic properties (long length and low axial force) may be contributing factors. Lastly, the stomach acidic environment may cause nitinol-induced chemical weakness. Despite the aforementioned theories, SEMS fracture etiology remains unclear. Until more data become available, it may be advisable to remove these stents within 6 weeks.
[18F]F-Poly(ADP-Ribose) Polymerase Inhibitor Radiotracers for Imaging PARP Expression and Their Potential Clinical Applications in Oncology
Authors: Ndlovu Honest , Lawal Ismaheel O. , Mdanda Sipho , Kgatle Mankgopo M. , Mokoala Kgomotso M. G. , Al-Ibraheem Akram , Sathekge Mike M.
Published: June 2024

Including poly(ADP-ribose) polymerase (PARP) inhibitors in managing patients with inoperable tumors has significantly improved outcomes. The PARP inhibitors hamper single-strand deoxyribonucleic acid (DNA) repair by trapping poly(ADP-ribose)polymerase (PARP) at sites of DNA damage, forming a non-functional “PARP enzyme–inhibitor complex” leading to cell cytotoxicity. The effect is more pronounced in the presence of PARP upregulation and homologous recombination (HR) deficiencies such as breast cancer-associated gene (BRCA1/2). Hence, identifying HR-deficiencies by genomic analysis—for instance, BRCA1/2 used in triple-negative breast cancer—should be a part of the selection process for PARP inhibitor therapy. Published data suggest BRCA1/2 germline mutations do not consistently predict favorable responses to PARP inhibitors, suggesting that other factors beyond tumor mutation status may be at play. A variety of factors, including tumor heterogeneity in PARP expression and intrinsic and/or acquired resistance to PARP inhibitors, may be contributing factors. This justifies the use of an additional tool for appropriate patient selection, which is noninvasive, and capable of assessing whole-body in vivo PARP expression and evaluating PARP inhibitor pharmacokinetics as complementary to the currently available BRCA1/2 analysis. In this review, we discuss [18F]Fluorine PARP inhibitor radiotracers and their potential in the imaging of PARP expression and PARP inhibitor pharmacokinetics. To provide context we also briefly discuss possible causes of PARP inhibitor resistance or ineffectiveness. The discussion focuses on TNBC, which is a tumor type where PARP inhibitors are used as part of the standard-of-care treatment strategy.
Development of Hydroacoustic Localization Algorithms for AUV Based on the Error-Corrected WMChan-Taylor Algorithm
Authors: Yang Huibao , Gao Xiujing , Li Bangshuai , Xiao Bo , Huang Hongwu
Published: June 2024

Autonomous underwater vehicles (AUVs) are susceptible to non-line-of-sight (NLOS) errors and noise bias at receiving stations during the application of hydroacoustic localization systems, leading to a degradation in positioning accuracy. To address this problem, this paper optimizes the Chan-Taylor algorithm. Initially, we propose the Weighted Modified Chan-Taylor (WMChan-Talor) algorithm, which introduces dynamic weights into the Chan algorithm to correct noise variance at measurement stations, thereby improving the accuracy of AUV positioning. Computer simulations validate the effectiveness of the WMChan-Taylor algorithm in enhancing positioning accuracy. To further address the accuracy degradation caused by noise deviations across different receiving stations, we introduce an error-corrected WMChan-Taylor algorithm. This algorithm utilizes a standard residual function to eliminate significant delays caused by large errors at receiving stations and applies standard residual weighting to improve the combined positioning solution. The performance of the error-corrected WMChan-Taylor algorithm is demonstrated through both computer and semi-physical simulation experiments, confirming its capability to isolate noisier stations and thus enhance overall positioning accuracy.
Defining the Consistent Velocity of Omnidirectional Mobile Platforms
Authors: Rubies Elena , Palacín Jordi
Published: June 2024

The maximum linear (or translational) velocity achievable by an omnidirectional platform is not uniform as it depends on the angular orientation of the motion. This velocity is limited by the maximum angular velocity of the motors driving the wheels and also depends on the mechanical configuration and orientation of the wheels. This paper proposes a procedure to compute an upper bound for the translational velocity, named the consistent velocity of the omnidirectional platform, which is defined as the minimum of the maximum translational velocities achievable by the platform in any angular orientation with no wheel slippage. The consistent velocity is then a uniform translational velocity always achievable by the omnidirectional platform regardless of the angular orientation of the motion. This paper reports the consistent velocity for a set of omnidirectional platforms with three omni wheels that have the same radius and angular distribution but different angular orientations. Results have shown that these platforms can achieve different maximum velocities in different angular orientations although the consistent velocity is the same for all of them. Results have also shown that the consistent velocity has a linear relation with the angular velocity of the motion. The consistent velocity of a mobile platform can be used by its path-planning algorithm as an upper bound that guarantees the execution of any omnidirectional motion at a uniform and maximum translational velocity.
Optimal Combination of the Splitting–Linearizing Method to SSOR and SAOR for Solving the System of Nonlinear Equations
Authors: Liu Chein-Shan , El-Zahar Essam R. , Chang Chih-Wen
Published: June 2024

The symmetric successive overrelaxation (SSOR) and symmetric accelerated overrelaxation (SAOR) are conventional iterative methods for solving linear equations. In this paper, novel approaches are presented by combining a splitting–linearizing method with SSOR and SAOR for solving a system of nonlinear equations. The nonlinear terms are decomposed at two sides through a splitting parameter, which are linearized around the values at the previous step, obtaining a linear equation system at each iteration step. The optimal values of parameters are determined to minimize the reciprocal of the maximal projection, which are sought in preferred ranges using the golden section search algorithm. Numerical tests assess the performance of the developed methods, namely, the optimal splitting symmetric successive over-relaxation (OSSSOR), and the optimal splitting symmetric accelerated over-relaxation (OSSAOR). The chief advantages of the proposed methods are that they do not need to compute the inverse matrix at each iteration step, and the computed orders of convergence by OSSSOR and OSSAOR are between 1.5 and 5.61; they, without needing the inner iterations loop, converge very fast with saving CPU time to find the true solution with a high accuracy.
A New Adaptive Eleventh-Order Memory Algorithm for Solving Nonlinear Equations
Authors: Panday Sunil , Mittal Shubham Kumar , Stoenoiu Carmen Elena , Jäntschi Lorentz
Published: June 2024

In this article, we introduce a novel three-step iterative algorithm with memory for finding the roots of nonlinear equations. The convergence order of an established eighth-order iterative method is elevated by transforming it into a with-memory variant. The improvement in the convergence order is achieved by introducing two self-accelerating parameters, calculated using the Hermite interpolating polynomial. As a result, the R-order of convergence for the proposed bi-parametric with-memory iterative algorithm is enhanced from 8 to 10.5208. Notably, this enhancement in the convergence order is accomplished without the need for extra function evaluations. Moreover, the efficiency index of the newly proposed with-memory iterative algorithm improves from 1.5157 to 1.6011. Extensive numerical testing across various problems confirms the usefulness and superior performance of the presented algorithm relative to some well-known existing algorithms.
Predicting Stroke Risk Based on ICD Codes Using Graph-Based Convolutional Neural Networks
Authors: Tiba Attila , Bérczes Tamás , Bérczes Attila , Zsuga Judit
Published: June 2024

In recent years, convolutional neural networks (CNNs) have emerged as highly efficient architectures for image and audio classification tasks, gaining widespread adoption in state-of-the-art methodologies. While CNNs excel in machine learning scenarios where the data representation exhibits a grid structure, they face challenges in generalizing to other data types. For instance, they struggle with data structured on 3D meshes (e.g., measurements from a network of meteorological stations) or data represented by graph structures (e.g., molecular graphs). To address such challenges, the scientific literature proposes novel graph-based convolutional network architectures, extending the classical convolution concept to data structures defined by graphs. In this paper, we use such a deep learning architecture to examine graphs defined using the ICD-10 codes appearing in the medical data of patients who suffered hemorrhagic stroke in Hungary in the period 2006–2012. The purpose of the analysis is to predict the risk of stroke by examining a patient’s ICD graph. Finally, we also compare the effectiveness of this method with classical machine learning classification methods. The results demonstrate that the graph-based method can predict the risk of stroke with an accuracy of over 73%, which is more than 10% higher than the classical methods.
Dynamic Asymmetric Volatility Spillover and Connectedness Network Analysis among Sectoral Renewable Energy Stocks
Authors: Alrweili Hleil , Ben-Salha Ousama
Published: June 2024

A wide range of statistical and econometric models have been applied in the extant literature to compute and assess the volatility spillovers among renewable stock prices. This research adds to the body of knowledge by analyzing the dynamic asymmetric volatility spillover between major NASDAQ OMX Green Economy Indices, including solar, wind, geothermal, fuel cell, and developer/operator. The novelty of the research is that it distinguishes between positive and negative volatility spillovers in a time-varying fashion and conducts a connectedness network analysis. To do so, the study implements the Time-Varying Parameter Vector Autoregression (TVP-VAR) approach, as well as the connectedness network. The empirical investigation is based on high-frequency data between 18 October 2010, and 2 April 2022. The main findings may be summarized as follows. First, the analysis reveals a shift in the dominance of positive and negative volatility transmission during the study period, which represents compelling evidence of dynamic asymmetric spillover in the volatility transmission between renewable energy stocks. Second, the connectedness analysis indicates that the operator/developer and solar sectors are the net transmitters of both positive and negative volatility to the system. In contrast, the wind, geothermal and fuel cell sectors receive shocks from other renewable energy stocks. The asymmetric spillovers between the renewable energy stocks are confirmed using the block bootstrapping technique. Finally, the dynamic analysis reveals a substantial impact of the COVID-19 outbreak on the interdependence between renewable energy stocks. The findings above are robust to different lag orders and prediction ranges.
Dynamic Mechanism Design for Repeated Markov Games with Hidden Actions: Computational Approach
Authors: Clempner Julio B.
Published: June 2024

This paper introduces a dynamic mechanism design tailored for uncertain environments where incentive schemes are challenged by the inability to observe players’ actions, known as moral hazard. In these scenarios, the system operates as a Markov game where outcomes depend on both the state of payouts and players’ actions. Moral hazard and adverse selection further complicate decision-making. The proposed mechanism aims to incentivize players to truthfully reveal their states while maximizing their expected payoffs. This is achieved through players’ best-reply strategies, ensuring truthful state revelation despite moral hazard. The revelation principle, a core concept in mechanism design, is applied to models with both moral hazard and adverse selection, facilitating optimal reward structure identification. The research holds significant practical implications, addressing the challenge of designing reward structures for multiplayer Markov games with hidden actions. By utilizing dynamic mechanism design, researchers and practitioners can optimize incentive schemes in complex, uncertain environments affected by moral hazard. To demonstrate the approach, the paper includes a numerical example of solving an oligopoly problem. Oligopolies, with a few dominant market players, exhibit complex dynamics where individual actions impact market outcomes significantly. Using the dynamic mechanism design framework, the paper shows how to construct optimal reward structures that align players’ incentives with desirable market outcomes, mitigating moral hazard and adverse selection effects. This framework is crucial for optimizing incentive schemes in multiplayer Markov games, providing a robust approach to handling the intricacies of moral hazard and adverse selection. By leveraging this design, the research contributes to the literature by offering a method to construct effective reward structures even in complex and uncertain environments. The numerical example of oligopolies illustrates the practical application and effectiveness of this dynamic mechanism design.
Editorial for “Special Abilities of Microbes and Their Application in Agro-Biology”
Authors: Ranjan Anuj , Rajput Vishnu D. , Chauhan Abhishek
Published: June 2024

Currently, climate change-related environmental issues associated with agriculture is alarming and poses a potential risk to global food security, causing significant global concern as a result [...]
Critical Involvement of the Thioredoxin Reductase Gene (trxB) in Salmonella Gallinarum-Induced Systemic Infection in Chickens
Authors: Zhu Zhihao , Hu Zuo , Ojima Shinjiro , Yu Xiaoying , Sugiyama Makoto , Ono Hisaya K. , Hu Dong-Liang
Published: June 2024

Salmonella enterica serovar Gallinarum biovar Gallinarum (SG) causes fowl typhoid, a notifiable infectious disease in poultry. However, the pathogenic mechanism of SG-induced systemic infection in chickens remains unclear. Thioredoxin reductase (TrxB) is a redox protein crucial for regulating various enzyme activities in Salmonella serovar, but the role in SG-induced chicken systemic infection has yet to be determined. Here, we constructed a mutant SG strain lacking the trxB gene (trxB::Cm) and used chicken embryo inoculation and chicken oral infection to investigate the role of trxB gene in the pathogenicity of SG. Our results showed that trxB::Cm exhibited no apparent differences in colony morphology and growth conditions but exhibited reduced tolerance to H2O2 and increased resistance to bile acids. In the chicken embryo inoculation model, there was no significant difference in the pathogenicity of trxB::Cm and wild-type (WT) strains. In the chicken oral infection, the WT-infected group exhibited typical clinical symptoms of fowl typhoid, with complete mortality between days 6 and 9 post infection. In contrast, the trxB::Cm group showed a 100% survival rate, with no apparent clinical symptoms or pathological changes observed. The viable bacterial counts in the liver and spleen of the trxB::Cm-infected group were significantly reduced, accompanied by decreased expression of cytokines and chemokines (IL-1β, IL-6, IL-12, CXCLi1, TNF-α, and IFN-γ), which were significantly lower than those in the WT group. These results show that the pathogenicity of the trxB-deficient strain was significantly attenuated, indicating that the trxB gene is a crucial virulence factor in SG-induced systemic infection in chickens, suggesting that trxB may become a potentially effective target for controlling and preventing SG infection in chickens.
Use of PCR Cycle Threshold and Clinical Interventions to Aid in the Management of Pediatric Clostridioides difficile Patients
Authors: Suleiman Mohammed , Tang Patrick , Imam Omar , Morales Princess , Altrmanini Diyna , Barr Kelli L. , Roberts Jill C. , Pérez-López Andrés
Published: June 2024

Better diagnostic tools are needed to improve the diagnosis of Clostridioides difficile infections (CDI) and reduce the overtreatment of colonized children. In this study, we evaluated two polymerase chain reaction (PCR) assays (Cepheid GeneXpert C. difficile and the Gastroenteritis PCR Panel by QIAstat-Dx) as a standalone method in combination with the PCR cycle threshold (Ct) value in positive samples to predict the presence of free toxins. We also evaluated the clinical impact of reporting toxin production results and provided comments alongside the PCR results in our pediatric population. PCR-positive stool samples from pediatric patients (aged 2 to 18 years old) were included in our study and tested for the presence of toxins A and B using the C. difficile Quik Chek Complete kit. For the clinical intervention, the CDI treatment rates 6 months pre- and post-intervention were compared. The use of PCR Ct value showed excellent sensitivity (100%) at a Ct value cutoff of 26.1 and 27.2 using the Cepheid GeneXpert C. difficile and the Gastroenteritis PCR Panel by QIAstat-Dx, respectively, while the toxin test showed inferior sensitivity of 64% in the PCR-positive samples. In addition, CDI treatment rates were decreased by 23% post-intervention. The results of our study suggest that nucleic acid amplification test (NAAT) assays supplemented by the use of PCR Ct value for positive samples can be used as standalone tests to differentiate CDI from colonization. Furthermore, the reporting of toxin production along with the PCR results can help reduce the unnecessary treatment of colonized children.
Genomic Insights into Edwardsiella ictaluri: Molecular Epidemiology and Antimicrobial Resistance in Striped Catfish (Pangasianodon hypophthalmus) Aquaculture in Vietnam
Authors: Erickson Vera Irene , Dung Tu Thanh , Khoi Le Minh , Hounmanou Yaovi Mahuton Gildas , Phu Tran Minh , Dalsgaard Anders
Published: June 2024

Edwardsiella ictaluri is responsible for causing bacillary necrosis (BNP) in striped catfish (Pangasianodon hypophthalmus) in Vietnam. This study offers a comprehensive genomic characterization of E. ictaluri to enhance understanding of the molecular epidemiology, virulence, and antimicrobial resistance. E. ictaluri isolates were collected from diseased striped catfish in the Mekong Delta. The species was confirmed through PCR. Antimicrobial susceptibility testing was conducted using minimum inhibitory concentrations for commonly used antimicrobials. Thirty representative isolates were selected for whole genome sequencing to delineate their genomic profiles and phylogeny. All strains belonged to ST-26 and exhibited genetic relatedness, differing by a maximum of 90 single nucleotide polymorphisms. Most isolates carried multiple antimicrobial resistance genes, with the tet(A) gene present in 63% and floR in 77% of the genomes. The ESBL gene, blaCTX-M-15, was identified in 30% of the genomes. Three plasmid replicon types were identified: IncA, p0111, and IncQ1. The genomes clustered into two clades based on their virulence gene profile, one group with the T3SS genes and one without. The genetic similarity among Vietnamese isolates suggests that disease spread occurs within the Mekong region, underscoring the importance of source tracking, reservoir identification, and implementation of necessary biosecurity measures to mitigate spread of BNP.
A Probiotic Bacterium with Activity against the Most Frequent Bacteria and Viruses Causing Pediatric Diarrhea: Bifidobacterium longum subsp. infantis CECT 7210 (B. infantis IM1®)
Authors: Moreno-Muñoz José Antonio , Ojeda Jesús Delgado , López Jesús Jiménez
Published: June 2024

The second leading cause of death in children under five years old is diarrheal disease. Probiotics, specifically bifidobacteria, have been associated with a reduction in the number of diarrhea episodes and their severity in babies. In this paper, we summarize the preclinical and clinical evidence of the efficacy of B. longum subsp. infantis IM1® against various gastrointestinal pathogens using in vitro models, animal models, and clinical studies carried out in our laboratory. The preclinical data demonstrate that IM1® effectively inhibits rotavirus replication (by up to 36.05%) in MA-104 and HT-29 cells and from infection (up to 48.50%) through the production of an 11-amino-acid peptide. IM1® displays the capability to displace pathogens from enterocytes, particularly Cronobacter sakazakii and Salmonella enterica, and to reduce the adhesion to the HT29 cells of C. sakazakii and Shigella sonnei. In animal models, the IM1® strain exhibits in vivo protection against rotavirus and improves the clinical symptomatology of bacterial gastroenteritis. A clinical study involving infants under 3 months of age revealed that IM1® reduced episodes of diarrhea, proving to be safe, well tolerated, and associated with a lower prevalence of constipation. B. infantis IM1® emerges as an effective probiotic, diminishing episodes of diarrhea caused by gastrointestinal pathogens.
Quantity, Duration, Adherence, and Reasons for Dietary Supplement Use among Adults: Results from NHANES 2011–2018
Authors: Liu Ligang , Tao Heqing , Xu Jinyu , Liu Lijun , Nahata Milap C.
Published: June 2024

Dietary supplement use is common among US adults. We aimed to investigate the quantity, duration, adherence, and reasons for supplement use in individuals who take supplements. Data from 2011 to 2018 from the National Health and Nutrition Examination Survey (NHANES) dataset were analyzed. Four cycles of data were combined to estimate these outcomes. Results are presented as overall group and by subgroups. All analyses were weighted to be nationally representative. The Taylor Series Linearization approach was used to generate variance estimates. A total of 12,529 participants were included. Over 70% of these individuals reported taking more than one unit of dietary supplements daily. Notably, approximately 40% had been taking supplements for more than five years and about 67% were highly adherent to at least one supplement. However, only 26.9% of these supplements were taken following a doctor’s recommendation. The primary reasons for dietary supplements intake included improving overall health (37.2%), maintaining health (34.7%), bone health (21.4%), and diet supplementation (20.3%). Our findings indicate that most participants proactively used multiple dietary supplements focused on self-managed health and prevention, with substantial dedication to long-term use and high adherence. Healthcare professionals should play a more active role in guiding such behaviors to optimize the health outcomes of dietary supplement users across the United States.
Repeated Sulforaphane Treatment Reverses Depressive-like Behavior and Exerts Antioxidant Effects in the Olfactory Bulbectomy Model in Mice
Authors: Pańczyszyn-Trzewik Patrycja , Stachowicz Katarzyna , Misztak Paulina , Nowak Gabriel , Sowa-Kućma Magdalena
Published: June 2024

Growing evidence suggests that activators of nuclear factor erythroid-derived 2-like 2 (Nrf2), such as sulforaphane, may represent promising novel pharmacological targets for conditions related to oxidative stress, including depressive disorder. Therefore, we conducted a study to explore the behavioral and biochemical effects of repeated (14 days) sulforaphane (SFN) treatment in the olfactory bulbectomy (OB) animal model of depression. An open field test (OFT), splash test (ST), and spontaneous locomotor activity test (LA) were used to assess changes in depressive-like behavior and the potential antidepressant-like activity of SFN. The OB model induced hyperactivity in mice during the OFT and LA as well as a temporary loss of self-care and motivation in the ST. The repeated administration of SFN (10 mg/kg) effectively reversed these behavioral changes in OB mice across all tests. Additionally, a biochemical analysis revealed that SFN (10 mg/kg) increased the total antioxidant capacity in the frontal cortex and serum of the OB model. Furthermore, SFN (10 mg/kg) significantly enhanced superoxide dismutase activity in the serum of OB mice. Overall, the present study is the first to demonstrate the antidepressant-like effects of repeated SFN (10 mg/kg) treatment in the OB model and indicates that these benefits may be linked to improved oxidative status.
Silent Bird Poisoning in Poland: Reconfirmation of Bromadiolone and Warfarin as the Proximal Causes Using GC-MS/MS-Based Methodology for Forensic Investigations
Authors: Kobylarz Damian , Paprotny Łukasz , Wianowska Dorota , Gnatowski Maciej , Jurowski Kamil
Published: June 2024

The extensive use of rodenticides poses a severe threat to non-target species, particularly birds of prey and scavengers. In this study, a GC-MS/MS-based method was used to unlock the cause of bird deaths in Poland. Organs (liver, heart, kidney, and lungs) collected during autopsies of two rooks (Corvus frugilegus) and one carrion crow (Corvus corone corone), as well as fecal samples, were analyzed for the presence of anticoagulant coumarin derivatives, i.e., warfarin and bromadiolone. As for warfarin, the highest concentration was found in crow samples overall, with concentrations in the feces and lungs at 5.812 ± 0.368 µg/g and 4.840 ± 0.256 µg/g, respectively. The heart showed the lowest concentration of this compound (0.128 ± 0.01 µg/g). In the case of bromadiolone, the highest concentration was recorded in the liver of a rook (16.659 ± 1.499 µg/g) and this concentration significantly exceeded the levels in the other samples. By revealing the reality of the threat, these discoveries emphasize the need to regulate and monitor the trade in rodenticides.
Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis
Authors: Zou Mingrui , Yang Jichun
Published: June 2024

Millions of patients suffer from type 1 diabetes (T1D) and its associated complications. Nevertheless, the pursuit of a cure for T1D has encountered significant challenges, with a crucial impediment being the lack of biomarkers that can accurately predict the progression of T1D and reliable therapeutic targets for T1D. Hence, there is an urgent need to discover novel protein biomarkers and therapeutic targets, which holds promise for targeted therapy for T1D. In this study, we extracted summary-level data on 4907 plasma proteins from 35,559 Icelanders and 2923 plasma proteins from 54,219 UK participants as exposures. The genome-wide association study (GWAS) summary statistics on T1D and T1D with complications were obtained from the R9 release results from the FinnGen consortium. Summary-data-based Mendelian randomization (SMR) analysis was employed to evaluate the causal associations between the genetically predicted levels of plasma proteins and T1D-associated outcomes. Colocalization analysis was utilized to investigate the shared genetic variants between the exposure and outcome. Moreover, transcriptome analysis and a protein–protein interaction (PPI) network further illustrated the expression patterns of the identified protein targets and their interactions with the established targets of T1D. Finally, a Mendelian randomization phenome-wide association study evaluated the potential side effects of the identified core protein targets. In the primary SMR analysis, we identified 72 potential protein targets for T1D and its complications, and nine of them were considered crucial protein targets. Within the group were five risk targets and four protective targets. Backed by evidence from the colocalization analysis, the protein targets were classified into four tiers, with MANSC4, CTRB1, SIGLEC5 and MST1 being categorized as tier 1 targets. Delving into the DrugBank database, we retrieved 11 existing medications for T1D along with their therapeutic targets. The PPI network clarified the interactions among the identified potential protein targets and established ones. Finally, the Mendelian randomization phenome-wide association study corroborated MANSC4 as a reliable target capable of mitigating the risk of various forms of diabetes, and it revealed the absence of adverse effects linked to CTRB1, SIGLEC5 and MST1. This study unveiled many protein biomarkers and therapeutic targets for T1D and its complications. Such advancements hold great promise for the progression of drug development and targeted therapy for T1D.
Formulation and Evaluation of Polysaccharide Microparticles for the Controlled Release of Propranolol Hydrochloride
Authors: Stojmenovski Aneta , Gatarić Biljana , Vučen Sonja , Railić Maja , Krstonošić Veljko , Kukobat Radovan , Mirjanić Maja , Škrbić Ranko , Račić Anđelka
Published: June 2024

Propranolol hydrochloride, a non-cardio-selective beta blocker, is used to treat several conditions in children, including hypertension, arrhythmias, hyperthyroidism, hemangiomas, etc. Commercial liquid formulations are available in Europe and the US, but they have disadvantages, such as limited stability, bitter taste, and the need for multiple daily doses due to the drug’s short half-life. Considering these limitations, controlled-release solid formulations, such as microparticles, may offer a better solution for pediatric administration. The main objective of this study was to formulate an encapsulation system for propranolol hydrochloride, based on sodium alginate and other polysaccharide polymers, to control and prolong its release. Microparticles were prepared using the ionotropic gelation method, which involves instilling a polymer solution into a solution of gelling ions via the extrusion technique. Physicochemical characterization was conducted by assessing the entrapment efficiency, drug loading, swelling index, microparticle size, rheological properties, and surface tension. In order to improve the characteristics of the tested microparticles, selected formulations were coated with chitosan. Further experimental work included differential scanning calorimetry (DSC), Fourier transform infrared (FTIR) analysis, and SEM imaging. This in vitro release study showed that chitosan-coated microparticles demonstrate favorable properties, suggesting a novel approach to formulating pediatric dosage forms, although further optimization is necessary.
Long-Term Stability Test for Femtosecond Laser-Irradiated SnO2-Nanowire Gas Sensor for C7H8 Gas Sensing
Authors: Ahn Sanghoon , Chun Kang Woo , Park Changkyoo
Published: June 2024

In this study, femtosecond (FS) laser irradiation with different laser energy densities of 138, 276, and 414 mJ/cm2 is applied to SnO2-nanowire (NW) gas sensors, and the effect of the FS laser irradiation on the gas sensor response toward toluene (C7H8) gas is investigated. The FS laser irradiation causes oxygen deficiency in the SnO2 NWs and forms SnO and SnOx. Moreover, an embossing surface with multiple nano-sized bumps is created on the SnO2 NW surface because of the FS laser irradiation. The FS laser-irradiated SnO2-NW gas sensor exhibits superior sensing performance compared with the pristine SnO2-NW gas sensor. Moreover, the FS laser energy density significantly affects gas-sensing performance, and the highest sensor response is achieved by the gas sensor irradiated at 138 mJ/cm2. The long-term stability test of the laser-irradiated SnO2-NW gas sensor is performed by comparing fresh and 6-month-old gas sensors in different gas concentrations and relative humidity levels. Comparable gas-sensing behaviors are examined between the fresh and 6-month-old gas sensor, and this verifies the robustness of the laser-irradiated SnO2-NW gas sensor.
Green Synthesis of Silver Nanoparticles with Hyssopus officinalis and Salvia officinalis Extracts, Their Properties, and Antifungal Activity on Fusarium spp.
Authors: Dėnė Lina , Chrapačienė Simona , Laurinaitytė Greta , Rudinskaitė Aira , Viškelis Jonas , Viškelis Pranas , Balčiūnaitienė Aistė
Published: June 2024

Recent focus has been given to nanoparticles as an alternative fungicidal compound instead of chemical ones. More environmentally friendly ways of synthesis are the highest priority regarding the antifungal agents in the agriculture sector. Therefore, in this research, hyssop (H. officinalis) and sage (S. officinalis) aqueous extracts were prepared and used as a reducing source in the green synthesis of silver nanoparticles (AgNPs). Aqueous extracts and green synthesized AgNPs were examined for phytochemical composition and antioxidant capacity. Hyssop and sage extracts based AgNPs were analyzed using UV-vis spectrometry, SEM-EDS, and TEM-EDS. Antifungal activity against Fusarium spp. isolates collected from different infected crops was determined. Fusarium spp. isolates from strawberry, asparagus, pea, carrot, wheat, and rapeseed samples identified at the molecular level by translation elongation factor 1-alpha (TEF1α) gene amplification and sequencing. Green synthesized AgNPs had lower phytochemical content, however higher antioxidant activity compared to pure extracts. Both hyssop and sage extracts are suitable reducing agents for AgNPs formation, and sage extract results in larger particle size. Aqueous hyssop extract had higher antifungal activity than aqueous sage extract. However, a 10% concentration of whole sage extract based AgNPs solution, added to the PDA medium, and a 5% concentration of hyssop extract based AgNPs inhibited Fusarium spp. the most. F. proliferatum was the most sensitive to all treatments among the other fungi.
Comprehensive Study on the 143 A.D. West Gangu Earthquake in the West Qinling Area, Northeastern Margin of Tibetan Plateau
Authors: Su Ruihuan , Yuan Daoyang , Xie Hong , Wang Aiguo , Wen Yameng , Yu Jinchao , Chen Yanwen , Li Hongqiang , Sun Hao , Zhang Lijun
Published: June 2024

The 143 A.D. west Gangu earthquake is documented to have occurred in the West Qinling area, which is located on the northeastern margin of the Tibetan Plateau. Initial limited historical records suggest the earthquake took place along the West Qinling fault (WQLF) in the western region of Gangu County. However, the absence of corresponding geological and geomorphological evidence has posed a considerable challenge in accurately quantifying parameters such as the precise location, magnitude, and seismogenic fault segment in earlier investigations. In this study, a comprehensive examination of multiple residual surface rupture zones within the macroseismic zone of this earthquake enabled the determination of the seismogenic structure, magnitude, and rupture zone scale through diverse methodologies, which include field geological investigations, chronology testing, Unmanned Aerial Vehicle (UAV) aerial surveying, and interpretation of landslides along the fault zone. The results reveal that the seismogenic structure of this seismic event is associated with the Zhangxian fault segment of the WQLF, also marked by a dense distribution of large landslides from Zhangxian to Yuanyangzhen. The epicenter was identified at the eastern end of the Zhangxian fault segment of the WQLF. Furthermore, the magnitude of the 143 A.D. west Gangu earthquake is estimated to be approximately Ms 7–7.3, with the residual surface rupture zone intermittently extending over about 22 km and a maximum horizontal dislocation along the rupture zone of 2.8 ± 0.5 m. This detailed investigation contributes foundational insights for further evaluating the seismic risk across various segments of the WQLF.
An Identification Method of Corner Reflector Array Based on Mismatched Filter through Changing the Frequency Modulation Slope
Authors: Xia Le , Wang Fulai , Pang Chen , Li Nanjun , Peng Runlong , Song Zhiyong , Li Yongzhen
Published: June 2024

The corner reflector is an effective means of interference for radar seekers due to its high jamming intensity, wide frequency band, and combat effectiveness ratio. Properly arranging multiple corner reflectors in an array can form dilution jamming that resembles ships, substantially enhancing the interference effect. This results in a significant decline in the precision attack efficiency of radar seekers. Hence, it is critical to accurately identify corner reflector array. The common recognition methods involve extracting features on the high-resolution range profile (HRRP) and polarization domain. However, the former is constrained by the number of corner reflectors, while the latter is affected by the accuracy of polarization measurement, both of which have limited performance on the identification of corner reflector array. In terms of the evident variations in physical structures, there must be differences in their scattering characteristics. To highlight the differences, this paper proposes a new method based on the concept of mismatched filtering, which involves changing the frequency modulation slope of the chirp signal in the filter. Then, the variance of width and intervals within a specific scope are extracted as features to characterize these differences, and an identification process is designed in combination with the support vector machine. The simulation experiments demonstrate that the proposed method exhibits stable discriminative performance and can effectively combat dilution jamming. Its accuracy rate exceeds 0.86 when the signal-to-noise ratio is greater than 0 dB. Compared to the HRRP methods, the recognition accuracy of the proposed algorithm improves 15% in relation to variations in the quantity of corner reflectors.
Harnessing Machine Learning and Data Fusion for Accurate Undocumented Well Identification in Satellite Images
Authors: Kadeethum Teeratorn , Downs Christine
Published: June 2024

This study utilizes satellite data to detect undocumented oil and gas wells, which pose significant environmental concerns, including greenhouse gas emissions. Three key findings emerge from the study. Firstly, the problem of imbalanced data is addressed by recommending oversampling techniques like Rotation–GaussianBlur–Solarization data augmentation (RGS), the Synthetic Minority Over-Sampling Technique (SMOTE), or ADASYN (an extension of SMOTE) over undersampling techniques. The performance of borderline SMOTE is less effective than that of the rest of the oversampling techniques, as its performance relies heavily on the quality and distribution of data near the decision boundary. Secondly, incorporating pre-trained models trained on large-scale datasets enhances the models’ generalization ability, with models trained on one county’s dataset demonstrating high overall accuracy, recall, and F1 scores that can be extended to other areas. This transferability of models allows for wider application. Lastly, including persistent homology (PH) as an additional input improves performance for in-distribution testing but may affect the model’s generalization for out-of-distribution testing. A careful consideration of PH’s impact on overall performance and generalizability is recommended. Overall, this study provides a robust approach to identifying undocumented oil and gas wells, contributing to the acceleration of a net-zero economy and supporting environmental sustainability efforts.
Enhancing Histopathological Image Classification Performance through Synthetic Data Generation with Generative Adversarial Networks
Authors: Ruiz-Casado Jose L. , Molina-Cabello Miguel A. , Luque-Baena Rafael M.
Published: June 2024

Breast cancer is the second most common cancer worldwide, primarily affecting women, while histopathological image analysis is one of the possibile methods used to determine tumor malignancy. Regarding image analysis, the application of deep learning has become increasingly prevalent in recent years. However, a significant issue is the unbalanced nature of available datasets, with some classes having more images than others, which may impact the performance of the models due to poorer generalizability. A possible strategy to avoid this problem is downsampling the class with the most images to create a balanced dataset. Nevertheless, this approach is not recommended for small datasets as it can lead to poor model performance. Instead, techniques such as data augmentation are traditionally used to address this issue. These techniques apply simple transformations such as translation or rotation to the images to increase variability in the dataset. Another possibility is using generative adversarial networks (GANs), which can generate images from a relatively small training set. This work aims to enhance model performance in classifying histopathological images by applying data augmentation using GANs instead of traditional techniques.
Displacement Sensing for Laser Self-Mixing Interferometry by Amplitude Modulation and Integral Reconstruction
Authors: Huang Yidan , Lai Wenzong , Chen Enguo
Published: June 2024

To robustly and adaptively reconstruct displacement, we propose the amplitude modulation integral reconstruction method (AM-IRM) for displacement sensing in a self-mixing interferometry (SMI) system. By algebraically multiplying the SMI signal with a high-frequency sinusoidal carrier, the frequency spectrum of the signal is shifted to that of the carrier. This operation overcomes the issue of frequency blurring in low-frequency signals associated with continuous wavelet transform (CWT), enabling the precise extraction of the Doppler frequency of the SMI signal. Furthermore, the synchrosqueezing wavelet transform (SSWT) is utilized to enhance the frequency resolution of the Doppler signal. Our experimental results demonstrate that the proposed method achieves a displacement reconstruction accuracy of 21.1 nm (0.89%). Additionally, our simulations demonstrated that this method can accurately reconstruct target displacement under the conditions of time-varying optical feedback intensity or a signal-to-noise ratio (SNR) of 0 dB, with a maximum root mean square (RMS) error of 22.2 nm. These results highlight its applicability in real-world environments. This method eliminates the need to manually determine the window length for time–frequency conversion, calculate the parameters of the SMI system, or add additional optical devices, making it easy to implement.
Research on Unsupervised Low-Light Railway Fastener Image Enhancement Method Based on Contrastive Learning GAN
Authors: Cai Yijie , Liu Xuehai , Li Huoxing , Lu Fei , Gu Xinghua , Qin Kang
Published: June 2024

The railway fastener, as a crucial component of railway tracks, directly influences the safety and stability of a railway system. However, in practical operation, fasteners are often in low-light conditions, such as at nighttime or within tunnels, posing significant challenges to defect detection equipment and limiting its effectiveness in real-world scenarios. To address this issue, this study proposes an unsupervised low-light image enhancement algorithm, CES-GAN, which achieves the model’s generalization and adaptability under different environmental conditions. The CES-GAN network architecture adopts a U-Net model with five layers of downsampling and upsampling structures as the generator, incorporating both global and local discriminators to help the generator to preserve image details and textures during the reconstruction process, thus enhancing the realism and intricacy of the enhanced images. The combination of the feature-consistency loss, contrastive learning loss, and illumination loss functions in the generator structure, along with the discriminator loss function in the discriminator structure, collectively promotes the clarity, realism, and illumination consistency of the images, thereby improving the quality and usability of low-light images. Through the CES-GAN algorithm, this study provides reliable visual support for railway construction sites and ensures the stable operation and accurate operation of fastener identification equipment in complex environments.
Characteristics and Clinical Assessment of Elbow Pain in Youth Baseball Players
Authors: Koseki Hironobu , Kajiyama Shiro , Shida Takayuki , Tomonaga Iku , Nishiyama Yuta , Yoshida Daisuke , Mizukami Satoshi , Yamaguchi Kazuhiro , Imai Chieko
Published: June 2024

Elbow injuries related to the throwing motion in baseball during the growth period present difficulties for early detection and may cause serious future disabilities. This study aimed to comprehensively determine the characteristics and clinical assessment of elbow pain in youth baseball players. Two hundred and sixteen young baseball players underwent elbow medical examination. Basic information and physical examination, clinical assessment, and ultrasonography results were examined. Univariate analyses were statistically performed between the pain-free (98 participants) and elbow pain (118 participants) groups. The mean age was 11.6 years, and ultrasonographic abnormalities were found on the medial side of the elbow in 37.5%. In total, 118 (54.6%) participants experienced elbow pain, with 64.4% of them complaining of elbow pain on the medial side. Players with multiple positions (≥2 positions) had a significantly higher prevalence of elbow pain. Height, weight, length of baseball experience, and positive rates of horizontal flexion and moving valgus stress tests were higher in the elbow pain group than in the pain-free group. The risk factors and clinical assessment for elbow pain are useful for the prevention and early detection of throwing elbow injuries in youth baseball players.