bluuebunny/crossref_metadata_2025 huggingface dataset:
Biomechanical and physiological biomarkers are useful indicators of military personnel readiness: a multi-institutional, multinational research collaboration
Authors: Doyle Timothy L A , Nindl BC , Wills JA , Koltun KJ , Fain AC
Published: October 2024

A ubiquitous problem facing military organisations is musculoskeletal injury (MSKI) risk identification. Recently, two research groups, each with their own funding, collaborated to address this problem. Combining their respective areas of expertise in biomechanics and physiological biomarkers, the group explored this problem in the laboratory and in the field. They have developed a machine learning model in a US Marine Corps (USMC) officer cadet cohort that identifies MSKI risk from a single jump test, identified a minimum inertial measurement unit sensor array to quantity jump and squat performance and have identified sex differences in overuse, lower-limb injury risk. This machine learning model was able to correctly predict lift to place within 4 kg using a testing data set and less than 1 kg in the training set of data. Such collaborative approaches are encouraged to address complicated research problems. To assemble an effective team, consider forming groups that best complement each other’s areas of expertise and prioritise securing separate funding to ensure each group can act independently. By doing this, the group has assessed the suitability and feasibility of various wearable technologies, used machine learning to gain insights into USMC physiological training adaptations, and developed an understanding of MSKI risk profiles within this cohort.
Challenge of cardiovascular prevention in primary care: achievement of lifestyle, blood pressure, lipids and diabetes targets for primary prevention in England – results from ASPIRE-3-PREVENT cross-sectional survey
Authors: Kotseva Kornelia , Jennings Catriona , Bassett Paul , Adamska Agnieszka , Hobbs Richard , Wood David
Published: October 2024

Background

Implementation of the cardiovascular disease (CVD) prevention guidelines in the UK has been repeatedly evaluated under the auspices of the British Cardiovascular Society in three Action on Secondary and Primary Prevention by Intervention to Reduce Events (ASPIRE) surveys in 1994–1995, 2008–2010 and 2017–2019. The primary care arm of ASPIRE-2-PREVENT (A-3-P) was conducted to evaluate lifestyle and medical risk factor management in people at high risk of atherosclerotic CVD in everyday clinical practice.

Methods

A-3-P was a cross-sectional survey in 27 general practices and health centres across 5 English National Health Service regions. Patients with no history of atherosclerotic CVD started on blood pressure and/or lipid and/or glucose lowering treatments were identified retrospectively and interviewed at least 6 months after the initiation of medication.

Results

557 patients attended the interview and examination (45.8% women; mean age 61.7±10.8 years). The risk factor control was poor: 9.3% of patients were smokers, 38.1% obese (body mass index≥30 kg/m2) and 53.5% centrally obese (waist circumference≥88 cm for women, ≥102 cm for men). Only 37.8% of patients on blood pressure-lowering therapies achieved the target of<140/90 mm Hg. Among treated dyslipidaemic patients, 59.5% reached the low-density lipoprotein cholesterol target of <2.6 mmol/L. 62% of patients with self-reported diabetes mellitus attained the glycated haemoglobin target of <7.0%.

Conclusion

The results of A-3-P survey show that large proportions of people at high CVD risk have poor control of lifestiles and medical risk factors. There is considerable potential to raise the standards of preventive cardiology care by providing comprehensive, multidisciplinary prevention programmes addressing all aspects of risk factor management to reduce the total risk of future CVD.
Coupled CFD–DEM modeling of surface erosion in granular soils: simulation of erosion function apparatus experiments
Authors: Ham Soo-Min , Zhang Kun , Petrie John , Kwon Tae-Hyuk
Published: October 2024

This study introduces a numerical modeling approach that couples the computational fluid dynamics (CFD) with the discrete element method (DEM) to simulate grain-scale soil erosion processes induced by water flows. In this modeling framework, CFD simulates fluid flows by solving the volume-averaged Navier–Stokes equations, and uses the k–ω turbulent model for turbulent flows. Simultaneously, DEM computes the displacement of solid particles by incorporating the fluid–particle interactions driven by fluid flows while adhering to Newton’s laws of motion. These interactions encompass drag force, buoyancy force, pressure-gradient force, and viscous force exerted by fluid flows and acting on the particles. The coupled CFD–DEM modeling adeptly replicates soil erosion processes, demonstrating good alignment with results obtained from laboratory erosion function apparatus tests. In particular, the DEM facilitates the estimation of shear stress acting on the soil surface based on fluid–particle interaction forces, which has been roughly approximated by empirical or semi-empirical models. This study underscores the capability of coupled CFD–DEM in providing valuable insights into the grain-scale behavior of soil particles subjected to fluid flows, with the potential for extension to address soil erosion and fines migration.
Classical mechanics in noncommutative spaces: confinement and more
Authors: Kupriyanov Vladislav , Kurkov Maxim , Sharapov Alexey
Published: October 2024

We consider a semi-classical approximation to the dynamics of a point particle in a noncommutative space. In this approximation, the noncommutativity of space coordinates is described by a Poisson bracket. For linear Poisson brackets, the corresponding phase space is given by the cotangent bundle of a Lie group, with the Lie group playing the role of a curved momentum space. We show that the curvature of the momentum space may lead to rather unexpected physical phenomena such as an upper bound on the velocity of a free nonrelativistic particle, bounded motion for repulsive central force, and no-fall-into-the-centre for attractive Coulomb potential. We also consider a superintegrable Hamiltonian for the Kepler problem in 3-space with $$\mathfrak {su}(2)$$

su
(
2
)

noncommutativity. The leading correction to the equations of motion due to noncommutativity is shown to be described by an effective monopole potential.
Influence of Entrepreneur Social Network on New Product Development Performance of Enterprises Under Intelligent Big Data
Authors: Su Yuantao
Published: October 2024

In the complex market environment, it is difficult for enterprises to innovate only by their own internal product resources. In order to improve the performance level of new product development, this paper puts forward the influence of entrepreneur social network on the performance of new product development under smart big data. The process of new product development is modeled, and the influence of entrepreneur social network on enterprise new product development performance is analyzed from two aspects: vertical network quality and horizontal network quality. According to the analysis results, build an intelligent big data platform, and use this platform to realize the mining and analysis of enterprise-related data; On this basis, EM algorithm is used to mine the performance data of enterprise new product development, DEA/AHP model is used to evaluate the performance level of enterprise new product development, and the evaluation results are combined with the influence model of entrepreneur social network on enterprise new product development performance to realize the influence analysis of entrepreneur social network on enterprise new product development performance. The experimental results show that the method is highly recognized by experts, which shows that the analysis results are reliable, and the correlation between entrepreneur social network and enterprise new product development performance can be obtained, which provides reference for enterprise new product development.
Visual Communication Method of Multi-Frame Film and Television Special Effects Images Based on Deep Learning
Authors: Qi Dawei
Published: October 2024

In the view of art form change, there is a perspective problem in the detail part of multi-frame film and television special effects (TSEs) images in the special effects rendering module, which leads to the greater ambiguity of multi-frame film and TSEs images. In order to advance the talent of identifying the detail structures and characteristics of multi-frame film and TSEs images, a visual communication technology of multi-frame film and TSEs images in the view of art form change grounded on deep learning is suggested. The transmission relation model of detail characteristics of multi-frame film and TSEs images in the field of artistic form change is constructed, and the attenuation treatment of detail action special effects of multi-frame film and TSEs images in the field of artistic form change is carried out with the assistance of deep learning approaches. The detailed information and color of multi-frame film and TSEs images are obtained by using prior map knowledge instead of rendering basic color. Over the technique of filtering and preserving, the multi-frame film and TSEs images are directed to screen the detailed feature quantity of the input film and TSEs images in the field of artistic form change. In addition, the Sobel operator is practiced to perceive the scrawny edge information of multi-frame film and TSEs images, and block fitting interpolation and depth filtering analysis are used in the edge area to realize the visual communication and color feature parameter identification and amplification of multi-frame film and TSEs images in the field of artistic form change, so as to improve the fuzzy enhancement of multi-frame film and TSEs images. The test results and results indicate that the average Peak signal-to-noise ratio (PSNR) of the proposed method is about 37.7166[Formula: see text]dB, which is 49.08% and 52.08% higher than the PSNRs of the Harris method and SUFR method, respectively. It has been confirmed that this scheme can successfully solve the edge blurring and distortion problems of multi-frame movies and image images in the field of art form change.
Improved Faster R-CNN Based on Multi-Scale Module for Detecting Weak Ground Targets in Remote Sensing Images
Authors: He Yinggang
Published: October 2024

In order to optimize the detection capability of small and weak ground targets in remote sensing images, a remote sensing image ground weak target detection method based on multi-scale module improved Faster R-CNN is proposed. By adjusting the Region Proposal Network (RPN) and Region of Interest (RoI) pooling layers, the model is better suited for feature extraction and classification of small targets. Generate feature maps at multiple scales by introducing additional convolutional layers to process inputs at different resolutions, with each layer focusing on targets within a specific size range. These multi-scale features are integrated and input into RPN to provide richer target proposal characteristics. By using image transformation techniques such as scaling, cropping, and rotation, the training dataset is expanded to simulate different small target scenes, enhancing the model’s adaptability to changes in target size, direction, and environment. The experimental results show that the proposed method not only outperforms other models in accuracy, recall, and F1 score, but also maintains high consistency and stability across different datasets. Its significant advantage in mean accuracy (MAP) further proves its reliability and effectiveness in remote sensing applications.
Research on the gradual change model of vibration characteristics of spatial steel truss structures under fatigue loading
Authors: Tang Sicong , Wang Hailong
Published: October 2024

A bottom–up multi-scale performance transfer chain is developed to ascertain the gradual change in the law of vibration characteristics in spatial steel truss structures under fatigue loading. This chain derives the interrelationship between vibration characteristics and the performance of each structural component. Based on the evolution characteristics of the performance model of the member scale in the transfer chain, a new analytical model of the shape function is established. Building on these foundations, a refined model was formulated to depict the gradual change of vibration characteristics in spatial steel truss systems under fatigue loading. This model integrates the cumulative damage rule, the structural residual performance rule, the finite element method and other pertinent theories. The gradual change in vibration characteristics of a steel truss girder bridge subjected to train loads was analyzed using a self-developed three-dimensional finite element analysis framework tailored explicitly for assessing gradual change issues in spatial steel truss structures. The analysis results indicate that the effective residual cross-sectional area and the structural frequency continuously decline as the service time increases. This comprehensive study advances the understanding of fatigue-induced changes in spatial steel truss structures. It offers analytical perspectives for predicting and mitigating the long-term impacts of dynamic loads on large-scale infrastructural components.
Experimental and numerical investigations on the effect of a rotating tube in an in-line tube bundle
Authors: Senouci Zine Eddine , Drai Ismail , Belharizi Morad , Yahiaoui Tayeb
Published: October 2024

This study investigates the impact of a rotating tube on the flow characteristics within a tube bank consisting of nine cylinders arranged in an in-line configuration, with a pitch-to-diameter ratio of 1.44, using both experimental and numerical approaches. Experiments are performed in a subsonic wind tunnel to measure pressure distributions at various azimuthal angles along the tubes, using a multi-channel differential pressure system. Drag forces are determined via a wire-strain gauge balance. Numerical simulations are conducted using ANSYS Fluent, employing the URANS-based Shear-Stress Transport (SST) k–[Formula: see text] model, to replicate turbulent cross-flow at two values of Reynolds numbers [Formula: see text] and [Formula: see text]. This study explores the effect of a tube rotation within the array on flow separation angles, pressure distributions and vortex shedding in the wake region, focusing on the effects of different positions of the rotating tube on the flow characteristics of the surrounding tubes. Numerical results closely match the experimental data, demonstrating that the rotational motion significantly mitigates flow separation and reduces drag forces on adjacent tubes. Additionally, the position of the rotating tube within the array plays a critical role in optimizing the fluid forces and pressure distribution, offering enhanced control over the flow within tube banks.
Resonant multi-wave, positive multi-complexiton, nonclassical Lie symmetries, and conservation laws to a generalized Hirota bilinear equation
Authors: Hosseini K. , Alizadeh F. , Hinçal E. , Baleanu D. , Osman M. S. , Wazwaz A. M.
Published: October 2024

This paper explores the evolutionary behavior of some specific waves for a Generalized Hirota Bilinear (GHB) equation with applications in modern sciences. More precisely, the linear superposition principle is first adopted to construct the resonant multi-wave of the GHB equation. Through the resonant N-wave and some particular computations, positive multi-complexiton to the governing model is then extracted with the use of computational packages. Furthermore, after deriving nonclassical Lie symmetries and their corresponding invariant solutions, Conservation Laws (CLs) for the GHB equation are formally constructed based on a general method developed by Ibragimov. The propagation dynamics of resonant double- and triple-waves as well as positive single- and double-complexitons are examined in detail by considering several case studies. The present results demonstrate how adjusting the nonlinear parameter can be used to control specific waves in nonlinear systems.
Optical dromions for M-fractional Kuralay equation via complete discrimination system approach along with sensitivity analysis and quasi-periodic behavior
Authors: Abbas Syed Oan , Shabbir Sana , Rizvi Syed T. R. , Seadawy Aly R.
Published: October 2024

This paper investigates new analytical wave solutions for the fractional Kuralay-IIB equations (FK-IIBE), including a new definition of the fractional derivative. This model works in disciplines such as ferromagnetic materials, optical fibers, wave mixing, and nonlinear optics. The integrable motion of space curves can be determined by our governing model. This research holds great importance in the area of optical fibers, exact and analytical solitons solution. The polynomial method’s complete discrimination system (CDSPM) is used to identify a variety of exact and analytical soliton solutions such as periodic, hyperbolic, rational, Jacobian elliptic (JE), and trigonometric functions. Additionally, we also convert the JE function into a solitary wave (SW) solution. To provide a comprehensive understanding of the dynamic aspects of the system, we also address bifurcation points, quasi-periodic behavior, sensitivity analysis, Poincarè maps, time series profile, and critical solution conditions. The research offers straightforward, efficient algorithms that can consistently and effectively address FK-IIBE. Machine learning technologies are also utilized to satisfy the criteria defined by dynamic analysis. Python regression learner tools are used for reverse engineering to analyze the mathematical model’s equilibrium based on parameter intervals and thresholds determined by dynamical analysis.
Fully Dynamic Submodular Maximization over Matroids
Authors: Dütting Paul , Fusco Federico , Lattanzi Silvio , Norouzi-Fard Ashkan , Zadimoghaddam Morteza
Published: October 2024

Maximizing monotone submodular functions under a matroid constraint is a classic algorithmic problem with multiple applications in data mining and machine learning. We study this significant problem in the fully dynamic setting, where elements can be both inserted and deleted in real-time. Our main result is a randomized algorithm that maintains an efficient data structure with an

\({\tilde{O}(\frac{{k^{2}}}{{\varepsilon}})}\)

amortized update time (in the number of insertions and deletions) and yields a

\({(4+O(\varepsilon))}\)

-approximate solution with respect to the dynamic optimum, where

\(k\)

is the rank of the matroid.
Addressing the Generalizability of AI in Radiology Using a Novel Data Augmentation Framework with Synthetic Patient Image Data: Proof-of-Concept and External Validation for Classification Tasks in Multiple Sclerosis
Authors: Brugnara Gianluca , Jayachandran Preetha Chandrakanth , Deike Katerina , Haase Robert , Pinetz Thomas , Foltyn-Dumitru Martha , Mahmutoglu Mustafa A. , Wildemann Brigitte , Diem Ricarda , Wick Wolfgang , Radbruch Alexander , Bendszus Martin , Meredig Hagen , Rastogi Aditya , Vollmuth Philipp
Published: October 2024

Generative adversarial network–based synthetic data augmentation during model training substantially improved performance of artificial intelligence models when applied to external MRI data and may be extended to a variety of clinical tasks to reduce domain shift on unseen data.
Neuroscience of the human thalamus related to acute pain and chronic “thalamic” pain
Authors: Lenz Fred A. , Dougherty Pat M. , Meeker Timothy J. , Saffer Mark I. , Oishi Kenichi
Published: October 2024

The association of posterior thalamic strokes with the presence of chronic “thalamic” pain was described in the early 1900s and revisited in a recent review of these patients. Acute pain in corporal structures is associated with the spinothalamic tract (STT), which originates in the dorsal horn of the spinal cord, whereas that associated with cranial structures is associated with the spinal division of the trigeminal nucleus. These pathways terminate in the ventral posterior nucleus (VP), including its posterior and inferior subnuclei and its core, which is classically associated with tactile and haptic functions. In medial nuclei (medial dorsal and intralaminar) receptive fields are large and stimulation evokes diffuse unpleasant sensations and pain while neurons in these nuclei subserve cognitive processes of attention, alerting, and conditioning. In the lateral nuclei neurons have small receptive and projected fields and high resolution of responses to somatic stimuli. Neurons in the lateral nuclei respond to stimuli producing pain, temperature, and visceral sensations while stimulation evokes similar sensations. Small strokes in VP core versus structures located inferior and posterior are associated with thalamic pain and decreased tactile, painful, and cold sensations and with decreased evoked potentials for painful (laser) heat and median nerve stimulation (electrical). Lesions of VP, but not ventral medial posterior nucleus (VMpo), are associated with thalamic pain, contrary to the recent “disinhibition” model. We review the evidence that the lateral nuclei are associated with multiple processes including tactile, nociceptive, visceral, and thermal content of stimuli, whereas the medial nuclei are related to cognitions about those stimuli.
Palytoxin evokes reversible spreading depolarization in the locust CNS
Authors: Wang Yuyang , Van Dusen Rachel A. , McGuire Catherine , Andrew R. David , Robertson R. Meldrum
Published: October 2024

Spreading depolarization (SD) is a critical mechanism underlying central nervous system (CNS) shutdown and injury under stress, yet the initiating ion channel remains unknown. Here, we used the marine poison palytoxin (PLTX), which converts the sodium-potassium ATPase (NKA) into an open channel, to initiate SD in intact locust CNS. We show for the first time that PLTX-induced SD is rapid and recoverable in vivo, providing support that NKA conversion to a channel may be the SD-initiating mechanism.
Inducing postactivation potentiation alters human motor unit behavior of the elbow extensors during unconstrained velocity contractions
Authors: Zero Alexander M. , Rice Charles L.
Published: October 2024

Inducing postactivation potentiation (PAP) increased motor unit (MU) recruitment thresholds, but decreased firing rates during dynamic isotonic contractions at 50% and 75% peak power compared with baseline (no PAP). Compared with previously described isometric tasks, modifications in MU activity with PAP were larger across a wider range of contractile intensities (75% maximum). Single MUs are responsive to activation history force potentiation and make compensatory adjustments in relation to the active state of the muscle.
Structural Damage Diagnosis of Aerospace CFRP Components: Leveraging Transfer Learning in the Matching Networks Framework
Authors: Xu Zhuojun , Li Hao , Yu Jianbo
Published: October 2024

This paper introduces a damage diagnosis method based on the reassignment method and matching networks (MNs) to study the structural health monitoring of aerospace composite material components. This aims to facilitate the mapping of signal features to complex failure modes. We introduce a signal processing technique based on the reassignment method, employing a sliding analysis window to re‐estimate local instantaneous frequency and group delay. By utilizing the short‐time phase spectrum of the signal, we correct the nominal time and frequency coordinates of the spectrum data, aligning them more accurately with the true support region of the analyzed signal. Subsequently, this paper developed a deep matching network (DMN) damage diagnosis model based on MNs. This model utilizes a convolutional neural network (CNN) to extract damage‐related features from the signal and introduces the full context embedding (FCE) method to enhance the compatibility of sample embeddings. In this process, the embeddings of each sample in the training set should be mutually independent, while the embeddings of test samples should be regulated by the distribution of training set sample data. Ultimately, the damage category of test samples is determined based on cosine similarity. We validate our model using damage sample data collected from experiments and simulations conducted under varying components and operating conditions. Comparative assessments with five mainstream methods reveal an average accuracy exceeding 96%. This underscores the exceptional recognition accuracy and generalization performance of our proposed method in cross‐operating condition fault diagnosis experiments concerning aircraft composite material components.
Consistency as the Currency in Psychological Measures: A Reliability Generalization Meta‐Analysis of Kessler Psychological Distress Scale (K‐10 and K‐6)
Authors: Wojujutari Ajele Kenni , Idemudia Erhabor Sunday
Published: October 2024

Background: Psychological distress is a critical concern in mental health, significantly impacting the quality of life across lifespan. Reliable and culturally adaptable assessment tools are essential for effective diagnosis and intervention. The Kessler Psychological Distress Scales (K‐10 and K‐6) are widely used for their efficiency and psychometric strength, but the reliability of K‐10 and K‐6 across different populations and settings remains to be determined.

Objective: This study aims to evaluate the reliability generalization (RG) of the K‐10 and K‐6 scales across diverse demographic and cultural contexts, providing a comprehensive meta‐analysis of their performance.

Method: A RG meta‐analysis was conducted using data from peer‐reviewed articles published between 2002 and 2024, sourced from databases such as Web of Science, Scopus, and ScienceDirect. The analysis included 48 studies that reported reliability measures like Cronbach’s α, focusing on the psychometric properties of the scales across various populations and settings.

Results: The meta‐analysis revealed high internal consistency for both the K‐10 (mean α = 0.90, 95% confidence interval (CI) [0.88, 0.91]) and K‐6 (mean α = 0.84, 95% CI [0.80, 0.88]) scales. Reliability varied across different populations and languages. For the K‐10, the highest reliability was found among adolescents (α = 0.93) and carers (α = 0.91). The K‐10 demonstrated exceptional reliability in settings such as Australia (α = 0.97) and significant variability in Tanzania (α = 0.78). The K‐6 scale showed high reliability among outpatients (α = 0.89) and the general population (α = 0.87). The scales were adapted into multiple languages, including English, Chinese, Swahili, Farsi, Indonesian, Japanese, Hindi, and Portuguese, reflecting their global applicability and adaptability.

Conclusion: The Kessler Psychological Distress Scales (K‐10 and K‐6) are reliable tools for measuring psychological distress in general and clinical populations. Their high reliability and adaptability across diverse settings highlight their value in clinical practice and research. These findings support the continued use and adaptation of these scales in global mental health assessments, emphasizing the importance of cultural and linguistic considerations.
Predictive Value of Inflammatory Indicators on the Efficacy of Preoperative Neoadjuvant Chemotherapy in Patients With Locally Advanced Rectal Cancer
Authors: Jin Zechuan , Zhou Dan , Yang TingHan , Wang Ziqiang
Published: October 2024

Objective: To investigate the relationship between peripheral blood neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), platelet‐to‐lymphocyte ratio (PLR), lymphocyte‐to‐C‐reactive‐protein ratio (LCR), and monocyte‐to‐leukocyte ratio (MWR) and the efficacy of neoadjuvant chemotherapy (NAC) for patients with locally advanced rectal cancer before and after chemotherapy.

Methods: Seventeen rectal cancer patients who underwent NAC at West China Hospital of Sichuan University from March 31, 2022, to April 30, 2024, were selected as the study subjects, and the predictive value of peripheral blood NLR, LMR, PLR, LCR, and MWR were included in the least absolute shrinkage and selection operator (LASSO) regression analysis for the pathological efficacy, and the significant variables were screened out and the nomogram was constructed from them. Decision curve analysis (DCA) was applied to evaluate the predictive performance of the model.

Results: LASSO regression screened three predictive variables of NLR, LMR and LCR before neoadjuvant therapy that could predict pathological complete remission (pCR), as well as changes in PLR, LCR, and MWR after neoadjuvant therapy that could predict chemotherapy inefficacy. Nomograms and DCA curves were drawn based on the variables, and internal validation showed that the model had good predictive ability.

Conclusion: The comprehensive hematological prediction model for effective NAC in rectal cancer has a good predictive ability for NAC efficacy, which can provide guidance for individualized patient treatment.
Screening Antioxidant Components in Yiwei Decoction Using Spectrum‐Effect Relationship and Network Pharmacology
Authors: Zhang Lei , Zhu Wei
Published: October 2024

Yiwei decoction (YWD) is a classic prescription with the function of nourishing stomach yin. In this study, the effective components of antioxidant activity of YWD and its possible mechanism were discussed from the point of view of spectral effect relationship and network pharmacology. Firstly, the fingerprints of 10 batches of YWD were established by UPLC‐PDA technique, and the 1,1‐diphenyl‐2‐picryl‐hydrazyl radical (DPPH) scavenging rate and total antioxidant capacity (T‐AOC) were used as the indicators for antioxidant activity in vitro. Then, the spectral effect relationship between the fingerprint profiles and antioxidant capacity was analyzed through grey relational analysis (GRA) and orthogonal projections to latent structures (OPLS). In addition, network pharmacology was employed to predict the potential mechanisms of YWD in the treatment of antioxidant‐related diseases. The spectrum‐effect relationship indicated that three common peaks were likely to be the most decisive active components, identified as verbascoside, psoralen, and vitexin, respectively. Based on network pharmacology analysis, a total of 83 target genes shared by the active components and antioxidant‐related diseases were collected. AKT1, HSP90AA1, SRC, CASP3, and MTOR were closely related to antioxidant therapy and considered as core therapeutic targets. The potential mechanisms of YWD were obtained through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, molecular docking simulations were conducted to evaluate the binding activities between the core therapeutic targets and corresponding compounds. The excellent core protein‐compound complexes obtained by molecular docking were simulated by molecular dynamics simulation. The results showed that the active compounds had good binding ability with the selected targets. This study successfully identified the effective components of YWD and predicted the potential targets and pathways, which provided a new idea for the application of YWD in the treatment of antioxidant stress in the future. In addition, the potential active components provide valuable implications for drug screening of related diseases.
Smoked and Fermented Bushmeat (Mpunam) Products: Risk Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) Resulting From Processing
Authors: Amponsah A. S. , Lutterodt H. E. , Ankar-Brewoo G. M. , Ofosu I. W.
Published: October 2024

The polycyclic aromatic hydrocarbons (PAHs) congener concentrations and risk upon human exposure to smoked bushmeat products were analyzed. GC/MS MRM and QuEChERS methods were used for the analysis. This work has become necessary due to the need for more information concerning the quantitative determination of these compounds and their health risk assessment. The 16 PAH congeners identified were acenaphthylene (ACA), naphthalene (NAP), acenaphthene (ACE), fluorene (FLU), anthracene (ANT), phenanthrene (PHE), fluoranthene (FLT), pyrene (PYR), benzo[b]fluoranthene (BBF), benzo[k]fluoranthene (BKF), benzo[a]anthracene (BAA), chrysene (CHR), indeno(1,2,3‐cd)pyrene (IND), dibenzo(a,h)anthracene (DAA), benzo(g,h,i)pyrene (BGP), and benzo[a]pyrene (BAP). At the 5% and 95% daily intake levels, BAP was at 3.34 and 17.39 μg/kg(bw)/day, ΣPAH4 was at 25.11 and 109.15 μg/kg(bw)/day, and ΣPAH8 was at 55.76 and 236.68 μg/kg(bw)/day, respectively. BAP, ΣPAH4, and ΣPAH8 concentration exceeded the European Union limits, as BAP concentration was as low as 6.09 μg/kg and as high as 34.19. The exposure values were significantly high. Specifically, the margin of exposure for BAP was as low as 2.09 × 10−2; for ΣPAH4, it was 1.36 × 10−−2; and for ΣPAH8, it was 1.95 × 10−2 all at the 95% level. These figures are substantially lower than the benchmark of 10,000, indicating a higher ILTCR. Furthermore, the ILTCR ranged from a minimum of 47.77 to a maximum of 248.53 at the 5% and 95% levels, respectively. This study makes smoked bushmeat a public health concern because the higher figures obtained indicate higher carcinogenicity upon consumption.
A Modification on Hoffman’s Pocket Technique With Scleral Fixation of Intraocular Lens (IOL), Case Series of Unique Scenarios
Authors: Alsirhy Ehab , Alanazi Tariq , Alghamdi Nawaf , Alorainy Jehad , Alanzan Abdullah , Alwadani Saeed
Published: October 2024

Purpose: The purpose of this study is to present our experience with Hoffman’s SFIOL using double‐armed Gore‐Tex sutures (polytetrafluoroethylene) instead of 9.0 polypropylene suture method in four cases.

Observation: In this case series article, we present our experience with Hoffman’s SFIOL using double‐armed Gore‐Tex sutures (polytetrafluoroethylene) instead of 9.0 polypropylene sutures; the postoperative evaluation revealed well‐centered IOL which did not exhibit any signs of instability in all four eyes, demonstrating a successful surgical outcome without observed complications.

Conclusions and Importance: Hoffman’s SFIOL using double‐armed Gore‐Tex could be safe and effective methods for cases with no adequate capsular support for the IOL implantation. Compared to prolene suture, Gore‐Tex gives more tensile strength and requires less manipulation during surgery minimizing postoperative inflammation which could be a valuable option in the nearby future for similar cases.
Fixed Point Theorems Over Extended (ϕ, ψ)‐Metric Spaces and Applications in Differential Equations
Authors: Taleb Mohammed M. A. , Al-Salehi Saeed A. A. , Borkar V. C.
Published: October 2024

The main aim of this research endeavor is to introduce a novel type of generalized metric space, termed an extended (ϕ, ψ)‐metric space, to establish new fixed point results and employ them to prove the existence and uniqueness of solutions to first‐order differential equations. To achieve this goal, we introduce the concepts of (α, θ)‐admissible Banach contraction, (α, θ)‐admissible crooked Banach contraction, and (α, θ)‐admissible (φ, β)‐contraction in an extended (ϕ, ψ)‐metric space. We augment our theoretical results by providing compelling and nontrivial illustrative examples.
Latest Trend and Challenges in Machine Learning– and Deep Learning–Based Computational Techniques in Poultry Health and Disease Management: A Review
Authors: V. Shwetha , B. S. Maddodi , Laxmi Vijaya , Kumar Abhinav , Shrivastava Sakshi
Published: October 2024

To determine the flock’s economic worth, free‐range chicken growers must determine the gender, bird movement, behavior, disease detection, and lameness of the chickens. However, because of the complex environmental background and the fluctuating chicken population, it is difficult for farmers to effectively and properly measure those characteristics. Manual estimation is also inaccurate and time‐consuming because probable identification occurs in their life cycle. Therefore, the industry benefits from automated systems that can produce findings quickly and precisely in managing health and diseases. The advancement of machine learning (ML)– and deep learning (DL)–based algorithms are boons for poultry health and disease management. This study reviews the literature using ML and DL techniques in prediction, classification, and disease detection in various metrics, namely, poultry health and disease management. We have considered the research article published from 2010 to 2023 in this study, which uses ML‐ and DL‐based computation techniques in poultry welfare metrics such as gender identification, tracking of poultry, analysis of broiler chicken behavior, detection of poultry diseases, lameness and broiler weight, and stress monitoring. In addition, this review explores the most recent developments, difficulties, strategies, and databases used in image preprocessing feature extraction and classification. The review addresses these challenges and discusses the approaches and techniques researchers employ to tackle them in the field of poultry management and disease detection.
A Rare Presentation of Intracerebellar Schwannoma: A Case Report
Authors: Alhantoobi Mohamed , Alkhoori Nadeen , Khayat Hassan , Zhang Euan , Algird Almunder , Provias John
Published: October 2024

Background: Intracerebellar schwannoma is an extremely rare disease entity with only 21 case reports described in the literature.

Case Description: A 68‐year‐old male presented with chronic headaches, dizziness, gait imbalance, and incoordination. Previous MRI had revealed a cystic lesion in the right cerebellum; however, patient was lost to follow‐up. Updated MRI revealed dramatic enlargement of the lesion in addition to worsening clinical status. The patient underwent successful surgical resection.

Conclusion: Intracerebellar schwannoma can be challenging to diagnose preoperatively due to its rare occurrence; however, it should be included in the differential diagnosis of cystic lesions in the cerebellum, and most cases can be successfully treated with complete surgical resection. Pathological examination revealed a spindle cell neoplasm with other typical histopathological features of schwannoma.
Myrtenol’s Effectiveness against Hospital‐Acquired Methicillin‐Resistant Staphylococcus aureus: Targeting Antibiofilm and Antivirulence Properties
Authors: Makled Amal F. , Labeeb Azza Z. , Badr Eman A. E. , Abdelmaksoud Amany M. , Elfiky Safa R. , Amer Asmaa K. , Sleem Asmaa S.
Published: October 2024

The emergence of methicillin‐resistant Staphylococcus aureus (MRSA) several years ago highlighted the challenge of multidrug‐resistant infections, emphasizing the critical need for innovative treatment approaches. Myrtenol, known for its antibacterial and antibiofilm properties, holds promise as a potential treatment option. This study aimed to evaluate the effectiveness of myrtenol against MRSA. The collected MRSA isolates were assessed for antimicrobial susceptibility following the Clinical and Laboratory Standards Institute (CLSI) guidelines 2023. Biofilm formation by MRSA was evaluated using the tissue culture plate (TCP) technique. The minimal inhibitory concentration (MIC), minimal bactericidal concentration (MBC), and minimal biofilm inhibitory concentration (MBIC) of myrtenol against MRSA were determined both individually and in combination with antibiotics. Real‐time PCR was employed to investigate the impact of myrtenol on the expression of virulence genes (sarA, agrA, and icaD) across the isolates. In this study, MRSA was identified in 90 out of 400 cases (22.5%) of hospital‐acquired pathogens. Among the collected MRSA isolates, 53 out of 90 (59%) were found to produce biofilms. The MIC of myrtenol was comparable to the MBC across all tested isolates, they were almost the same. Combinations of myrtenol with most tested antibiotics exhibited synergistic effects exceeding 60%. Among the 53 biofilm‐producing isolates, 45 isolates (85%) expressed the sarA gene, 49% expressed the agrA gene, and all biofilm‐producing MRSA isolates (100%) expressed the icaD gene. A notable reduction in the relative quantity (RQ) values of virulence gene expression was observed after treatment with the MBIC of myrtenol across all tested isolates. Myrtenol demonstrated strong antimicrobial activity against MRSA, notably reducing the expression of key virulence genes linked to biofilm formation. This suggests its potential as a therapeutic agent for treating biofilm‐associated MRSA infections.
Enhancing Sustainability and Efficiency in Offshore Oil and Gas Engineering through the Integration of Chaotic Local Search and Particle Swarm Optimization for Microenergy Systems Optimization
Authors: Lu Jia , Siaw Fei Lu , Thio Tzer Hwai Gilbert , Wang Junjie
Published: October 2024

The offshore oil and gas industry is under increasing pressure to reduce carbon emissions while maintaining energy reliability. Offshore oil and gas platforms (OOGPs) face significant challenges in integrating low‐carbon operations with their energy systems. This study introduces an optimized scheduling approach for offshore microintegrated energy system (OMIES) that incorporates a hybrid energy storage system, including a floating power‐to‐gas associated gas storage (FP2G‐AGS) module, to address the intermittency of renewable energy sources. An economic optimization model is formulated, accounting for carbon emissions, operational costs, and the status of gas turbine generator sets. To solve the complex optimization problem, this study develops a hybrid chaotic local search and particle swarm optimization (CLPSO) algorithm. The CLPSO algorithm synergizes the global search ability of PSO with the local refinement of chaotic local search, enhancing the convergence to optimal solutions. Experimental results demonstrate that the proposed CLPSO algorithm effectively achieves optimal solutions within a range of 48.2–51.7. Case studies validate the model’s capability to promote new energy integration, reduce operational costs, and decrease CO2 emissions across various scenarios. This research significantly contributes to achieving low‐carbon operations on OOGPs and promotes the sustainable development of marine resources.
KRAS Loss of Heterozygosity Promotes MAPK-Dependent Pancreatic Ductal Adenocarcinoma Initiation and Induces Therapeutic Sensitivity to MEK Inhibition
Authors: Fey Sigrid K. , Najumudeen Arafath K. , Watt Dale M. , Millett Laura M. , Ford Catriona A. , Gilroy Kathryn , Simpson Rosalin J. , McLay Kathy , Upstill-Goddard Rosanna , Chang David , Clark William , Nixon Colin , Birch Joanna L. , Barry Simon T. , Morton Jennifer P. , Campbell Andrew D. , Sansom Owen J.
Published: October 2024

Pancreatic cancer is characterized by the prevalence of oncogenic mutations in KRAS. Previous studies have reported that altered KRAS gene dosage drives progression and metastasis in pancreatic cancer. Whereas the role of oncogenic KRAS mutations is well characterized, the relevance of the partnering wild-type (WT) KRAS allele in pancreatic cancer is less well understood and controversial. Using in vivo mouse modeling of pancreatic cancer, we demonstrated that WT KRAS restrains the oncogenic impact of mutant KRAS and dramatically impacts both KRAS-mediated tumorigenesis and therapeutic response. Mechanistically, deletion of WT Kras increased oncogenic KRAS signaling through the downstream MAPK effector pathway, driving pancreatic intraepithelial neoplasia initiation. In addition, in the KPC mouse model, a more aggressive model of pancreatic cancer, lack of WT KRAS led to accelerated initiation but delayed tumor progression. These tumors had altered stroma and an enrichment of immunogenic gene signatures. Importantly, loss of WT Kras sensitized Kras mutant tumors to MEK1/2 inhibition though tumors eventually became resistant and then rapidly progressed. This study demonstrates the repressive role of WT KRAS during pancreatic tumorigenesis and highlights the critical impact of the presence of WT KRAS in both tumor progression and therapeutic response in pancreatic cancer.

Significance: KRAS allelic status impacts pancreatic cancer progression and has the potential to guide effective treatment in a substantial subset of patients.
Large-Scale Comparative Analysis of Canine and Human Osteosarcomas Uncovers Conserved Clinically Relevant Tumor Microenvironment Subtypes
Authors: Patkar Sushant , Mannheimer Joshua , Harmon Stephanie A. , Ramirez Christina J. , Mazcko Christina N. , Choyke Peter L. , Brown Gregory Thomas , Turkbey Baris , LeBlanc Amy K. , Beck Jessica A.
Published: October 2024

Purpose:

Osteosarcoma is an aggressive bone cancer lacking robust biomarkers for personalized treatment. Despite its scarcity in humans, it is relatively common in adult pet dogs. This study aimed to analyze clinically annotated bulk tumor transcriptomic datasets of canine and patients with human osteosarcoma to identify potentially conserved patterns of disease progression.

Experimental Design:

Bulk transcriptomic data from 245 pet dogs with treatment-naïve appendicular osteosarcoma were analyzed using deconvolution to characterize the tumor microenvironment (TME). The TME of both primary and metastatic tumors derived from the same dog was compared, and its impact on canine survival was assessed. A machine learning model was developed to classify the TME based on its inferred composition using canine tumor data. This model was applied to eight independent human osteosarcoma datasets to assess its generalizability and prognostic value.

Results:

This study found three distinct TME subtypes of canine osteosarcoma based on cell type composition of bulk tumor samples: immune enriched, immune enriched dense extracellular matrix-like, and immune desert. These three TME-based subtypes of canine osteosarcomas were conserved in humans and could predict progression-free survival outcomes of human patients, independent of conventional prognostic factors such as percent tumor necrosis post standard of care chemotherapy treatment and disease stage at diagnosis.

Conclusions:

These findings demonstrate the potential of leveraging data from naturally occurring cancers in canines to model the complexity of the human osteosarcoma TME, offering a promising avenue for the discovery of novel biomarkers and developing more effective precision oncology treatments.
Figure 7 from Blocking Tryptophan Catabolism Reduces Triple-Negative Breast Cancer Invasive Capacity
Authors: Kuo Li-Wei , Crump Lyndsey S. , O’Neill Kathleen , Williams Michelle M. , Christenson Jessica L. , Spoelstra Nicole S. , Roy Micaela Kalani , Argabright Amy , Reisz Julie A. , D’Alessandro Angelo , Boorgula Meher P. , Goodspeed Andrew , Bickerdike Mike , Bitler Benjamin G. , Richer Jennifer K.
Published: October 2024

Pharmacologic inhibition of TDO2/IDO1 or TDO2 KD reduces the EMT signature. A–C, GSEA was performed to analyze RNA-seq data from BT549 treated with AT-0174 or vehicle (AT-0174 vs. vehicle) for 48 hours, and BT549 with TDO2 KD [shTDO2-82 vs. shSCR and shTDO2-98 (IDO1 comp) vs. shTDO2-82], with biological triplicate for each condition. Significant pathways (P adj. < 0.05) with negative (blue) and positive (red) NES for the hallmark of EMT genes are shown. D and E, Heatmaps of the EMT gene subset from RNA-seq data with z-score-transformed CPM. F and G,VIM and CDH2 mRNA as by qPCR following AT-0174 treatment for 48 hours. Data are displayed as mean ± SD with t test or one-way ANOVA analysis. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. CDH2, N-cadherin; CPM, counts per million; NES, normalized enrichment score; VIM, vimentin.