bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantitative monitoring of icing on CFRP laminate with guided wave combining forward modeling and inverse characterization
Authors: Tian Yuan , Duongthipthewa Anchalee , Chen Qi , Guo Haotian , Liu Menglong , Zhang Jifeng , Zhou Limin
Published: February 2024

Aircraft icing is one of the critical factors for flight safety. Timely and accurate monitoring of in-flight ice accretion is essential for flight systems to take immediate and effective action to significantly improve the efficiency of subsequent de-icing processes and ensure flight safety. Since carbon fiber reinforced polymer (CFRP) are now widely used in the aviation industry, the study of ice accretion on the surfaces of CFRP with anisotropic properties is of great importance. In this work, a three-dimensional frequency domain finite element model for icing CFRP laminate is first established, via which the mechanism of mode conversion of ultrasonic guided waves (UGWs) at different ice layer thicknesses is quantitatively analyzed. Then, the time-domain finite element simulation was performed, from which the time–frequency domain spectrogram of the acquired UGW signal is obtained by short-time Fourier transform (STFT). The extracted frequency–time-of-flight (ToF) curve of the signal via STFT shows high agreement with the theoretical results, which confirms the influence of icing on UGW propagation. Finally, numerous experiments with bonded lead zirconate titanate wafers to excite and acquire UGWs are conducted with different ice layer thicknesses and lengths on CFRP. The extracted frequency–ToF curves of UGW signals are used as input to a two-layer feedforward artificial neural network (ANN) to accurately evaluate the length and thickness of the ice layer. The high reliability of this method with ANN is confirmed, which shows the potential of the proposed UGW-based method for quantitative monitoring of icing length and thickness on aircraft CFRP laminate.
Multi-source domain adversarial graph convolutional networks for rolling mill health states diagnosis under variable working conditions
Authors: Zhao Shuai , Bao Leping , Hou Changhui , Bai Yang , Yu Yue
Published: February 2024

As the rolling mill often encounters variable and complicated working conditions and shock loads, unsupervised domain adaptive (UDA) methods are imperative in its health monitoring. However, efforts of applying UDA methods on the rolling mill are negligible, and many existing approaches have constraints in domain adaptation, domain label, and data construction that prevent meaningful features from being extracted. Hence, a multi-source domain adversarial graph convolutional networks framework (MSDAGCNs) is presented to overcome these challenges and combine three essential elements to achieve cross-domain health states diagnosis under variable working conditions. First, a shared feature extract module is introduced to extract common features. Then, the features are input to a multi-source feature extract module to extract the data construction from the graphs generated by a graph construction module. Meanwhile, a multi-source domain adversarial classifier module is modeled to extract multi-source invariant features and classify them. After that, the local maximum mean discrepancy is employed to align the domain categories. Next, a task classifier module integrates the results of the multi-source classifier for reliable health state diagnosis. Results on the two cases can verify that the proposed MSDAGCNs can not only outperform other state-of-the-art methods, but also extract domain-invariant knowledge. Compared with the best-performing method, the proposed method can boost accuracy by 0.53% and 0.83% in the simplest task of the two case studies, respectively. Furthermore, the arrangement of sensors on the rolling mill is discussed to select the optimal location for collecting vibrations.
Automatic high-precision crack detection of post-earthquake structure based on self-supervised transfer learning method and SegCrackFormer
Authors: Meng Shiqiao , Zhou Ying , Jafari Abouzar
Published: February 2024

Accurate crack detection is essential for structural damage assessment after earthquake disasters. However, due to the gap between the target domain of the detected structure and the source domain, it is challenging to achieve high-precision crack segmentation when performing crack detection based on deep learning (DL) in actual engineering. This article proposes a crack segmentation transfer learning method based on a self-supervised learning mechanism and a high-quality pseudo-label generation method, which can significantly improve the detection accuracy in the target domain without pre-made annotations. Besides, to improve the crack segmentation model’s ability to extract local and global features, this article proposes a SegCrackFormer model, which embeds convolutional layers and multi-head self-attention modules. An experiment of the crack segmentation transfer learning method is performed on two open-source crack datasets, METU and Crack500, and a newly proposed LD dataset. The experimental results show that the crack segmentation transfer learning method proposed in this article can improve the mean intersection over union (mIoU) by 38.41% and 15.66% on the Crack500 and LD datasets, respectively. The proposed SegCrackFormer is evaluated through comparative experiments, which demonstrate its superiority over existing crack segmentation models on the METU dataset. Additionally, the proposed method is shown to require significantly less computational resources than other existing models, which highlights the potential of SegCrackFormer as a powerful and efficient model for crack segmentation in practical applications.
Intelligent fault diagnosis of storage stacking machinery under variable working conditions using attention-based adaptive multimodal feature fusion networks
Authors: Meng Xiangyin , Li Yang , Xie Xinxin , Peng Zhicheng , Li Shichu , Xie Lei , Huang Huiping , Zhang Jian , Guo Peng , Zhang Min , Xiao Shide
Published: February 2024

Due to the harsh working environment of storage stacking machinery, the fault information of important components is significantly complex, which leads to the problem of low classification accuracy and high computational complexity of existing deep learning-based fault diagnosis methods. To alleviate the problem, this paper presents a novel architecture named attention-based adaptive multimodal feature fusion networks for intelligent fault diagnosis of storage stacking machinery, which is aimed at improving the diagnostic precision and robustness of feature fusion network and learning the broader feature representation. Firstly, the long short-term memory layer is introduced to extract the feature information of multiple time steps to improve the self-extraction ability of multi-temporal features. Then, the maximum temporal feature fusion module is utilized to highlight the recognizability of deep fusion features. Finally, a residual layer with spanning connections is added to increase the utilization and characterization capability of deep fusion features. Experimental results demonstrate the effectiveness and superiority of the proposed method in intelligent fault diagnosis of storage stacking machinery under variable working conditions compared with some state-of-the-art deep learning-based methodologies.
A miniaturized passive wireless patch antenna sensor for structural crack sensing
Authors: Li Xianzhi , Xue Songtao , Xie Liyu , Wan Guochun
Published: February 2024

This paper presents a miniaturized patch antenna sensor for structural crack sensing, and the patch antenna sensor can be interrogated wirelessly. The proposed patch antenna sensor can detect the expansion of structural crack through relative movement between antenna components, and the relationships between the antenna resonant frequency and the crack width were studied. By using Rogers RO3010 laminate with high dielectric constant as the dielectric substrate of the antenna, the size of the proposed antenna sensor is significantly reduced, and higher sensing sensitivity is achieved. Furthermore, the wireless interrogation methods of the patch antenna sensor were also studied. The resonant frequency of the patch antenna sensor was wirelessly interrogated using linearly polarized wide-band antennas. Compared with the previous patch antenna sensor, the overall area of the proposed antenna sensor has been reduced to 33.4%, and the miniaturized patch antenna sensor shows a sensing sensitivity of 116.1 MHz/mm, which is 2.6 times higher than the previous patch antenna sensor. A series of simulations and experiments have demonstrated the feasibility of the proposed patch antenna sensor for structural crack sensing and the effectiveness of wireless interrogation methods.
Preliminary evaluation of properties and performance of natural rubber (NR) latex band for microplastic capturing in seawater
Authors: Ahmad Shahrul Amin Nur Ayunni , Mohd Sabri Nur Shauqina , Nai Sem Neettha , Mohd Zaini Makhtar Muaz , Shafiq Mohamad Danial
Published: February 2024

Microplastic particles are emerging water-laden waste that cause a worrying concern towards the environment and humans health. Due to its small size and geometry, and uncertain surface properties, the microplastic waste capturing method in water is still evolving. To date, a number of findings report on the emergence of microplastic surface charging, especially when exposed to water environment. In this study, the natural rubber (NR) latex band was utilized to capture the microplastic waste via a surface capturing mechanism. The NR band was produced using a film casting and curing methods. The surface charging mechanism on the NR band was introduced via the usage of high amount of ZDEC accelerator and, periodic stretching and relaxation procedures. In this work, ZDEC was used as an accelerator for the rubber formulation, and surface charge booster for the NR band. The surface charge of the NR band generates electrostatic interaction with the microplastic waste in water. The polypropylene (PP) microplastic was captured via the surface attraction mechanism using the manufactured NR band. Based on FTIR analysis, the presence of PP microplastic can be quantified on the contaminated NR band surface. The NR band shows the improvement in tensile and tear properties and crosslink density, mainly due to high amount of ZDEC used. At ZDEC loading of 20 phr, the NR band recorded the highest surface potential value, and this is owing to the formation of Zn2+ complex ions on its surface. XRF analysis indicates that the increment of Zn content in the NR band with increasing ZDEC content, that suggests the formation of Zn2+ complex ions.
Pathways to—But Not Through? Revisiting the Trauma and Recidivism Relationship Among System-Involved Youth
Authors: McKenna Nicole C. , Anderson Valerie R.
Published: February 2024

Research has demonstrated that exposure to traumatic experiences in childhood and adolescence can result in adverse outcomes, including mental health concerns, school troubles, delinquency, and juvenile justice system involvement. The current study draws on a framework informed by feminist pathways and trauma theories to revisit the effect of traumatic experiences on recidivism two years following initial system contact. Data from a Midwestern juvenile court illustrated traumatic experiences are common pathways into the system but are not predictive of experiences through the system using general recidivism outcome measures. However, several other variables predicted youth receiving new petitions. The effects of race/ethnicity and age are more pronounced when the sample was disaggregated by referral unit (truancy vs. delinquency unit). We discuss different methodological and measurement factors to consider when examining the trauma-recidivism relationship.
Investigation of slashing mechanisms and behavior of high-performance fabrics
Authors: El Messiry Magdi , Ayman Yasmin , Eid Elshiamaa M
Published: February 2024

The slashing mechanism is influenced by various properties that impact fabric slicing, contingent upon both fabric design and yarn-slicing characteristics. This study explores the slash resistance of soft armor, underscoring the essential need for enhancements in fabric design and fiber properties. Yarn-slicing qualities and the fabric’s pattern play pivotal roles in the fabric-cutting mechanism. The fabric stabbing resistance force demonstrates strong positive correlations with multiple factors, encompassing values such as friction force between warp and weft, yarn cutting force, yarn pull-off force, fabric shear modulus, and fabric flexural stiffness. The investigation explores the relationship between slash resistance in high-performance fabrics, revealing a robust correlation with factors such as yarn cutting force, yarn pull-off force, fabric shear modulus, friction force between warp and weft, and fabric flexural rigidity. Fabrics constructed from Kevlar 129 or 29 showcase the highest slashing resistance force. Experimental results unveil that the Kevlar 129 plain weave exhibits the utmost resistance, recording a force of 100.37 N and a fabric-slashing energy of 3.65 J. In contrast, the Kevlar 29 plain weave structure withstands a slash resistance force of 67 N, while the Kevlar 29-carbon plain weave displays a slash resistance of 62.97 N. The correlation coefficients between various variables linked to fabric-slashing resistance force unveil a strong, positive, and highly interrelated association for the majority of factors investigated. These factors encompass yarn-cutting force, yarn pull-off force, fabric shear modulus, and fabric flexural rigidity. Additionally, there exists a positive correlation with the friction force between warp and weft.
Effect of coating MoS2 nanoflakes onto CuCo2O4 on the electrochemical performance as electrode materials of supercapacitors
Authors: Zhao Rong , Wang Ji , Han Yiming
Published: February 2024

CuCo2O4@MoS2 microflowers have been synthesized on Ni foam using a hydrothermal method, and their electrochemical performances as supercapacitor electrodes are investigated. The influence of MoS2 loading on the specific capacity and cycle stability of the nanocomposites is systematically analyzed. It is found that the addition of MoS2 significantly enhances the specific capacity of the CuCo2O4 microflowers, while the cycle stability varies with MoS2 content. Competitive mechanistic insights into the interplay between MoS2 content, electrochemical behavior, and structural stability during cycling are provided. Notably, the CuCo2O4@MoS2-60 sample exhibits an impressive specific capacity of 11.1 F cm−2 at a discharge current density of 0.003 A cm−2, with a remarkable capacity retention rate of 94.6% after 1800 charge–discharge cycles. Moreover, the practical application prospects are demonstrated through the fabrication of symmetric supercapacitors. This study offers valuable guidance for the rational design and optimization of CuCo2O4@MoS2 nanocomposites for high-performance supercapacitor applications.
The impact of ketamine on delayed neurocognitive recovery in elderly patients undergoing spinal anaesthesia for orthopaedic procedures, a pilot study
Authors: Abbas Mostafa Samy , Abo-Zeid Mohamed Gamal , Askar Fatma Gad-Elrab , Askar Omnia Ahmed
Published: February 2024

Objective:

Delayed neurocognitive recovery is an objectively measurable decline in the cognitive status at varying intervals after surgery under both general and spinal anaesthesia. In this study, we used the Short Portable Mental Status Questionnaire to evaluate the protective effect of ketamine infusion on cognitive function of elderly patients undergoing spinal anaesthesia for orthopaedic procedures.

Methods:

A randomised, double-blinded placebo-controlled trial. Forty-two geriatric patients listed for elective orthopaedic surgery under spinal anaesthesia were randomly assigned to receive an intravenous infusion of either ketamine (0.3mg/kg) or isotonic saline (control group) after receiving spinal anaesthesia, which continued throughout the procedure. Cognitive performance was evaluated, as a primary outcome, with Short Portable Mental Status Questionnaire.

Results:

Baseline cognitive performance was comparable in both groups. Patients in the ketamine group showed statistically significant fewer errors in the postoperative Short Portable Mental Status Questionnaire compared with the baseline evaluations (p = 0.038). Patients in the ketamine group showed significantly lower verbal numerical scale scores than the control group (p = 0.04) at six hours after surgery.

Conclusion:

Elderly patients undergoing spinal anaesthesia showed a better cognitive status after receiving an intravenous infusion of 0.3mg/kg ketamine. However, further research with a larger sample size and different assessment tools might be required to verify our results.
Digging in the dark: Unveiling the unlikely protagonists in medical science advancements – The grave robbers!
Authors: Bates Ann
Published: February 2024

This research article aims to shed light on the unconventional profession of grave robbers and explore their unexpected contribution to medical knowledge. While initially seen as villains, grave robbers have inadvertently played a significant role in advancing medical science. By examining historical instances and controversial cases, this study delves into the positive outcomes resulting from their unconventional activities.
Presurgical depressive symptom and anaesthetic requirements in patients undergoing surgery for malignant and non-malignant conditions: A prospective observational cohort study
Authors: Narayanan Viswanath , Lata Suman , Jha Ajay Kumar , Bharadwaj Balaji
Published: February 2024

The incidence and magnitude of depression are rarely assessed during preanaesthetic evaluation. The shared physiological mechanisms of depression and anaesthetic drugs are likely to alter the pharmacodynamics of propofol. Therefore, the study aimed to evaluate the burden of presurgical depression and its effect on propofol consumption during anaesthesia. This prospective, observational, cross-sectional, analytical study included adult patients (> 18 years) undergoing surgery. During the preoperative period, depressive symptoms were evaluated by the psychiatrist on 9-point Patient Health Questionnaire-9 (PHQ-9). The propofol requirements were recorded during anaesthesia and compared with those for patients without depression. One hundred and seventy-four patients (87 patients each with and without cancer) underwent presurgical evaluation. The prevalence of depression (>4 Patient Health Questionnaire-9) and moderate to severe depression (>9 PHQ-9) among patients with cancer was 58.6% and 35.6%, respectively. The prevalence of depression (>4 PHQ-9) and moderate to severe depression (>9 PHQ-9) among patients without cancer was 18.4% and 3.4%, respectively. In the cancer group, propofol requirement was significantly lower (114.7 ± 22.9mg vs. 126.4 ± 24.3mg; p = 0.025) in patients with depression than that in those without depression. In conclusion, the burden of depression during the preanaesthetic period among patients with cancer is substantial, and depression reduces propofol requirement during surgery.
Profile of cough triggers and their relationship with capsaicin cough sensitivity in chronic cough
Authors: Xu Tingting , Chen Zhiyin , Zhan Chen , Zhan Wenzhi , Yi Fang , Lai Kefang
Published: February 2024

Background:

Cough hypersensitivity is an important part of the neurophysiology of cough, which presents with increased cough response to a lower level of stimuli or triggers. Classification of stimuli might bring about additional insight into the underlying mechanisms and management.

Objectives:

This study investigated the profile of cough triggers in chronic cough patients and their relationship with capsaicin cough sensitivity.

Design:

This was a cross-sectional observational study.

Methods:

We enrolled patients with different causes of chronic cough from 2006 to 2021. Cough triggers were defined as cough response to chemical triggers, mechanical triggers, meal triggers, or thermal trigger. Cough sensitivity to capsaicin was evaluated by the capsaicin challenge test, which was expressed as the lowest concentration of capsaicin inducing 5 or more coughing (C5).

Results:

Among 1211 patients with chronic cough, 1107 (91.4%) patients reported at least one cough trigger. Chemical triggers (66.9%) were the most common cough triggers, followed by thermal exposure (50.6%), mechanical triggers (48.2%), and meal triggers (21.2%). There was no difference in the proportion of chemical triggers among different etiologies. Patients with refractory chronic cough reported the highest prevalence of cough triggers (97.1%). A higher number of meal triggers (34.9%) was associated with gastroesophageal reflux-related cough, and meal triggers and mechanical triggers were more common in refractory chronic cough. Among 254 patients who completed capsaicin challenge test, both the number of total triggers and the number of chemical triggers had a significant but mild correlation with capsaicin cough sensitivity.

Conclusion:

Cough hypersensitivity as reflected by a variety of cough triggers is a common feature in chronic cough patients, but different etiologies present specific profiles of cough triggers, which could not be evaluated comprehensively by capsaicin cough sensitivity.
The efficacy of vardenafil and tamsulosin in treatment of lower urinary tract symptoms secondary to benign prostatic hyperplasia: A randomised clinical trial
Authors: Zaza Mohamed Mahmoud , Hussien Adham Hussien Mohamed , Salem Tarek Abdel-Majid , Ali Soliman Mohamed Hassan
Published: February 2024

Objectives:

This randomised controlled trial (RCT) aimed to evaluate the efficacy of vardenafil monotherapy, tamsulosin monotherapy, and combination therapy of vardenafil and tamsulosin in treating lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH).

Methods:

This RCT involved 75 patients presenting with LUTS secondary to BPH. Patients were randomly allocated into three groups, receiving either vardenafil monotherapy, tamsulosin monotherapy, or a combination of both drugs. Assessments and follow-ups were conducted 1, 3, and 6 months after treatment initiation, focusing on improvements in LUTS, uroflowmetry measurements, and patients’ sexual performance. Data analysis was performed using Microsoft Office Excel 2007 and IBM SPSS statistics software version 22.0.

Results:

This study included 75 participants divided into three groups. No significant differences were found in terms of patients’ age (p = 0.504) or treatment duration (p = 0.680) between the groups. The combination of vardenafil/tamsulosin consistently showed the lowest International Prostate Symptom Score (IPSS) scores and grades, followed by the tamsulosin group (p < 0.001). Regarding Q-max and post-void residual urine (PVRU), significant differences were observed between the vardenafil group and the other two groups (p > 0.001), but no significant differences were found between the tamsulosin and vardenafil/tamsulosin groups.

Conclusion:

The combination therapy with vardenafil and tamsulosin is more effective in improving LUTS secondary to BPH than monotherapy. Tamsulosin monotherapy also appears to be more effective than vardenafil monotherapy. Combination therapy provides a viable treatment option for patients who do not respond adequately to monotherapy or experience adverse effects from either drug.

Level of Evidence:

Moderate
Do AIs know what the most important issue is? Using language models to code open-text social survey responses at scale
Authors: Mellon Jonathan , Bailey Jack , Scott Ralph , Breckwoldt James , Miori Marta , Schmedeman Phillip
Published: February 2024

Can artificial intelligence accurately label open-text survey responses? We compare the accuracy of six large language models (LLMs) using a few-shot approach, three supervised learning algorithms (SVM, DistilRoBERTa, and a neural network trained on BERT embeddings), and a second human coder on the task of categorizing “most important issue” responses from the British Election Study Internet Panel into 50 categories. For the scenario where a researcher lacks existing training data, the accuracy of the highest-performing LLM (Claude-1.3: 93.9%) neared human performance (94.7%) and exceeded the highest-performing supervised approach trained on 1000 randomly sampled cases (neural network: 93.5%). In a scenario where previous data has been labeled but a researcher wants to label novel text, the best LLM’s (Claude-1.3: 80.9%) few-shot performance is only slightly behind the human (88.6%) and exceeds the best supervised model trained on 576,000 cases (DistilRoBERTa: 77.8%). PaLM-2, Llama-2, and the SVM all performed substantially worse than the best LLMs and supervised models across all metrics and scenarios. Our results suggest that LLMs may allow for greater use of open-ended survey questions in the future.
Emerging Adults’ Experiences of Managing Social Group Disruptions
Authors: Hawkins Jared , D’Aniello-Heyda Carissa , Fife Stephen , Cravens Jaclyn Pickens , Bean Roy
Published: February 2024

Emerging adults experience frequent life transitions that disrupt social groups and increase loneliness. However, limited research examines how emerging adults respond to social group disruptions. Drawing upon the Social Identity Model of Identity Change (SIMIC), this study explored 11 emerging adults’ experiences of managing social group disruptions. Using interpretive phenomenological analysis (IPA), we identified seven themes that helped participants mitigate loneliness after experiencing social group disruptions. Themes included: (a) engaging with existing social groups, (b) proactively forming new relationships, (c) using technology, (d) becoming more selective about forming and maintaining friendships, (e) increasing acceptance and positive thinking, (f) engaging in meaningful activities, and (g) focusing on self-development. The results call for further research on how emerging adults can effectively manage social group disruptions to mitigate loneliness.
Role of Optical Coherence Tomography in Coronary Interventions
Authors: Maddali Vikas Reddy , Koganti Sudheer
Published: February 2024

Optical coherence tomography (OCT) is an optical analog of intravascular ultrasound (IVUS) used to examine the coronary arteries with a higher resolution. Based on polarization properties, OCT can differentiate tissue characteristics (fibrous, calcified, or lipid-rich plaque) and identify vulnerable plaque. Because of the strong attenuation of light by blood, OCT requires a field of view that is free of blood. OCT can provide detailed information on coronary intervention such as dissection, tissue prolapse, thrombus stent malapposition, and under expansion. Despite the diagnostic utility of OCT, facilitated by its high resolution, the impact of intracoronary OCT on clinical practice has thus far been limited for various reasons. Herein, we provide a comprehensive up-to-date overview on the utility of OCT in coronary artery disease, specifically acute coronary syndromes along with a summary of the evidence, work in progress, and future directions.
Simulation of 0–7.5 Hz physics-based nonlinear ground motions for maximum credible earthquake scenarios at the Long Valley Dam, CA
Authors: Yeh Te-Yang , Olsen Kim Bak
Published: February 2024

We have conducted three-dimensional (3D) 0–7.5 Hz physics-based wave propagation simulations to model the seismic response of the Long Valley Dam (LVD), which has formed Lake Crowley in Central California, to estimate peak ground motions and settlement of the dam expected during maximum credible earthquake (MCE) scenarios on the nearby Hilton Creek Fault (HCF). We calibrated the velocity structure, anelastic attenuation model, and the overall elastic properties of the dam via linear simulations of a Mw 3.7 event as well as the Mw 6.2 Chalfant Valley earthquake of 1986, constrained by observed ground motions on and nearby the LVD. The Statewide California Earthquake Center (SCEC) Community Velocity Model CVM-S4.26.M01 superimposed with a geotechnical layer using [Formula: see text] information tapered from the surface to a 700-m depth was used in the simulations. We found optimal fit of simulated and observed ground motions at the LVD using frequency-independent attenuation of [Formula: see text] ([Formula: see text] in m/s). Using the calibrated model, we simulated 3D nonlinear ground motions at the LVD for Mw 6.6 rupture scenarios on the HCF using an Iwan-type, multi-yield-surface technique. We use a two-step method where the computationally expensive nonlinear calculations were carried out in a small domain with the plane wave excitation along the bottom boundary obtained from a full-domain 3D linear finite-fault simulation. Our nonlinear MCE simulation results show that peak ground velocities (PGVs) and peak ground accelerations (PGAs) as high as 72 cm/s and 0.55 g, respectively, can be expected at the crest of the LVD. Compared with linear ground motion simulation results, our results show that Iwan nonlinear damping reduces PGAs on the dam crest by up to a factor of 8 and increasingly depletes the high-frequency content of the waves toward the dam crest. We find horizontal relative displacements of the material inside the dam of up to [Formula: see text] and up to [Formula: see text] of vertical subsidence, equivalent to 1% of the dam height.
Molecular characterization of antibiotic-resistant bacteria associated with maggots obtained from chicken droppings
Authors: Ajibade Olumide Alaba , Akinduro Adebayonle Olayiwola , Omojufehinsi Gbajesu , Odetoyin Babatunde , Olaniyi Oladipo Oladiti
Published: February 2024

Background

The use of maggots, developed from chicken droppings as alternative fish meal might serve as a reservoir and vehicle for the widespread of single and multiple antibiotic resistant bacteria (MARB). This study aimed at investigating antibiotic resistant bacteria from chicken droppings and maggots developed from them, and the associated resistance genes and mobile genetic elements in their genomes. Freshly collected poultry droppings obtained from three commercial poultry farms, in Akure, Nigeria and maggots developed from their composting were plated on Luria–Bertani (LB) agar plates that had been incorporated with antibiotics. The emerged MARB were presumptively identified by conventional cultural microbiological methods and then authenticated using 16S rRNA gene sequence analysis. The antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in the genome of MARB were detected by standard molecular tools.

Results

Potential bacterial pathogens isolated include Escherichia coli, Bacillus cereus, Salmonella enterica, Providencia stuartii, P. rettgeri, Pseudomonas aeruginosa, Staphylococcus aureus, Alcaligenes faecalis, Paelnalcaligenes hominis and Micrococcus luteus. Seventeen ARGs were widely distributed among the 19 ARB/MARB. Tetracycline resistance gene was widely distributed among the ARB/MARB with prevalence of 62%, while macrolides and beta lactam resistance gene had 17% and 13%, respectively. At least six MARB isolates showed the presence of two or more class 1 integron, while five isolates was detected to carry two or more class 2 integron among the 19 MARB.

Conclusions

The results highlight a much higher risk of ARGs spreading through maggots derived from chicken droppings to humans and environmental microbiota.
A supervised learning method for classifying methylation disorders
Authors: Walsh Jesse R. , Sun Guangchao , Balan Jagadheshwar , Hardcastle Jayson , Vollenweider Jason , Jerde Calvin , Rumilla Kandelaria , Koellner Christy , Koleilat Alaa , Hasadsri Linda , Kipp Benjamin , Jenkinson Garrett , Klee Eric
Published: February 2024

Background

DNA methylation is one of the most stable and well-characterized epigenetic alterations in humans. Accordingly, it has already found clinical utility as a molecular biomarker in a variety of disease contexts. Existing methods for clinical diagnosis of methylation-related disorders focus on outlier detection in a small number of CpG sites using standardized cutoffs which differentiate healthy from abnormal methylation levels. The standardized cutoff values used in these methods do not take into account methylation patterns which are known to differ between the sexes and with age.

Results

Here we profile genome-wide DNA methylation from blood samples drawn from within a cohort composed of healthy controls of different age and sex alongside patients with Prader–Willi syndrome (PWS), Beckwith–Wiedemann syndrome, Fragile-X syndrome, Angelman syndrome, and Silver–Russell syndrome. We propose a Generalized Additive Model to perform age and sex adjusted outlier analysis of around 700,000 CpG sites throughout the human genome. Utilizing z-scores among the cohort for each site, we deployed an ensemble based machine learning pipeline and achieved a combined prediction accuracy of 0.96 (Binomial 95% Confidence Interval 0.868$$-$$
-
0.995).

Conclusion

We demonstrate a method for age and sex adjusted outlier detection of differentially methylated loci based on a large cohort of healthy individuals. We present a custom machine learning pipeline utilizing this outlier analysis to classify samples for potential methylation associated congenital disorders. These methods are able to achieve high accuracy when used with machine learning methods to classify abnormal methylation patterns.
TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations
Authors: Wang Yu , Jiang Zhonghua , Liang Pengkuan , Liu Zhuochong , Cai Haoyang , Sun Qun
Published: February 2024

The most widely practiced strategy for constructing the deep learning (DL) prediction model for drug resistance of Mycobacterium tuberculosis (MTB) involves the adoption of ready-made and state-of-the-art architectures usually proposed for non-biological problems. However, the ultimate goal is to construct a customized model for predicting the drug resistance of MTB and eventually for the biological phenotypes based on genotypes. Here, we constructed a DL training framework to standardize and modularize each step during the training process using the latest tensorflow 2 API. A systematic and comprehensive evaluation of each module in the three currently representative models, including Convolutional Neural Network, Denoising Autoencoder, and Wide & Deep, which were adopted by CNNGWP, DeepAMR, and WDNN, respectively, was performed in this framework regarding module contributions in order to assemble a novel model with proper dedicated modules. Based on the whole-genome level mutations, a de novo learning method was developed to overcome the intrinsic limitations of previous models that rely on known drug resistance-associated loci. A customized DL model with the multilayer perceptron architecture was constructed and achieved a competitive performance (the mean sensitivity and specificity were 0.90 and 0.87, respectively) compared to previous ones. The new model developed was applied in an end-to-end user-friendly graphical tool named TB-DROP (TuBerculosis Drug Resistance Optimal Prediction: https://github.com/nottwy/TB-DROP), in which users only provide sequencing data and TB-DROP will complete analysis within several minutes for one sample. Our study contributes to both a new strategy of model construction and clinical application of deep learning-based drug-resistance prediction methods.
Network pharmacology-based strategy to investigate the mechanisms of artemisinin in treating primary Sjögren’s syndrome
Authors: Liao Jia-he , He Qian , Huang Zi-wei , Yu Xin-bo , Yang Jian-ying , Zhang Yan , Song Wei-jiang , Luo Jing , Tao Qing-wen
Published: February 2024

Objective

The study aimed to explore the mechanism of artemisinin in treating primary Sjögren’s syndrome (pSS) based on network pharmacology and experimental validation.

Methods

Relevant targets of the artemisinin and pSS-related targets were integrated by public databases online. An artemisinin-pSS network was constructed by Cytoscape. The genes of artemisinin regulating pSS were imported into STRING database to construct a protein-protein interaction (PPI) network in order to predict the key targets. The enrichment analyses were performed to predict the crucial mechanism and pathway of artemisinin against pSS. The active component of artemisinin underwent molecular docking with the key proteins. Artemisinin was administered intragastrically to SS-like NOD/Ltj mice to validate the efficacy and critical mechanisms.

Results

Network Pharmacology analysis revealed that artemisinin corresponded to 412 targets, and pSS related to 1495 genes. There were 40 intersection genes between artemisinin and pSS. KEGG indicated that therapeutic effects of artemisinin on pSS involves IL-17 signaling pathway, HIF-1 signaling pathway, apoptosis signaling pathway, Th17 cell differentiation, PI3K-Akt signaling pathway, and MAPK signaling pathway. Molecular docking results further showed that the artemisinin molecule had higher binding energy by combining with the key nodes in IL-17 signaling pathway. In vivo experiments suggested artemisinin can restored salivary gland secretory function and improve the level of glandular damage of NOD/Ltj mice. It contributed to the increase of regulatory T cells (Tregs) and the downregulated secretion of IL-17 in NOD/Ltj model.

Conclusion

The treatment of pSS with artemisinin is closely related to modulating the balance of Tregs and Th17 cells via T cell differentiation.
It needs more than a myocardial infarction to start exercising: the CoLaus|PsyCoLaus prospective study
Authors: Flammer François , Paraschiv-Ionescu Anisoara , Marques-Vidal Pedro
Published: February 2024

Background

Increased physical activity (PA) is recommended after an acute coronary event to prevent recurrences. Whether patients with acute coronary event actually increase their PA has not been assessed using objective methods such as accelerometer. We aimed to assess the subjectively and objectively measured physical activity (PA) levels of patients before and after an acute coronary event.

Methods

Data from the three follow-up surveys of a prospective study conducted in Lausanne, Switzerland. Self-reported PA was assessed by questionnaire in the first (2009–2012) and second (2014–2017) follow-ups. Objective PA was assessed by a wrist-worn accelerometer in the second and third (2018–2021) follow-ups. Participants who developed an acute coronary event between each survey period were considered as eligible. PA levels were compared before and after the event, and changes in PA levels were also compared between participants who developed an acute event with three gender and age-matched healthy controls.

Results

For self-reported PA, data from 43 patients (12 women, 64 ± 9 years) were used. No differences were found for all PA levels expressed in minutes/day before and after the event: moderate PA, median and [interquartile range] 167 [104–250] vs. 153 [109–240]; light PA: 151 [77–259] vs. 166 [126–222], and sedentary behaviour: 513 [450–635] vs. 535 [465–642] minutes/day. Comparison with gender- and age-matched healthy controls showed no differences regarding trends in reported PA. For accelerometer-assessed PA, data from 32 patients (16 women, 66 ± 9 years) were used. No differences were found for all PA levels expressed in minutes/day before and after the event: moderate PA: 159 [113–189] vs. 141 [111–189]; light PA: 95.8 [79–113] vs. 95.9 [79–117], and sedentary behaviour: 610 [545–659] vs. 602 [540–624]. Regarding the comparison with gender- and age-matched healthy controls, controls had an increase in accelerometer-assessed sedentary behaviour as % of day: multivariable adjusted average standard error 2.7 ± 0.6, while no increase was found for cases: 0.1 ± 1.1; no differences were found for the other PA levels.

Conclusion

Patients do not seem to change their PA levels after a first coronary event. Our results should be confirmed in larger samples.
Coronary artery disease incidence, risk factors, awareness, and medication utilization in a 10-year cohort study
Authors: Sarebanhassanabadi Mohammadtaghi , Mirjalili Seyed Reza , Marques-Vidal Pedro , Kraemer Alexander , Namayandeh Seyedeh Mahdieh
Published: February 2024

Background

There is a substantial disparity in coronary artery disease (CAD) burden between Iran and other nations that place a strong emphasis on the assessment of CAD risk factors and individuals’ awareness and ability to control them.

Methods

Two thousand participants of a community-based Iranian population aged 20–74 years were investigated with a mean follow-up of 9.9 years (range: 7.6 to 12.2). An analysis of Cox regression was conducted to determine the association between CAD development and classic risk factors such as age, sex, smoking, physical activity, education, obesity, dyslipidemia, hypertension, and diabetes mellitus. Furthermore, we computed the population attributable fraction for these risk factors.

Results

After a follow-up period of nearly 10 years, 225 CAD events were reported, constituting 14.5% of the overall incidence. Nighty three percent of participants had more than one risk factor. Age was the most predictive risk factor, with a hazard ratio (HR) and confidence interval (CI) of 5.56 (3.87–7.97, p < 0.001) in men older than 45 and females older than 55 compared to lower ages. In comparison to females, males had an HR of 1.45 (CI: 1.11–1.90, p value = 0.006) for developing CAD. Nearly 80% of the patients had dyslipidemia, with a hazard ratio of 2.19 (CI: 1.40–3.44, p = 0.01). Among the participants, 28.9% had hypertension, and 52% had prehypertension, which had HRs of 4.1 (2.4–7.2, p < 0.001) and 2.4 (1.4–4.2, p < 0.001), respectively. Diabetes, with a prevalence of 17%, had an HR of 2.63 (CI: 2 -3.47, p < 0.001), but prediabetes was not significantly associated with CAD. Awareness of diabetes, dyslipidemia, and hypertension was 81%, 27.9%, and 48.1%, respectively. Regarding medication usage, the corresponding percentages were 51% for diabetes, 13.2% for dyslipidemia, and 41% for hypertension.

Conclusions

Compared to previous studies in Iran and neighboring countries, the current study found a higher incidence of CAD, more prevalent risk factors, and a lower awareness and ability to control these risk factors. Thus, an effective preventive strategy is needed to reduce the CAD burden in Iran.
Psychologists’ involvement in and experiences of treating patients with stress-related exhaustion in primary care
Authors: Ellbin Susanne , Lindegård Agneta , Jonsdottir Ingibjörg H. , Dahlborg Elisabeth
Published: February 2024

Background

Primary health care is the setting for most patients with stress-related mental health problems. Good care processes are important for patients with stress-related mental health problems and the complex needs of these patients has become a challenge for primary care settings which is traditionally designed to manage acute episodes of one illness. The care process of these patients is thus interesting to investigate. The aim of this study was to explore psychologists´ involvement and experiences regarding the organisation of the care process and treatment of patients seeking care for stress-related exhaustion.

Method

Fifteen psychologists (14 women and 1 man, age range 27–72 years)c from fifteen different primary health care centres in the western part of Sweden, located in both rural and urban areas were included. Qualitative content analysis of individual semi-structured interviews was conducted.

Results

The analysis resulted in eight subcategories within the two main categories studied illuminating psychologists’ involvement and experiences regarding the organisation of the care process and challenges regarding treatment of patients seeking care for stress-related exhaustion.

Conclusion

The care process of patients with stress-related exhaustion is perceived to be ineffective and not congruent with the needs of the patients. A lack of holistic overview of the care process, a lack of collaboration and poor utilization of the health care professionals’ competence leads to an unstructured process forcing the patients to be the carriers and coordinators of their own care.
Hsa-miR-194-5p and hsa-miR-195-5p are down-regulated expressed in high dysplasia HPV-positive Pap smear samples compared to normal cytology HPV-positive Pap smear samples
Authors: Dehghani Ali , Khajepour Fardin , Dehghani Mohammad , Razmara Ehsan , Zangouey Mohammadreza , Abadi Maryam Fekri Soofi , Nezhad Reza Bahram Abadi , Dabiri Shahriar , Garshasbi Masoud
Published: February 2024

Background

The human papillomavirus (HPV) infection may affect the miRNA expression pattern during cervical cancer (CC) development. To demonstrate the association between high-risk HPVs and the development of cervix dysplasia, we examined the expression patterns of hsa-miR-194-5p and hsa-miR-195-5p in Pap smear samples from southeast Iranian women. We compared samples that were HPV-positive but showed no abnormality in the cytological examination to samples that were HPV-positive and had severe dysplasia.

Methods

Pap smear samples were obtained from 60 HPV-positive (HPV-16/18) patients with histologically confirmed severe dysplasia (cervical intra-epithelial neoplasia (CIN 3) or carcinoma in situ) and the normal cytology group. The expression of hsa-miR-194-5p and hsa-miR-195-5p was analyzed by real-time quantitative PCR, using specific stem-loop primers and U6 snRNA as the internal reference gene. Clinicopathological features were associated with miRNA expression levels. Furthermore, functional enrichment analysis was conducted using in silico tools. The Kaplan–Meier survival method was also obtained to discriminate survival-significant candidate miRNAs in CC, and receiver operating characteristic (ROC) curves were constructed to assess the diagnostic value.

Results

Compared to HPV-positive cytologically normal Pap smear samples, hsa-miR-194-5p and hsa-miR-195-5p relative expression decreased significantly in HPV-positive patients with a severe dysplasia Pap smear. Kaplan–Meier analysis indicated a significant association between the miR-194 decrease and poor CC survival. In essence, ROC curve analysis showed that miR-194-5p and miR-195-5p could serve as valuable markers for the development of cervix dysplasia in individuals who are positive for high-risk HPVs.

Conclusions

This study revealed that hsa-miR-194-5p and hsa-miR-195-5p may possess tumor suppressor capabilities in the context of cervical dysplasia progression. However, it remains uncertain whether these microRNAs are implicated in the transition of patients with high dysplasia to cervical cancer. We also showed the potential capability of candidate miRNAs as novel diagnostic biomarkers related to cervical dysplasia progression.