bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Procedure for Multi-Focus Images Using Image Fusion with qshiftN DTCWT and MPCA in Laplacian Pyramid Domain
Authors: Mohan Chinnem Rama , Chouhan Kuldeep , Rout Ranjeet Kumar , Sahoo Kshira Sagar , Jhanjhi Noor Zaman , Ibrahim Ashraf Osman , Abdelmaboud Abdelzahir
Published: September 2022

Multi-focus image fusion (MIF) uses fusion rules to combine two or more images of the same scene with various focus values into a fully focused image. An all-in-focus image refers to a fully focused image that is more informative and useful for visual perception. A fused image with high quality is essential for maintaining shift-invariant and directional selectivity characteristics of the image. Traditional wavelet-based fusion methods, in turn, create ringing distortions in the fused image due to a lack of directional selectivity and shift-invariance. In this paper, a classical MIF system based on quarter shift dual-tree complex wavelet transform (qshiftN DTCWT) and modified principal component analysis (MPCA) in the laplacian pyramid (LP) domain is proposed to extract the focused image from multiple source images. In the proposed fusion approach, the LP first decomposes the multi-focus source images into low-frequency (LF) components and high-frequency (HF) components. Then, qshiftN DTCWT is used to fuse low and high-frequency components to produce a fused image. Finally, to improve the effectiveness of the qshiftN DTCWT and LP-based method, the MPCA algorithm is utilized to generate an all-in-focus image. Due to its directionality, and its shift-invariance, this transform can provide high-quality information in a fused image. Experimental results demonstrate that the proposed method outperforms many state-of-the-art techniques in terms of visual and quantitative evaluations.
Analysis of Coating Loss from Coated Stainless Steel Orthodontic Wire
Authors: Ito Arata , Kitaura Hideki , Noguchi Takahiro , Ohori Fumitoshi , Mizoguchi Itaru
Published: September 2022

The leaching of metal ions from orthodontic appliances into the oral cavity is problematic for metal-allergic patients. Non-metal orthodontic appliances, such as plastic and ceramic brackets and elastomeric materials, have been clinically used and are effective for treatment of metal-allergic patients. However, only a few types of orthodontic wire are available for use in patients with metal allergies, thus restricting the establishment of orthodontic force systems in these patients. Wire surfaces can be coated with various substances to prevent leaching of metal ions. However, detachment of the coating may occur during orthodontic procedures, resulting in metal ion leaching from the substrate material. This study was performed to examine the resilience of various types of coated stainless steel wire to low pH, bending, and brushing. Wire surface characteristics were examined by stereomicroscopy and scanning electron microscopy. The degree of coating detachment due to bending of the wire was quantified by determining the change in the amount of metal ions eluted from the site of the bend immersed in hydrochloric acid. Exposure of the substrate metal by brushing was investigated by energy dispersive spectrometry. The results indicated that polyethylene naphthalate (PEN)-coated wire is resilient to bending, while gold (Au)-coated and titanium nitride (TiN)-coated wires are resilient to brushing.
Research on the Spatiotemporal Characteristics and Concentration Prediction Model of PM2.5 during Winter in Jiangbei New District, Nanjing, China
Authors: Li Yuanxi , Zhu Zhongzheng , Xin Chengrui , Chen Zhilong , Wang Sunyuan , Liang Zhenyu , Zou Xiuguo
Published: September 2022

Accurate prediction of PM2.5 concentration is one of the key tasks of air pollution assessment, early warning, and treatment. In this paper, four monitoring sites were arranged in Jiangbei New District of Nanjing City, China. The environmental parameters such as PM2.5/PM10 concentration, temperature, and humidity were monitored from January to February 2020. A gated recurrent unit (GRU) network based on the PM2.5 concentration prediction model was established to predict PM2.5 concentration. The mean relative error (MRE), root mean square error (RMSE), and Pearson correlation coefficient were selected as the evaluation criteria for the accuracy of the GRU model. The data set was divided into a training set, a test set and a validation set at a ratio of 7:2:1, and the GRU model was used to predict the hourly value of PM2.5 concentration in the next week. The prediction results show that the Pearson correlation coefficients between the predicted values and the monitored values of the four monitoring sites have reached more than 0.9, reflecting a strong correlation. The relative average errors are around 10%. The GRU model prediction of NJAU (Nanjing Agricultural University)-Pukou Campus Site is the most accurate, and the correlation coefficient, MRE, and RMSE are 0.970, 7.85%, and 9.6049, respectively, reflecting the good prediction performance of the model. Therefore, this research supports the prediction of air quality in different cities and regions, so people can take protective measures in advance and reduce the damage caused by air pollution to human bodies.
Estimation of Sensible and Latent Heat Fluxes Using Flux Variance Method under Unstable Conditions: A Case Study of Tea Plants
Authors: Buttar Noman Ali , Hu Yongguang , Tanny Josef , Raza Ali , Niaz Yasir , Khan Muhammad Imran , Saddique Naeem , Sarwar Abid , Azeem Ahmad , Ahmed Fiaz , Bilal Idrees Muhammad
Published: September 2022

Evapotranspiration is essential for precise irrigation and water resource management. Previous literature suggested that eddy covariance (EC) systems could directly measure evapotranspiration in agricultural fields. However, the eddy covariance method remains difficult for routine use, due to its high cost, operational complexity, and relatively multifaceted raw data processing. An alternative method is the flux variance (FV) method, which can estimate the sensible heat flux using high-frequency air temperature measurements by fine-wire thermocouples, at relatively low-cost and with less complexity. Additional measurements of the net radiation and soil heat flux permit the extraction of latent heat flux through the energy balance closure equation. This study examined the performance of the FV method and the results were compared against direct eddy covariance measurements. Data were collected from November 2018 to July 2019, covering seasonal variations. Due to the method’s limitation, only the data under unstable conditions were used for the analysis and days with rainfall were omitted. The results showed that the FV-estimated sensible heat flux was in good agreement with that of eddy covariance in the seasons of winter 2018 and summer 2019. The best agreement between the estimated and measured sensible heat fluxes was observed in the summer, with R2 = 0.83, RMSE = 34.97 Wm−2 and RE = 8.20%. The FV extracted latent heat flux was in good agreement with that measured by EC for both seasons. The best result was obtained in the summer, with R2 = 0.92, RMSE = 23.12 Wm−2, and RE = 6.37%. Overall estimations of sensible and latent heat fluxes by the FV method were in close relation with the eddy covariance data.
Editorial for the Special Issue “Atmospheric Composition and Regional Climate Studies in Bulgaria”
Authors: Ganev Kostadin , Gadzhev Georgi
Published: September 2022

The Special Issue “Atmospheric composition and regional climate studies in Bulgaria” is focused on the following two problems, which are of great societal and scientific importance: [...]
Evaluation of Urban Canopy Models against Near-Surface Measurements in Houston during a Strong Frontal Passage
Authors: Hendricks Eric A. , Knievel Jason C.
Published: September 2022

Urban canopy models (UCMs) in mesoscale numerical weather prediction models need evaluation to understand biases in urban environments under a range of conditions. The authors evaluate a new drag formula in the Weather Research and Forecasting (WRF) model’s multilayer UCM, the Building Effect Parameterization combined with the Building Energy Model (BEP+BEM), against both in-situ measurements in the urban environment as well as simulations with a simple bulk scheme and BEP+BEM using the old drag formula. The new drag formula varies with building packing density, while the old drag formula is constant. The case study is a strong cold frontal passage that occurred in Houston during the winter of 2017, causing high winds. It is found that both BEP+BEM simulations have lower peak wind speeds, consistent with near-surface measurements, while the bulk simulation has winds that are too strong. The constant-drag BEP+BEM simulation has a near-zero wind speed bias, while the new-drag simulation has a negative bias. Although the focus is on the impact of drag on the urban wind speeds, both BEP+BEM simulations have larger negative biases in the near-surface temperature than the bulk-scheme simulation. Reasons for the different performances are discussed.
Dynamics of Site Selectivity in Dissociative Electron Attachment in Aromatic Molecules
Authors: Tadsare Vishvesh , Das Sukanta , Gokhale Samata , Krishnakumar E. , Prabhudesai Vaibhav S.
Published: September 2022

Dissociative electron attachment has shown site selectivity in aliphatic molecules based on the functional groups present in them. This selectivity arises from the core excited resonances that have excited parent states localized to a specific site of the functional group. Here, we show that such site selectivity is also observed in the amine group when present in aromatic molecules. However, the proximity of the aromatic ring to the functional group under investigation has a substantial effect on the dissociation dynamics. This effect is evident in the momentum distribution of the hydride ions generated from the amine group. Our results unravel the hitherto unknown facets of the site selectivity in aromatic organic molecules.
Photosynthesis Monitoring in Microalgae Cultures Grown on Municipal Wastewater as a Nutrient Source in Large-Scale Outdoor Bioreactors
Authors: Masojídek Jiří , Gómez-Serrano Cintia , Ranglová Karolína , Cicchi Bernardo , Encinas Bogeat Ángel , Câmara Manoel João A. , Sanches Zurano Ana , Silva Benavides Ana Margarita , Barceló-Villalobos Marta , Robles Carnero Victor A. , Ördög Vince , Gómez Pinchetti Juan Luis , Vörös Lajos , Arbib Zouhayr , Rogalla Frank , Torzillo Giuseppe , Lopez Figueroa Félix , Acién-Fernándéz Francisco Gabriel
Published: September 2022

Microalgae cultures were used for a WW treatment to remediate nutrients while producing biomass and recycling water. In these trials, raceway ponds (RWPs; 1 and 0.5 ha) were located next to a municipal (WW) treatment plant in Mérida, Spain. The ponds were used for continuous, all-year-round microalgae production using WW as a source of nutrients. Neither CO2 nor air was supplied to cultures. The objective was to validate photosynthesis monitoring techniques in large-scale bioreactors. Various in-situ/ex-situ methods based on chlorophyll fluorescence and oxygen evolution measurements were used to follow culture performance. Photosynthesis variables gathered with these techniques were compared to the physiological behavior and growth of cultures. Good photosynthetic activity was indicated by the build-up of dissolved oxygen concentration up to 380% saturation, high photochemical yield (Fv/Fm = 0.62–0.71), and relative electron transport rate rETR between 200 and 450 μmol e− m−2 s−1 at midday, which resulted in biomass productivity of about 15–25 g DW m−2 day−1. The variables represent reliable markers reflecting the physiological status of microalgae cultures. Using waste nutrients, the biomass production cost can be significantly decreased for abundant biomass production in large-scale bioreactors, which can be exploited for agricultural purposes.
Influence of Rigor Mortis on Tendon Mobility in an Animal Fresh Cadaver Model
Authors: Luecke Christoph , Schnetzke Marc , Weiss Christel , Studier-Fischer Stefan , Guehring Thorsten , Gruetzner Paul A. , Porschke Felix
Published: September 2022

(1) Many biomechanical studies are performed using fresh frozen cadavers or embalmed specimens, although the biomechanical characteristics do not match the characteristics of in vivo tendons. Therefore, a fresh in vivo-like cadaver model has been introduced recently. As a limitation for studies with fresh cadavers, rigor mortis must be considered. The aim of this study was to evaluate the impact of the biomechanical properties and time of occurrence of rigor mortis in a fresh cadaver model. (2) For this study, 15 fresh porcine cadaver shoulders were used in an established biomechanical in vitro model to evaluate the onset of rigor mortis. Measurements took place at ten points of time (t1–t10) beginning 103 min post mortem (pm). The mobility of the supraspinatus tendon was measured in Newton (N) with a modified sensor-enhanced arthroscopic grasper. (3) The mean load measured at the time point t1 was 28.0 ± 11.2 N. The first significant decrease of mobility occurred 151 min post mortem (t4) at a mean load of 30.2 ± 13.7 N. From 227 min pm to 317 min pm, there was no further significant increase. (4) Tendon mobility decreases significantly within the first three hours after the killing. Therefore, reliable results can be obtained within 150 min post mortem before the onset of rigor mortis alters the biomechanical properties.
Shortened Hinge Design of Fab x sdAb-Fc Bispecific Antibodies Enhances Redirected T-Cell Killing of Tumor Cells
Authors: Huang Shuyu , Segués Aina , Waterfall Martin , Wright David , Vayssiere Charlotte , van Duijnhoven Sander M. J. , van Elsas Andrea , Sijts Alice J. A. M. , Zaiss Dietmar M.
Published: September 2022

T cell engager (TCE) antibodies have emerged as promising cancer therapeutics that link cytotoxic T-cells to tumor cells by simultaneously binding to CD3E on T-cells and to a tumor-associated antigen (TAA) expressed by tumor cells. We previously reported a novel bispecific format, the IgG-like Fab x sdAb-Fc (also known as half-IG_VH-h-CH2-CH3), combining a conventional antigen-binding fragment (Fab) with a single domain antibody (sdAb). Here, we evaluated this Fab x sdAb-Fc format as a T-cell redirecting bispecific antibody (TbsAbs) by targeting mEGFR on tumor cells and mCD3E on T cells. We focused our attention specifically on the hinge design of the sdAb arm of the bispecific antibody. Our data show that a TbsAb with a shorter hinge of 23 amino acids (TbsAb.short) showed a significantly better T cell redirected tumor cell elimination than the TbsAb with a longer, classical antibody hinge of 39 amino acids (TbsAb.long). Moreover, the TbsAb.short form mediated better T cell-tumor cell aggregation and increased CD69 and CD25 expression levels on T cells more than the TbsAb.long form. Taken together, our results indicate that already minor changes in the hinge design of TbsAbs can have significant impact on the anti-tumor activity of TbsAbs and may provide a new means to improve their potency.
“Fingerprinting” Benign and Cancerous Skin Lesions Using Vibrational Optical Coherence Tomography: Differentiation among Cancerous Lesion Types Based on the Presence of New Cells, Blood Vessels, and Fibrosis
Authors: Silver Frederick H. , Deshmukh Tanmay , Ryan Nicole , Romm Arielle , Nadiminti Hari
Published: September 2022

In this study, we use vibrational optical coherence tomography (VOCT) to examine the morphology and stiffness of benign and cancerous lesions. Lesion images and 3D plots of weighted displacement versus frequency and depth were used to compare the cellular, dermal collagen, new blood vessels, and fibrotic composition of normal skin, actinic keratoses (AK), nodular and superficial basal cell carcinomas (BCCs), squamous cell carcinomas (SCCs), and melanomas. The results of this study suggest that benign and cancerous lesions differ based on the addition of new cells with increased resonant frequency and stiffness (80 Hz, 1.8 MPa), new blood vessel peaks (130 Hz, 4.10 MPa) that appear to be less stiff than normal blood vessels, and new fibrous tissue peaks (260 Hz, 15–17 MPa) that are present in carcinomas but not in normal skin and only partially present (80 Hz and 130 Hz only) in AKs. Results obtained by creating images based on the location of the 80 Hz, 130 Hz, and 260 Hz peaks of cancerous skin lesions suggest that the fibrous tissue appears to surround the new cells and new lesion blood vessels. The results of this study suggest that the morphology and location of the fibrous tissues in relation to the new cancer-associated cells and lesion blood vessels may provide information on the invasiveness and metastatic potential of skin cancers. The invasiveness and metastatic potential of melanomas may be a result of the cancer-associated cells laying down fibrous tissue that is used as a pathway for migration. The new cancer-associated blood vessels in the vicinity of the new cancer-associated cells may promote this migration and eventual metastasis. The ratios of peak heights 50/130 Hz and 80/130 Hz of normal cells, new lesion cells, new lesion blood vessels, and fibrotic tissue may be used as a “fingerprint” for detecting melanoma and to differentiate it from other skin cancers non-invasively using VOCT.
Liraglutide Attenuates Glucolipotoxicity-Induced RSC96 Schwann Cells’ Inflammation and Dysfunction
Authors: Kornelius Edy , Tsou Sing-Hua , Chang Ching-Chi , Ho Ying-Jui , Lin Sheng-Chieh , Chen Wei-Liang , Huang Chien-Ning , Lin Chih-Li
Published: September 2022

Diabetic neuropathy (DN) is a type of sensory nerve damage that can occur in patients with diabetes. Although the understanding of pathophysiology is incomplete, DN is often associated with structural and functional alterations of the affected neurons. Among all possible causes of nerve damage, Schwann cells (SCs) are thought to play a key role in repairing peripheral nerve injury, suggesting that functional deficits occurring in SCs may potentially exhibit their pathogenic roles in DN. Therefore, elucidating the mechanisms that underlie this pathology can be used to develop novel therapeutic targets. In this regard, glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have recently attracted great attention in ameliorating SCs’ dysfunction. However, the detailed mechanisms remain uncertain. In the present study, we investigated how GLP-1 RA Liraglutide protects against RSC96 SCs dysfunction through a diabetic condition mimicked by high glucose and high free fatty acid (FFA). Our results showed that high glucose and high FFAs reduced the viability of RSC96 SCs by up to 51%, whereas Liraglutide reduced oxidative stress by upregulating antioxidant enzymes, and thus protected cells from apoptosis. Liraglutide also inhibited NFκB-mediated inflammation, inducing SCs to switch from pro-inflammatory cytokine production to anti-inflammatory cytokine production. Moreover, Liraglutide upregulated the production of neurotrophic factors and myelination-related proteins, and these protective effects appear to be synergistically linked to insulin signaling. Taken together, our findings demonstrate that Liraglutide ameliorates diabetes-related SC dysfunction through the above-mentioned mechanisms, and suggest that modulating GLP-1 signaling in SCs may be a promising strategy against DN.
From Small Peptides to Large Proteins against Alzheimer’sDisease
Authors: Picone Pasquale , Sanfilippo Tiziana , Vasto Sonya , Baldassano Sara , Guggino Rossella , Nuzzo Domenico , Bulone Donatella , San Biagio Pier Luigi , Muscolino Emanuela , Monastero Roberto , Dispenza Clelia , Giacomazza Daniela
Published: September 2022

Alzheimer’s disease (AD) is the most common neurodegenerative disorder in the elderly. The two cardinal neuropathological hallmarks of AD are the senile plaques, which are extracellular deposits mainly constituted by beta-amyloids, and neurofibrillary tangles formed by abnormally phosphorylated Tau (p-Tau) located in the cytoplasm of neurons. Although the research has made relevant progress in the management of the disease, the treatment is still lacking. Only symptomatic medications exist for the disease, and, in the meantime, laboratories worldwide are investigating disease-modifying treatments for AD. In the present review, results centered on the use of peptides of different sizes involved in AD are presented.
Comparative Evaluation of Inducible Cre Mouse Models for Fibroblast Targeting in the Healthy and Infarcted Myocardium
Authors: Aguado-Alvaro Laura Pilar , Garitano Nerea , Abizanda Gloria , Larequi Eduardo , Prosper Felipe , Pelacho Beatriz
Published: September 2022

Several Cre recombinase transgenic mouse models have been generated for cardiac fibroblast (CF) tracking and heart regulation. However, there is still no consensus on the ideal mouse model to optimally identify and/or regulate these cells. Here, a comparative evaluation of the efficiency and specificity of the indirect reporter Cre-loxP system was carried out in three of the most commonly used fibroblast reporter transgenic mice (Pdgfra-CreERT2, Col1a1-CreERT2 and PostnMCM) under healthy and ischemic conditions, to determine their suitability in in vivo studies of cardiac fibrosis. We demonstrate optimal Cre recombinase activity in CF (but also, although moderate, in endothelial cells (ECs)) derived from healthy and infarcted hearts in the PDGFRa-creERT2 mouse strain. In contrast, no positive reporter signal was found in CF derived from the Col1a1-CreERT2 mice. Finally, in the PostnMCM line, fluorescent reporter expression was specifically detected in activated CF but not in EC, which leads us to conclude that it may be the most reliable model for future studies on cardiovascular disease. Importantly, no lethality or cardiac fibrosis were induced after tamoxifen administration at the established doses, either in healthy or infarcted mice of the three fibroblast reporter lineages. This study lays the groundwork for future efficient in vivo CF tracking and functional analyses.
Alpha7 Nicotinic Acetylcholine Receptor Antagonists Prevent Meningitic Escherichia coli-Induced Blood–Brain Barrier Disruptions by Targeting the CISH/JAK2/STAT5b Axis
Authors: Gong Zelong , Gao Xuefeng , Li Yubin , Zou Jinhu , Lun Jingxian , Chen Jie , Zhou Chengxing , He Xiaolong , Cao Hong
Published: September 2022

Despite the availability of antibiotics over the last several decades, excessive antibiotic treatments for bacterial sepsis and meningitis (BSM) in children may result in several adverse outcomes. Hematogenous pathogens may directly induce permeability increases in human brain microvascular endothelial cells (HBMECs) and blood–brain barrier (BBB) dysfunctions. Our preliminary studies demonstrated that the alpha7 nicotinic acetylcholine receptor (α7nAChR) played an important role in the pathogenesis of BSM, accompanied by increasing cytokine-inducible SH2-containing protein (CISH) at the transcriptome level, but it has remained unclear how α7nAChR-CISH works mechanistically. The study aims to explore the underlying mechanism of α7nAChR and CISH during E. coli-induced BSM in vitro (HBMECs) and in vivo (α7nAChR-KO mouse). We found that in the stage of E. coli K1-induced BBB disruptions, α7nAChR functioned as the key regulator that affects the integrity of HBMECs by activating the JAK2–STAT5 signaling pathway, while CISH inhibited JAK2–STAT5 activation and exhibited protective effects against E. coli infection. Notably, we first validated that the expression of CISH could be regulated by α7nAChR in HBMECs. In addition, we determined the protective effects of MLA (methyllycaconitine citrate) and MEM (memantine hydrochloride) (functioning as α7nAChR antagonists) on infected HBMECs and suggested that the α7nAChR–CISH axis could explain the protective effects of the two small-molecule compounds on E. coli-induced HBMECs injuries and BBB disruptions. In conclusion, we dissected the α7nAChR/CISH/JAK2/STAT5 axis as critical for the pathogenesis of E. coli-induced brain microvascular leakage and BBB disruptions and provided novel evidence for the development of α7nAChR antagonists in the prevention of pediatric E. coli BSM.
Voltammetry Peak Tracking for Longer-Lasting and Reference-Electrode-Free Electrochemical Biosensors
Authors: McHenry Adam , Friedel Mark , Heikenfeld Jason
Published: September 2022

Electrochemical aptamer-based sensors offer reagent-free and continuous analyte measurement but often suffer from poor longevity and potential drift even with a robust 3-electrode system. Presented here is a simple, software-enabled approach that tracks the redox-reporter peak in an electrochemical aptamer-based sensor and uses the measurement of redox peak potential to reduce the scanning window to a partial measure of redox-peak-height vs. baseline (~10X reduction in voltage range). This same measurement further creates a virtual reference standard in buffered biofluids such as blood and interstitial fluid, thereby eliminating the effects of potential drift and the need for a reference electrode. The software intelligently tracks voltammogram peak potential via the inflection points of the rising and falling slopes of the measured redox peak. Peak-tracking-derived partial scanning was validated over several days and minimized electrochemically induced signal loss to <5%. Furthermore, the peak-tracking approach was shown to be robust against confounding effects such as fouling. From an applied perspective in creating wearable biosensors, the peak-tracking approach further enables use of a single implanted working electrode, while the counter/reference-electrode may utilize a simple gel-pad electrode on the surface of the skin, compared to implanting working, counter, and reference electrodes conventionally used for stability and reliability but is also costly and invasive. Cumulatively, peak-tracking provides multiple leaps forward required for practical molecular monitoring by extending sensor longevity, eliminating potential drift, simplifying biosensor device construction, and in vivo placement for any redox-mediated sensor that forms parabolic-like data.
The Facial Skin Blood Flow Change of Stroke Patients with Facial Paralysis after Peripheral Magnetic Stimulation: A Pilot Study
Authors: Zhang Yongli , Chen Shugeng , Ruan Yinglu , Lin Jiaying , Li Chengdong , Li Chong , Xu Shuo , Yan Zhijie , Liu Xiangyun , Miao Peng , Jia Jie
Published: September 2022

Background: Facial paralysis (FP) is a common symptom after stroke, which influences the quality of life and prognosis of patients. Recently, peripheral magnetic stimulation (PMS) shows potential effects on peripheral and central nervous system damage. However, the effect of PMS on FP after stroke is still unclear. Methods: In this study, we applied PMS on the facial nerve of nine stroke patients with FP. At the same time, laser speckle contrast imaging (LSCI) was used to explore the facial skin blood flow (SkBF) in 19 healthy subjects and nine stroke patients with FP before and after the PMS intervention. The whole face was divided into 14 regions to compare the SkBF in different sub-areas. Results: In baseline SkBF, we found that there were no significant differences in the SkBF between the left and right faces in the healthy subjects. However, there was a significant difference in the SkBF between the affected and unaffected faces in Region 7 (Chin area, p = 0.046). In the following five minutes after the PMS intervention (Pre_0–5 min), the SkBF increased in Region 5 (p = 0.014) and Region 7 (p = 0.046) and there was an increasing trend in Region 3 (p = 0.088) and Region 6 (p = 0.069). In the five to ten minutes after the intervention (Post_6–10 min), the SkBF increased in Region 5 (p = 0.009), Region 6 (p = 0.021) and Region 7 (p = 0.023) and there was an increasing trend in Region 3 (p = 0.080) and left and right whole face (p = 0.051). Conclusions: These pilot results indicate that PMS intervention could increase facial skin blood flow in stroke patients with FP. A further randomized controlled trial can be performed to explore its possible clinical efficacy.
Epileptic Seizure Detection Based on Variational Mode Decomposition and Deep Forest Using EEG Signals
Authors: Liu Xiang , Wang Juan , Shang Junliang , Liu Jinxing , Dai Lingyun , Yuan Shasha
Published: September 2022

Electroencephalography (EEG) records the electrical activity of the brain, which is an important tool for the automatic detection of epileptic seizures. It is certainly a very heavy burden to only recognize EEG epilepsy manually, so the method of computer-assisted treatment is of great importance. This paper presents a seizure detection algorithm based on variational modal decomposition (VMD) and a deep forest (DF) model. Variational modal decomposition is performed on EEG recordings, and the first three variational modal functions (VMFs) are selected to construct the time–frequency distribution of the EEG signals. Then, the log−Euclidean covariance matrix (LECM) is computed to represent the EEG properties and form EEG features. The deep forest model is applied to complete the EEG signal classification, which is a non-neural network deep model with a cascade structure that performs feature learning through the forest. In addition, to improve the classification accuracy, postprocessing techniques are performed to generate the discriminant results by moving average filtering and adaptive collar expansion. The algorithm was evaluated on the Bonn EEG dataset and the Freiburg long−term EEG dataset, and the former achieved a sensitivity and specificity of 99.32% and 99.31%, respectively. The mean sensitivity and specificity of this method for the 21 patients in the Freiburg dataset were 95.2% and 98.56%, respectively, with a false detection rate of 0.36/h. These results demonstrate the superior performance advantage of our algorithm and indicate its great research potential in epilepsy detection.
Uneven Implications of Lockdown Amid COVID-19 in India: From Harassment, Stigma, Crime, and Internally Displaced People to Stress and Coping Strategies in the Middle/Upper Class
Authors: Nasir Shagufta , Ghazi Shahnawaz Mohammad , Giménez-Llort Lydia
Published: September 2022

A content analysis of an English Newspaper, The Times of India (the world’s largest newspaper by circulation) during the first national lockdown amid the COVID-19 pandemic identified nine different categories culled out from a total of 129 news categories reporting unprecedented COVID-19 stories. Half of them portrayed two sides of a coin: from daily wagers and migrant workers, including internally displaced people (23/129), harassment and stigma (4/129), and crime (3/129) to stressors and coping strategies for middle/upper class individuals (39/129). Reports evidenced increased vulnerability in the lower layers of Indian stratified society. Yet, two years later, the uneven implications on physical and mental health are scarcely studied by scientific researchers.
Left-Behind Children’s Subtypes of Antisocial Behavior: A Qualitative Study in China
Authors: Liu Wen , Wang Weiwei , Xia Lingxiang , Lin Shuang , Wang Yining
Published: September 2022

As a result of the recent decades of urbanization and industrialization, millions of people have migrated to cities in search of better work opportunities in China. Meanwhile, their children have often been left behind in the care of other family members. To classify the subtypes of antisocial behavior of the left-behind children, this qualitative study interviewed a total of 71 participants, including five groups: left-behind children, parents, teachers, principals and community workers. The findings showed that left-behind children’s antisocial behavior is manifested as the type of limited adolescent antisocial behavior, and the three subtypes of left-behind children’s antisocial behavior were rule-breaking behavior, delinquent behavior and criminal behavior. In addition, the development of children’s antisocial behavior could range from general violations to delinquent behaviors and even to criminal behaviors.
Mechanical Steel Stitches: An Innovative Approach for Strengthening Shear Deficiency in Undamaged Reinforced Concrete Beams
Authors: Aksoylu Ceyhun , Özkılıç Yasin Onuralp , Arslan Musa Hakan
Published: September 2022

In this study, reinforced concrete beams with insufficient shear capacity were strengthened on both sides of the beam along the shear openings by a novel approach: Mechanical Steel Stitches (MSS). This innovative method facilitates the application of strengthening the beams with a low-cost solution. In this concept, six specimens were experimentally investigated under vertical load. While one of the specimens was tested as a reference, the others were strengthened with MSS application at different ratios (ρMS), ranging from 0.2% to 1% at both the beams’ shear span. MSS were applied with the angle of 90° considering stirrup logic. The diameter, anchorage depth and mechanical properties of the MSSs were kept constant, and their effects on the strengthening of the beams in terms of ductility, strength, stiffness, and energy dissipation capacities were investigated by changing the spacing of the MSSs. The results revealed that increasing MSS ratio caused a dramatic positive change in the behavior in terms of both strength and energy dissipation capacity. MSSs to be made at appropriate intervals ((%1) MSS ratio or (d/5) MSS spacing) significantly improved the shear capacity. However, a 43% loss in stiffness occurred with the increase in ρMS since the MSSs are applied to the beams by drilling and anchoring from the outside.
Internet of Things (IoT), Building Information Modeling (BIM), and Digital Twin (DT) in Construction Industry: A Review, Bibliometric, and Network Analysis
Authors: Baghalzadeh Shishehgarkhaneh Milad , Keivani Afram , Moehler Robert C. , Jelodari Nasim , Roshdi Laleh Sevda
Published: September 2022

The present study uses a bibliometric and systematic literature review (SLR) to examine the use of Building Information Modeling (BIM), the Internet of Things (IoT), and Digital Twins (DT) in the construction industry. The network visualization and other approaches based on the Web of Science (WOS) database and the patterns of research interactions were explored in 1879 academic publications using co-occurrence and co-citation investigations. Significant publications, conferences, influential authors, countries, organizations, and funding agencies have been recognized. Our study demonstrates that BIM, IoT, and DT in construction, Heritage BIM (HBIM), Smart Contracts, BIM, and Ontology, and VR and AR in BIM and DT are the main study themes. Finally, several prospective areas for future study are identified, including BIM and Metaverse technology, BIM and Artificial Intelligence (AI), Metaheuristic algorithms for optimization purposes in BIM, and the Circular Economy with BIM and IoT.
Machine Learning-Based Method for Detached Energy-Saving Residential Form Generation
Authors: Guo Haixu , Duan Ding , Yan Jincheng , Ding Keyuan , Xiang Fengkui , Peng Ran
Published: September 2022

In recent years, machine learning has gradually been applied to building energy-saving designs to reduce the time consumption of the optimization screening stage. However, since most of the existing research scholars come from the fields of computers and engineering, the application of machine learning technology mostly involves complex programming as well as software in the field of engineering, which requires multiple software to be coupled to achieve. In view of the differences between disciplines and the high learning threshold, these theories are difficult to apply and promote in practical work in the field of architecture. In this regard, this paper focuses on the improvement of methods, based on the Grasshopper platform, proposes a detached energy-saving residential form generation design method and process, to explore the optimal energy-saving building form in a more concise and efficient way. Based on this new method, on the basis of verifying its feasibility through a residential building case, two machine learning algorithms, neural network (ANN) and support vector machine (SVM), are compared and studied, and the applicability of these two algorithms in different building performance indicators is further discussed. The results show that the ANN model has the highest accuracy and is more suitable for the prediction of building energy consumption; in view of the simple and fast operation of SVM, it is more suitable for comfort prediction with relatively low accuracy requirements. By combining the above two machine learning methods, work efficiency can be improved while satisfying the prediction of relevant performance indicators. This method can help architects quickly search for the best building energy-saving form design scheme in the scheme design stage and provide data support and information feedback for architects in design conception and deepening.
Addition of Chromosome 17 Polysomy and HER2 Amplification Status Improves the Accuracy of Clinicopathological Factor-Based Progression Risk Stratification and Tumor Grading of Non-Muscle-Invasive Bladder Cancer
Authors: Kocsmár Ildikó , Kocsmár Éva , Pajor Gábor , Kulka Janina , Székely Eszter , Kristiansen Glen , Schilling Oliver , Nyirády Péter , Kiss András , Schaff Zsuzsa , Riesz Péter , Lotz Gábor
Published: September 2022

Progression of non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive disease (MIBC) significantly worsens life expectancy. Its risk can be assessed by clinicopathological factors according to international guidelines. However, additional molecular markers are needed to refine and improve the prediction. Therefore, in the present study, we aimed to predict the progression of NMIBCs to MIBC by assessing p53 expression, polysomy of chromosome 17 (Chr17) and HER2 status in the tissue specimens of the tumors of 90 NMIBC patients. Median follow-up was 77 months (range 2–158). Patients with Chr17 polysomy or HER2 gene amplification had a higher rate of disease progression (hazard ratio: 7.44; p < 0.001 and 4.04; p = 0.033, respectively; univariate Cox regression). Multivariable Cox regression models demonstrated that the addition of either Chr17 polysomy or HER2 gene amplification status to the European Association of Urology (EAU) progression risk score increases the c-index (from 0.741/EAU/ to 0.793 and 0.755, respectively), indicating that Chr17 polysomy/HER2 amplification status information improves the accuracy of the EAU risk table in predicting disease progression. HER2/Chr17 in situ hybridization can be used to select non-progressive cases not requiring strict follow-up, by reclassifying non-HER2-amplified, non-polysomic NMIBCs from the high- and very high-risk groups of EAU to the intermediate-risk group.
Advances in Dietary Phenolic Compounds to Improve Chemosensitivity of Anticancer Drugs
Authors: Bouyahya Abdelhakim , Omari Nasreddine El , Bakrim Saad , Hachlafi Naoufal El , Balahbib Abdelaali , Wilairatana Polrat , Mubarak Mohammad S.
Published: September 2022

Despite the significant advances and mechanistic understanding of tumor processes, therapeutic agents against different types of cancer still have a high rate of recurrence associated with the development of resistance by tumor cells. This chemoresistance involves several mechanisms, including the programming of glucose metabolism, mitochondrial damage, and lysosome dysfunction. However, combining several anticancer agents can decrease resistance and increase therapeutic efficacy. Furthermore, this treatment can improve the effectiveness of chemotherapy. This work focuses on the recent advances in using natural bioactive molecules derived from phenolic compounds isolated from medicinal plants to sensitize cancer cells towards chemotherapeutic agents and their application in combination with conventional anticancer drugs. Dietary phenolic compounds such as resveratrol, gallic acid, caffeic acid, rosmarinic acid, sinapic acid, and curcumin exhibit remarkable anticancer activities through sub-cellular, cellular, and molecular mechanisms. These compounds have recently revealed their capacity to increase the sensitivity of different human cancers to the used chemotherapeutic drugs. Moreover, they can increase the effectiveness and improve the therapeutic index of some used chemotherapeutic agents. The involved mechanisms are complex and stochastic, and involve different signaling pathways in cancer checkpoints, including reactive oxygen species signaling pathways in mitochondria, autophagy-related pathways, proteasome oncogene degradation, and epigenetic perturbations.
CNN-Based Approaches with Different Tumor Bounding Options for Lymph Node Status Prediction in Breast DCE-MRI
Authors: Santucci Domiziana , Faiella Eliodoro , Gravina Michela , Cordelli Ermanno , de Felice Carlo , Beomonte Zobel Bruno , Iannello Giulio , Sansone Carlo , Soda Paolo
Published: September 2022

Background: The axillary lymph node status (ALNS) is one of the most important prognostic factors in breast cancer (BC) patients, and it is currently evaluated by invasive procedures. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), highlights the physiological and morphological characteristics of primary tumor tissue. Deep learning approaches (DL), such as convolutional neural networks (CNNs), are able to autonomously learn the set of features directly from images for a specific task. Materials and Methods: A total of 155 malignant BC lesions evaluated via DCE-MRI were included in the study. For each patient’s clinical data, the tumor histological and MRI characteristics and axillary lymph node status (ALNS) were assessed. LNS was considered to be the final label and dichotomized (LN+ (27 patients) vs. LN− (128 patients)). Based on the concept that peritumoral tissue contains valuable information about tumor aggressiveness, in this work, we analyze the contributions of six different tumor bounding options to predict the LNS using a CNN. These bounding boxes include a single fixed-size box (SFB), a single variable-size box (SVB), a single isotropic-size box (SIB), a single lesion variable-size box (SLVB), a single lesion isotropic-size box (SLIB), and a two-dimensional slice (2DS) option. According to the characteristics of the volumes considered as inputs, three different CNNs were investigated: the SFB-NET (for the SFB), the VB-NET (for the SVB, SIB, SLVB, and SLIB), and the 2DS-NET (for the 2DS). All the experiments were run in 10-fold cross-validation. The performance of each CNN was evaluated in terms of accuracy, sensitivity, specificity, the area under the ROC curve (AUC), and Cohen’s kappa coefficient (K). Results: The best accuracy and AUC are obtained by the 2DS-NET (78.63% and 77.86%, respectively). The 2DS-NET also showed the highest specificity, whilst the highest sensibility was attained by the VB-NET based on the SVB and SIB as bounding options. Conclusion: We have demonstrated that a selective inclusion of the DCE-MRI’s peritumoral tissue increases accuracy in the lymph node status prediction in BC patients using CNNs as a DL approach.
Identification and Morphological Characterization of Features of Circulating Cancer-Associated Macrophage-like Cells (CAMLs) in Endometrial Cancers
Authors: Sulaiman Raed , De Pradip , Aske Jennifer C. , Lin Xiaoqian , Dale Adam , Vaselaar Ethan , Ageton Cheryl , Gaster Kris , Espaillat Luis Rojas , Starks David , Dey Nandini
Published: September 2022

The blood of patients with solid tumors contains circulating tumor-associated cells, including epithelial cells originating from the tumor mass, such as circulating tumor cells (CTCs), or phagocytic myeloid cells (differentiated monocytes), such as circulating cancer-associated macrophage-like cells (CAMLs). We report for the first time the identification and in-depth morphologic characterization of CAMLs in patients with endometrial cancers. We isolated CAMLs by size-based filtration on lithographically fabricated membranes followed by immunofluorescence, using a CD45+/CK 8,18,19+/EpCAM+/CD31+/macrophage-like nuclear morphology, from > 70 patients. Irrespective of the histological and pathological parameters, 98% of patients were positive for CAMLs. Two size-based subtypes of CAMLs, <20 µm (tiny) and >20 µm (giant) CAMLs, of distinctive polymorphic morphologies with mononuclear or fused polynuclear structures in several morphological states were observed, including apoptotic CAMLs, CAML–WBC doublets, conjoined CAMLs, CAML–WBC clusters, and CTC–CAML–WBC clusters. In contrast, CAMLs were absent in patients with non-neoplastic/benign tumors, healthy donors, and leucopaks. Enumerating CTCs simultaneously from the same patient, we observed that CTC-positive patients are positive for CAMLs, while 55% out of all CAML-positive patients were found positive for CTCs. Our study demonstrated for the first time the distinctive morphological characteristics of endometrial CAMLs in the context of the presence of CTCs in patients.
Regulatory T Cells in Pancreatic Cancer: Of Mice and Men
Authors: Mota Reyes Carmen , Demir Elke , Çifcibaşı Kaan , Istvanffy Rouzanna , Friess Helmut , Demir Ihsan Ekin
Published: September 2022

Regulatory T cells (Treg) are one of the major immunosuppressive cell subsets in the pancreatic tumor microenvironment. Tregs influence tumor growth by acting either directly on cancer cells or via the inhibition of effector immune cells. Treg cells mechanisms form a partially redundant network with other immunosuppressive cells such as myeloid-derived suppressor cells (MDSC) that confer robustness to tumor immunosuppression and resistance to immunotherapy. The results obtained in preclinical studies where after Treg depletion, MDSCs concomitantly decreased in early tumors whereas an inverse association was seen in advanced PCa, urge a comprehensive analysis of the immunosuppressive profile of PCa throughout tumorigenesis. One relevant context to analyse these complex compensatory mechanisms may be the tumors of patients who underwent neoTx. Here, we observed a parallel decrease in the numbers of both intratumoral Tregs and MDSC after neoTx even in locally advanced PCa. NeoTx also led to decreased amounts of αSMA+ myofibroblastic cancer-associated fibroblasts (myCAF) and increased proportions of CD8+ cytotoxic T lymphocytes in the tumor. In order to understand these dynamics and to uncover stage-specific actional strategies involving Tregs, pre-clinical models that allow the administration of neoTx to different stages of PCa may be a very useful platform.
Using Intervention Mapping to Develop an Education and Career Support Service for Adolescents and Young Adults Diagnosed with Cancer: Identification of the Contextual Factors That Influence Participation in Education and Employment
Authors: Davis Esther L. , Clarke Kristina S. , Patterson Pandora , Cohen Jennifer
Published: September 2022

Adolescents and young adults (AYAs) diagnosed with cancer experience disrupted engagement in education and employment, which can have profound and long-term impacts on their quality of life. It is therefore vital to offer AYAs access to tailored, evidence-based services to help them to achieve their education and employment goals. However, few such services exist for this population. This paper presents the results from the first step in developing an education and career support service for AYAs diagnosed with cancer using Intervention Mapping. This first step involved developing a logic model that describes the influences of health and demographic factors, individual determinants, behaviours, and environmental conditions on AYA participation in education or employment. The logic model was developed by integrating data from an integrative literature review; cross-sectional survey of AYA clients of a community-based organisation; and feedback from a planning group of stakeholders. It is a valuable framework that will be used to direct the focus of the education and career support service for AYAs diagnosed with cancer. More broadly, the logic model has implications for guiding clinical, service, research, and policy improvements for AYA education, employment, and career support, with the aim of improving AYA quality of life.