bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of SARS-CoV-2 Spike Protein Wild-Type and the Variants of Concern Real-Time Interactions with Monoclonal Antibodies and Convalescent Human Serum
Authors: Plikusiene Ieva , Maciulis Vincentas , Juciute Silvija , Ramanavicius Arunas , Ramanaviciene Almira
Published: August 2023

The spike (S) protein and its receptor-binding domain (RBD) of the coronavirus SARS-CoV-2 have been continually evolving, yielding the majority of significant missense mutations and new variants of concern. In this study, we examined how monoclonal antibodies against RBD (mAbs-SCoV2-RBD) and polyclonal antibodies present in convalescent human serum specifically interact with the S protein of wild-type and SARS-CoV-2 variants of concern (VOCs) in real time and how this can be reflected through surface mass density. Moreover, we combined two distinct, label-free measurement techniques: one based on changes in surface electromagnetic waves after reflection from the surface, and the other on changes in acoustic waves. The results demonstrated that dry surface mass density (ΓSE) of mAbs-SCoV2-RBD attached to the RBD of the S protein decreases three-fold, from 148 ng/cm2 to 46 ng/cm2, due to the B.1.351 or so-called beta mutation of coronavirus and its S protein (SCoV2-β). Consequently, the obtained wet mass ΓQCM-D resulted in values two times lower, from 319 ng/cm2 to 158 ng/cm2, and the hydration of mAbs-SCoV2-RBD/SCoV2-β immune complex was 70.88%. Conversely, when polyclonal antibodies present in convalescent human serum form immune complexes with the S protein of SARS-CoV-2 variants of concern, the ΓSE decreased from 279 ng/cm2 to 249 ng/cm2, and ΓQCM-D from 1545 ng/cm2 to 1366 ng/cm2. These results can give insights into the differences between the interaction of monoclonal and polyclonal antibodies with SARS-CoV-2 VOCs.
Biosensors with Boronic Acid-Based Materials as the Recognition Elements and Signal Labels
Authors: Liu Lin , Ma Xiaohua , Chang Yong , Guo Hang , Wang Wenqing
Published: August 2023

It is of great importance to have sensitive and accurate detection of cis-diol-containing biologically related substances because of their important functions in the research fields of metabolomics, glycomics, and proteomics. Boronic acids can specifically and reversibly interact with 1,2- or 1,3-diols to form five or six cyclic esters. Based on this unique property, boronic acid-based materials have been used as synthetic receptors for the specific recognition and detection of cis-diol-containing species. This review critically summarizes the recent advances with boronic acid-based materials as recognition elements and signal labels for the detection of cis-diol-containing biological species, including ribonucleic acids, glycans, glycoproteins, bacteria, exosomes, and tumor cells. We also address the challenges and future perspectives for developing versatile boronic acid-based materials with various promising applications.
Electric Double Layer Based Epidermal Electronics for Healthcare and Human-Machine Interface
Authors: Gao Yuan , Zhang Hanchu , Song Bowen , Zhao Chun , Lu Qifeng
Published: August 2023

Epidermal electronics, an emerging interdisciplinary field, is advancing the development of flexible devices that can seamlessly integrate with the skin. These devices, especially Electric Double Layer (EDL)-based sensors, overcome the limitations of conventional electronic devices, offering high sensitivity, rapid response, and excellent stability. Especially, Electric Double Layer (EDL)-based epidermal sensors show great potential in the application of wearable electronics to detect biological signals due to their high sensitivity, fast response, and excellent stability. The advantages can be attributed to the biocompatibility of the materials, the flexibility of the devices, and the large capacitance due to the EDL effect. Furthermore, we discuss the potential of EDL epidermal electronics as wearable sensors for health monitoring and wound healing. These devices can analyze various biofluids, offering real-time feedback on parameters like pH, temperature, glucose, lactate, and oxygen levels, which aids in accurate diagnosis and effective treatment. Beyond healthcare, we explore the role of EDL epidermal electronics in human-machine interaction, particularly their application in prosthetics and pressure-sensing robots. By mimicking the flexibility and sensitivity of human skin, these devices enhance the functionality and user experience of these systems. This review summarizes the latest advancements in EDL-based epidermal electronic devices, offering a perspective for future research in this rapidly evolving field.
Delayed Intracerebral Hematoma after Ventriculoperitoneal Shunt in the Context of Ruptured Brain Arteriovenous Malformation: A Literature Review
Authors: Dannhoff Guillaume , Chibbaro Salvatore , Mallereau Charles-Henry , Ganau Mario , Agbo-Ponzo Martial , Santin Marie des Neiges , Ollivier Irène , Pop Raoul , Proust François , Todeschi Julien
Published: August 2023

Hemorrhagic complications arising from ventricular drainage procedures are typically asymptomatic and of low volume. A particular subset of these complications, known as delayed intracranial hemorrhage (DICH), is however recognized for its particularly poor prognosis. We primarily aimed to identify epidemiological characteristics associated with DICH, to shed light on its occurrence and potential risk factors. To do so, we performed a retrospective analysis of a series of ten patients who presented with DICH in the context of a ruptured brain arteriovenous malformation (bAVM) and a systematic literature review of all DICH cases reported in the literature. Our ten patients showed delayed neurological deterioration after a ventriculoperitoneal shunt (VPS) procedure, with a computed tomography (CT) scan revealing a DICH surrounding the ventricular catheter, distinct and away from the nidus of their previously ruptured bAVM. Four patients (40%) rapidly declined and passed away, three (30%) required surgical management and the remaining three (30%) demonstrated gradual clinical improvement with conservative management. In the literature, most patients presenting with DICH had hydrocephalus associated with neurovascular disorders (47% of cases), such as bAVM rupture in our present series. These constatations point out the significance of the underlying pathologies potentially being predisposed to these unusual complications.
Relationships between Affect Recognition, Empathy, Alexithymia, and Co-Occurring Conditions in Autism
Authors: Raman Nandita , Ringold Sofronia , Jayashankar Aditya , Butera Christiana , Kilroy Emily , Harrison Laura , Cermak Sharon , Aziz-Zadeh Lisa
Published: August 2023

Prior studies show differences in empathy and affect-recognition ability between those with autism spectrum disorder (ASD) and typically developing (TD) individuals. Autistic individuals also exhibit increased behavioral, gastrointestinal, and sleep issues. In the current study, we explored the differences in empathy and affect recognition between the ASD and TD groups; and we investigated their associations with conditions co-occurring in ASD. A total of 54 TD and 56 ASD children (8–17 years) were included. As compared to the TD group, the ASD group showed lower scores for affect recognition and perspective taking (PT) and higher scores for personal distress (PD). Interestingly, results from hierarchical linear regressions suggested that disparities in the PD and PT between the groups were primarily attributable to attenuated levels of alexithymia, rather than being mediated by the presence of an autism diagnosis. Differences in affect-recognition ability, however, were mediated by both an autism diagnosis and alexithymia. We also found significant correlations between empathy and affect recognition and measures of related conditions common in ASD. Alexithymia, hence, contributes to difficulties in empathy while both alexithymia and autism are associated with affect-recognition ability in ASD. Additionally, the association between affect recognition and empathic ability with co-occurring conditions in ASD needs to be considered during assessments and interventions.
Self-Awareness of Goals Task (SAGT) and Planning Skills: The Neuroscience of Decision Making
Authors: Balconi Michela , Angioletti Laura , Acconito Carlotta
Published: August 2023

A goal’s self-awareness and the planning to achieve it drive decision makers. Through a neuroscientific approach, this study explores the self-awareness of goals by analyzing the explicit and implicit processes linked to the ability to self-represent goals and sort them via an implicit dominant key. Thirty-five professionals performed a novel and ecological decision-making task, the Self-Awareness of Goals Task (SAGT), aimed at exploring the (i) self-representation of the decision-making goals of a typical working day; (ii) self-representation of how these goals were performed in order of priority; (iii) temporal sequence; and (iv) in terms of their efficacy. Electrophysiological (i.e., alpha, beta, and gamma band), autonomic, behavioral, and self-report data (General Decision Making Style and Big Five Inventory) are collected. Higher self-awareness of goals by time as well as efficacy and the greater activation of alpha, beta, and gamma bands in the temporoparietal brain area were found. Correlations reported positive associations between the self-awareness of goals via a time and dependent decision-making style and a conscientious personality, but also between the self-awareness of goals via an efficacy and rational decision-making style. The results obtained in this study suggest that the SAGT could activate recursive thinking in the examinee and grasp individual differences in self-representation and aware identification of decision-making goals.
Statins in Cancer Prevention and Therapy
Authors: Ricco Natalia , Kron Stephen J.
Published: August 2023

Statins, a class of HMG-CoA reductase inhibitors best known for their cholesterol-reducing and cardiovascular protective activity, have also demonstrated promise in cancer prevention and treatment. This review focuses on their potential applications in head and neck cancer (HNC), a common malignancy for which established treatment often fails despite incurring debilitating adverse effects. Preclinical and clinical studies have suggested that statins may enhance HNC sensitivity to radiation and other conventional therapies while protecting normal tissue, but the underlying mechanisms remain poorly defined, likely involving both cholesterol-dependent and -independent effects on diverse cancer-related pathways. This review brings together recent discoveries concerning the anticancer activity of statins relevant to HNC, highlighting their anti-inflammatory activity and impacts on DNA-damage response. We also explore molecular targets and mechanisms and discuss the potential to integrate statins into conventional HNC treatment regimens to improve patient outcomes.
Cell State and Cell Type: Deconvoluting Circulating Tumor Cell Populations in Liquid Biopsies by Multi-Omics
Authors: Welter Lisa , Zheng Serena , Setayesh Sonia Maryam , Morikado Michael , Agrawal Arushi , Nevarez Rafael , Naghdloo Amin , Pore Milind , Higa Nikki , Kolatkar Anand , Thiele Jana-Aletta , Sharma Priyanka , Moore Halle C. F. , Richer Jennifer K. , Elias Anthony , Pienta Kenneth J. , Zurita Amado J. , Gross Mitchell E. , Shishido Stephanie N. , Hicks James , Velasco Carmen Ruiz , Kuhn Peter
Published: August 2023

Bi-directional crosstalk between the tumor and the tumor microenvironment (TME) has been shown to increase the rate of tumor evolution and to play a key role in neoplastic progression, therapeutic resistance, and a patient’s overall survival. Here, we set out to use a comprehensive liquid-biopsy analysis to study cancer and specific TME cells in circulation and their association with disease status. Cytokeratin+, CD45- circulating rare cells (CRCs) from nine breast and four prostate cancer patients were characterized through morphometrics, single-cell copy number analysis, and targeted multiplexed proteomics to delineate cancer cell lineage from other rare cells originating in the TME. We show that we can detect epithelial circulating tumor cells (EPI.CTC), CTCs undergoing epithelial-to-mesenchymal transition (EMT.CTC) and circulating endothelial cells (CECs) using a universal rare event detection platform (HDSCA). Longitudinal analysis of an index patient finds that CTCs are present at the time of disease progression, while CECs are predominately present at the time of stable disease. In a small cohort of prostate and breast cancer patients, we find high inter-patient and temporal intra-patient variability in the expression of tissue specific markers such as ER, HER2, AR, PSA and PSMA and EpCAM. Our study stresses the importance of the multi-omic characterization of circulating rare cells in patients with breast and prostate carcinomas, specifically highlighting overlapping and cell type defining proteo-genomic characteristics of CTCs and CECs.
Prediction of Surgical Outcome by Tumor Volume Doubling Time via Stereo Imaging Software in Early Non-Small Cell Lung Cancer
Authors: Liu Chia-Chi , Cheng Ya-Fu , Ke Pei-Cing , Chen Yi-Ling , Lin Ching-Min , Wang Bing-Yen
Published: August 2023

Background: Volume doubling time (VDT) has been proven to be a powerful predictor of lung cancer progression. In non-small cell lung cancer patients receiving sublobar resection, the discussion of correlation between VDT and surgery was absent. We proposed to investigate the surgical outcomes according to VDT. Methods: We retrospectively studied 96 cases post sublobar resection from 2012 to 2018, collecting two chest CT scans preoperatively of each case and calculating the VDT. The receiver operating characteristic curve was constructed to identify the optimal cut-off point of VDTs as 133 days. We divided patients into two groups: VDT < 133 days and VDT ≥ 133 days. Univariable and multivariable analyses were performed for comparative purposes. Results: Univariable and multivariable analyses revealed that the consolidation and tumor diameter ratio was the factor of overall survival (OS), and VDT was the only factor of disease-free survival (DFS). The five year OS rates of patients with VDTs ≥ 133 days and VDTs < 133 days, respectively, were 89.9% and 71.9%, and the five year DFS rates were 95.9% and 61.5%. Conclusion: As VDT serves as a powerful prognostic predictor and provides an essential role in planning surgical procedures, the evaluation of VDT preoperatively is highly suggested.
Correlation between [68Ga]Ga-FAPI-46 PET Imaging and HIF-1α Immunohistochemical Analysis in Cervical Cancer: Proof-of-Concept
Authors: Mokoala Kgomotso M. G. , Lawal Ismaheel O. , Maserumule Letjie C. , Bida Meshack , Maes Alex , Ndlovu Honest , Reed Janet , Mahapane Johncy , Davis Cindy , Van de Wiele Christophe , Popoola Gbenga , Giesel Frederik L. , Vorster Mariza , Sathekge Mike M.
Published: August 2023

Hypoxia leads to changes in tumor microenvironment (upregulated CAFs) with resultant aggressiveness. A key factor in the physiological response to hypoxia is hypoxia-inducible factor-1alpha (HIF-1α). [68Ga]Ga-FAPI PET imaging has been demonstrated in various cancer types. We hypothesized that [68Ga]Ga-FAPI PET may be used as an indirect tracer for mapping hypoxia by correlating the image findings to pathological analysis of HIF-1α expression. The [68Ga]Ga-FAPI PET/CT scans of women with cancer of the cervix were reviewed and the maximum and mean standardized uptake value (SUVmax and SUVmean) and FAPI tumor volume (FAPI-TV) were documented. Correlation analysis was performed between PET-derived parameters and immunohistochemical staining as well as between PET-derived parameters and the presence of metastasis. Ten women were included. All patients demonstrated tracer uptake in the primary site or region of the primary. All patients had lymph node metastases while only six patients had distant visceral or skeletal metastases. The mean SUVmax, SUVmean, and FAPI-TV was 18.89, 6.88, and 195.66 cm3, respectively. The average FAPI-TV for patients with additional sites of metastases was higher than those without. Immunohistochemistry revealed varying intensities of HIF-1α expression in all tested samples. There was a positive correlation between the presence of skeletal metastases and staining for HIF-1α (r=0.80;p=0.017). The presence of skeletal metastasis was correlated to the HIF-1⍺ staining (percentage distribution). Furthermore, the FAPI-TV was a better predictor of metastatic disease than the SUVmax.
Integrated Analysis Identifies DPP7 as a Prognostic Biomarker in Colorectal Cancer
Authors: Zhang Wei , Wang Haidong , Wang Huadi , Xu Chuchu , Zhao Rongjie , Yao Junlin , Zhai Chongya , Han Weidong , Pan Hongming , Sheng Jin
Published: August 2023

Colorectal cancer has a poor prognosis and is prone to recurrence and metastasis. DPP7, a prolyl peptidase, is reported to regulate lymphocyte quiescence. However, the correlation of DPP7 with prognosis in CRC remains unclear. With publicly available cohorts, the Wilcoxon rank-sum test and logistic regression were employed to analyze the relationship between DPP7 expression and the clinicopathological features of CRC patients. Specific pathways of differentially expressed genes were determined through biofunctional analysis and gene set enrichment analysis (GSEA). qPCR and immunohistochemical staining were used to determine DPP7 expression levels in surgical specimens. The public dataset and analysis of the biospecimens of CRC patients revealed that DPP7, in the CRC samples, was expressed significantly higher than in non-tumor tissues. Moreover, increased DPP7 was significantly associated with a higher N stage, lymphatic invasion, and shorter overall survival. Functionally, DPP7 is involved in neuroactive ligand–receptor interaction and olfactory transduction signaling. We identified a series of targeted drugs and small-molecule drugs with responses to DPP7. To conclude, DPP7 is a valuable diagnostic and prognostic biomarker for CRC and considered as a new therapeutic target.
Early Increase in Circulating PD-1+CD8+ T Cells Predicts Favorable Survival in Patients with Advanced Gastric Cancer Receiving Chemotherapy
Authors: Shin Kabsoo , Kim Joori , Park Se Jun , Kim Hyunho , Lee Myung Ah , Kim Okran , Park Juyeon , Kang Nahyeon , Kim In-Ho
Published: August 2023

The clinical significance of PD-1 expression in circulating CD8+ T cells in patients with gastric cancer (GC) receiving chemotherapy remains unelucidated. Therefore, we aimed to examine its prognostic significance in blood samples of 68 patients with advanced GC who received platinum-based chemotherapy. The correlation between peripheral blood mononuclear cells, measured using fluorescence-activated cell sorting, was evaluated. Patients were divided into two groups according to the changes in PD-1+CD8+ T-cell frequencies between day 0 and 7. They were categorized as increased or decreased PD-1+CD8+ T-cell groups. The increased PD-1+CD8+ T-cell group showed longer progression-free survival (PFS) and overall survival (OS) than the decreased PD-1+CD8+ T-cell group (PFS: 8.7 months vs. 6.1 months, p = 0.007; OS: 20.7 months vs. 10.8 months, p = 0.003). The mean duration of response was significantly different between the groups (5.7 months vs. 2.5 months, p = 0.041). Multivariate analysis revealed that an increase in PD-1+CD8+ T-cell frequency was an independent prognostic factor. We concluded that the early increase in PD-1+CD8+ T-cell frequency is a potential predictor of favorable prognoses and durable responses in patients with advanced GC receiving chemotherapy.
Machine Learning-Based Prediction of Distant Recurrence in Invasive Breast Carcinoma Using Clinicopathological Data: A Cross-Institutional Study
Authors: Sukhadia Shrey S. , Muller Kristen E. , Workman Adrienne A. , Nagaraj Shivashankar H.
Published: August 2023

Breast cancer is the most common type of cancer worldwide. Alarmingly, approximately 30% of breast cancer cases result in disease recurrence at distant organs after treatment. Distant recurrence is more common in some subtypes such as invasive breast carcinoma (IBC). While clinicians have utilized several clinicopathological measurements to predict distant recurrences in IBC, no studies have predicted distant recurrences by combining clinicopathological evaluations of IBC tumors pre- and post-therapy with machine learning (ML) models. The goal of our study was to determine whether classification-based ML techniques could predict distant recurrences in IBC patients using key clinicopathological measurements, including pathological staging of the tumor and surrounding lymph nodes assessed both pre- and post-neoadjuvant therapy, response to therapy via standard-of-care imaging, and binary status of adjuvant therapy administered to patients. We trained and tested four clinicopathological ML models using a dataset (144 and 17 patients for training and testing, respectively) from Duke University and validated the best-performing model using an external dataset (8 patients) from Dartmouth Hitchcock Medical Center. The random forest model performed better than the C-support vector classifier, multilayer perceptron, and logistic regression models, yielding AUC values of 1.0 in the testing set and 0.75 in the validation set (p < 0.002) across both institutions, thereby demonstrating the cross-institutional portability and validity of ML models in the field of clinical research in cancer. The top-ranking clinicopathological measurement impacting the prediction of distant recurrences in IBC were identified to be tumor response to neoadjuvant therapy as evaluated via SOC imaging and pathology, which included tumor as well as node staging.
In Vivo Thermal Ablation of Deep Intrahepatic Targets Using a Super-Convergent MRgHIFU Applicator and a Pseudo-Tumor Model
Authors: Lorton Orane , Guillemin Pauline Coralie , Peloso Andrea , M’Rad Yacine , Crowe Lindsey Alexandra , Koessler Thibaud , Poletti Pierre-Alexandre , Boudabbous Sana , Ricoeur Alexis , Salomir Rares
Published: August 2023

Background: HIFU ablation of liver malignancies is particularly challenging due to respiratory motion, high tissue perfusion and the presence of the rib cage. Based on our previous development of a super-convergent phased-array transducer, we aimed to further investigate, in vivo, its applicability to deep intrahepatic targets. Methods: In a series of six pigs, a pseudo-tumor model was used as target, visible both on intra-operatory MRI and post-mortem gross pathology. The transcostal MRgHIFU ablation was prescribed coplanar with the pseudo-tumor, either axial or sagittal, but deliberately shifted 7 to 18 mm to the side. No specific means of protection of the ribs were implemented. Post-treatment MRI follow-up was performed at D7, followed by animal necropsy and gross pathology of the liver. Results: The pseudo-tumor was clearly identified on T1w MR imaging and subsequently allowed the MRgHIFU planning. The peak temperature at the focal point ranged from 58–87 °C. Gross pathology confirmed the presence of the pseudo-tumor and the well-delineated MRgHIFU ablation at the expected locations. Conclusions: The specific design of the transducer enabled a reliable workflow. It demonstrated a good safety profile for in vivo transcostal MRgHIFU ablation of deep-liver targets, graded as challenging for standard surgery.
Development of Drop Size Distribution Model for Dropwise Condensation on a Superhydrophobic Surface
Authors: Denoga Gerald Jo C. , Balbarona Juvy A. , Salapare Hernando S.
Published: August 2023

This study presents a mathematical model of drop size distribution during dropwise condensation on a superhydrophobic surface. The model is developed by combining a power law growth model, an exponentially decaying population model, and a Gaussian probability model for growth variations. The model is validated against experiment data, with correlations ranging from 88% to 94%. The growth model is shown to sufficiently describe the growth of drops from 0.02 mm to 0.1 mm but may be extrapolated to describe the growth of even smaller drops. The experiment data show that drop size distribution or frequency distribution of drops of different sizes varies significantly with time and may be considered pseudo-cyclic. The developed model, together with the sweep rate of drops, sufficiently describes this behavior and, consequently, may also be used to better estimate the heat transfer rate due to dropwise condensation.
Relationship between the Coloration Mechanism and Gemological Properties of Purple Scapolite
Authors: Rao Yinghua , Guo Qingfeng , Zhang Sixue , Liao Libing
Published: August 2023

Purple scapolite is a precious gemstone. In this paper, we compared the crystal structure and spectral characteristics of purple scapolite before and after heat treatment with conventional gemological tests, EPMA, XRF, LA-ICP-MS, infrared spectroscopy, Raman spectroscopy, UV–vis spectrophotometer, EPR, and other tests. The XRD results showed that the structure of purple scapolite fits perfectly with that of marialite. Compositional analyses indicate that purple scapolite has an average Me value of 16.85 and belongs to the subspecies marialite, and thus its specific gravity and refractive index are low. The absorption peak at 1045 cm−1 in the infrared spectra has a direct relationship with the Me value, which is blue-shifted with increasing Me value. After heating at 400 °C for 2 h, the purple scapolite changed to colorless, and no phase transformation or significant structural changes occurred during this process. But this process is accompanied by the disappearance of the signal at g = 2.011 in the EPR spectra, which indicates the presence of oxygen hole centers, thus proving that the color of purple scapolite is caused by oxygen hole centers rather than Fe3+. The chlorine in the marialite structure occupies the structural center, which provides for the appearance of oxygen hole centers, and thus purple scapolite always has a high marialite content. This further leads to the refractive index and specific gravity always being lower. That is a new explanation for the relationship between scapolite coloration mechanism, specific gravity, and refractive index.
Predictive Efficacy of the Perfusion Index for Hypotension following Spinal Anesthesia in Parturient Undergoing Elective Cesarean Section: A Systematic Review and Meta-Analysis
Authors: Hung Kuo-Chuan , Liu Chien-Cheng , Huang Yen-Ta , Wu Jheng-Yan , Chen Jen-Yin , Ko Ching-Chung , Lin Chien-Ming , Hsing Chung-Hsi , Yew Ming , Chen I-Wen
Published: August 2023

This meta-analysis assessed the predictive efficacy of perfusion index for hypotension following spinal anesthesia (SA) in parturients undergoing elective cesarean section (CS). Electronic databases, including Google Scholar, EMBASE, Cochrane Library, and MEDLINE, were searched from inception to June 2023. The primary outcome was the diagnostic accuracy of the perfusion index in predicting the probability of perioperative hypotension following SA. The review included 12 studies involving 2009 patients, published between 2017 and 2023. The pooled sensitivity and specificity were 0.81 (95% confidence interval (CI) = 0.72–0.87) and 0.75 (95% CI = 0.67–0.82), respectively. Additionally, the pooled area under the curve (AUC) was calculated as 0.84 (95% CI = 0.81–0.87), suggesting a moderate to good accuracy of the diagnostic test. Using Fagan’s nomogram plot, the positive likelihood ratio (LR) and negative LR were found to be 3 and 0.26, respectively. The results demonstrated that the perfusion index exhibited an acceptable level of accuracy in predicting perioperative hypotension after spinal anesthesia in parturients undergoing elective CS. These findings highlight the potential value of incorporating a perfusion index as a useful tool for clinicians to integrate into routine clinical practice, which necessitates further large-scale studies for verification.
Focal Lesions of the Liver and Radiomics: What Do We Know?
Authors: Anichini Matilde , Galluzzo Antonio , Danti Ginevra , Grazzini Giulia , Pradella Silvia , Treballi Francesca , Bicci Eleonora
Published: August 2023

Despite differences in pathological analysis, focal liver lesions are not always distinguishable in contrast-enhanced magnetic resonance imaging (MRI), contrast-enhanced computed tomography (CT), and positron emission tomography (PET). This issue can cause problems of differential diagnosis, treatment, and follow-up, especially in patients affected by HBV/HCV chronic liver disease or fatty liver disease. Radiomics is an innovative imaging approach that extracts and analyzes non-visible quantitative imaging features, supporting the radiologist in the most challenging differential diagnosis when the best-known methods are not conclusive. The purpose of this review is to evaluate the most significant CT and MRI texture features, which can discriminate between the main benign and malignant focal liver lesions and can be helpful to predict the response to pharmacological or surgical therapy and the patient’s prognosis.
A Deep Learning-Based Multi-Signal Radio Spectrum Monitoring Method for UAV Communication
Authors: Hou Changbo , Fu Dingyi , Zhou Zhichao , Wu Xiangyu
Published: August 2023

Unmanned aerial vehicles (UAVs), relying on wireless communication, are inevitably influenced by the complex electromagnetic environment, attributed to the development of wireless communication technology. The modulation information of signals can assist in identifying device information and interference in the environment, which is significant for UAV communication environment monitoring. Therefore, in scenarios involving the communication of UAVs, it is necessary to find out how to perform the spectrum monitoring method to obtain the modulation information. Most existing methods are unsuitable for scenarios where multiple signals appear in the same spectrum sequence or do not use an end-to-end structure. Firstly, we established a spectrum dataset to simulate the UAV communication environment and developed a label method. Then, detection networks were employed to extract the presence and location information of signals in the spectrum. Finally, decision-level fusion was used to combine the output results of multiple nodes. Five modulation types, including ASK, FSK, 16QAM, DSB-SC, and SSB, were used to simulate different signal sources in the communication environment. Accuracy, recall, and F1 score were used as evaluation metrics. The networks were tested at different signal-to-noise ratios (SNRs). Among the different modulation types, FSK exhibits the most stable recognition performance across different models. The proposed method is of great significance for wireless radio spectrum monitoring in complex electromagnetic environments and is adaptable to scenarios where multiple receivers are used in vast terrains, providing a deep learning-based approach to radio monitoring solutions for UAV communication.
Model-Free Guidance Method for Drones in Complex Environments Using Direct Policy Exploration and Optimization
Authors: Liu Hongxun , Suzuki Satoshi
Published: August 2023

In the past few decades, drones have become lighter, with longer hang times, and exhibit more agile performance. To maximize their capabilities during flights in complex environments, researchers have proposed various model-based perception, planning, and control methods aimed at decomposing the problem into modules and collaboratively accomplishing the task in a sequential manner. However, in practical environments, it is extremely difficult to model both the drones and their environments, with very few existing model-based methods. In this study, we propose a novel model-free reinforcement-learning-based method that can learn the optimal planning and control policy from experienced flight data. During the training phase, the policy considers the complete state of the drones and environmental information as inputs. It then self-optimizes based on a predefined reward function. In practical implementations, the policy takes inputs from onboard and external sensors and outputs optimal control commands to low-level velocity controllers in an end-to-end manner. By capitalizing on this property, the planning and control policy can be improved without the need for an accurate system model and can drive drones to traverse complex environments at high speeds. The policy was trained and tested in a simulator, as well as in real-world flight experiments, demonstrating its practical applicability. The results show that this model-free method can learn to fly effectively and that it holds great potential to handle different tasks and environments.
An Overview of Drone Applications in the Construction Industry
Authors: Choi Hee-Wook , Kim Hyung-Jin , Kim Sung-Keun , Na Wongi S.
Published: August 2023

The integration of drones in the construction industry has ushered in a new era of efficiency, accuracy, and safety throughout the various phases of construction projects. This paper presents a comprehensive overview of the applications of drones in the construction industry, focusing on their utilization in the design, construction, and maintenance phases. The differences between the three different types of drones are discussed at the beginning of the paper where the overview of the drone applications in construction industry is then described. Overall, the integration of drones in the construction industry has yielded transformative advancements across all phases of construction projects. As technology continues to advance, drones are expected to play an increasingly critical role in shaping the future of the construction industry.
Early Diagnosis of Pine Wood Nematode Disease Based on Chlorophyll Fluorescence Parameters and Organic Acids
Authors: Shen Luyang , Lin Xiaoyu , Liu Fei , Huang Yingzhen , Ye Jianren , Tan Jiajin
Published: August 2023

Pine wood nematode disease is a destructive disease to the ecological environment and forest resources. The disease is produced by Bursaphelenchus xylophilus, and the onset rate is extremely fast and the pathogenesis of the disease is not clear. Prevention of this disease is still important in production, so it is of great significance to explore its early diagnosis. In this study, the changes of chlorophyll fluorescence dynamic induction parameters, non-photochemical quenching parameters and organic acid content in needles of 7-year-old-infected Pinus hwangshanensis were studied by chlorophyll fluorescence technology and organic acid mass combined technology. The results showed that in the chlorophyll fluorescence dynamic induction group, Fm/Fo, Fv/Fo, Fm, Psi_o and Pi_Abs showed a significant downward trend, while Phi_Do, ABS/RC, TRO/RC and DIO/RC showed a significant uptrend. In non-photochemical quenching, Fm showed a downward trend, while Qp_L1, Qp_L2, QY_L1, QY_L2 and QY_Lss showed a significant upward trend. In the change of organic acid content, ferulic acid, syringic acid, gallic acid and jasmonic acid showed a significant increasing trend, while benzoic acid and salicylic acid showed a first increasing trend and then decreasing trend. Experimental results show that pine wood nematode had significant effects on photosynthesis and the organic acid content of pine before it showed symptoms of the disease. After comprehensive analysis, chlorophyll fluorescence dynamic induction parameters Pi_Abs, Fm, Phi_Do, TRO/RC, Psi_o, non-photochemical quenching parameters QY_L2, Qp_L1, QY_Lss, QY_L1 and organic acids ferulic acid, syringic acid, benzoic acid and gallic acid contents are ideal indicators for early diagnosis of pine wood nematodiasis.
The Effect of Regulating Soil pH on the Control of Pine Wilt Disease in a Black Pine Forest
Authors: Fan Ying , Liu Lin , Wu Chuchen , Yu Guoxu , Wang Zhengyu , Fan Jingjing , Tu Chengyi
Published: August 2023

Pine wilt disease (PWD) is a highly destructive disease in forest ecosystems, resulting in extensive forest decline and substantial economic losses. As soil pH plays a critical role in soil microbial activity and significantly impacts the prevalence and severity of diseases, we conducted an experiment to regulate soil pH for alleviating PWD in a black pine (Pinus thunbergii) forest. The result reveals that: (1) The pH of the soil under a P. thunbergii forest was 5.19 ± 0.40, which was significantly lower than that of soils under other vegetation types at 8.53 ± 0.44. (2) Finely ground shell powder (F-SP) was the optimal size for long-term and efficient regulation, but quicklime (QL) exhibited the strongest efficacy in raising soil pH, followed by F-SP and plant ash. The regulation effect strengthened with the dosage amount. (3) In the situ experiments, part of symptomatic black pine in F-SP or QL plots were apparently improved and converted to asymptomatic trees separately by 15.9% and 5.4%. Applying F-SP can alleviate PWD in a sustainable way. This paper presents the first investigation to assess the effects of regulating soil pH for controlling PWD. It holds significant practical value for the rational planning and the sustainable development of artificial forests in coastal regions.
Formulating Equations for Estimating Forest Stand Carbon Stock for Various Tree Species Groups in Northern Thailand
Authors: Duangsathaporn Khwanchai , Sangram Narapong , Omule Yenemurwon , Prasomsin Patsi , Palakit Kritsadapan , Lumyai Pichit
Published: August 2023

Through this study, we established equations for estimating the standing tree carbon stock based on 24 tree species in multiple size classes in a case study at the Ngao Demonstration Forest (NDF) in northern Thailand. Four hundred thirty-nine wood samples from trees in mixed deciduous forest (MDF), dry dipterocarp forest (DDF), and dry evergreen forest (DEF) were collected using non-destructive methods to estimate aboveground carbon equations through statistical regression. The equations were established based on four criteria: (1) the coefficient of determination (R2), (2) standard error of estimate (SE), (3) F-value, and (4) significant value (p-value, α ≤ 0.05). The aboveground carbon stock (C) equations for standing trees in the MDF was C = 0.0199DBH2.1887H0.5825, for DDF was C = 0.0145DBH2.1435H0.748, for DEF was C = 0.0167DBH2.1423H0.7070, and the general equation for all species/wood density groups was C = 0.017543DBH2.1625H0.6614, where DBH is tree diameter at breast height, and H is tree total height. The aboveground carbon stock in the DDF, MDF, and DEF was 142, 53.02, and 12 tons/ha, respectively, and the estimated aboveground carbon stock in the Mae Huad sector at the NDF was 61 tons/ha.
Arrested Policy Development of Private Fire Shelters (Fire Bunkers) Is a Barrier to Adaptation to the Australian Bushfire Crisis
Authors: Bowman David M. J. S. , McCormack Phillipa C.
Published: August 2023

The Victorian Government Inquiry into wildfires that killed 173 people in 2009 has driven an Australian policy shift from self-evacuation or staying and defending a well-prepared property (‘go or stay’) to self-evacuation under catastrophic fire weather (‘leave early’). The Inquiry also led to the establishment of national ‘performance standards’ for Private Fire Shelters (PFSs, that are also known as bunkers). Nonetheless, the incorporation of PFSs into national bushfire policy remains embryonic, with only Victoria having streamlined accreditation and planning approval processes. Arguments against PFSs include potentially engendering complacency about preparing dwellings to survive fire and encouraging risky behaviour in response to a fire threat. Counteracting these arguments is research that shows that residents without PFSs have low engagement with bushfire preparation and typically delay evacuation. In any case, because wildfire is unpredictable, it is accepted that self-evacuation plans must have fallback positions that include sheltering ‘in place’ from the bushfire, making properly used and well-maintained PFSs an important element of bushfire safety. A less discussed barrier to PFS uptake outside Victoria appears to hinge on a lack of clarity about obligations for their design, certification, and consistency with planning approvals. The escalating Australian fire crisis demands much greater research and development in legal frameworks, policy and planning processes for PFSs, as well as design and construction standards. Progress in enhancing Australian laws and policies on this issue may offer important opportunities for other jurisdictions that will experience similar challenges as climate change intensifies fire regimes around the world.
Overcoming Nonlinear Dynamics in Diabetic Retinopathy Classification: A Robust AI-Based Model with Chaotic Swarm Intelligence Optimization and Recurrent Long Short-Term Memory
Authors: Özçelik Yusuf Bahri , Altan Aytaç
Published: August 2023

Diabetic retinopathy (DR), which is seen in approximately one-third of diabetes patients worldwide, leads to irreversible vision loss and even blindness if not diagnosed and treated in time. It is vital to limit the progression of DR disease in order to prevent the loss of vision in diabetic patients. It is therefore essential that DR disease is diagnosed at an early phase. Thanks to retinal screening at least twice a year, DR disease can be diagnosed in its early phases. However, due to the variations and complexity of DR, it is really difficult to determine the phase of DR disease in current clinical diagnoses. This paper presents a robust artificial intelligence (AI)-based model that can overcome nonlinear dynamics with low computational complexity and high classification accuracy using fundus images to determine the phase of DR disease. The proposed model consists of four stages, excluding the preprocessing stage. In the preprocessing stage, fractal analysis is performed to reveal the presence of chaos in the dataset consisting of 12,500 color fundus images. In the first stage, two-dimensional stationary wavelet transform (2D-SWT) is applied to the dataset consisting of color fundus images in order to prevent information loss in the images and to reveal their characteristic features. In the second stage, 96 features are extracted by applying statistical- and entropy-based feature functions to approximate, horizontal, vertical, and diagonal matrices of 2D-SWT. In the third stage, the features that keep the classifier performance high are selected by a chaotic-based wrapper approach consisting of the k-nearest neighbor (kNN) and chaotic particle swarm optimization algorithms (CPSO) to cope with both chaoticity and computational complexity in the fundus images. At the last stage, an AI-based classification model is created with the recurrent neural network-long short-term memory (RNN-LSTM) architecture by selecting the lowest number of feature sets that can keep the classification performance high. The performance of the DR disease classification model was tested on 2500 color fundus image data, which included five classes: no DR, mild non-proliferative DR (NPDR), moderate NPDR, severe NPDR, and proliferative DR (PDR). The robustness of the DR disease classification model was confirmed by the 10-fold cross-validation. In addition, the classification performance of the proposed model is compared with the support vector machine (SVM), which is one of the machine learning techniques. The results obtained show that the proposed model can overcome nonlinear dynamics in color fundus images with low computational complexity and is very effective and successful in precisely diagnosing all phases of DR disease.
Qualitative Analysis for Solving a Fractional Integro-Differential Equation of Hyperbolic Type with Numerical Treatment Using the Lerch Matrix Collocation Method
Authors: Alsulaiman Raniyah E. , Abdou Mohamed A. , ElBorai Mahmoud M. , El-Sayed Wagdy G. , Youssef Eslam M. , Taha Mai
Published: August 2023

In this research, we present a qualitative analysis for studying a new modification of a nonlinear hyperbolic fractional integro-differential equation (NHFIDEq) in dual Banach space CEE, J. Under some suitable conditions, the existence and uniqueness of a solution are demonstrated with the use of fixed-point theorems. The verification of the offered method has been conducted by applying the Lerch matrix collocation (LMC) method as a numerical treatment. The major motivation for selecting the LMC approach is that it reduces the solution of the given NHFIDEq to a matrix representation form corresponding to a linear system of algebraic equations; additionally, to demonstrate that the proposed strategy has better precision than alternative numerical methods, we study the error and the convergence analysis. Finally, we introduce numerical examples illustrating comparisons between the exact solutions and numerical solutions for different values of the Lerch parameters λ and time  t as well as how the absolute error in each example is calculated.
Co-Occurrence of Germline Genomic Variants and Copy Number Variations in Hereditary Breast and Colorectal Cancer Patients
Authors: Côrtes Luiza , Basso Tatiane Ramos , Villacis Rolando André Rios , Souza Jeferson dos Santos , Jørgensen Mads Malik Aagaard , Achatz Maria Isabel , Rogatto Silvia Regina
Published: August 2023

Hereditary Breast and Ovarian Cancer (HBOC) syndrome is an autosomal dominant disease associated with a high risk of developing breast, ovarian, and other malignancies. Lynch syndrome is caused by mutations in mismatch repair genes predisposing to colorectal and endometrial cancers, among others. A rare phenotype overlapping hereditary colorectal and breast cancer syndromes is poorly characterized. Three breast and colorectal cancer unrelated patients fulfilling clinical criteria for HBOC were tested by whole exome sequencing. A family history of colorectal cancer was reported in two patients (cases 2 and 3). Several variants and copy number variations were identified, which potentially contribute to the cancer risk or prognosis. All patients presented copy number imbalances encompassing PMS2 (two deletions and one duplication), a known gene involved in the DNA mismatch repair pathway. Two patients showed gains covering the POLE2 (cases 1 and 3), which is associated with DNA replication. Germline potentially damaging variants were found in PTCH1 (patient 3), MAT1A, and WRN (patient 2). Overall, concurrent genomic alterations were described that may increase the risk of cancer appearance in HBOC patients with breast and colorectal cancers.
Prenatal Diagnosis of Mucopolysaccharidosis-Plus Syndrome (MPSPS)
Authors: Sofronova Viktoriia , Gotovtseva Lyutsiya , Danilova Anastasia , Sukhomyasova Aitalina , Moriwaki Takahito , Terawaki Seigo , Otomo Takanobu , Maksimova Nadezhda
Published: August 2023

Mucopolysaccharidosis-plus syndrome (MPSPS) is an autosomal-recessive disorder caused by c.1492C>T (p.R498W) in the VPS33A gene. MPSPS is a severe disorder that causes a short lifespan in patients. Currently, there is no specific treatment for patients. The Yakut population is more prone to this disease than others. Diagnosing MPSPS relies on clinical manifestations, and genetic testing (GT) is used to confirm the diagnosis. In this research, we examined two pregnancy cases, one of which involved a prenatal diagnosis for MPSPS. Notably, neither pregnant woman had a known family history of the disorder. During their pregnancies, both women underwent prenatal ultrasonography, which revealed increased prenasal thickness during the second trimester. In the first case, ultrasonography indicated increased prenasal thickness in the second trimester, but a definitive diagnosis was not made at that time. The patient was eventually diagnosed with MPSPS at 11 months of age. On the contrary, in the second case, GT uncovered that the parents were carriers of MPSPS. Consequently, a placental biopsy was performed, leading to an early diagnosis of MPSPS. This study emphasizes the importance of ultrasonography findings in prenatal MPSPS diagnosis. Combining ultrasonography with GT can be a valuable approach to confirming MPSPS at an early stage, allowing for the appropriate planning of delivery methods and medical care. Ultimately, this comprehensive approach can significantly enhance the quality of life of both affected patients and their parents.