bluuebunny/crossref_metadata_2025 huggingface dataset:
Some New Integral Inequalities for Generalized Preinvex Functions in Interval-Valued Settings
Authors: Khan Muhammad Bilal , Macías-Díaz Jorge E. , Soliman Mohamed S. , Noor Muhammad Aslam
Published: November 2022

In recent years, there has been a significant amount of research on the extension of convex functions which are known as preinvex functions. In this paper, we have used this approach to generalize the preinvex interval-valued function in terms of (£1, £2)-preinvex interval-valued functions because of its extraordinary applications in both pure and applied mathematics. The idea of (£1, £2)-preinvex interval-valued functions is explained in this work. By using the Riemann integral operator, we obtain Hermite-Hadamard and Fejér-type inequalities for (£1, £2)-preinvex interval-valued functions. To discuss the validity of our main results, we provide non-trivial examples. Some exceptional cases have been discussed that can be seen as applications of main outcomes.
Reliable Online Internal Short Circuit Diagnosis on Lithium-Ion Battery Packs via Voltage Anomaly Detection Based on the Mean-Difference Model and the Adaptive Prediction Algorithm
Authors: Cao Rui , Zhang Zhengjie , Lin Jiayuan , Lu Jiayi , Zhang Lisheng , Xiao Lingyun , Liu Xinhua , Yang Shichun
Published: November 2022

The safety issue of lithium-ion batteries is a great challenge for the applications of EVs. The internal short circuit (ISC) of lithium-ion batteries is regarded as one of the main reasons for the lithium-ion batteries failure. However, the online ISC diagnosis algorithm for real vehicle data remains highly imperfect at present. Based on the onboard data from the cloud battery management system (BMS), this work proposes an ISC diagnosis algorithm for battery packs with high accuracy and high robustness via voltage anomaly detection. The mean-difference model (MDM) is applied to characterize large battery packs. A diagram of the adaptive integrated prediction algorithm combining MDM and a bi-directional long short-term memory (Bi-LSTM) neural network is firstly proposed to approach the voltage prediction of each cell. The diagnosis of an ISC is realized based on the residual analysis between the predicted and the actual state. The experimental data in DST conditions evaluate the proposed algorithm by comparing it with the solo equivalent circuit-based prediction algorithm and the Bi-LSTM based prediction algorithm. Finally, through the practical vehicle data from the cloud BMS, the diagnosis and pre-warn ability of the proposed algorithm for an ISC and thermal runaway (TR) in batteries are verified. The ISC diagnosis algorithm that is proposed in this paper can effectively identify the gradual ISC process in advance of it.
Research Progress of Working Electrode in Electrochemical Extraction of Lithium from Brine
Authors: Wang Yangyang , Zhang Guangya , Dong Guangfeng , Zheng Heng
Published: November 2022

Efficient extraction of Li from brine at a low cost is becoming a key technology to solve energy and environmental problems. Electrochemical extraction of Li has become a research hotspot due to its low energy consumption, high selectivity, and environmental friendliness. LiMn2O4, LiFePO4, and LiNi1/3Co1/3Mn1/3O2 are widely used as cathode materials for the electrochemical extraction of Li but they also have some drawbacks, such as a small adsorption capacity. In this paper, the principle of electrochemical Li extraction from brine is reviewed and the research progress and analysis of the above three working electrode materials is summarized. In addition, analysis of the extraction of other rare ions from the working electrode material and the effect of micro-organisms on the working electrode material is also presented. Next, the shortcomings of working electrode materials are expounded upon and the research direction of working electrode materials in electrochemical Li extraction technology are prospected. It is hoped that this paper can provide insights and guidance for the research and application of electrochemical Li extraction from brine.
The Combination of Hydrogels with 3D Fibrous Scaffolds Based on Electrospinning and Meltblown Technology
Authors: Erben Jakub , Jirkovec Radek , Kalous Tomas , Klicova Marketa , Chvojka Jiri
Published: November 2022

This study presents the advantages of combining three-dimensional biodegradable scaffolds with the injection bioprinting of hydrogels. This combination takes advantage of the synergic effect of the properties of the various components, namely the very favorable mechanical and structural properties of fiber scaffolds fabricated from polycaprolactone and the targeted injection of a hydrogel cell suspension with a high degree of hydrophilicity. These properties exert a very positive impact in terms of promoting inner cell proliferation and the ability to create compact tissue. The scaffolds were composed of a mixture of microfibers produced via meltblown technology that ensured both an optimal three-dimensional porous structure and sufficient mechanical properties, and electrospun nanofibers that allowed for good cell adhesion. The scaffolds were suitable for combination with injection bioprinting thanks to their mechanical properties, i.e., only one nanofibrous scaffold became deformed during the injection process. A computer numerical-control manipulator featuring a heated printhead that allowed for the exact dosing of the hydrogel cell suspension into the scaffolds was used for the injection bioprinting. The hyaluronan hydrogel created a favorable hydrophilic ambiance following the filling of the fiber structure. Preliminary in vitro testing proved the high potential of this combination with respect to the field of bone tissue engineering. The ideal structural and mechanical properties of the tested material allowed osteoblasts to proliferate into the inner structure of the sample. Further, the tests demonstrated the significant contribution of printed hydrogel-cell suspension to the cell proliferation rate. Thus, the study led to the identification of a suitable hydrogel for osteoblasts.
Intelligent Control with Artificial Neural Networks for Automated Insulin Delivery Systems
Authors: de Farias João Lucas Correia Barbosa , Bessa Wallace Moreira
Published: November 2022

Type 1 diabetes mellitus is a disease that affects millions of people around the world. Recent progress in embedded devices has allowed the development of artificial pancreas that can pump insulin subcutaneously to automatically regulate blood glucose levels in diabetic patients. In this work, a Lyapunov-based intelligent controller using artificial neural networks is proposed for application in automated insulin delivery systems. The adoption of an adaptive radial basis function network within the control scheme allows regulation of blood glucose levels without the need for a dynamic model of the system. The proposed model-free approach does not require the patient to inform when they are going to have a meal and is able to deal with inter- and intrapatient variability. To ensure safe operating conditions, the stability of the control law is rigorously addressed through a Lyapunov-like analysis. In silico analysis using virtual patients are provided to demonstrate the effectiveness of the proposed control scheme, showing its ability to maintain normoglycemia in patients with type 1 diabetes mellitus. Three different scenarios were considered: one long- and two short-term simulation studies. In the short-term analyses, 20 virtual patients were simulated for a period of 7 days, with and without prior basal therapy, while in the long-term simulation, 1 virtual patient was assessed over 63 days. The results show that the proposed approach was able to guarantee a time in the range above 95% for the target glycemia in all scenarios studied, which is in fact well above the desirable 70%. Even in the long-term analysis, the intelligent control scheme was able to keep blood glucose metrics within clinical care standards: mean blood glucose of 119.59 mg/dL with standard deviation of 32.02 mg/dL and coefficient of variation of 26.78%, all below the respective reference values.
Noble Metal Nanoparticles for Point-of-Care Testing: Recent Advancements and Social Impacts
Authors: Luciano Keven , Wang Xiaochuan , Liu Yaning , Eyler Gabriella , Qin Zhenpeng , Xia Xiaohu
Published: November 2022

Point-of-care (POC) tests for the diagnosis of diseases are critical to the improvement of the standard of living, especially for resource-limited areas or countries. In recent years, nanobiosensors based on noble metal nanoparticles (NM NPs) have emerged as a class of effective and versatile POC testing technology. The unique features of NM NPs ensure great performance of associated POC nanobiosensors. In particular, NM NPs offer various signal transduction principles, such as plasmonics, catalysis, photothermal effect, and so on. Significantly, the detectable signal from NM NPs can be tuned and optimized by controlling the physicochemical parameters (e.g., size, shape, and elemental composition) of NPs. In this article, we introduce the inherent merits of NM NPs that make them attractive for POC testing, discuss recent advancement of NM NPs-based POC tests, highlight their social impacts, and provide perspectives on challenges and opportunities in the field. We hope the review and insights provided in this article can inspire new fundamental and applied research in this emerging field.
Crystal Structure of Schizosaccharomyces pombe Rho1 Reveals Its Evolutionary Relationship with Other Rho GTPases
Authors: Huang Qingqing , Xie Jiarong , Seetharaman Jayaraman
Published: November 2022

The Rho protein, a homolog of Ras, is a member of the Ras superfamily of small GTPases. Rho family proteins are involved in cytoskeletal organization, cell mobility, and polarity, and are implicated in cancer morphogenesis. Although Rho homologs from higher-order mammalian organisms are well studied, there are few studies examining Rho proteins in lower-level single-celled organisms. Here, we report on the crystal structure of Rho1 from Schizosaccharomyces pombe (SpRho1) in complex with GDP in the presence of Mg2+ at a 2.78 Å resolution. The overall structure is similar to that of known Rho homologs, including human RhoA, human RhoC, and Aspergillus fumigatus Rho1 (AfRho1), with some exceptions. We observed subtle differences at the Switch I and II regions, in β2 and β3, and in the Rho insert domain and loop from Phe107 to Pro112. Our analysis suggests that SpRho is evolutionarily closer to HsRhoC than HsRhoA, as previously believed.
Climate Change Drives the Transmission and Spread of Vector-Borne Diseases: An Ecological Perspective
Authors: Ma Jian , Guo Yongman , Gao Jing , Tang Hanxing , Xu Keqiang , Liu Qiyong , Xu Lei
Published: November 2022

Climate change affects ecosystems and human health in multiple dimensions. With the acceleration of climate change, climate-sensitive vector-borne diseases (VBDs) pose an increasing threat to public health. This paper summaries 10 publications on the impacts of climate change on ecosystems and human health; then it synthesizes the other existing literature to more broadly explain how climate change drives the transmission and spread of VBDs through an ecological perspective. We highlight the multi-dimensional nature of climate change, its interaction with other factors, and the impact of the COVID-19 pandemic on transmission and spread of VBDs, specifically including: (1) the generally nonlinear relationship of local climate (temperature, precipitation and wind) and VBD transmission, with temperature especially exhibiting an n-shape relation; (2) the time-lagged effect of regional climate phenomena (the El Niño–Southern Oscillation and North Atlantic Oscillation) on VBD transmission; (3) the u-shaped effect of extreme climate (heat waves, cold waves, floods, and droughts) on VBD spread; (4) how interactions between non-climatic (land use and human mobility) and climatic factors increase VBD transmission and spread; and (5) that the impact of the COVID-19 pandemic on climate change is debatable, and its impact on VBDs remains uncertain. By exploring the influence of climate change and non-climatic factors on VBD transmission and spread, this paper provides scientific understanding and guidance for their effective prevention and control.
Mitochondrial Impairments in Peripheral Blood Mononuclear Cells of Multiple Sclerosis Patients
Authors: Domínguez-Mozo María Inmaculada , García-Frontini Nieto María Celeste , Gómez-Calcerrada María Isabel , Pérez-Pérez Silvia , García-Martínez María Ángel , Villar Luisa María , Villarrubia Noelia , Costa-Frossard Lucienne , Arroyo Rafael , Alvarez-Lafuente Roberto
Published: November 2022

Although impaired mitochondrial function has been proposed as a hallmark of multiple sclerosis (MS) disease, few studies focus on the mitochondria of immune cells. We aimed to compare the mitochondrial function of the peripheral blood mononuclear cells (PBMCs) from MS patients with (M+) and without (M−) lipid-specific oligoclonal immunoglobulin M bands (LS-OCMB), and healthydonors (HD). We conducted an exploratory cross-sectional study with 19 untreated MS patients (M+ = 9 and M− = 10) and 17 HDs. Mitochondrial superoxide anion production and mitochondrial mass in PBMCs were assessed without and with phytohemagglutinin by flow cytometry. The PBMCs’ mitochondrial function was analyzed using Seahorse technology. Superoxide anion production corrected by the mitochondrial mass was higher in MS patients compared with HDs (p = 0.011). Mitochondrial function from M+ patients showed some impairments compared with M− patients. Without stimulus, we observed higher proton leak (p = 0.041) but lower coupling efficiency (p = 0.041) in M+ patients; and under stimulation, lower metabolic potential ECAR (p = 0.011), and lower stressed OCR/ECAR in the same patients. Exclusively among M+ patients, we described a higher mitochondrial dysfunction in the oldest ones. The mitochondrial impairments found in the PBMCs from MS patients, specifically in M+ patients, could help to better understand the disease’s physiopathology.
Possible Application of Melatonin in Long COVID
Authors: Cardinali Daniel P. , Brown Gregory M. , Pandi-Perumal Seithikurippu R.
Published: November 2022

Clinical sequelae and symptoms for a considerable number of COVID-19 patients can linger for months beyond the acute stage of SARS-CoV-2 infection, “long COVID”. Among the long-term consequences of SARS-CoV-2 infection, cognitive issues (especially memory loss or “brain fog”), chronic fatigue, myalgia, and muscular weakness resembling myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are of importance. Melatonin may be particularly effective at reducing the signs and symptoms of SARS-CoV-2 infection due to its functions as an antioxidant, anti-inflammatory, and immuno-modulatory agent. Melatonin is also a chronobiotic medication effective in treating delirium and restoring the circadian imbalance seen in COVID patients in the intensive care unit. Additionally, as a cytoprotector, melatonin aids in the prevention of several COVID-19 comorbidities, including diabetes, metabolic syndrome, and ischemic and non-ischemic cardiovascular diseases. This narrative review discusses the application of melatonin as a neuroprotective agent to control cognitive deterioration (“brain fog”) and pain in the ME/CFS syndrome-like documented in long COVID. Further studies on the therapeutic use of melatonin in the neurological sequelae of SARS-CoV-2 infection are warranted.
Post-Translational Modifications by Lipid Metabolites during the DNA Damage Response and Their Role in Cancer
Authors: Zhu Guangrong , Zheng Xiangyang , Wang Zhifeng , Xu Xingzhi
Published: November 2022

Genomic DNA damage occurs as an inevitable consequence of exposure to harmful exogenous and endogenous agents. Therefore, the effective sensing and repair of DNA damage are essential for maintaining genomic stability and cellular homeostasis. Inappropriate responses to DNA damage can lead to genomic instability and, ultimately, cancer. Protein post-translational modifications (PTMs) are a key regulator of the DNA damage response (DDR), and recent progress in mass spectrometry analysis methods has revealed that a wide range of metabolites can serve as donors for PTMs. In this review, we will summarize how the DDR is regulated by lipid metabolite-associated PTMs, including acetylation, S-succinylation, N-myristoylation, palmitoylation, and crotonylation, and the implications for tumorigenesis. We will also discuss potential novel targets for anti-cancer drug development.
LC-MS/MS Isomeric Profiling of N-Glycans Derived from Low-Abundant Serum Glycoproteins in Mild Cognitive Impairment Patients
Authors: Reyes Cristian D. Gutierrez , Hakim Md. Abdul , Atashi Mojgan , Goli Mona , Gautam Sakshi , Wang Junyao , Bennett Andrew I. , Zhu Jianhui , Lubman David M. , Mechref Yehia
Published: November 2022

Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities, such as language or virtual/spatial comprehension. This cognitive decline is mostly observed with the aging of individuals. Recently, MCI has been considered as a prodromal phase of Alzheimer’s disease (AD), with a 10–15% conversion rate. However, the existing diagnostic methods fail to provide precise and well-timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of serum N-glycan expression could represent essential contributors to the overall pathophysiology of neurodegenerative diseases and be used as a potential marker to assess MCI diagnosis using non-invasive procedures. Herein, we undertook an LC-MS/MS glycomics approach to determine and characterize potential N-glycan markers in depleted blood serum samples from MCI patients. For the first time, we profiled the isomeric glycome of the low abundant serum glycoproteins extracted from serum samples of control and MCI patients using an LC-MS/MS analytical strategy. Additionally, the MRM validation of the identified data showed five isomeric N-glycans with the ability to discriminate between healthy and MCI patients: the sialylated N-glycans GlcNAc5,Hex6,Neu5Ac3 and GlcNAc6,Hex7,Neu5Ac4 with single AUCs of 0.92 and 0.87, respectively, and a combined AUC of 0.96; and the sialylated-fucosylated N-glycans GlcNAc4,Hex5,Fuc, Neu5Ac, GlcNAc5,Hex6,Fuc, Neu5Ac2, and GlcNAc6,Hex7,Fuc, Neu5Ac3 with single AUCs of 0.94, 0.67, and 0.88, respectively, and a combined AUC of 0.98. According to the ingenuity pathway analysis (IPA) and in line with recent publications, the identified N-glycans may play an important role in neuroinflammation. It is a process that plays a fundamental role in neuroinflammation, an important process in the progression of neurodegenerative diseases.
Macrophages in Skin Wounds: Functions and Therapeutic Potential
Authors: Sim Seen Ling , Kumari Snehlata , Kaur Simranpreet , Khosrotehrani Kiarash
Published: November 2022

Macrophages regulate cutaneous wound healing by immune surveillance, tissue repair and remodelling. The depletion of dermal macrophages during the early and middle stages of wound healing has a detrimental impact on wound closure, characterised by reduced vessel density, fibroblast and myofibroblast proliferation, delayed re-epithelization and abated post-healing fibrosis and scar formation. However, in some animal species, oral mucosa and foetal life, cutaneous wounds can heal normally and remain scarless without any involvement of macrophages. These paradoxical observations have created much controversy on macrophages’ indispensable role in skin wound healing. Advanced knowledge gained by characterising macrophage subsets, their plasticity in switching phenotypes and molecular drivers provides new insights into their functional importance during cutaneous wound healing. In this review, we highlight the recent findings on skin macrophage subsets, their functional role in adult cutaneous wound healing and the potential benefits of targeting them for therapeutic use.
Contemporary Drug Therapy for Renal Cell Carcinoma—Evidence Accumulation and Histological Implications in Treatment Strategy
Authors: Yamana Kazutoshi , Ohashi Riuko , Tomita Yoshihiko
Published: November 2022

Renal cell carcinoma (RCC) is a heterogeneous disease comprising a variety of histological subtypes. Approximately 70–80% of RCC cases are clear cell carcinoma (ccRCC), while the remaining subtypes constitute non-clear cell carcinoma (nccRCC). The medical treatment of RCC has greatly changed in recent years through advances in molecularly targeted therapies and immunotherapies. Most of the novel systemic therapies currently available have been approved based on ccRCC clinical trial data. nccRCC can be subdivided into more than 40 histological subtypes that have distinct clinical, histomorphological, immunohistochemical, and molecular features. These entities are listed as emerging in the 2022 World Health Organization classification. The diagnosis of nccRCC and treatments based on cancer histology and biology remain challenging due to the disease’s rarity. We reviewed clinical trials focused on recent discoveries regarding clinicopathological features.
Cell-Free DNA in the Pathogenesis and Therapy of Non-Infectious Inflammations and Tumors
Authors: Műzes Györgyi , Bohusné Barta Bettina , Szabó Orsolya , Horgas Vanessza , Sipos Ferenc
Published: November 2022

The basic function of the immune system is the protection of the host against infections, along with the preservation of the individual antigenic identity. The process of self-tolerance covers the discrimination between self and foreign antigens, including proteins, nucleic acids, and larger molecules. Consequently, a broken immunological self-tolerance results in the development of autoimmune or autoinflammatory disorders. Immunocompetent cells express pattern-recognition receptors on their cell membrane and cytoplasm. The majority of endogenous DNA is located intracellularly within nuclei and mitochondria. However, extracellular, cell-free DNA (cfDNA) can also be detected in a variety of diseases, such as autoimmune disorders and malignancies, which has sparked interest in using cfDNA as a possible biomarker. In recent years, the widespread use of liquid biopsies and the increasing demand for screening, as well as monitoring disease activity and therapy response, have enabled the revival of cfDNA research. The majority of studies have mainly focused on the function of cfDNA as a biomarker. However, research regarding the immunological consequences of cfDNA, such as its potential immunomodulatory or therapeutic benefits, is still in its infancy. This article discusses the involvement of various DNA-sensing receptors (e.g., absent in melanoma-2; Toll-like receptor 9; cyclic GMP–AMP synthase/activator of interferon genes) in identifying host cfDNA as a potent danger-associated molecular pattern. Furthermore, we aim to summarize the results of the experimental studies that we recently performed and highlight the immunomodulatory capacity of cfDNA, and thus, the potential for possible therapeutic consideration.
MXene-Based Nucleic Acid Biosensors for Agricultural and Food Systems
Authors: Wang Weizheng , Gunasekaran Sundaram
Published: November 2022

MXene is a two-dimensional (2D) nanomaterial that exhibits several superior properties suitable for fabricating biosensors. Likewise, the nucleic acid (NA) in oligomerization forms possesses highly specific biorecognition ability and other features amenable to biosensing. Hence the combined use of MXene and NA is becoming increasingly common in biosensor design and development. In this review, MXene- and NA-based biosensors are discussed in terms of their sensing mechanisms and fabrication details. MXenes are introduced from their definition and synthesis process to their characterization followed by their use in NA-mediated biosensor fabrication. The emphasis is placed on the detection of various targets relevant to agricultural and food systems, including microbial pathogens, chemical toxicants, heavy metals, organic pollutants, etc. Finally, current challenges and future perspectives are presented with an eye toward the development of advanced biosensors with improved detection performance.
Artificial Intelligence Methodologies Applied to Technologies for Screening, Diagnosis and Care of the Diabetic Foot: A Narrative Review
Authors: Chemello Gaetano , Salvatori Benedetta , Morettini Micaela , Tura Andrea
Published: November 2022

Diabetic foot syndrome is a multifactorial pathology with at least three main etiological factors, i.e., peripheral neuropathy, peripheral arterial disease, and infection. In addition to complexity, another distinctive trait of diabetic foot syndrome is its insidiousness, due to a frequent lack of early symptoms. In recent years, it has become clear that the prevalence of diabetic foot syndrome is increasing, and it is among the diabetes complications with a stronger impact on patient’s quality of life. Considering the complex nature of this syndrome, artificial intelligence (AI) methodologies appear adequate to address aspects such as timely screening for the identification of the risk for foot ulcers (or, even worse, for amputation), based on appropriate sensor technologies. In this review, we summarize the main findings of the pertinent studies in the field, paying attention to both the AI-based methodological aspects and the main physiological/clinical study outcomes. The analyzed studies show that AI application to data derived by different technologies provides promising results, but in our opinion future studies may benefit from inclusion of quantitative measures based on simple sensors, which are still scarcely exploited.
Recent Advances, Opportunities, and Challenges in Developing Nucleic Acid Integrated Wearable Biosensors for Expanding the Capabilities of Wearable Technologies in Health Monitoring
Authors: Janghorban Mohammad , Aradanas Irvyne , Kazemi Sara , Ngaju Philippa , Pandey Richa
Published: November 2022

Wearable biosensors are becoming increasingly popular due to the rise in demand for non-invasive, real-time monitoring of health and personalized medicine. Traditionally, wearable biosensors have explored protein-based enzymatic and affinity-based detection strategies. However, in the past decade, with the success of nucleic acid-based point-of-care diagnostics, a paradigm shift has been observed in integrating nucleic acid-based assays into wearable sensors, offering better stability, enhanced analytical performance, and better clinical applicability. This narrative review builds upon the current state and advances in utilizing nucleic acid-based assays, including oligonucleotides, nucleic acid, aptamers, and CRISPR-Cas, in wearable biosensing. The review also discusses the three fundamental blocks, i.e., fabrication requirements, biomolecule integration, and transduction mechanism, for creating nucleic acid integrated wearable biosensors.
Improving Upper Limb and Gait Rehabilitation Outcomes in Post-Stroke Patients: A Scoping Review on the Additional Effects of Non-Invasive Brain Stimulation When Combined with Robot-Aided Rehabilitation
Authors: Naro Antonino , Calabrò Rocco Salvatore
Published: November 2022

Robot-aided rehabilitation (RAR) and non-invasive brain stimulation (NIBS) are the two main interventions for post-stroke rehabilitation. The efficacy of both approaches in combination has not been well established yet. The importance of coupling these interventions, which both enhance brain plasticity to promote recovery, lies in augmenting the rehabilitation potential to constrain the limitation in daily living activities and the quality of life following stroke. This review aimed to evaluate the evidence of NIBS coupled with RAR in improving rehabilitation outcomes of upper limb and gait motor impairment in adult individuals with stroke. We included 18 clinical trials in this review. All studies were highly heterogeneous concerning the technical characteristics of robotic devices and NIBS protocols. However, the studies reported a global improvement in body structure and function and activity limitation for the upper limb, which were non-significant between the active and control groups. Concerning gait training protocols, the active group outperformed the control group in improving walking capacity and recovery. According to this review, NIBS and RAR in combination are promising but not yet largely recommendable as a systematic approach for stroke rehabilitation as there is not enough data about this. Therefore, more homogenous clinical trials are required, pointing out the best characteristics of the combined therapeutic protocols.
Research on Safety Resilience Evaluation Model of Data Center Physical Infrastructure: An ANP-Based Approach
Authors: Xiahou Xiaer , Chen Jialong , Zhao Bangyi , Yan Zixuan , Cui Peng , Li Qiming , Yu Zhou
Published: November 2022

With the development of the digital economy, the number and scale of data centers are expanding rapidly. Data centers are playing an increasingly important role in social and economic development. However, a short downtime of a data center may result in huge losses. The safety management of data centers’ physical infrastructure is of great significance to address this concern. We applied resilience theory to the safety management of data center physical infrastructures. We analyzed the resilience connotation and evaluated the system resilience using the resilience indexes. The data center infrastructure was regarded as a system of systems. Through theoretical analysis, the resilience framework of data center infrastructures was established, which formed the main dimensions of resilience assessment. The Delphi method determined the resilience indices, and the ANP method was adopted to set up the evaluation model. The results revealed the important indexes affecting data center infrastructure system safety resilience. Based on the findings, this paper argues for improving redundancy and adaptability, paying attention to the resilience management of energy flow and thermal flow, and establishing an automatic systematic data management system. These suggested measures would not only effectively make contributions to the data center infrastructure safety management theory but also provide an important reference for construction industry practices.
Research on Resilience Evaluation and Enhancement of Deep Foundation Pit Construction Safety System
Authors: Shen Ling , Xue Zhijian , Tang Lingyi , Ge Hongyan
Published: November 2022

Deep foundation pit (DFP) projects have been a high incidence area of safety accidents because of their own high danger and complexity. Therefore, it is necessary to study the resilience of their construction safety system. This paper systematically identifies the key factors affecting the resilience of deep foundation pit construction based on the analysis of the composition of the deep foundation pit construction safety system (DFPCTSS), the synergistic relationship of its subsystems in the face of the interference and impact of internal and external disaster-causing factors, and the causal mechanism of typical accidents in DFP accidents and the emergent process of system resilience. A resilience evaluation indicator system based on four capacity dimensions of prevention absorption, resistance, recovery, and learning adaptation was constructed by using the fuzzy Delphi method, which is characterized by the resilience emergence process. Then the correlation and weight of evaluation indexes were analyzed based on the DEMATEL–ANP method, the boundary cloud parameters of the resilience evaluation grade were set according to the normal extension cloud model, and the membership degree of the resilience evaluation level was calculated to complete the evaluation of the resilience level. Finally, taking a DFP project of a metro station as an example, the above model was used to evaluate the resilience level of its construction safety system, and suggestions for resilience enhancement were put forward. The results show that the evaluation results are consistent with the actual situation of the project, and the evaluation model is conducive to providing a systematic analysis method and improvement countermeasures for deep foundation pit construction safety management from the perspective of resilience.
Seismic Analysis of RC High-Rise Buildings Rested on Cellular Raft
Authors: Shaaban Mohammed , Abouelsaad Mohamed Naguib , El Bagalaty Salah , El Madawy Mohamed E.
Published: November 2022

This paper includes the investigation of the soil–structure interaction (SSI) effect on the seismic response of 20 and 30-story reinforced concrete moment resisting frames (MRFs) rested on a piled raft foundation using the direct approach. After that, a study is conducted to show the impact of using a cellular raft instead of the designed solid raft on the dynamic response of the building. A study is introduced to select the best gap size for the cellular raft. The soil model is assumed as a single layer of sandy clay. Time history analysis by the direct integration method is performed under seven earthquake records (El-Centro, Northridge, Kobe, Chichi, Friuli, Kocaeli, and Loma), which are scaled to the Egyptian Code for Loads (ECP-201) response spectrum using a full 3D model by a finite element software named (Midas GTS NX). It is concluded that considering SSI significantly affects the dynamic response of high-rise buildings, and using cellular rafts generally leads to a decrease in their dynamic response.
Preoperative Serum Markers and Risk Classification in Intrahepatic Cholangiocarcinoma: A Multicenter Retrospective Study
Authors: Kaibori Masaki , Yoshii Kengo , Kosaka Hisashi , Ota Masato , Komeda Koji , Ueno Masaki , Hokutou Daisuke , Iida Hiroya , Matsui Kosuke , Sekimoto Mitsugu
Published: November 2022

Accurate risk stratification selects patients who are expected to benefit most from surgery. This retrospective study enrolled 225 Japanese patients with intrahepatic cholangiocellular carcinoma (ICC) who underwent hepatectomy between January 2009 and December 2020 and identified preoperative blood test biomarkers to formulate a classification system that predicted prognosis. The optimal cut-off values of blood test parameters were determined by ROC curve analysis, with Cox univariate and multivariate analyses identifying prognostic factors. Risk classifications were established using classification and regression tree (CART) analysis. CART analysis revealed decision trees for recurrence-free survival (RFS) and overall survival (OS) and created three risk classifications based on machine learning of preoperative serum markers. Five-year rates differed significantly (p < 0.001) between groups: 60.4% (low-risk), 22.8% (moderate-risk), and 4.1% (high-risk) for RFS and 69.2% (low-risk), 32.3% (moderate-risk), and 9.2% (high-risk) for OS. No difference in OS was observed between patients in the low-risk group with or without postoperative adjuvant chemotherapy, although OS improved in the moderate group and was prolonged significantly in the high-risk group receiving chemotherapy. Stratification of patients with ICC who underwent hepatectomy into three risk groups for RFS and OS identified preoperative prognostic factors that predicted prognosis and were easy to understand and apply clinically.
The Glasgow Prognostic Score Predicts Survival Outcomes in Neuroendocrine Neoplasms of the Gastro–Entero–Pancreatic (GEP-NEN) System
Authors: Gebauer Niklas , Ziehm Maria , Gebauer Judith , Riecke Armin , Meyhöfer Sebastian , Kulemann Birte , von Bubnoff Nikolas , Steinestel Konrad , Bauer Arthur , Witte Hanno M.
Published: November 2022

Background: Across a variety of solid tumors, prognostic implications of nutritional and inflammation-based risk scores have been identified as a complementary resource of risk stratification. Methods: In this retrospective study, we performed a comparative analysis of several established risk scores and ratios, such as the Glasgow Prognostic Score (GPS), in neuroendocrine neoplasms of the gastro–entero–pancreatic (GEP-NEN) system with respect to their prognostic capabilities. Clinicopathological and treatment-related data for 102 GEP-NEN patients administered to the participating institutions between 2011 and 2021 were collected. Scores/ratios significantly associated with overall or progression-free survival (OS, PFS) upon univariate analysis were subsequently included in a Cox-proportional hazard model for the multivariate analysis. Results: The median age was 62 years (range 18–95 years) and the median follow-up period spanned 51 months. Pancreatic or intestinal localization at the initial diagnosis were present in 41 (40.2%) and 44 (43.1%) cases, respectively. In 17 patients (16.7%), the primary manifestation could not be ascertained (NNUP; neuroendocrine neoplasms of unknown primary). Histological grading (HG) revealed 24/102 (23.5%) NET/NEC (poorly differentiated; high grade G3) and 78/102 (76.5%) NET (highly or moderately differentiated; low–high grade G1–G2). In total, 53/102 (51.9%) patients presented with metastatic disease (UICC IV), 11/102 (10.7%) patients presented with multifocal disease, and 56/102 (54.9%) patients underwent a primary surgical or endoscopic approach, whereas 28 (27.5%) patients received systemic cytoreductive treatment. The univariate analysis revealed the GPS and PI (prognostic index), as well as UICC-stage IV, HG, and the Charlson comorbidity index (CCI) to predict both the PFS and OS in GEP-NEN patients. However, the calculation of the survival did not separate GPS subgroups at lower risk (GPS 0 versus GPS 1). Upon the subsequent multivariate analysis, GPS was the only independent predictor of both OS (p < 0.0001; HR = 3.459, 95% CI = 1.263–6.322) and PFS (p < 0.003; HR = 2.119, 95% CI = 0.944–4.265). Conclusion: In line with previous results for other entities, the present study revealed the GPS at baseline to be the only independent predictor of survival across all stages of GEP-NEN, and thus supports its clinical utility for risk stratification in this group of patients.
Aptamers, a New Therapeutic Opportunity for the Treatment of Multiple Myeloma
Authors: Amundarain Ane , Pastor Fernando , Prósper Felipe , Agirre Xabier
Published: November 2022

Multiple Myeloma (MM) remains an incurable disease due to high relapse rates and fast development of drug resistances. The introduction of monoclonal antibodies (mAb) has caused a paradigm shift in MM treatment, paving the way for targeted approaches with increased efficacy and reduced toxicities. Nevertheless, antibody-based therapies face several difficulties such as high immunogenicity, high production costs and limited conjugation capacity, which we believe could be overcome by the introduction of nucleic acid aptamers. Similar to antibodies, aptamers can bind to their targets with great affinity and specificity. However, their chemical nature reduces their immunogenicity and production costs, while it enables their conjugation to a wide variety of cargoes for their use as delivery agents. In this review, we summarize several aptamers that have been tested against MM specific targets with promising results, establishing the rationale for the further development of aptamer-based strategies against MM. In this direction, we believe that the study of novel plasma cell surface markers, the development of intracellular aptamers and further research on aptamers as building blocks for complex nanomedicines will lead to the generation of next-generation targeted approaches that will undoubtedly contribute to improve the management and life quality of MM patients.
Histone Deacetylase Functions in Gastric Cancer: Therapeutic Target?
Authors: Badie Amandine , Gaiddon Christian , Mellitzer Georg
Published: November 2022

Gastric cancer (GC) is one of the most aggressive cancers. Therapeutic treatments are based on surgery combined with chemotherapy using a combination of platinum-based agents. However, at metastatic stages of the disease, survival is extremely low due to late diagnosis and resistance mechanisms to chemotherapies. The development of new classifications has not yet identified new prognostic markers for clinical use. The studies of epigenetic processes highlighted the implication of histone acetylation status, regulated by histone acetyltransferases (HATs) and by histone deacetylases (HDACs), in cancer development. In this way, inhibitors of HDACs (HDACis) have been developed and some of them have already been clinically approved to treat T-cell lymphoma and multiple myeloma. In this review, we summarize the regulations and functions of eighteen HDACs in GC, describing their known targets, involved cellular processes, associated clinicopathological features, and impact on survival of patients. Additionally, we resume the in vitro, pre-clinical, and clinical trials of four HDACis approved by Food and Drug Administration (FDA) in cancers in the context of GC.
Validation of the DNA Methylation Landscape of TFF1/TFF2 in Gastric Cancer
Authors: Qian Ze , Jiang Yifan , Shou Chunhui , Yu Jinghua , Huang Dongdong , Xie Haiyang , Zhou Lin , Chen Diyu , Zheng Shusen
Published: November 2022

As one of the most frequently occurring tumor types, the increasing incidence of gastric cancer (GC) has been observed in the past decades. The recent studies have illustrated that epigenetic modifications mediated by DNA methyltransferases (DNMTs) are the major epigenetic hallmark in GC progression. Nowadays, DNA methylation was considered to be necessary for inducing the silence of tumor suppressor genes (TSGs). As an important group of peptides, the TFF family has been confirmed to function as a TSG in various kinds of cancers. However, whether TFFs could be modified by DNA methylation in gastric cancer remains unknown. Here, we initially screened out two transcriptional sequencing profiles about GC from Gene Expression Omnibus (GEO) database. The lower expression levels of TFF1 and TFF2 were observed in GC tumor tissues as compared to those in normal tissues. Additionally, utilizing the Kaplan–Meier analysis, the expressions of TFF1 and TFF2 were identified to be associated with the prognosis of GC patients. Subsequently, the integrative analysis was performed to estimate the DNA methylation level of each site in TFF1/TFF2 CpG islands. Importantly, our findings indicated that hyper-methylation of cg01886855 and cg26403416 were separately responsible for the downregulation of TFF1 and TFF2 in GC samples. In addition, utilizing the experiments in vitro, we demonstrated that TFF1/TFF2 could suppress the proliferation of GC cells. Based on these results, we suspected that TFF1/TFF2 could potentially act as the putative tumor suppressor in GC, and these two TFFs were of great value for predicting the overall survival (OS) status in the gastric cancer cohort. Totally, our findings revealed a potential therapeutic method for targeting the TFFs for the treatment of GC.
Two-Stage Deep Learning Model for Automated Segmentation and Classification of Splenomegaly
Authors: Meddeb Aymen , Kossen Tabea , Bressem Keno K. , Molinski Noah , Hamm Bernd , Nagel Sebastian N.
Published: November 2022

Splenomegaly is a common cross-sectional imaging finding with a variety of differential diagnoses. This study aimed to evaluate whether a deep learning model could automatically segment the spleen and identify the cause of splenomegaly in patients with cirrhotic portal hypertension versus patients with lymphoma disease. This retrospective study included 149 patients with splenomegaly on computed tomography (CT) images (77 patients with cirrhotic portal hypertension, 72 patients with lymphoma) who underwent a CT scan between October 2020 and July 2021. The dataset was divided into a training (n = 99), a validation (n = 25) and a test cohort (n = 25). In the first stage, the spleen was automatically segmented using a modified U-Net architecture. In the second stage, the CT images were classified into two groups using a 3D DenseNet to discriminate between the causes of splenomegaly, first using the whole abdominal CT, and second using only the spleen segmentation mask. The classification performances were evaluated using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). Occlusion sensitivity maps were applied to the whole abdominal CT images, to illustrate which regions were important for the prediction. When trained on the whole abdominal CT volume, the DenseNet was able to differentiate between the lymphoma and liver cirrhosis in the test cohort with an AUC of 0.88 and an ACC of 0.88. When the model was trained on the spleen segmentation mask, the performance decreased (AUC = 0.81, ACC = 0.76). Our model was able to accurately segment splenomegaly and recognize the underlying cause. Training on whole abdomen scans outperformed training using the segmentation mask. Nonetheless, considering the performance, a broader and more general application to differentiate other causes for splenomegaly is also conceivable.
Combined Targeting of Pathogenetic Mechanisms in Pancreatic Neuroendocrine Tumors Elicits Synergistic Antitumor Effects
Authors: Gulde Sebastian , Foscarini Alessia , April-Monn Simon L. , Genio Edoardo , Marangelo Alessandro , Satam Swapna , Helbling Daniel , Falconi Massimo , Toledo Rodrigo A. , Schrader Jörg , Perren Aurel , Marinoni Ilaria , Pellegata Natalia S.
Published: November 2022

Pancreatic neuroendocrine neoplasms (PanNENs) are the second most common malignancy of the pancreas. Surgery remains the only curative treatment for localized disease. For patients with inoperable advanced or metastatic disease, few targeted therapies are available, but their efficacy is unpredictable and variable. Exploiting prior knowledge on pathogenetic processes involved in PanNEN tumorigenesis, we tested buparlisib (PI3K inhibitor) and ribociclib (CDK4/6 inhibitor), as single agents or in combination, in different preclinical models. First, we used cell lines representative of well-differentiated (INS-1E, NT-3) and poorly differentiated (BON-1) PanNENs. The combination of buparlisib with ribociclib reduced the proliferation of 2D and 3D spheroid cultures more potently than the individual drugs. Buparlisib, but not ribociclib, induced apoptosis. The anti-proliferative activity of the drugs correlated with downstream target inhibition at mRNA and protein levels. We then tested the drugs on primary islet microtissues from a genetic PanNET animal model (Men1-defective mice) and from wild-type mice: the drug combination was effective against the former without altering islet cell physiology. Finally, we treated PanNET patient-derived islet-like 3D tumoroids: the combination of buparlisib with ribociclib was effective in three out of four samples. Combined targeting of PI3K and CDK4/6 is a promising strategy for PanNENs spanning various molecular and histo-pathological features.