bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Bioinformatic Analysis of the Proteomes of Rabbit and Human Sex Chromosomes
Authors: Pinto-Pinho Patrícia , Soares João , Esteves Pedro , Pinto-Leite Rosário , Fardilha Margarida , Colaço Bruno
Published: January 2024

Studying proteins associated with sex chromosomes can provide insights into sex-specific proteins. Membrane proteins accessible through the cell surface may serve as excellent targets for diagnostic, therapeutic, or even technological purposes, such as sperm sexing technologies. In this context, proteins encoded by sex chromosomes have the potential to become targets for X- or Y-chromosome-bearing spermatozoa. Due to the limited availability of proteomic studies on rabbit spermatozoa and poorly annotated databases for rabbits compared to humans, a bioinformatic analysis of the available rabbit X chromosome proteome (RX), as well as the human X (HX) and Y (HY) chromosomes proteome, was conducted to identify potential targets that could be accessible from the cell surface and predict which of the potential targets identified in humans might also exist in rabbits. We identified 100, 211, and 3 proteins associated with the plasma membrane or cell surface for RX, HX, and HY, respectively, of which 61, 132, and 3 proteins exhibit potential as targets as they were predicted to be accessible from the cell surface. Cross-referencing the potential HX targets with the rabbit proteome revealed an additional 60 proteins with the potential to be RX targets, resulting in a total of 121 potential RX targets. In addition, at least 53 possible common HX and RX targets have been previously identified in human spermatozoa, emphasizing their potential as targets of X-chromosome-bearing spermatozoa. Further proteomic studies on rabbit sperm will be essential to identify and validate the usefulness of these proteins for application in rabbit sperm sorting techniques as targets of X-chromosome-bearing spermatozoa.
Deepwater 3D Measurements with a Novel Sensor System
Authors: Bräuer-Burchardt Christian , Munkelt Christoph , Bleier Michael , Baumann Anja , Heinze Matthias , Gebhart Ingo , Kühmstedt Peter , Notni Gunther
Published: January 2024

A novel 3D sensor system for underwater application is presented, primarily designed to carry out inspections on industrial facilities such as piping systems, offshore wind farm foundations, anchor chains, and other structures at deep depths of up to 1000 m. The 3D sensor system enables high-resolution 3D capture at a measuring volume of approximately 1 m3, as well as the simultaneous capture of color data using active stereo scanning with structured lighting, producing highly accurate and detailed 3D images for close-range inspection. Furthermore, the system uses visual inertial odometry to map the seafloor and create a rough 3D overall model of the environment via Simultaneous Localization and Mapping (SLAM). For this reason, the system is also suitable for geological, biological, or archaeological applications in underwater areas. This article describes the overall system and data processing, as well as initial results regarding the measurement accuracy and applicability from tests of the sensor system in a water basin and offshore with a Remotely Operating Vehicle (ROV) in the Baltic Sea.
Influence of Acoustic Streams on the Efficiency of Ultrasonic Particle Agglomeration
Authors: Khmelev Vladimir Nikolaevich , Shalunov Andrey Victorovich , Nesterov Viktor Aleksandrovich , Terentiev Sergey Aleksandrovich
Published: January 2024

The article is devoted to the study of ultrasonic agglomeration of PM 2.5 in homogeneous and inhomogeneous ultrasonic fields. The possibility of increasing the efficiency of ultrasonic agglomeration by initiating acoustic streams in a resonant inhomogeneous ultrasonic field is shown. A inhomogeneous ultrasonic field with zones of high and low sound pressure levels formed using a bending-oscillating disk transmitter made it possible to initiate acoustic vortex-type streaming that promotes the movement of particles into the nodal areas of a standing wave and between them. Due to the formation of a inhomogeneous ultrasonic field, the efficiency of particle collection is increased: for PM 2.5, the efficiency reaches 95%; PM 1.5—92%; PM 0.5—85%. The results were obtained under the following conditions: concentration 2 × 10−2 g/m3, sound pressure level 165 dB, flow rate 6.2 m3/h. For comparison, when a homogeneous ultrasonic field is formed in the agglomeration chamber (under similar conditions), the efficiency of particle capture by inertial gas cleaning equipment does not exceed the following: for PM 2.5—89%; PM 1.5—85%; and PM 0.5—76%. The obtained research results made it possible to propose a design for an agglomeration chamber that can greatly increase the productivity of ultrasonic flow processing.
Patient and Provider Perspectives on Barriers and Facilitators to the Acceptance of Pain Neuroscience Education in Chronic Musculoskeletal Pain Conditions: A Qualitative Systematic Review Protocol
Authors: Kühn Lukas , Reiter Nils Lennart , Wengemuth Eileen , Choi Kyung-Eun (Anna)
Published: January 2024

Objective: To identify and map barriers and facilitators to the acceptance of pain neuroscience education for chronic musculoskeletal pain conditions. Introduction: Pain neuroscience education aims to reconceptualize the understanding of the biology of pain. This includes the acknowledgment of physiological and psychological processes relevant to pain experiences to ultimately change maladaptive beliefs and behaviors. Pain neuroscience education in chronic musculoskeletal pain conditions has been demonstrated to positively influence relevant treatment outcomes. Inclusion criteria: Only qualitative studies will be included. The population will include patients with chronic musculoskeletal pain and healthcare providers involved in pain management. The phenomenon of interest encompasses educational interventions on the biology and psychology of pain, which aim to reconceptualize patients’ understanding of pain. Methods: A comprehensive search strategy will be conducted on MEDLINE (PubMed), Web of Science, PsycInfo, and CINHAL. Two reviewers will independently conduct the study selection process, critical appraisal, data extraction, and data synthesis. Discrepancies will be resolved by a third reviewer. The assessment of methodological quality will be guided by JBI’s critical appraisal checklist for qualitative research. Qualitative data synthesis will follow the JBI SUMARI meta-aggregation approach. Considerations of the certainty in the results will be reported in accordance with a ConQual Summary of Findings.
Diversity in Selected Grain Mineral and Protein among Pigeonpea Landraces
Authors: Mashifane Dipoo C. , Chiulele Rogerio M. , Gwata Eastonce T.
Published: January 2024

Pigeonpea (Cajanus cajan) is an important grain legume that provides highly nutritious food for human consumption. It contains high amounts of protein, carbohydrates, fats as well as both macro- and micronutrients. This study examined the genetic diversity of grain mineral and protein content among fourteen pigeonpea landraces. There were highly significant differences (p ≤ 0.001) among the landraces for most of the mineral elements including calcium (Ca), copper (Cu), potassium (K), magnesium (Mg), manganese (Mn), phosphorus (P) and zinc (Zn). The K and P content ranged from 8874.21 to 15,817.38 mg/kg and 2899.23 to 4945.12 mg/kg, respectively. Relatively high amounts of Ca (2103.43 mg/kg) and Mn (73.11 mg/kg) were observed in ‘G-03’, but ‘G-09’ attained the highest content of K (15,817.38 mg/kg) and Zn (38.56 mg/kg). Highly significant (p ≤ 0.001) negative correlations were observed between Mn and Cu. The principal component analysis showed that three landraces (‘G-03’, ‘G-04’ and ‘G-05’) were highly associated with Ca, P, Mg and Mn. The three landraces (‘G-03’ for Ca and Mn; ‘G-04’ for Mg and P; ‘G-09’ for Cu, K and Zn) possessing high grain mineral and protein (‘G-10’) contents can be utilized in pigeonpea breeding programs that are aimed at improving the grain’s traits.
Online and Offline Model for Housekeeping Order Assignment Based on Dynamic Programming Algorithm
Authors: Shi Yongkun , Li Jiangkuan , Sun Jiaquan , Lu Cunhao , Chen Jian , Sun Xiaoguang
Published: January 2024

With the booming development of door-to-door housekeeping service, the platform faces the problem of order assignment. Improving the matching mechanism between orders and housekeepers based on a dynamic programming (DP) algorithm can not only achieve flexible order allocation but can also improve the service efficiency and service quality. In this paper, a single objective nonlinear programming model is established, which takes the maximum total weight value as the objective function to study the order allocation problem under offline and online conditions. Under the offline condition, the number of housekeepers is taken as the decision variable. The status of order and housekeeper, order time, and action trajectory are taken as constraints. For online assignment, the order backlog status is treated as the decision variable. The reliability of the model was verified using real data from 20 groups of housekeepers and 50 groups of orders. Finally, the effect of order backlog on online allocation is discussed and the optimal threshold and maximum weight are found. The online order assignment model is compared with the nearest distance assignment model. The results show that the online assignment model with a total weighted score of 1045.14 is better than the nearest distance assignment model with a score of 810.25.
Monitoring and Calibrating Building Materials Drying Kinetics with Capacitance Sensors
Authors: Karoglou Maria , Mouzakis Charalampos , Bakolas Asterios , Asimakopoulos Simos , Mustapha Gamal
Published: January 2024

Building materials’ moisture content defines the overall durability and serviceability of buildings and infrastructures. Conventionally, moisture content is estimated by weighing the materials before and after drying. In this work, the results of capacitance wired sensors for measuring moisture content were investigated. These sensors facilitate in situ measurement of capacitance values, with the aid of specialized installation equipment, and the results are accessible via a cloud-based software application. In practice, the main drawback associated with the application of these sensors is related to their calibration. Thus, it is important to investigate different algorithms which convert capacitance readings into moisture content values. To address this, various specimens covering a diverse set of building materials were prepared in the laboratory. This study focused on examining two bricks, two sedimentary stones with low and high porosity values. and four different kinds of mortars (with different binders, namely hydrated lime putty, cement, natural hydraulic lime, and hydrated lime powder and pozzolan). The results indicated that a linear model can be recommended for calibrating sensor capacitance to moisture content measurements. This model can be used for the prediction of building material moisture content with high accuracy, from saturated to the dry state, covering the full range of drying kinetics.
Predicting Model of Dual-Mode Shield Tunneling Parameters in Complex Ground Using Recurrent Neural Networks and Multiple Optimization Algorithms
Authors: Yang Taihua , Wen Tian , Huang Xing , Liu Bin , Shi Hongbing , Liu Shaoran , Peng Xiaoxiang , Sheng Guangzu
Published: January 2024

Based on the left tunnel of the Liuxiandong Station to Baimang Station section of Shenzhen Metro Line 13 (China), a prediction model for the advanced rate of dual-mode shield tunneling in complex strata was established to explore intelligent tunneling technology in complex ground. Firstly, geological parameters of the complex strata and on-site monitoring parameters of EPB/TBM dual-mode shield tunneling were collected, with tunneling parameters, shield tunneling mode, and strata parameters selected as input features. Subsequently, the Isolation Forest algorithm was employed to remove outliers from the original advance parameters, and an improved mean filtering algorithm was applied to eliminate data noise, resulting in the steady-state phase parameters of the shield tunneling process. The base model was chosen as the Long-Short Term Memory (LSTM) recurrent neural network. During the model training process, particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), and Bayesian optimization (BO) algorithms were, respectively, combined to optimize the model’s hyperparameters. Via rank analysis based on evaluation metrics, the BO-LSTM model was found to have the shortest runtime and highest accuracy. Finally, the dropout algorithm and five-fold time series cross-validation were incorporated into the BO-LSTM model, creating a multi-algorithm-optimized recurrent neural network model for predicting tunneling speed. The results indicate that (1) the Isolation Forest algorithm can conveniently identify outliers while considering the relationship between tunneling speed and other parameters; (2) the improved mean filtering algorithm exhibits better denoising effects on cutterhead speed and tunneling speed; and (3) the multi-algorithm optimized LSTM model exhibits high prediction accuracy and operational efficiency under various geological parameters and different excavation modes. The minimum Mean Absolute Percentage Error (MAPE) prediction result is 8.3%, with an average MAPE prediction result below 15%.
Sustainable Recovery of an Agricultural Area Impacted by an Oil Spill Using Enhanced Phytoremediation
Authors: Vocciante Marco , Franchi Elisabetta , Fusini Danilo , Pedron Francesca , Barbafieri Meri , Petruzzelli Gianniantonio , Reverberi Andrea P.
Published: January 2024

In this paper, a viability study is conducted for a bioremediation intervention in a cultivated area contaminated by a pipeline oil spill. In this context, green technologies such as bioremediation and phytoremediation could represent an optimal solution for reducing pollution without deteriorating soil quality. The phytoremediation test was conducted at the microcosm scale using three plant species (Zea mays, Lupinus albus and Medicago sativa) and at the mesocosm scale (Zea mays), also evaluating the application of plant growth-promoting bacteria (PGPB). The results showed that the selected plants, being able to grow satisfactorily, are able to lessen the presence of hydrocarbons in the soil. An increase of 15–18% in the degradation of the C > 12 fractions in vegetated soils was observed, confirming the effect of plants on the biodegradation of hydrocarbons in the soil. Moreover, a further improvement was recorded after adding PGPB, resulting in fresh biomass production being up to 50% higher than the controls and the degradation of the C > 12 fraction increasing by up to an additional 10%. Particular attention was also paid to pyrene, considered an indicator of PAH contamination. At the end of the experimentation in vegetated soils, pyrene removal reached values above 50%. By favoring plant growth, the addition of PGPB resulted in a further up to 20% reduction in the content of the contaminant in the soil. The primary role of the plants in soil contaminated by petroleum derivatives was to accelerate the degradation of contaminants through the stimulation of microbial activity. Therefore, the cooperation between plants and microorganisms can be concretely used as a nature-based solution in a sustainable and economical way.
Development of an Anisotropic Hyperelastic Material Model for Porcine Colorectal Tissues
Authors: Fahmy Youssef , Trabia Mohamed B. , Ward Brian , Gallup Lucas , Froehlich Mary
Published: January 2024

Many colonic surgeries include colorectal anastomoses whose leaks may be life-threatening, affecting thousands of patients annually. Various studies propose that mechanical interaction between the staples and neighboring tissues may play an important role in anastomotic leakage. Therefore, understanding the mechanical behavior of colorectal tissue is essential to characterizing the reasons for this type of failure. So far, experimental data characterizing the mechanical properties of colorectal tissue have been few and inconsistent, which has significantly limited understanding their behavior. This research proposes an approach to developing an anisotropic hyperelastic material model for colorectal tissues based on uniaxial testing of freshly harvested porcine specimens, which were collected from several age- and weight-matched pigs. The specimens were extracted from the same colon tract of each pig along their circumferential and longitudinal orientations. We propose a constitutive model combining Yeoh isotropic hyperelastic material with fibers oriented in two directions to account for the hyperelastic and anisotropic nature of colorectal tissues. Experimental data were used to accurately determine the model’s coefficients (circumferential, R2 = 0.9968; longitudinal, R2 = 0.9675). The results show that the proposed model can be incorporated into a finite element model that can simulate procedures such as colorectal anastomoses reliably.
Bi-Exponential 3D UTE-T1ρ Relaxation Mapping of Ex Vivo Human Knee Patellar Tendon at 3T
Authors: Malhi Bhavsimran Singh , Moazamian Dina , Shin Soo Hyun , Athertya Jiyo S. , Silva Livia , Jerban Saeed , Jang Hyungseok , Chang Eric , Ma Yajun , Carl Michael , Du Jiang
Published: January 2024

Introduction: The objective of this study was to assess the bi-exponential relaxation times and fractions of the short and long components of the human patellar tendon ex vivo using three-dimensional ultrashort echo time T1ρ (3D UTE-T1ρ) imaging. Materials and Methods: Five cadaveric human knee specimens were scanned using a 3D UTE-T1ρ imaging sequence on a 3T MR scanner. A series of 3D UTE-T1ρ images were acquired and fitted using single-component and bi-component models. Single-component exponential fitting was performed to measure the UTE-T1ρ value of the patellar tendon. Bi-component analysis was performed to measure the short and long UTE-T1ρ values and fractions. Results: The single-component analysis showed a mean single-component UTE-T1ρ value of 8.4 ± 1.7 ms for the five knee patellar tendon samples. Improved fitting was achieved with bi-component analysis, which showed a mean short UTE-T1ρ value of 5.5 ± 0.8 ms with a fraction of 77.6 ± 4.8%, and a mean long UTE-T1ρ value of 27.4 ± 3.8 ms with a fraction of 22.4 ± 4.8%. Conclusion: The 3D UTE-T1ρ sequence can detect the single- and bi-exponential decay in the patellar tendon. Bi-component fitting was superior to single-component fitting.
Advances in Fracture Healing Research
Authors: Ehnert Sabrina , Histing Tina
Published: January 2024

Despite a constant refinement of surgical techniques and bone fixation methods, up to 15% of fractures result in impaired healing or even develop a non-union [...]
Perfusable Tissue Bioprinted into a 3D-Printed Tailored Bioreactor System
Authors: Gensler Marius , Malkmus Christoph , Ockermann Philipp , Möllmann Marc , Hahn Lukas , Salehi Sahar , Luxenhofer Robert , Boccaccini Aldo , Hansmann Jan
Published: January 2024

Bioprinting provides a powerful tool for regenerative medicine, as it allows tissue construction with a patient’s specific geometry. However, tissue culture and maturation, commonly supported by dynamic bioreactors, are needed. We designed a workflow that creates an implant-specific bioreactor system, which is easily producible and customizable and supports cell cultivation and tissue maturation. First, a bioreactor was designed and different tissue geometries were simulated regarding shear stress and nutrient distribution to match cell culture requirements. These tissues were then directly bioprinted into the 3D-printed bioreactor. To prove the ability of cell maintenance, C2C12 cells in two bioinks were printed into the system and successfully cultured for two weeks. Next, human mesenchymal stem cells (hMSCs) were successfully differentiated toward an adipocyte lineage. As the last step of the presented strategy, we developed a prototype of an automated mobile docking station for the bioreactor. Overall, we present an open-source bioreactor system that is adaptable to a wound-specific geometry and allows cell culture and differentiation. This interdisciplinary roadmap is intended to close the gap between the lab and clinic and to integrate novel 3D-printing technologies for regenerative medicine.
Preparation and Characterization of Novel Polyelectrolyte Liposomes Using Chitosan Succinate Layered over Chitosomes: A Potential Strategy for Colon Cancer Treatment
Authors: Yosef Asmaa Mokhtar , Alqarni Raghad Saleh , Sayd Fai Yahya , Alhawiti Manar Saleem , Almahlawi Raghad M. , Prabahar Kousalya , Uthumansha Ubaidulla , Alanazi Mansuor A. , El-Sherbiny Mohamed , Elsherbiny Nehal , Qushawy Mona
Published: January 2024

Chitosan succinate is distinguished by its ability to shield the loaded drug from the acidic environment, localize and keep the drug at the colon site, and release the drug over an extended time at basic pH. The current study attempts to develop polyelectrolyte liposomes (PEL), using chitosan and chitosan succinate (CSSC), as a carrier for liposomal-assisted colon target delivery of 5 fluorouracil (5FU). The central composite design was used to obtain an optimized formulation of 5FU-chitosomes. The chitosan-coated liposomes (chitosomes) were prepared by thin lipid film hydration technique. After that, the optimized formulation was coated with CSSC, which has several carboxylic (COOH) groups that produce an anionic charge that interacts with the cation NH2 in chitosan. The prepared 5FU-chitosomes formulations were evaluated for entrapment efficiency % (EE%), particle size, and in vitro drug release. The optimized 5FU-chitosomes formulation was examined for particle size, zeta potential, in vitro release, and mucoadhesive properties in comparison with the equivalent 5FU-liposomes and 5FU-PEL. The prepared 5FU-chitosomes exhibited high EE%, small particle size, low polydispersity index, and prolonged drug release. PEL significantly limited the drug release at acidic pH due to the deprotonation of carboxylate ions in CSSC, which resulted in strong repulsive forces, significant swelling, and prolonged drug release. According to a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay, PEL treatment significantly decreased the viability of HT-29 cells. When compared to 5FU-liposome and 5FU-chitosome, the in vivo pharmacokinetics characteristics of 5FU-PEL significantly (p < 0.05) improved. The findings show that PEL enhances 5FU permeability, which permits high drug concentrations to enter cells and inhibits the growth of colon cancer cells. Based on the current research, PEL may be used as a liposomal-assisted colon-specific delivery.
Anti-Aging Drugs and the Related Signal Pathways
Authors: Du Nannan , Yang Ruigang , Jiang Shengrong , Niu Zubiao , Zhou Wenzhao , Liu Chenyu , Gao Lihua , Sun Qiang
Published: January 2024

Aging is a multifactorial biological process involving chronic diseases that manifest from the molecular level to the systemic level. From its inception to 31 May 2022, this study searched the PubMed, Web of Science, EBSCO, and Cochrane library databases to identify relevant research from 15,983 articles. Multiple approaches have been employed to combat aging, such as dietary restriction (DR), exercise, exchanging circulating factors, gene therapy, and anti-aging drugs. Among them, anti-aging drugs are advantageous in their ease of adherence and wide prevalence. Despite a shared functional output of aging alleviation, the current anti-aging drugs target different signal pathways that frequently cross-talk with each other. At present, six important signal pathways were identified as being critical in the aging process, including pathways for the mechanistic target of rapamycin (mTOR), AMP-activated protein kinase (AMPK), nutrient signal pathway, silent information regulator factor 2-related enzyme 1 (SIRT1), regulation of telomere length and glycogen synthase kinase-3 (GSK-3), and energy metabolism. These signal pathways could be targeted by many anti-aging drugs, with the corresponding representatives of rapamycin, metformin, acarbose, nicotinamide adenine dinucleotide (NAD+), lithium, and nonsteroidal anti-inflammatory drugs (NSAIDs), respectively. This review summarized these important aging-related signal pathways and their representative targeting drugs in attempts to obtain insights into and promote the development of mechanism-based anti-aging strategies.
Biomimetic Adaptive Pure Pursuit Control for Robot Path Tracking Inspired by Natural Motion Constraints
Authors: Zhao Suna , Zhao Guangxin , He Yan , Diao Zhihua , He Zhendong , Cui Yingxue , Jiang Liying , Shen Yongpeng , Cheng Chao
Published: January 2024

The essence of biomimetics in human–computer interaction (HCI) is the inspiration derived from natural systems to drive innovations in modern-day technologies. With this in mind, this paper introduces a biomimetic adaptive pure pursuit (A-PP) algorithm tailored for the four-wheel differential drive robot (FWDDR). Drawing inspiration from the intricate natural motions subjected to constraints, the FWDDR’s kinematic model mirrors non-holonomic constraints found in biological entities. Recognizing the limitations of traditional pure pursuit (PP) algorithms, which often mimic a static behavioral approach, our proposed A-PP algorithm infuses adaptive techniques observed in nature. Integrated with a quadratic polynomial, this algorithm introduces adaptability in both lateral and longitudinal dimensions. Experimental validations demonstrate that our biomimetically inspired A-PP approach achieves superior path-following accuracy, mirroring the efficiency and fluidity seen in natural organisms.
Numerical Simulation of Crack Propagation and Branching Behaviors in Heterogeneous Rock-like Materials
Authors: Xu Wei , Zhao Shijun , Zhang Weizhao , Zhao Xinbo
Published: January 2024

The characterization and understanding of crack evolution in non-uniform geological structures are crucial for predicting the mechanical response of rock-like materials or structures under varying loading conditions. In this study, an improved Peridynamic model with a degree of heterogeneity characterized by random pre-breaking “bonds” coefficients is introduced to capture the intricacies of crack initiation, propagation, and branching behaviors in heterogeneous rock-like materials. MATLAB discrete programs for heterogeneous material models and PD simulation programs based on the FORTRAN language were developed. The effectiveness of the heterogeneous PD model in simulating crack propagation and branching patterns in heterogeneous materials has been verified through dynamic and static (quasi-static) loading cases with pre-notch. The different levels of heterogeneity not only affect the direction of crack propagation but also determine the crack deflection direction and branching patterns. The crack propagation path appears to possess obvious asymmetry in the crack propagation direction. As the load applied continues to increase, the asymmetric multi-crack branching phenomenon will occur. The higher the level of heterogeneity, the more complex the behaviors of crack propagation and branching become. This research provides valuable insights into the interplay of material heterogeneity and crack evolution, offering a foundation for improved numerical simulations and contributing to the broader field of geomechanics.
Comment on Mahajan, S.; Schmidt, M.H.H. Distinct Lineage of Slow-Cycling Cells Amidst the Prevailing Heterogeneity in Glioblastoma. Cancers 2023, 15, 3843
Authors: Yang Changlin , Mitchell Duane A. , Deleyrolle Loic P.
Published: January 2024

We greatly appreciate the interest, careful reading, and appraisal by Mahajan and Schmidt [...]
Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy for Peritoneal Metastases from Colorectal Cancer—An Overview of Current Status and Future Perspectives
Authors: Graf Wilhelm , Ghanipour Lana , Birgisson Helgi , Cashin Peter H.
Published: January 2024

Peritoneal metastases (PM) are observed in approximately 8% of patients diagnosed with colorectal cancer, either synchronously or metachronously during follow-up. PM often manifests as the sole site of metastasis. PM is associated with a poor prognosis and typically shows resistance to systemic chemotherapy. Consequently, there has been a search for alternative treatment strategies. This review focuses on the global evolution of the combined approach involving cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) for the management of PM. It encompasses accepted clinical guidelines, principles for patient selection, surgical and physiological considerations, biomarkers, pharmacological protocols, and treatment outcomes. Additionally, it integrates the relevant literature and findings from previous studies. The role of CRS and HIPEC, in conjunction with other therapies such as neoadjuvant and adjuvant chemotherapy, is discussed, along with the management of patients presenting with oligometastatic disease. Furthermore, potential avenues for future development in this field are explored.
The 31-Gene Expression Profile Test Outperforms AJCC in Stratifying Risk of Recurrence in Patients with Stage I Cutaneous Melanoma
Authors: Podlipnik Sebastian , Martin Brian J. , Morgan-Linnell Sonia K. , Bailey Christine N. , Siegel Jennifer J. , Petkov Valentina I. , Puig Susana
Published: January 2024

Background: Patients with stage I cutaneous melanoma (CM) are considered at low risk for metastasis or melanoma specific death; however, because the majority of patients are diagnosed with stage I disease, they represent the largest number of melanoma deaths annually. The 31-gene expression profile (31-GEP) test has been prospectively validated to provide prognostic information independent of staging, classifying patients as low (Class 1A), intermediate (Class 1B/2A), or high (Class 2B) risk of poor outcomes. Methods: Patients enrolled in previous studies of the 31-GEP were combined and evaluated for recurrence-free (RFS) and melanoma-specific survival (MSS) (n = 1261, “combined”). A second large, unselected real-world cohort (n = 5651) comprising clinically tested patients diagnosed 2013–2018 who were linked to outcomes data from the NCI Surveillance, Epidemiology, and End Results (SEER) Program registries was evaluated for MSS. Results: Combined cohort Class 1A patients had significantly higher RFS than Class 1B/2A or Class 2B patients (97.3%, 88.6%, 77.3%, p < 0.001)—better risk stratification than AJCC8 stage IA (97.5%) versus IB (89.3%). The SEER cohort showed better MSS stratification by the 31-GEP (Class 1A = 98.0%, Class 1B/2A = 97.5%, Class 2B = 92.3%; p < 0.001) than by AJCC8 staging (stage IA = 97.6%, stage IB = 97.9%; p < 0.001). Conclusions: The 31-GEP test significantly improved patient risk stratification, independent of AJCC8 staging in patients with stage I CM. The 31-GEP provided greater separation between high- (Class 2B) and low-risk (Class 1A) groups than seen between AJCC stage IA and IB. These data support integrating the 31-GEP into clinical decision making for more risk-aligned management plans.
Outcome of High-Dose Chemotherapy Followed by Autologous Stem Cell Transplantation in Relapsed/Refractory Hodgkin Lymphoma after Different Numbers of Salvage Regimens
Authors: Mariotti Jacopo , Ricci Francesca , Giordano Laura , Taurino Daniela , Sarina Barbara , De Philippis Chiara , Mannina Daniele , Carlo-Stella Carmelo , Bramanti Stefania , Santoro Armando
Published: January 2024

The introduction of novel drugs (PD-1 inhibitors and/or brentuximab vedotin) into salvage regimens has improved the response rate and the outcome of patients with relapsed/refractory Hodgkin lymphoma. However, the impact of new drugs on the outcome has not been adequately investigated so far. We retrospectively analyzed 42 consecutive patients treated at our institution with high-dose chemotherapy/autologous stem cell transplantation after either one standard chemotherapy represented by BEGEV (n = 28) or >1 salvage therapy (ST) comprising novel drugs (n = 14). With a median follow-up of 24 months, the 2-year cumulative incidence of relapse was similar between the two cohorts: 26% for 1 ST and 18% for >1 ST (p = 0.822). Consistently, overall survival and progression-free survival did not differ among the two groups: 3-year overall survival was 91% and 89% (p = 0.731), respectively, and 3-year progression-free survival was 74% and 83% (p = 0.822) for only one and more than one salvage regimens, respectively. Of note, the post-transplant side effects and engraftment rates were similar between the 1 ST and >1 ST cohorts. In conclusion, consolidation with high-dose chemotherapy/autologous stem cell transplantation is a safe and curative option, even for patients achieving disease response after more than one rescue line of therapy.
Thermo-Mechanical Stress Distributions in a Ceramic Matrix Composites Turbine Vane Coated with Environmental Barrier Coatings
Authors: Chen Mingzhu , Fang Guangwu , Gao Xiguang , Song Yingdong
Published: January 2024

It is of great significance to obtain an accurate stress assessment when replacing traditional metal components with ceramic matrix composites (CMCs) in turbine engines. The current study aims to investigate the stress characteristics of CMCs turbine vanes with multilayer-structured environmental barrier coatings (EBCs) using numerical simulation techniques. A three-dimensional finite element model of CMCs turbine vanes coated with EBCs was formulated. The distribution of thermal residual stresses generated during the manufacturing process of EBCs and the distribution of stresses under different loading conditions were calculated and compared. The results show that the hoop stress (σ11) and spanwise stress (σ22) in the turbine vanes are significantly higher than the through-thickness stress (σ33) under coupled loads. The maximum hoop stress (σ11) is approximately 346 MPa. The thermal residual stress induced during the EBCs manufacturing process reaches a maximum of approximately 360 MPa. The loading conditions significantly influence the stress distribution of EBCs, and the stress distribution of EBCs exhibits certain regularities at different heights under varying loading conditions. These results enable us to gain a deeper understanding of the failure mechanism of CMCs/EBCs turbine vanes and can improve the optimization capabilities for these components.
The Properties of Ultra-High-Performance Concrete with Assembly Unit of Secondary Aluminum Dross and Waste Fly Ash
Authors: Sun Houchao , Shi Feiting , Wang Hui
Published: January 2024

Waste fly ash (WFA) and secondary aluminum dross (SAD) are common solid wastes inducing environmental pollution. These materials contain certain active substances that can be used in cement-based materials. Therefore, cement concrete can be used to solidify these solid wastes. In this study, the influence of the assembly unit of secondary aluminum dross (SAD) and waste fly ash (WFA) on the properties of ultra-high-performance concrete (UHPC) is investigated. The slump flow, the plastic viscosity, the yield shear stress, and the initial setting time of fresh UHPC are measured. Moreover, the flexural and compressive strengths and the dry shrinkage rate (DSR) are determined. The electrical resistance and reactance are tested. The electron microscopy spectroscopy (EDS), thermogravimetric analysis (TG), and X-ray diffraction spectrum (XRD) curves are obtained for revealing the mechanism of macroscopic performances. Results show that due to the optimal specific surface area and the volcanic ash effect, the UHPC with the assembly unit of 50% SAD and 50% WFA provides the highest slump flow, DSR, and mechanical strengths, while the corresponding plastic viscosity, yield shear stress, and electrical resistance are the lowest. The SAD can delay the setting time of UHPC. The relationship between the electrical resistance or the electrical reactance and the mass ratio of SAD accords with the quadratic function. The corresponding electrical resistance is the lowest. The relationship between the mechanical strengths and the electrical resistance fits with the cubic function. The leaching amounts of Zn and Cr increase in the form of cubic function with the immersing time. Meanwhile, the SAD can decrease the Zn and Cr by 0%–46.3% and 0%–45.2% respectively. As obtained from the EDS results, the element of Al is increased by adding SAD. The XRD curves show that the crystals of Al2O3 are increased and the SiO2 crystals are decreased by the added SAD. UHPC with 50% SAD exhibits the highest compact microstructures and the least Ca(OH)2 and 3CaO·SiO2 hydration products. The TG results show that UHPC with 50% SAD shows the lowest TG values of all the groups. This research will provide new UHPC materials and techniques applied in solidifying the WFA and SAD in the future.
Solution-Processed Monolithic Tandem Perovskite/n-Si Hybrid Solar Cells Using MoO3/InZnO Bilayer-Based Interconnecting and Window Layers
Authors: Ukai Ryuichi , Wasai Yoko , Izumi Yuki , Shirai Hajime
Published: January 2024

A metal oxide-based interconnecting and window layer consisting of a molybdenum oxide (MoO3)/Zn-doped In2O3 (IZO) bilayer was investigated in efficient solution-processed perovskite/n-Si monolithic tandem solar cells using formamidinium cesium lead triiodide, FA0.9Cs0.1PbI3, and poly(3,4-ethylenedioxythiophene)/poly(polystyrene sulfonate) (PEDOT:PSS). The MoO3/IZO bilayer with and without Au nanoparticle play a significant role in the charge extraction and recombination within the interconnecting layer and the window layer of the top cell, respectively. A power conversion efficiency of 18–19% was achieved with a short-circuit current, Jsc, of 17.8 mA/cm2; an open-circuit voltage, Voc, of 1.48 V; and an FF of 0.74 by adjusting the layer thicknesses of MoO3 (5 nm), Au nanoparticle layer (5 nm), and sputtered IZO (42 nm for ICL and 80 nm for window layer).
Transistor-Based Synaptic Devices for Neuromorphic Computing
Authors: Huang Wen , Zhang Huixing , Lin Zhengjian , Hang Pengjie , Li Xing’ao
Published: January 2024

Currently, neuromorphic computing is regarded as the most efficient way to solve the von Neumann bottleneck. Transistor-based devices have been considered suitable for emulating synaptic functions in neuromorphic computing due to their synergistic control capabilities on synaptic weight changes. Various low-dimensional inorganic materials such as silicon nanomembranes, carbon nanotubes, nanoscale metal oxides, and two-dimensional materials are employed to fabricate transistor-based synaptic devices. Although these transistor-based synaptic devices have progressed in terms of mimicking synaptic functions, their application in neuromorphic computing is still in its early stage. In this review, transistor-based synaptic devices are analyzed by categorizing them into different working mechanisms, and the device fabrication processes and synaptic properties are discussed. Future efforts that could be beneficial to the development of transistor-based synaptic devices in neuromorphic computing are proposed.
Validation of Diagnostic Accuracy and Disease Severity Correlation of Chest Computed Tomography Severity Scores in Patients with COVID-19 Pneumonia
Authors: Brumini Ivan , Dodig Doris , Žuža Iva , Višković Klaudija , Mehmedović Armin , Bartolović Nina , Šušak Helena , Cekinović Grbeša Đurđica , Miletić Damir
Published: January 2024

The aim of our study was to establish and compare the diagnostic accuracy and clinical applicability of published chest CT severity scoring systems used for COVID-19 pneumonia assessment and to propose the most efficient CT scoring system with the highest diagnostic performance and the most accurate prediction of disease severity. This retrospective study included 218 patients with PCR-confirmed SARS-CoV-2 infection and chest CT. Two radiologists blindly evaluated CT scans and calculated nine different CT severity scores (CT SSs). The diagnostic validity of CT SSs was tested by ROC analysis. Interobserver agreement was excellent (intraclass correlation coefficient: 0.982–0.995). The predominance of either consolidations or a combination of consolidations and ground-glass opacities (GGOs) was a predictor of more severe disease (both p < 0.005), while GGO prevalence alone was not. Correlation between all CT SSs was high, ranging from 0.848 to 0.971. CT SS 30 had the highest diagnostic accuracy (AUC = 0.805) in discriminating mild from severe COVID-19 disease compared to all the other proposed scoring systems (AUC range 0.755–0.788). In conclusion, CT SS 30 achieved the highest diagnostic accuracy in predicting the severity of COVID-19 disease while maintaining simplicity, reproducibility, and applicability in complex clinical settings.
Dual-Layer Spectral Detector Computed Tomography Quantitative Parameters: A Potential Tool for Lymph Node Activity Determination in Lymphoma Patients
Authors: Chen Hebing , Fang Yuxiang , Gu Jin , Sun Peng , Yang Lian , Pan Feng , Wu Hongying , Ye Tianhe
Published: January 2024

Dual-energy CT has shown promising results in determining tumor characteristics and treatment effectiveness through spectral data by assessing normalized iodine concentration (nIC), normalized effective atomic number (nZeff), normalized electron density (nED), and extracellular volume (ECV). This study explores the value of quantitative parameters in contrast-enhanced dual-layer spectral detector CT (SDCT) as a potential tool for detecting lymph node activity in lymphoma patients. A retrospective analysis of 55 lymphoma patients with 289 lymph nodes, assessed through 18FDG-PET/CT and the Deauville five-point scale, revealed significantly higher values of nIC, nZeff, nED, and ECV in active lymph nodes compared to inactive ones (p < 0.001). Generalized linear mixed models showed statistically significant fixed-effect parameters for nIC, nZeff, and ECV (p < 0.05). The area under the receiver operating characteristic curve (AUROC) values of nIC, nZeff, and ECV reached 0.822, 0.845, and 0.811 for diagnosing lymph node activity. In conclusion, the use of g nIC, nZeff, and ECV as alternative imaging biomarkers to PET/CT for identifying lymph node activity in lymphoma holds potential as a reliable diagnostic tool that can guide treatment decisions.
Scalable and Multi-Channel Real-Time Low Cost Monitoring System for PEM Electrolyzers Based on IoT Applications
Authors: Paredes-Baños Ana Belén , Molina-Garcia Angel , Mateo-Aroca Antonio , López-Cascales José Javier
Published: January 2024

This paper discusses and evaluates a novel multi-channel real-time architecture aimed at monitoring a Proton Exchange Membrane (PEM) electrolyzer, both at the individual cell and stack levels. The proposed solution includes two primary subsystems: a hardware subsystem dedicated to data acquisition (DAQ) and a software subsystem focused on monitoring purposes. The DAQ subsystem utilizes an Arduino platform, being an affordable and open-source solution. The real-time monitoring data can be encoded in JSON format, widely used as a light-weight inter-exchange data format between a variety of IoT applications. They are also available to be transferred to Excel. Indeed, and to enhance convenience, the proposed system integrates graphs displaying a template based on Excel spreadsheets, which are commonly used in industrial environments. The current, voltage, temperature, and pressure data of both individual cells and stacks were monitored and collected, being configurable under a variety of ranges. As a case study, the validation of the system involved static and dynamic operational modes using a 1.2 kW PEM electrolyzer prototype (100 A, 1 A/cm2). The results successfully provided the monitored variables across individual cells and within the stack. The proposed approach exhibits relevant key characteristics such as scalability, flexibility, user-friendliness, versatility, and affordability and are suitable to monitor PEM electrolyzers in real-time at both the cell and stack levels.
Image–Text Cross-Modal Retrieval with Instance Contrastive Embedding
Authors: Zeng Ruigeng , Ma Wentao , Wu Xiaoqian , Liu Wei , Liu Jie
Published: January 2024

Image–text cross-modal retrieval aims to bridge the semantic gap between different modalities, allowing for the search of images based on textual descriptions or vice versa. Existing efforts in this field concentrate on coarse-grained feature representation and then utilize pairwise ranking loss to pull image–text positive pairs closer, pushing negative ones apart. However, using pairwise ranking loss directly on coarse-grained representation lacks reliability as it disregards fine-grained information, posing a challenge in narrowing the semantic gap between image and text. To this end, we propose an Instance Contrastive Embedding (IConE) method for image–text cross-modal retrieval. Specifically, we first transfer the multi-modal pre-training model to the cross-modal retrieval task to leverage the interactive information between image and text, thereby enhancing the model’s representational capabilities. Then, to comprehensively consider the feature distribution of intra- and inter-modality, we design a novel two-stage training strategy that combines instance loss and contrastive loss, dedicated to extracting fine-grained representation within instances and bridging the semantic gap between modalities. Extensive experiments on two public benchmark datasets, Flickr30k and MS-COCO, demonstrate that our IConE outperforms several state-of-the-art (SoTA) baseline methods and achieves competitive performance.
Improved Tree Segmentation Algorithm Based on Backpack-LiDAR Point Cloud
Authors: Zhu Dongwei , Liu Xianglong , Zheng Yili , Xu Liheng , Huang Qingqing
Published: January 2024

For extracting tree structural data from LiDAR point clouds, individual tree segmentation is of great significance. Most individual tree segmentation algorithms miss segmentation and misrecognition, requiring manual post-processing. This study utilized a hierarchical approach known as segmentation based on hierarchical strategy (SHS) to improve individual tree segmentation. The tree point cloud was divided into the trunk layer and the canopy layer to carry out trunk detection and canopy segmentation, respectively. The effectiveness of SHS was evaluated on three mixed broadleaf forest plots. The segmentation efficacy of SHS was evaluated on three mixed broadleaf forest plots and compared with the point cloud segmentation algorithm (PCS) and the comparative shortest-path algorithm (CSP). In the three plots, SHS correctly identified all the trunk portion, had a recall (r) of 1, 0.98, and 1, a precision (p) of 1, and an overall segmentation rate (F) of 1, 0.99, and 1. CSP and PCS are less accurate than SHS. In terms of overall plots, SHS had 10%–15% higher F-scores than PCS and CSP. SHS extracted crown diameters with R2s of 0.91, 0.93, and 0.89 and RMSEs of 0.24 m, 0.23 m, and 0.30 m, outperforming CSP and PCS. Afterwards, we evaluate the three algorithms’ findings, examine the SHS algorithm’s parameters and constraints, and discuss the future directions of this research. This work offers an enhanced SHS that improves upon earlier research, addressing missed segmentation and misrecognition issues. It improves segmentation accuracy, individual tree segmentation, and provides both theoretical and data support for the LiDAR application in forest detection.