bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine learning algorithms in microbial classification: a comparative analysis
Authors: Wu Yuandi , Gadsden S. Andrew
Published: October 2023

This research paper presents an overview of contemporary machine learning methodologies and their utilization in the domain of healthcare and the prevention of infectious diseases, specifically focusing on the classification and identification of bacterial species. As deep learning techniques have gained prominence in the healthcare sector, a diverse array of architectural models has emerged. Through a comprehensive review of pertinent literature, multiple studies employing machine learning algorithms in the context of microbial diagnosis and classification are examined. Each investigation entails a tabulated presentation of data, encompassing details about the training and validation datasets, specifications of the machine learning and deep learning techniques employed, as well as the evaluation metrics utilized to gauge algorithmic performance. Notably, Convolutional Neural Networks have been the predominant selection for image classification tasks by machine learning practitioners over the last decade. This preference stems from their ability to autonomously extract pertinent and distinguishing features with minimal human intervention. A range of CNN architectures have been developed and effectively applied in the realm of image classification. However, addressing the considerable data requirements of deep learning, recent advancements encompass the application of pre-trained models using transfer learning for the identification of microbial entities. This method involves repurposing the knowledge gleaned from solving alternate image classification challenges to accurately classify microbial images. Consequently, the necessity for extensive and varied training data is significantly mitigated. This study undertakes a comparative assessment of various popular pre-trained CNN architectures for the classification of bacteria. The dataset employed is composed of approximately 660 images, representing 33 bacterial species. To enhance dataset diversity, data augmentation is implemented, followed by evaluation on multiple models including AlexNet, VGGNet, Inception networks, Residual Networks, and Densely Connected Convolutional Networks. The results indicate that the DenseNet-121 architecture yields the optimal performance, achieving a peak accuracy of 99.08%, precision of 99.06%, recall of 99.00%, and an F1-score of 98.99%. By demonstrating the proficiency of the DenseNet-121 model on a comparatively modest dataset, this study underscores the viability of transfer learning in the healthcare sector for precise and efficient microbial identification. These findings contribute to the ongoing endeavors aimed at harnessing machine learning techniques to enhance healthcare methodologies and bolster infectious disease prevention practices.
Recruitment of older adult-caregiver dyads during the COVID-19 pandemic: an example from a study to evaluate a novel activities of daily living (ADL) sensor system
Authors: Williams Rachel , Fitch John , Lary Elaine , Fitch Sarah , SoRelle Melissa , Green Aval-Na'Ree
Published: October 2023

Under ideal circumstances, recruitment of older adult-caregiver dyads to dementia research is challenging. The COVID-19 pandemic introduced additional barriers to recruitment, necessitating swift adjustments to pre-pandemic recruitment strategies and schedules. This brief research report describes the challenges, yield, and cost of recruiting older adult-caregiver dyads to an 18-month observational research study during COVID-19. The study aimed to evaluate the effectiveness of a novel in-home sensor system at identifying cognitive change in older adults with Alzheimer's disease and related dementias (ADRD) through background monitoring of activities of daily living (ADL). Recruitment methods included flyers distributed alongside home-delivered meals, direct mailings, publicly available brochures, community presentations, periodical advertisements, and various other strategies. Of 510 inquiries, 117 older adult-caregiver dyads were enrolled at a total cost of ~$368,000, yielding an average per dyad recruiting cost of $3,148. Distributing flyers alongside home-delivered meals produced the most dyads (n = 46, 39%) and the least non-labor costs ($24.33) per enrolled dyad. Recruitment during the pandemic exceeded the pre-COVID-19 budget, but enrollment goals were nevertheless achieved through community-based methods. Our experience illustrates the challenge of recruiting older adult-caregiver dyads to dementia research and the value of trusted community partners in recruiting this population. Our strategies and recommendations may benefit researchers who plan to recruit community-based older adults and their caregivers for future dementia research.
Virulent Newcastle disease virus genotypes V.3, VII.2, and XIII.1.1 and their coinfections with infectious bronchitis viruses and other avian pathogens in backyard chickens in Tanzania
Authors: Kariithi Henry M. , Volkening Jeremy D. , Chiwanga Gaspar H. , Goraichuk Iryna V. , Olivier Tim L. , Msoffe Peter L. M. , Suarez David L.
Published: October 2023

Oropharyngeal (OP) and cloacal (CL) swabs from 2049 adult backyard chickens collected at 12 live bird markets, two each in Arusha, Dar es Salaam, Iringa, Mbeya, Morogoro and Tanga regions of Tanzania were screened for Newcastle disease virus (NDV) using reverse transcription real-time PCR (rRT-PCR). The virus was confirmed in 25.23% of the birds (n = 517; rRT-PCR CT ≤ 30), with the highest positivity rates observed in birds from Dar es Salaam region with higher prevalence during the dry season (September–November 2018) compared to the rainy season (January and April–May 2019). Next-generation sequencing of OP/CL samples of 20 out of 32 birds that had high amounts of viral RNAs (CT ≤ 25) resulted in the assembly of 18 complete and two partial genome sequences (15,192 bp and 15,045–15,190 bp in length, respectively) of NDV sub-genotypes V.3, VII.2 and XIII.1.1 (n = 1, 13 and 4 strains, respectively). Two birds had mixed NDV infections (V.3/VII.2 and VII.2/XIII.1.1), and nine were coinfected with viruses of families Astroviridae, Coronaviridae, Orthomyxoviridae, Picornaviridae, Pneumoviridae, and Reoviridae. Of the coinfecting viruses, complete genome sequences of two avastroviruses (a recombinant chicken astrovirus antigenic group-Aii and avian nephritis virus genogroup-5) and two infectious bronchitis viruses (a turkey coronavirus-like recombinant and a GI-19 virus) were determined. The fusion (F) protein F1/F2 cleavage sites of the Tanzanian NDVs have the consensus motifs 112 RRRKR↓F 117 (VII.2 strains) and 112 RRQKR↓F 117 (V.3 and XIII.1.1 strains) consistent with virulent virus; virulence was confirmed by intracerebral pathogenicity index scores of 1.66–1.88 in 1-day-old chicks using nine of the 20 isolates. Phylogenetically, the complete F-gene and full genome sequences regionally cluster the Tanzanian NDVs with, but distinctly from, other strains previously reported in eastern and southern African countries. These data contribute to the understanding of NDV epidemiology in Tanzania and the region.
Recent advances and future directions in etiopathogenesis and mechanisms of reactive oxygen species in cancer treatment
Authors: Verma Priyanka , Rishi Bhavika , George Noreen Grace , Kushwaha Neetu , Dhandha Himanshu , Kaur Manpreet , Jain Ankur , Jain Aditi , Chaudhry Sumita , Singh Amitabh , Siraj Fouzia , Misra Aroonima
Published: October 2023

A class of exceptionally bioactive molecules known as reactive oxygen species (ROS) have been widely studied in the context of cancer. They play a significant role in the etiopathogenesis for cancer. Implication of ROS in cancer biology is an evolving area, considering the recent advances; insights into their generation, role of genomic and epigenetic regulators for ROS, earlier thought to be a chemical process, with interrelations with cell death pathways- Apoptosis, ferroptosis, necroptosis and autophagy has been explored for newer targets that shift the balance of ROS towards cancer cell death. ROS are signal transducers that induce angiogenesis, invasion, cell migration, and proliferation at low to moderate concentrations and are considered normal by-products of a range of biological activities. Although ROS is known to exist in the oncology domain since time immemorial, its excessive quantities are known to damage organelles, membranes, lipids, proteins, and nucleic acids, resulting in cell death. In the last two decades, numerous studies have demonstrated immunotherapies and other anticancer treatments that modulate ROS levels have promising in vitro and in vivo effects. This review also explores recent targets for therapeutic interventions in cancer that are based on ROS generation or inhibition to disrupt the cell oxidative stress balance. Examples include-metabolic targets, targeted therapy with biomarkers, natural extracts and nutraceuticals and targets developed in the area of nano medicine. In this review, we present the molecular pathways which can be used to create therapy plans that target cancer by regulating ROS levels, particularly current developments and potential prospects for the effective implementation of ROS-mediated therapies in clinical settings. The recent advances in complex interaction with apoptosis especially ferroptosis and its role in epigenomics and modifications are a new paradigm, to just mechanical action of ROS, as highlighted in this review. Their inhibition by nutraceuticals and natural extracts has been a scientific challenging avenue that is explored. Also, the inhibition of generation of ROS by inhibitors, immune modulators and inhibitors of apoptosis and ferroptosis is explored in this review.
A Methodology for Assessing Capacity of the Terminal Maneuvering Area Based on Service Resource Equilibrium
Authors: Mou Qifeng , Yang Ze , Zhang Liming
Published: October 2023

To effectively estimate and optimize the airport terminal maneuvering area throughput based on the equilibrium of air traffic service resource supply and demand, this research proposes an approach to assess terminal maneuvering area capacity from the perspective of air traffic service resource availability. Terminal maneuvering area capacity is optimized based on the equilibrium of air traffic service resource supply and demand. The supply–demand nexus is examined in consideration of terminal maneuvering area route structure, traffic flow characteristics, and safety regulations. A flight service probability matrix and a terminal maneuvering area demand and supply service time model are constructed to quantify resource expenditure at varied capacity levels. An optimization model is then developed to allocate the airport resources effectively, fully utilizing the capacity to provide maximal outputs under resource limitations. Model computation and simulation results demonstrate the deviation between estimated and amended capacities is under 0.3 flight sorties per hour. The outcomes are congruent with historical statistics, thereby validating the accuracy and reliability of the model proposed in this study. Given capacity parameters, the model can deduce the maximal aircraft quantity served concurrently in terminal maneuvering areas during peak periods. These revelations indicate that the submitted model furnishes theoretical foundation and reference for terminal maneuvering area sector partition and traffic alerting.
Evaluation of the Accuracy of the Remote Determination of the Brewster Angle When Measuring Physicochemical Parameters of Soil
Authors: Linets Gennadiy Ivanovich , Bazhenov Anatoliy Vyacheslavovich , Malygin Sergey Vladimirovich , Grivennaya Natalia Vladimirovna , Melnikov Sergey Vladimirovich , Goncharov Vladislav Dmitrievich
Published: October 2023

In precision farming technology, the moisture of the soil, its granulometric composition, specific conductivity and a number of other physical and chemical parameters are determined using remote radar sensing. The most important parameters are those measured in the area of the plant root system located well below the “air-surface” boundary. In order to create conditions for the penetration of electromagnetic waves through the “air-surface” interface with a minimum reflection coefficient, the irradiation of the Earth’s surface is carried out obliquely with an angle of incidence close to the Brewster angle. The reflection coefficient, and, consequently, the Brewster angle, depend on the complex dielectric permittivity of the surface soil layer and are not known a priori. To determine the Brewster angle, the usual method is to search for the minimum amplitude of the vertically polarized signal reflected from the surface. Another approach is when the first derivative of the dependence of the modulus of the complex amplitude of a vertically polarized interference wave, taken with respect to the angle of incidence, is set equal to zero. In turn, in real dielectrics such as agricultural soils, the amplitude of the vertically polarized signal reflected from the surface is directly proportional to the reflection coefficient and does not have a pronounced minimum, which reduces the accuracy of the measurements. Based on the solution of the Helmholtz wave equation for a three-layered structure of the propagation medium (air, upper fertile soil layer, soil layer below the groundwater level), a model of the process of forming an interference wave under oblique irradiation of a planar layered dielectric with losses has been developed. Using the developed model, factors influencing the accuracy of determining the Brewster angle have been identified. For the first time, it is proposed to use the phase shift between the oscillations of the interference waves with vertical and horizontal polarization to measure the Brewster angle. A comparative assessment of the accuracy of determining the Brewster angle using known amplitude methods and the proposed phase method has been carried out. The adequacy of the method was experimentally confirmed. Recommendations have been developed for the practical application of the phase method of finding the Brewster angle for assessing the dielectric permittivity of soil and its moisture content.
Deep Learning Performance Characterization on GPUs for Various Quantization Frameworks
Authors: Shafique Muhammad Ali , Munir Arslan , Kong Joonho
Published: October 2023

Deep learning is employed in many applications, such as computer vision, natural language processing, robotics, and recommender systems. Large and complex neural networks lead to high accuracy; however, they adversely affect many aspects of deep learning performance, such as training time, latency, throughput, energy consumption, and memory usage in the training and inference stages. To solve these challenges, various optimization techniques and frameworks have been developed for the efficient performance of deep learning models in the training and inference stages. Although optimization techniques such as quantization have been studied thoroughly in the past, less work has been done to study the performance of frameworks that provide quantization techniques. In this paper, we have used different performance metrics to study the performance of various quantization frameworks, including TensorFlow automatic mixed precision and TensorRT. These performance metrics include training time and memory utilization in the training stage along with latency and throughput for graphics processing units (GPUs) in the inference stage. We have applied the automatic mixed precision (AMP) technique during the training stage using the TensorFlow framework, while for inference we have utilized the TensorRT framework for the post-training quantization technique using the TensorFlow TensorRT (TF-TRT) application programming interface (API).We performed model profiling for different deep learning models, datasets, image sizes, and batch sizes for both the training and inference stages, the results of which can help developers and researchers to devise and deploy efficient deep learning models for GPUs.
A Preliminary Report on the Combined Effect of Intra-Articular Platelet-Rich Plasma Injections and Photobiomodulation in Canine Osteoarthritis
Authors: Alves J. C. , Santos Ana , Carreira L. Miguel
Published: October 2023

Osteoarthritis (OA) is highly prevalent in the canine population. Due to the multiple dimensions of the disease, a multimodal approach is usually favored by clinicians. To evaluate the combined treatment with intra-articular platelet-rich plasma (PRP) and photobiomodulation in dogs with bilateral hip OA, thirty dogs were assigned to a PRP group (PRPG, n = 10), a photobiomodulation group (PBMTG, n = 10), or a combined therapies group (PRP+PBMTG, n = 10). The PRPG received two intra-articular administrations of platelet-rich plasma 14 days apart. The PBMTG received photobiomodulation with a therapeutic laser, with three sessions every other day in week one; two sessions in week two; a single session in week three; and one session/month on follow-up evaluation days. The PRP+PBMTG received the two combined therapies. The response to treatment was evaluated with weight-bearing distribution and the Canine Brief Pain Inventory, the Liverpool Osteoarthritis in Dogs, and the Canine Orthopedic Index. Evaluations were conducted before treatment and +8, +15, +30, +60, and +90 days after initial treatment. Normality was assessed with a Shapiro–Wilk test, and the groups’ results in each evaluation moment were compared using a Mann–Whitney U test. Animals of both sexes (male n = 19, female n = 11) were included in the sample, with a mean age of 7.8 ± 2.5 years and a body weight of 26.5 ± 4.7 kg. Joints were classified as mild (n = 6, three in PRPG, two in PBMTG, and one in PRP+PBMTG), moderate (n = 18, six in PRPG, five in PBMTG, and seven in PRP+PBMTG), and severe (n = 6, one in PRPG, three in PBMTG, and two in PRP+PBMTG). No differences were found between groups at the initial evaluation. All treatments produced clinically significant improvements compared to the assessment on treatment day. The combination of PRP and photobiomodulation produced greater, longer-lasting improvements. PRP and photobiomodulation can improve objective outcomes and client-reported outcome measures in dogs with OA. Their combined use leads to greater, longer-lasting, clinically significant improvements.
Modeling for Smart Vaccination against Peste des Petits Ruminants (PPR) in the Emirate of Abu Dhabi, United Arab Emirates
Authors: Eltahir Yassir M. , Aburizq Wael , Bensalah Oum Keltoum , Mohamed Meera S. , Al Shamisi Aysha , AbdElkader Ayman I. , Al-Majali Ahmad
Published: October 2023

Peste des petits ruminants (PPR) is a contagious and economically important transboundary viral disease of small ruminants. The United Arab Emirates (UAE) national animal health plan aimed to control and eradicate PPR from the country by following the global PPR control and eradication strategy which adopts small ruminants’ mass vaccination to eradicate the disease from the globe by 2030. A smart vaccination approach, which is less expensive and has longer-term sustainable benefits, is needed to accelerate the eradication of PPR. In this study, a mathematical algorithm was developed based on animals’ identification and registration data, belonging to the Abu Dhabi Agriculture and Food Safety Authority (ADAFSA), and other different parameters related to PPR risk occurrence. The latter included animal holding vaccination history, the number of animals per holding, forecasting of the number of animals and newborns per holding, the proximity of an animal holding to a PPR outbreak and the historical animal holding owner vaccination rejection attitude. The developed algorithm successfully prioritized animal holdings at risk of PPR infection within Abu Dhabi Emirate to be targeted by vaccination. This in turn facilitated the mobilization of field vaccination teams to target specific sheep and goat holdings to ensure the generation of immunity against the disease on a risk-based approach. The vaccination coverage of the targeted livestock population was increased to 86% and the vaccination rejection attitude was reduced by 35%. The duration of the vaccination campaign was reduced to 30 compared to 70 working days and hence can alleviate the depletion of human and logistic resources commonly used in classical mass vaccination campaigns. The results obtained from implementing the algorithm-based PPR vaccination campaign will reduce the negative impact of PPR on the UAE livestock sector and accelerate the achievement of the national PPR eradication plan requirements.
Dietary Supplementation with Pithecellobium dulce (Roxb) Benth Fruits to Fattening Rabbits
Authors: Apáez-Barrios Jairo , Ocampo-López Juan , Soto-Simental Sergio , Aguilar-Raymundo Victoria Guadalupe , Ayala-Martínez Maricela
Published: October 2023

Pithecellobium dulce produces a fruit used in alternative medicine that could be utilized to feed rabbits. The objective of this study was to measure the effect of the P. dulce fruit on productive performance, carcass traits, meat characteristics, and meat product quality as well as shelf-life. Seventy-two California × English pot crossbreed rabbits (35 d age) were randomly distributed into two treatments: a control group without P. dulce and another group fed with 5% of P. dulce, and fattening for 28 d. Productive performance parameters, blood biochemistry and hematology, apparent digestibility, carcass traits, meat characteristics, and meat product shelf-life were measured. The results indicate inclusion of 5% P. dulce improves (p < 0.05) dry and organic matter digestibility and feed conversion rate, but some serum blood enzymes were increased (p < 0.05). The a* value, hardness, and pH decreased (p < 0.05) in the group fed with P. dulce. Antioxidant properties in the meatballs were different (p < 0.05), improving shelf-life and acceptance in sensory analysis. In conclusion, the use of 0.5% of P. dulce fruits to feed fattening rabbits can be used to improve the shelf-life of rabbit meat.
The Food-Crushing Reflex and Its Inhibition
Authors: Vaahtoniemi Lauri H.
Published: October 2023

Anterior tooth (ANT) contacts induce a short-latency reflex inhibition of the human jaw-closing muscles. The jaw is a rigid class 1 lever for pinpoint targeting muscle force into a single bite point, the pivoting food particle. Seesaw reflex movements around the food particle fulcrum multiply the food-crushing force. Unpredictable jolts of reaction force caused by food crushing are subjected to the rostral ANT and caudally to the two articulate ends of the jaw triangle. The compression/distraction strains of food crushing must be monitored and inhibited by withdrawal reflexes. The mesencephalic ganglion (Vmes), neural myelin sheath, and muscle stretch receptors evolved subsequently to the advent of jaws to improve the velocity of proprioceptive and withdrawal reflexes. In mammalians, the spindles of the taut motor units, stretched by the food fulcrum, send excitatory monosynaptic feedback for the efferent neurons of the respective ipsilateral muscle units via the Vmes. In the Vmes, the spindle-input-mediating afferent neurons are coupled with another source of afferent feedback, which is also excitatory, from the back tooth (BAT) mechanoreceptors. The two sources of excitatory pulses are summated and targeted for the efferent neurons to boost the stretched and taut motor units. Likewise, the afferent feedback from the ANT mechanoreceptors is also coupled in the Vmes with concomitant feedback from spindles. The ANT output, however, is inhibitory to negate the excitatory feedback from the stretched jaw muscle units. The inhibitory feed from the anterior teeth temporarily blocks the excitatory potential of the masticatory motor efferent neurons to protect the anterior teeth and jaw joints from inadvertent strains. The inhibitory inputs from the anterior teeth alternate with the excitatory inputs from the BAT to determine which jaw-closing muscle units are activated or inhibited at any given instant of food crushing. The Vmes exists in all jawed vertebrates, and its evolution was probably motivated by demands for the control of bite force. The monosynaptic unilateral food-crushing excitatory and inhibitory reflexes (UFCRs) override the coexisting bilaterally executed feed for the jaw muscles from the central nervous system. The hypothesis proposed in this study is that the Vmes-mediated UFCRs combine neural inputs from tooth contacts with concomitant feedback from the muscle stretch receptors for the control of the mammalian food-crushing bite force.
Influence of the Crusher Settings and a Thermal Pre-Treatment on the Properties of the Fine Fraction (Black Mass) from Mechanical Lithium-Ion Battery Recycling
Authors: Wilke Christian , Werner Denis Manuel , Kaas Alexandra , Peuker Urs Alexander
Published: October 2023

With the increasing number of electric vehicles (EVs) rises the need to recycle their used lithium-ion batteries (LIBs). During the mechanical process of the recycling of the LIB cells, a fine fraction, the so-called black mass, is created. This black mass consists mostly of the coatings originating from the cells’ electrodes and residues from the electrolyte, together with a low amount of Al and Cu from the crushed current collector foils. The amount of black mass as well as its composition is influenced by the chosen grid size at the crusher discharge. To reduce solvent emissions during the recycling process, a thermal pre-treatment can be added before crushing, which also influences the black mass and its properties due to changes in the adhesion between electrode foils and coating. This study investigates the influence of the crusher settings as well as the pre-treatment temperatures to find an optimum between the recovery of the coating and conductive salt, while limiting the amount of Al and Cu in the black mass.
Rapid Segmentation and Diagnosis of Breast Tumor Ultrasound Images at the Sonographer Level Using Deep Learning
Authors: Yang Lei , Zhang Baichuan , Ren Fei , Gu Jianwen , Gao Jiao , Wu Jihua , Li Dan , Jia Huaping , Li Guangling , Zong Jing , Zhang Jing , Yang Xiaoman , Zhang Xueyuan , Du Baolin , Wang Xiaowen , Li Na
Published: October 2023

Background: Breast cancer is one of the most common malignant tumors in women. A noninvasive ultrasound examination can identify mammary-gland-related diseases and is well tolerated by dense breast, making it a preferred method for breast cancer screening and of significant clinical value. However, the diagnosis of breast nodules or masses via ultrasound is performed by a doctor in real time, which is time-consuming and subjective. Junior doctors are prone to missed diagnoses, especially in remote areas or grass-roots hospitals, due to limited medical resources and other factors, which bring great risks to a patient’s health. Therefore, there is an urgent need to develop fast and accurate ultrasound image analysis algorithms to assist diagnoses. Methods: We propose a breast ultrasound image-based assisted-diagnosis method based on convolutional neural networks, which can effectively improve the diagnostic speed and the early screening rate of breast cancer. Our method consists of two stages: tumor recognition and tumor classification. (1) Attention-based semantic segmentation is used to identify the location and size of the tumor; (2) the identified nodules are cropped to construct a training dataset. Then, a convolutional neural network for the diagnosis of benign and malignant breast nodules is trained on this dataset. We collected 2057 images from 1131 patients as the training and validation dataset, and 100 images of the patients with accurate pathological criteria were used as the test dataset. Results: The experimental results based on this dataset show that the MIoU of tumor location recognition is 0.89 and the average accuracy of benign and malignant diagnoses is 97%. The diagnosis performance of the developed diagnostic system is basically consistent with that of senior doctors and is superior to that of junior doctors. In addition, we can provide the doctor with a preliminary diagnosis so that it can be diagnosed quickly. Conclusion: Our proposed method can effectively improve diagnostic speed and the early screening rate of breast cancer. The system provides a valuable aid for the ultrasonic diagnosis of breast cancer.
The Three-Dimensional Body Center of Mass at the Workplace under Hypogravity
Authors: Maillard Tatiana
Published: October 2023

The center of mass dynamics of the seated posture of humans in a work environment under hypogravity (0 < g < 1) have rarely been investigated, and such research is yet to be carried out. The present study determined the difference in the body system of 32 participants working under simulated 1/6 g (Moon) and 1 g (Earth) for comparison using static and dynamic task measurements. This was based on a markerless motion capture method that analyzed participants’ center of mass at the start, middle and end of the task when they began to get fatigued. According to this analysis, there is a positive relationship (p < 0.01) with a positive coefficient of correlation between the downward center of mass body shift along the proximodistal axis and gravity level for males and females. At the same time, the same positive relationship (p < 0.01) between the tilt of the body backward along the anterior–posterior axis and the level of gravity was found only in females. This offers fresh perspectives for comprehending hypogravity in a broader framework regarding its impact on musculoskeletal disorders. It can also improve workplace ergonomics, body stability, equipment design, and biomechanics.
Understanding the Immunopathology of HTLV-1-Associated Adult T-Cell Leukemia/Lymphoma: A Comprehensive Review
Authors: Nakahata Shingo , Enriquez-Vera Daniel , Jahan M. Ishrat , Sugata Kenji , Satou Yorifumi
Published: October 2023

Human T-cell leukemia virus type-1 (HTLV-1) causes adult T-cell leukemia/lymphoma (ATL). HTLV-1 carriers have a lifelong asymptomatic balance between infected cells and host antiviral immunity; however, 5–10% of carriers lose this balance and develop ATL. Coinfection with Strongyloides promotes ATL development, suggesting that the immunological status of infected individuals is a determinant of HTLV-1 pathogenicity. As CD4+ T cells play a central role in host immunity, the deregulation of their function and differentiation via HTLV-1 promotes the immune evasion of infected T cells. During ATL development, the accumulation of genetic and epigenetic alterations in key host immunity-related genes further disturbs the immunological balance. Various approaches are available for treating these abnormalities; however, hematopoietic stem cell transplantation is currently the only treatment with the potential to cure ATL. The patient’s immune state may contribute to the treatment outcome. Additionally, the activity of the anti-CC chemokine receptor 4 antibody, mogamulizumab, depends on immune function, including antibody-dependent cytotoxicity. In this comprehensive review, we summarize the immunopathogenesis of HTLV-1 infection in ATL and discuss the clinical findings that should be considered when developing treatment strategies for ATL.
Novel Solution for Using Neural Networks for Kidney Boundary Extraction in 2D Ultrasound Data
Authors: Peng Tao , Gu Yidong , Ruan Shanq-Jang , Wu Qingrong Jackie , Cai Jing
Published: October 2023

Background and Objective: Kidney ultrasound (US) imaging is a significant imaging modality for evaluating kidney health and is essential for diagnosis, treatment, surgical intervention planning, and follow-up assessments. Kidney US image segmentation consists of extracting useful objects or regions from the total image, which helps determine tissue organization and improve diagnosis. Thus, obtaining accurate kidney segmentation data is an important first step for precisely diagnosing kidney diseases. However, manual delineation of the kidney in US images is complex and tedious in clinical practice. To overcome these challenges, we developed a novel automatic method for US kidney segmentation. Methods: Our method comprises two cascaded steps for US kidney segmentation. The first step utilizes a coarse segmentation procedure based on a deep fusion learning network to roughly segment each input US kidney image. The second step utilizes a refinement procedure to fine-tune the result of the first step by combining an automatic searching polygon tracking method with a machine learning network. In the machine learning network, a suitable and explainable mathematical formula for kidney contours is denoted by basic parameters. Results: Our method is assessed using 1380 trans-abdominal US kidney images obtained from 115 patients. Based on comprehensive comparisons of different noise levels, our method achieves accurate and robust results for kidney segmentation. We use ablation experiments to assess the significance of each component of the method. Compared with state-of-the-art methods, the evaluation metrics of our method are significantly higher. The Dice similarity coefficient (DSC) of our method is 94.6 ± 3.4%, which is higher than those of recent deep learning and hybrid algorithms (89.4 ± 7.1% and 93.7 ± 3.8%, respectively). Conclusions: We develop a coarse-to-refined architecture for the accurate segmentation of US kidney images. It is important to precisely extract kidney contour features because segmentation errors can cause under-dosing of the target or over-dosing of neighboring normal tissues during US-guided brachytherapy. Hence, our method can be used to increase the rigor of kidney US segmentation.
Decoding Hidden Messengers: Proteomic Profiling of Exosomes in Mammary Cancer Research
Authors: Novais Adriana Alonso , Tamarindo Guilherme Henrique , Chuffa Luiz Gustavo de Almeida , Zuccari Debora Aparecida Pires de Campos
Published: October 2023

Cancer is a complex and heterogeneous disease, influenced by various factors that affect its progression and response to treatment. Although a histopathological diagnosis is crucial for identifying and classifying cancer, it may not accurately predict the disease’s development and evolution in all cases. To address this limitation, liquid biopsy has emerged as a valuable tool, enabling a more precise and non-invasive analysis of cancer. Liquid biopsy can detect tumor DNA fragments, circulating tumor cells, and exosomes released by cancer cells into the bloodstream. Exosomes attracted significant attention in cancer research because of their specific protein composition, which can provide valuable insights into the disease. The protein profile of exosomes often differs from that of normal cells, reflecting the unique molecular characteristics of cancer. Analyzing these proteins can help identify cancer-associated markers that play important roles in tumor progression, invasion, and metastasis. Ongoing research and clinical validation are essential to advance and effectively utilize protein biomarkers in cancer. Nevertheless, their potential to improve diagnosis and treatment is highly promising. This review discusses several exosome proteins of interest in breast cancer, particularly focusing on studies conducted in mammary tissue and cell lines in humans and experimental animals. Unfortunately, studies conducted in canine species are scarce. This emphasis sheds light on the limited research available in this field. In addition, we present a curated selection of studies that explored exosomal proteins as potential biomarkers, aiming to achieve benefits in breast cancer diagnosis, prognosis, monitoring, and treatment.
The Correlation between Islet β Cell Secretion Function and Gallbladder Stone Disease: A Retrospective Study Based on Chinese Patients with Newly Diagnosed Type 2 Diabetes Mellitus
Authors: Wu Tiantian , Wang Qiang , Pu Changsheng , Zhang Keming
Published: October 2023

Background: This study aimed to analyze the correlation between islet β cell function and gallbladder stone (GBS) in newly diagnosed type 2 diabetes mellitus (T2DM) patients. Methods: A total of 438 newly diagnosed T2DM patients in Peking University International Hospital from January 2017 to August 2022 were retrospectively analyzed and divided into a non-GBS group and a GBS group. Results: (1) The homeostasis model assessment of the insulin resistance (HOMA-IR) of the GBS group was higher than that of the non-GBS group (p < 0.05), while the homeostasis model assessment of β cell (HOMA-β), disposition index (DI0), and Matsuda index of the GBS group were lower than those of the non-GBS group (all p < 0.05). (2) For male patients, HOMA-IR is an independent risk factor for GBS (OR = 2.00, 95% CI:1.03, 3.88, p < 0.05), and the Matsuda index value is a protective factor for GBS (OR = 0.76, 95% CI:0.60, 0.96, p < 0.05). For female patients, HOMA-IR is an independent risk factor for GBS (OR = 2.80, 95% CI:1.03, 7.58, p < 0.05) and the Matsuda index value is a protective factor for GBS (OR = 0.59, 95% CI:0.39, 0.90, p < 0.05). (3) For male patients, the area under curve (AUC) for predicting GBS was 0.77 (95% CI 0.67, 0.87), with a specificity of 75.26%, a sensitivity of 80.00%, and an accuracy of 75.64%. For female patients, the AUC for predicting GBS was 0.77 (95% CI 0.63, 0.88), with a specificity of 79.63%, a sensitivity of 71.43%, and an accuracy of 78.69%. Conclusions: Insulin resistance may be an independent risk factor for the incidence of GBS in patients with newly diagnosed T2DM, both male or female, which provides a new clinical basis and research direction for the prevention and treatment of GBS in patients with T2DM. This study has established a predictive model of GBS in T2DM and found it to be accurate, thus representing an effective tool for the early prediction of GBS in patients with T2DM.
Serum Cytokines and Growth Factors in Subjects with Type 1 Diabetes: Associations with Time in Ranges and Glucose Variability
Authors: Klimontov Vadim V. , Mavlianova Kamilla R. , Orlov Nikolai B. , Semenova Julia F. , Korbut Anton I.
Published: October 2023

The detrimental effect of hyperglycemia and glucose variability (GV) on target organs in diabetes can be implemented through a wide network of regulatory peptides. In this study, we assessed a broad panel of serum cytokines and growth factors in subjects with type 1 diabetes (T1D) and estimated associations between concentrations of these molecules with time in ranges (TIRs) and GV. One hundred and thirty subjects with T1D and twenty-seven individuals with normal glucose tolerance (control) were included. Serum levels of 44 cytokines and growth factors were measured using a multiplex bead array assay. TIRs and GV parameters were derived from continuous glucose monitoring. Subjects with T1D compared to control demonstrated an increase in concentrations of IL-1β, IL-1Ra, IL-2Rα, IL-3, IL-6, IL-7, IL-12 p40, IL-16, IL-17A, LIF, M-CSF, IFN-α2, IFN-γ, MCP-1, MCP-3, and TNF-α. Patients with TIR ≤ 70% had higher levels of IL-1α, IL-1β, IL-6, IL-12 p70, IL-16, LIF, M-CSF, MCP-1, MCP-3, RANTES, TNF-α, TNF-β, and b-NGF, and lower levels of IL-1α, IL-4, IL-10, GM-CSF, and MIF than those with TIR > 70%. Serum IL-1β, IL-10, IL-12 p70, MCP-1, MCP-3, RANTES, SCF, and TNF-α correlated with TIR and time above range. IL-1β, IL-8, IL-10, IL-12 p70, MCP-1, RANTES, MIF, and SDF-1α were related to at least one amplitude-dependent GV metric. In logistic regression models, IL-1β, IL-4, IL-10, IL-12 p70, GM-CSF, HGF, MCP-3, and TNF-α were associated with TIR ≤ 70%, and MIF and PDGF-BB demonstrated associations with coefficient of variation values ≥ 36%. These results provide further insight into the pathophysiological effects of hyperglycemia and GV in people with diabetes.
Probabilistic Dual-Space Fusion for Real-Time Human-Robot Interaction
Authors: Li Yihui , Wu Jiajun , Chen Xiaohan , Guan Yisheng
Published: October 2023

For robots in human environments, learning complex and demanding interaction skills from humans and responding quickly to human motions are highly desirable. A common challenge for interaction tasks is that the robot has to satisfy both the task space and the joint space constraints on its motion trajectories in real time. Few studies have addressed the issue of hyperspace constraints in human-robot interaction, whereas researchers have investigated it in robot imitation learning. In this work, we propose a method of dual-space feature fusion to enhance the accuracy of the inferred trajectories in both task space and joint space; then, we introduce a linear mapping operator (LMO) to map the inferred task space trajectory to a joint space trajectory. Finally, we combine the dual-space fusion, LMO, and phase estimation into a unified probabilistic framework. We evaluate our dual-space feature fusion capability and real-time performance in the task of a robot following a human-handheld object and a ball-hitting experiment. Our inference accuracy in both task space and joint space is superior to standard Interaction Primitives (IP) which only use single-space inference (by more than 33%); the inference accuracy of the second order LMO is comparable to the kinematic-based mapping method, and the computation time of our unified inference framework is reduced by 54.87% relative to the comparison method.
Decrease in the P2 Amplitude of Object Working Memory after 8 h-Recovery Sleep Following 36 h-Total Sleep Deprivation: An ERP Study
Authors: Shao Yongcong , Peng Ziyi , Xu Lin , Lian Jie , An Xin , Cheng Ming-Yang
Published: October 2023

The impact of sleep deprivation on working memory can only be reversed by recovery sleep (RS). However, there are limited electrophysiological studies on the effect of RS on the improvement in working memory after sleep deprivation, and the changes in the early components of event-related potentials (ERPs) before and after RS are still unclear. Therefore, this study aims to explore the effects of RS on the earlier ERP components related to object working memory following 36 h of total sleep deprivation (TSD). Twenty healthy male participants performed an object working memory task after 36 h of TSD and after 8 h of RS. Electroencephalogram data were recorded accordingly while the task was performed. Repeated ANOVA showed that P2 amplitudes related to object working memory decreased significantly after 8 h of RS compared to after a 36 h period of TSD, but there was no significant difference from baseline (BS), which indicates a trend of recovery to the baseline state. An 8 h RS can partially improve impaired object working memory caused by TSD. However, a longer period of RS is needed for the complete recovery of cognitive function after a long period of TSD.
Cardiac 123I-Metaiodobenzylguanidine (MIBG) Scintigraphy in Parkinson’s Disease: A Comprehensive Review
Authors: Pitton Rissardo Jamir , Fornari Caprara Ana Letícia
Published: October 2023

Cardiac sympathetic denervation, as documented on 123I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy, is relatively sensitive and specific for distinguishing Parkinson’s disease (PD) from other neurodegenerative causes of parkinsonism. The present study aims to comprehensively review the literature regarding the use of cardiac MIBG in PD. MIBG is an analog to norepinephrine. They share the same uptake, storage, and release mechanisms. An abnormal result in the cardiac MIBG uptake in individuals with parkinsonism can be an additional criterion for diagnosing PD. However, a normal result of cardiac MIBG in individuals with suspicious parkinsonian syndrome does not exclude the diagnosis of PD. The findings of cardiac MIBG studies contributed to elucidating the pathophysiology of PD. We investigated the sensitivity and specificity of cardiac MIBG scintigraphy in PD. A total of 54 studies with 3114 individuals diagnosed with PD were included. The data were described as means with a Hoehn and Yahr stage of 2.5 and early and delayed registration H/M ratios of 1.70 and 1.51, respectively. The mean cutoff for the early and delayed phases were 1.89 and 1.86. The sensitivity for the early and delayed phases was 0.81 and 0.83, respectively. The specificity for the early and delayed phases were 0.86 and 0.80, respectively.
Acute or Chronic Exposure to Corticosterone Promotes Wakefulness in Mice
Authors: Yao Zhen , Zhang Bei-Xuan , Chen Hui , Jiang Xiao-Wei , Qu Wei-Min , Huang Zhi-Li
Published: October 2023

Elevated glucocorticoid levels triggered by stress potentially contribute to sleep disturbances in stress-induced depression. However, sleep changes in response to elevated corticosterone (CORT), the major glucocorticoid in rodents, remain unclear. Here, we investigated the effects of acute or chronic CORT administration on sleep using electroencephalogram (EEG) and electromyography (EMG) recordings in freely moving mice. Acute CORT exposure rapidly promoted wakefulness, marked by increased episodes and enhanced EEG delta power, while simultaneously suppressing rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, with the latter marked by decreased mean duration and reduced delta power. Prolonged 28-day CORT exposure led to excessive wakefulness and REM sleep, characterized by higher episodes, and decreased NREM sleep, characterized by higher episodes and reduced mean duration. EEG theta activity during REM sleep and delta activity during NREM sleep were attenuated following 28-day CORT exposure. These effects persisted, except for REM sleep amounts, even 7 days after the drug withdrawal. Elevated plasma CORT levels and depressive phenotypes were identified and correlated with observed sleep changes during and after administration. Fos expression significantly increased in the lateral habenula, lateral hypothalamus, and ventral tegmental area following acute or chronic CORT treatment. Our findings demonstrate that CORT exposure enhanced wakefulness, suppressed and fragmented NREM sleep, and altered EEG activity across all stages. This study illuminates sleep alterations during short or extended periods of heightened CORT levels in mice, providing a neural link connecting insomnia and depression.
Unlocking Colchicine’s Untapped Potential: A Paradigm Shift in Hepatocellular Carcinoma Prevention
Authors: Lin Jung-Ju , Lin Cheng-Li , Chen Chun-Chung , Lin Yu-Hsiang , Cho Der-Yang , Chen XianXiu , Chen Der-Cherng , Chen Hung-Yao
Published: October 2023

Background: Liver cancer and notably hepatocellular carcinoma (HCC), results in significantly high mortality rates worldwide. Chronic hepatitis and fatty liver, recognized precursors, underscore the imperative need for effective preventive strategies. This study explores colchicine, traditionally acknowledged for its anti-inflammatory properties and investigates its potential in liver cancer prevention. Methods: Utilizing the iHi Data Platform of China Medical University Hospital, Taiwan, this study analyzed two decades of medical data, incorporating 10,353 patients each in the Colchicine and Non-Colchicine cohorts, to investigate the association between colchicine use and liver cancer risk. Results: The study identified that colchicine users exhibited a 19% reduction in liver cancer risk, with a multivariable-adjusted odds ratio of 0.81 after accounting for confounding variables. Additionally, the influence of gender and comorbidities like diabetes mellitus on liver cancer risk was identified, corroborating the existing literature. A notable finding was that the prolonged use of colchicine was associated with improved outcomes, indicating a potential dose–response relationship. Conclusions: This study proposes a potential new role for colchicine in liver cancer prevention, extending beyond its established anti-inflammatory applications. While the findings are promising, further research is essential to validate these results. This research may serve as a foundation for future studies, aiming to further explore colchicine’s role via clinical trials and in-depth investigations, potentially impacting preventive strategies for liver cancer.