Human Body Research Articles

Fishing net-inspired PVA-chitosan-CNT hydrogels with high stretchability, sensitivity, and environmentally stability for textile strain sensors

Soft electronic products are being extensively investigated in diverse applications including sensors and devices, due to their superior softness, responsiveness, and biocompatibility. One-dimensional (1-D) fiber electronic devices are recognized for their lightweight, wearable, and stretchable qualities, thus emerging as critical constituents for seamless integration with the human body and attire, exhibiting great potential in wearable applications. However, wearable conductive hydrogel fibers usually face challenges in combining stretchability and excellent stability, notably in high-temperature environment. Herein, a novel stretchable conductive hydrogel fiber, namely PVA-CS-CNT (Polyvinyl Alcohol-Chitosan-Carbon Nanotube) hydrogel fiber, was successfully prepared through a straightforward low-temperature process. This hydrogel fiber not only maintains stable signal transmission at high temperatures but also exhibits significant mechanical and sensing capabilities, ensuring signal stability during repetitive cyclic stretching. Inspired by fishing net, textile sensors were fabricated by weaving PVA-CS-CNT hydrogel fibers, which offered breathability, high stability (withstanding over 500 stretch cycles), high sensitivity (detecting strains as low as 1 %), and exceptional mechanical strength (exceeding 17 MPa). The wearable sensor could not only accurately monitor human movements like stretching and bending, but also adeptly captured delicate signals such as pulses and sounds. These characteristics demonstrated the potential applications of the hydrogel fibers encompassing human motion tracking, intelligent textiles, and soft robotics.

Drug-Resistant Epilepsy and Gut-Brain Axis: an Overview of a New Strategy for Treatment.

Drug-resistant epilepsy (DRE), also known as intractable epilepsy or refractory epilepsy, is a disease state with long-term poorly controlled seizures attack. Without effective treatment, patients are at an elevated risk of injury, premature death, mental disorders, and poor quality of life, increasing the need for a fresh perspective on the etiology and treatment of DRE. The gut is known to harbor a wide variety of microorganisms that can regulate the host's response to exogenous signals and participate in various physiological and pathological processes in the human body. Interestingly, emerging evidence has uncovered the changes in gut microbiota in patients with epilepsy, particularly those with DRE. In addition, both dietary interventions and specific antibiotic therapy have been proven to be effective in restoring the microecological environment and, more importantly, reducing seizures. Here, we reviewed recent studies on DRE and the involvement of gut microbiota in it, describing changes in the gut microflora composition in patients with DRE and corresponding animal models. Furthermore, the influence of the ketogenic diet, probiotics, fecal microbiota transplantation (FMT), and antibiotics as microbiome-related factors on seizure control and its possible mechanisms are broadly discussed. Finally, we highlighted the significance of gut microbiome in DRE, in order to provide a new prospect for early identification and individualized treatment of patients with DRE.

Exploring a Secure Device Pairing Using Human Body as a Conductor

Exploring a Secure Device Pairing Using Human Body as a Conductor

Psychosomatic Disorder: The Current Implications and Challenges.

In recent years, there has been increasing global concern about the rising prevalence and rapid progression of psychosomatic disorders (PD). This surge can be attributed to irregular biological conditions and the increasingly stressful lifestyles that individuals lead, ultimately resulting in functional impairments of vital organs. PD arises from intricate interactions involving the central nervous, endocrine, and immune systems. Notably, the hypothalamic-pituitaryadrenal (HPA) axis plays an essential role, as its dysregulation is influenced by prolonged stress and psychological distress. Consequently, stress hormones, including cortisol, exert detrimental effects on immunological function, inflammation, and homeostatic equilibrium. It emerges as physical symptoms influenced by psychological factors, such as persistent pain, gastrointestinal disturbances, or respiratory complications, and is pertinent to highlight that excessive and chronic stress, anxiety, or emotional distress may engender the onset or exacerbation of cardiovascular disorders, namely hypertension and heart disease. Although several therapeutic strategies have been proposed so far, the precise etiology of PD remains elusive due to the intricate nature of disease progression and the underlying modalities of action. This comprehensive review seeks to elucidate the diverse classifications of psychosomatic disorders, explicate their intricate mechanisms, and shed light on their impact on the human body, which may act as catalysts for the development of various other diseases. Additionally, it explores the inherent medico-clinical challenges posed by PD and also explores the cutting-edge technologies, tools, and data analytics pipelines that are being applied in the contemporary era to effectively analyze psychosomatic data.

When subcellular chemical imaging enlightens our understanding on intestinal absorption, intracellular fate and toxicity of PFOA in vitro

Perfluorooctanoic acid (PFOA) is a persistent organic pollutant that accumulates in the human body, leading to major health issues. Upon oral uptake, the gastrointestinal tract is the first biological barrier against PFOA. However, the localization of PFOA and its impact on the intestinal wall are largely unknown. Here we achieve a breakthrough in the knowledge of intestinal absorption, intracellular fate and toxicity of PFOA using in vitro assays combined with novel analytical imaging techniques. For the first time, we localized PFOA in the cytosol of Caco-2 cells after acute exposure using high spatial resolution mass spectrometry imaging, and we estimated the PFOA cytosolic concentration. Knowing that PFOA enters and accumulates in the intestinal cells, we also performed common toxicity assays assessing cell metabolic activity, membrane integrity, oxidative stress response, and cell respiration. This study integrating powerful analytical techniques with widely used toxicology assays provides insightful information to better understand potential negative impacts of PFOA and opens new opportunities in toxicology and life science in general.

A physiologically based toxicokinetic model for microplastics and nanoplastics in mice after oral exposure and its implications for human dietary exposure assessment

Evidence of microplastics (MPs) and nanoplastics (NPs) in foods and daily-use products, along with their frequent detection in the human body, has raised concerns regarding their potential impact on human health through dietary ingestion. However, there is a lack of quantitative tools to simulate their bioaccumulation and tissue distribution following environmental exposure. To address this gap, we developed the first physiologically based toxicokinetic (PBTK) model for predicting the biodistribution of MPs and NPs in mice following oral exposure under various exposure scenarios. This novel model incorporated key kinetic mass transport processes, such as membrane permeability, albumin binding, and cellular uptake. We identified that the absorption rate in the gastrointestinal tract and fecal excretion rate constant had significant impacts on organ dosimetry. Our regression analysis indicated that the size-dependent dissociation constant and urine clearance rate constant sharply increased by a factor of 3 as NPs particle size increased to 1µm. Finally, we developed a graphical user interface to enable interactive visualization and analysis for future applications, supporting human dietary exposure and risk assessment using available food consumption data and MPs/NPs residue data. The simulation results offer a mechanistic perspective, enhancing understanding of the internal organ dosimetry burden and health impacts from dietary exposure to MPs and NPs.

Unveiling Current Advances in Bioelectronic Medicine: A Comprehensive Review

Background: Bioelectronic medicine is an emerging therapy that makes use of neural signals and the nervous system to help in the treatment of injuries and diseases. The nervous sys-tem consists of disciplined circuits that involve the communication of every major organ of the human body as all the organs of the human body are regulated and controlled by neural circuits. Objective: The objective of this review is to overview the current implementations of bioelectron-ic medicines within the human body. The main target is to heal the body without administering a wide array of exogenous drugs. On understanding these neural circuits at a molecular level, it could be possible to understand, manipulate, and modify the body’s functioning with the help of electrical impulses to modify neural impulses. Methods: The literature related to bioelectronic medicines, and their applications was collected through different websites, academic research portals, and databases, sorted, and presented in this review. Results: Bioelectronic medicine is emerging as a cutting-edge area in healthcare, demonstrating its potential to transform the diagnosis and management of inflammation and related conditions. With established efficacy in a variety of disorders and marketed available treatments, it highlights an enormous shift toward individualized and specialized therapeutic approaches, providing prom-ise for improved outcomes and a higher quality of life for patients worldwide. Conclusion: The study focuses on potential advances in bioelectronic medicine for alleviating in-flammation and inflammatory disorders such as rheumatoid arthritis, diabetes, and spinal cord in-jury. Bioelectronic treatments provide innovative therapeutic options with the potential for con-siderable clinical effects.

Automated blood cancer detection models based on EfficientNet-B3 architecture and transfer learning

In blood smear images, there are difficulties in diagnosing blood cancer diseases like leukemia and lymphoma because of their various forms that appear in the human body. In this paper, a method for automatic detection of blood cancer is suggested that uses the EfficientNet-B3 architecture along with transfer learning techniques to improve accuracy and efficiency. We first fine-tuned the EfficientNet-B3 model, which was pre-trained on a large dataset consisting of annotated blood smear images, to capture pertinent features linked with blood malignant cells. To expedite the training process and adapt the model to our task, we use transfer learning. The proposed approach’s results from our experiments show that it outperforms traditional deep learning models and state-of-the-art methods in blood cancer detection. Additionally, with high precision and recall rates, this model also detects different types of blood cancers with robustness in its performance since its accuracy is over 99%. This means that when used together with the EfficientNet-B3 architecture, transfer learning can help the developed methods generalize among different types of blood cancers and conditions.

The first-in-human study of QHRD106 functioning as a safe and effective long-acting kallikrein drug potentially aiding ischemic stroke

ABSTRACT Background This study assessed the pharmacokinetics (PK), pharmacodynamics (PD) and safety of QHRD106, and made a comparison with urinary kallindinogenase (UKN) in healthy volunteers. Methods This study comprised a randomized, double-blind, placebo-controlled, single-dose escalation phase and an open-label, multiple-dose escalation phase. 94 subjects received intramuscular injections of QHRD106/placebo only once and 30 subjects received QHRD106 four times. 6 subjects received 0.15 PNA units UKN intravenously for 7 d. PK and PD analysis were conducted by using a electrochemiluminescent assay and a liquid chromatography/mass spectrometry methodology respectively. Cerebral circulation was assessed by the magnetic resonance imaging system. Results QHRD106 exhibited a slow absorption profile in the human body. Compared to UKN, QHRD106 induced changes in bradykinin concentration later, but with a noticeably prolonged duration. Compared to baseline, cerebral blood flow exhibited a significant improvement on d 7 after a single dose of 18,900 IU and an improvement from d 2 to d 14 after multiple dose of 8400 IU of QHRD106. QHRD106 appeared generally good safety and no severe adverse events occurred in all the groups. Conclusions This study provided initial evidence of potential treatment for ischemic strokes that the QHRD106 injection functioned as a safe and effective long-acting kallikrein drug. Registration This study was registered on ClinicalTrials.gov with the identifier NCT06380699 and NCT06388772.

Carbohydrate storage in cells: a laboratory activity for the assessment of glycogen stores in biological tissues.

Carbohydrates and fats constitute our primary energy sources. The importance of each of these energy substrates varies across cell types and physiological conditions. For example, the brain normally relies almost exclusively on glucose oxidation, whereas skeletal muscle shifts from lipids toward higher carbohydrate oxidation rates as exercise intensity increases. Understanding how carbohydrates are stored in our cells and which tissues contain significant carbohydrate stores is crucial for health professionals, especially given the role of carbohydrate metabolism in various pathophysiological conditions. This laboratory activity uses a simple and low-cost iodine binding method to quantify glycogen in mouse skeletal muscle and liver samples. By integrating the results of this activity with literature data, students can determine overall glycogen storage in the human body. The primary goal of the activity is to enhance students' understanding of the importance and limitations of glycogen stores in energy metabolism.NEW & NOTEWORTHY Carbohydrates are one of the primary energy sources utilized by our cells. Liver and skeletal muscle glycogen, which are the main carbohydrate reserves in the body, play a central role in energy metabolism, especially during periods of fasting and exercise. In this laboratory activity, students measure glycogen levels in tissues to gain insights into how carbohydrates are stored in our cells and understand the role and limitations of liver and muscle carbohydrate stores.

Enhancing aglycone isoflavones in soymilk through soybean germination and incubation

As a group of important bioactive compounds in soybeans, isoflavones are beneficial to human health, and aglycone isoflavones are more readily absorbed and utilized by the human body. Soymilk is a widely consumed soy-based beverage. The reduction in isoflavones content during soymilk production can lower its nutritional quality. This study aimed to increase the total isoflavones content and the proportion of aglycone isoflavones in soymilk through seeds germination and the followed soymilk incubation. In this study, changes in the isoflavone content and composition of soymilk made from germinated and raw soybeans were detected at different processing stages. Single-factor and response surface experiments were carried out to optimize the incubation conditions, aiming to enhance the content of aglycone isoflavones in soymilk made of germinated soybeans. The results showed that total isoflavones content increased from 3722.23 μg/g DW to 4337.93 μg/g DW in 2-day germinated soybeans, and incubation promoted the conversion of conjugated isoflavones to aglycone isoflavones in soymilk. Under the optimal incubation conditions (53.26 ± 1.0 °C for 56.64 ± 1.0 min), the content of aglycone isoflavones in soymilk significantly increased by 44.43% compared with the control, and the incubation with optimized conditions had little effect on its microbial safety, nutrients content and overall flavor, consequently leading to no significant deterioration in its quality after incubation. Therefore, the combination of germination and incubation is an efficient strategy to enhance the aglycone isoflavones content in soymilk, providing valuable information for enhancing the isoflavones bioactivity of soymilk during processing.

The possibility of modeling on mannequin using liquid fabric to develop fashion design and displaying it using digital programs (3D)

Abstract With the technological advancements in fashion design and the textile industry, the research explores the integration of three main axes: the formation axis on the mannequin, the liquid fabric axis, and the digital fashion axis. These are interconnected through the establishment of a robust technological infrastructure that enables work in the realms of textile technology and digital transformation in the field of fashion design. Despite these advantages, there are obstacles limiting its full potential. Can this technology be applied to the mannequin in a room with a temperature resembling the human body to safeguard and showcase it using 3D virtual displays? Thus, the research problem emerges, leading to the following question: What is the extent of the possibility of molding the mannequin using liquid fabric to contribute to the development of fashion design and presenting these designs using digital fashion? Its application in the field of fashion design? Since the liquid textile industry is modern in the fashion world, this research aims to study the possibility of using liquid fabric in the development of the fashion industry and formation of mannequin instead of the human body in a way that helps preserve the environment. This is done by conducting an experimental and descriptive study to achieve some liquid texture strategies shaping the mannequin in the fashion design industry and by linking them to digital fashion using the experimental method and the descriptive method to compare and analyze the results. The results were as follows: 1. Obtain multiple and varied creations in the field of fashion design 2. Speed up the design and production of models 3. Save time, effort, and money. 4. Use modern technology in applying the world of virtual fashion with ease, facilitating electronic commerce. 5. Easily recycle liquid fabric after obtaining the raw material of its product into a liquid material that can be re-sprayed and reshaped, thereby preserving the environment from pollution. Keywords: Liquid fabric, Sculpting on the mannequin, Digital fashion.

Embryologie und Wirbelsäule – Teil 1: Entstehung und Entwicklung der Somiten als Anlage der Wirbelsäule

The early embryonic segmentation and vertebral column arise from the genetic material of the somites and, as in every other organ in the human body, they are part of, and inseparable from, the overall development of the embryo. The first somites and their subcomponents arise from the end of the 3rd week of development in a constructively logical succession as a gradual differentiation of the unsegmented mesenchyme. Following the development of the somites, a closed series of formative processes then leads to the development of the vertebral column. Resegmentation of somites does not occur in the formation of the vertebral column. This is the first time that we have described the basic embryological principles according to Blechschmidt in this way.

Artificial Intelligence-Based Classification of CT Images Using a Hybrid SpinalZFNet.

The kidney is an abdominal organ in the human body that supports filtering excess water and waste from the blood. Kidney diseases generally occur due to changes in certain supplements, medical conditions, obesity, and diet, which causes kidney function and ultimately leads to complications such as chronic kidney disease, kidney failure, and other renal disorders. Combining patient metadata with computed tomography (CT) images is essential to accurately and timely diagnosing such complications. Deep Neural Networks (DNNs) have transformed medical fields by providing high accuracy in complex tasks. However, the high computational cost of these models is a significant challenge, particularly in real-time applications. This paper proposed SpinalZFNet, a hybrid deep learning approach that integrates the architectural strengths of Spinal Network (SpinalNet) with the feature extraction capabilities of Zeiler and Fergus Network (ZFNet) to classify kidney disease accurately using CT images. This unique combination enhanced feature analysis, significantly improving classification accuracy while reducing the computational overhead. At first, the acquired CT images are pre-processed using a median filter, and the pre-processed image is segmented using Efficient Neural Network (ENet). Later, the images are augmented, and different features are extracted from the augmented CT images. The extracted features finally classify the kidney disease into normal, tumor, cyst, and stone using the proposed SpinalZFNet model. The SpinalZFNet outperformed other models, with 99.9% sensitivity, 99.5% specificity, precision 99.6%, 99.8% accuracy, and 99.7% F1-Score in classifying kidney disease.

General skills amidst the details: alternative learning objectives and a framework of competencies for human anatomy.

The field of anatomy is often seen by nonanatomists as concerned primarily with the tasks of locating, naming, and describing structures; these tasks, in turn, are often assumed to require only lower-order cognitive skills (LOCSs), i.e., the Knowledge or Comprehension levels of Bloom's taxonomy. Many nonanatomists may thus believe that studying anatomy does not develop transferable higher-order cognitive skills. Published lists of anatomy learning objectives (LOs) might reinforce this view by focusing attention on numerous details of specific structures and regions. To explore this issue further, we have analyzed the structure of published peer-reviewed LOs by characterizing their organization (single-tiered or multi-tiered), inclusion of function, use of action verbs, and dependence on or independence of context. Our results suggest that previously published LO lists, despite their value, may not fully showcase opportunities for students to develop higher-order skills. In the hope of stimulating further discussion and scholarship, we present here a two-tiered framework of human anatomy competencies, i.e., generalizable skills beyond straightforward recognition and memorization. This framework, which is intended to be both student-facing and faculty-facing, illustrates how anatomy courses may be reframed as opportunities to think critically and develop sophisticated, professionally relevant skills.NEW & NOTEWORTHY Although skilled anatomists know that anatomy is much more than memorization, nonanatomists are often unsure how to emphasize general skills and problem-solving in their teaching of the subject. Here we show how a multi-tiered approach to defining and assessing learning objectives (LOs) can reframe anatomy courses as more than long lists of structures to remember.

Assembling a physical model helps students grasp human somatosensory pathways.

Mastering the complexity of the nervous system is essential for education programs in physiology, anatomy, and neuroscience. Students often struggle when learning somatosensory pathways, which convey information from sensory neurons to the somatosensory cortex in the brain. Active learning activities incorporating physical models have been shown to increase content comprehension as well as enjoyment of the learning process. Here, we present a three-dimensional physical model of somatosensory pathways constructed of durable, affordable, and widely available materials. In an upper level human physiology lab, students assembled the model and then used it to complete case study questions connecting damage to the spinal cord to resulting sensory deficits. This model-based activity was highly effective as indicated by significant increases in content knowledge and positive responses to survey questions on the effectiveness of the activity. This activity incorporates many evidence-based teaching practices that have been shown to increase engagement, inclusion, and mastery of content and provides an effective and fun way for students to learn a challenging topic.NEW & NOTEWORTHY This model-building activity for learning somatosensory neural pathways increases students' content knowledge and is an enjoyable way to learn a complex system. This activity adds to an ever-growing collection of evidence-based learning activities for human physiology courses.

Ecological risks caused by neonicotinoid pesticides in sediments: A case study of freshwater basins in China.

Neonicotinoid insecticides (NNIs) are extensively used in agricultural production in China due to their selective neurotoxicity towards target insects. In recent years, the rapid development of agriculture has increased the use and residue of NNIs. Consequently, the sediment environment, serving as the ultimate sink, is significantly impacted by NNIs. Upon release into the environment, NNIs can enter the human body through the food chain, posing potential ecological and human health risks. This study analyzed 79 sediment samples from two major river basins in North and South China, the Liaohe River basin in Liaoning Province and the Jianjiang River basin in Guangdong Province. The content, composition, distribution, and source of eight NNIs were analyzed, and assess the ecological and human health risks of the target compounds in these regions. The results indicated that the average concentration of NNIs in the sediments of the Jianjiang River basin (2.34 μg/kg) is slightly higher than that of the Liaohe River basin (2.32 μg/kg), and the sources of NNIs in the two areas were different, with differences in the sources of NNIs likely attributable to varying types of agricultural production. The risk assessment revealed that the ecotoxicological and public health risks were more pronounced in the Jianjiang River basin compared to the Liaohe River basin, underscoring the critical need for surveillance and management of hazardous substances like NNIs. The insights findings from this study can provide scientific guidance for the risk evaluation and environmental management of NNIs.

High-strength polyvinyl alcohol/gelatin/LiCl dual-network conductive hydrogel for multifunctional sensors and supercapacitors

The synthesis of conductive hydrogels with high mechanical strength, toughness, optimal fracture growth rate and the capability to detect diverse human body movements poses a significant challenge in the realm of flexible electronics. In this study, a one-pot technique utilized effectively to fabricate conductive materials by doping LiCl into a mixture of polyvinyl alcohol (PVA) and gelatin. The PVA/gelatin/LiCl0.3(PGL) conductive hydrogel demonstrates exceptional robustness, flexibility, and resistance to deformation, enabling the monitoring of various physiological signals such as temperature and humidity. Additionally, the PGL demonstrates exceptional elongation properties (up to 1111.32 %), high lifting capacity (up to 25 kg), resistance to deformation, and sustained stability of peak signals even after 300 cycles at 50 % strain. The hydrogel electrolyte exhibits a conductivity of 2.114 S/m at 25 °C and a specific capacitance of up to 48.75 F/g, along with favorable mechanical and electrochemical characteristics. These findings suggest that the PVA/gelatin/LiCl0.3 hydrogel supercapacitor (PGLSC) conductive hydrogel shows significant potential for integration into flexible electronics and wearable technology devices.

Antiviral Medications: Unravelling their Significance in Context to COVID-19

Abstract: Viruses represent a significant health menace due to their rapid transmissibility and potential to cause worldwide pandemics, resulting in substantial loss of human life. Antiviral agents play a pivotal role in mitigating the impact of viral infections. Nonetheless, treating viral infections is a multifaceted process due to the inherent characteristics of viruses, such as their capacity to undergo mutations and rapid evolution. Consequently, the effectiveness of current antiviral therapies can be impeded. This review encompasses the diverse manners in which viruses, emphasizing COVID-19, affect the human body and elucidates the challenges encountered in formulating efficacious antiviral treatments. Moreover, the limitations of conventional antiviral therapies are underscored. Additionally, a comprehensive compendium of 41 antiviral drugs is presented, detailing their mechanisms of action and routes of administration. Subsequently, the discussion includes 9 drugs repurposed for treating COVID-19, delineating their primary use as well as any accompanying side effects. In conclusion, while antiviral drugs remain pivotal in the battle against viral infections, the obstacles associated with their development and usage warrant careful consideration. Ongoing research is imperative to devise more potent and less toxic antiviral interventions against COVID-19 infection.

Performance Analysis of Semi-refined Digital Forearm Modeling and Simplified Forearm Model in Electromagnetic Simulation

Objective: The objective of this study is to analyze the performance difference between simplified and digital models based on medical images. Methods: According to the characteristics of human anatomy, the finite element simulation software COMSOL Multiphysics 5.5 was employed to construct a simplified arm model using cylinders and a digital arm model based on Chinese digital human regarding electroacupuncture therapy as an example. A comparative analysis was then performed considering three aspects: mesh number, potential distribution, and resource consumption. Results: Through analysis, the digital arm model based on Chinese digital human requires significantly more mesh cells than the simplified arm model in mesh generation. Meanwhile, because the digital arm model based on the Chinese digital human fully expresses the nonuniformity of the tissue distribution in a real human body, its signal distribution in its interior is also relatively scattered, and the coupling potential slightly differs at the electrode vertex with the smallest change. In addition, the digital arm model has much higher resource consumption and computer hardware resource requirements compared with the simplified arm model. Conclusion: As a result, the digital model based on the Chinese digital human can more fully express the tissue distribution and electrical signal characteristics of a real human body. However, due to its high computational requirements, appropriate simplification can be selected to improve the computational efficiency of the model in practical applications.