Impact of stalling events on microcirculatory hemodynamics in the aged brain.

OBJECTIVE: The role of cerebral microvasculature in cognitive dysfunction can be investigated by identifying the impact of blood flow on cortical tissue oxygenation. In this paper, the impact of capillary stalls on microcirculatory characteristics such as flow and hematocrit (Ht) in the cortical angioarchitecture is studied. METHODS: Using a deterministic mathematical model to simulate blood flow in a realistic mouse cortex, hemodynamics parameters, including pressure, flow, vessel diameter-adjustable hematocrit, and transit time are calculated as a function of stalling events. RESULTS: Using a non-linear plasma skimming model, it is observed that Ht increases in the penetrating arteries from the pial vessels as a function of cortical depth. The incidence of stalling on Ht distribution along the blood network vessels shows reduction of RBCs around the tissue near occlusion sites and decreased Ht concentration downstream from the blockage points. Moreover, upstream of the occlusion, there is a noticeable increase of the Ht, leading to larger flow resistance due to higher blood viscosity. We predicted marked changes in transit time behavior due to stalls which match trends observed in mice in vivo. CONCLUSIONS: These changes to blood cell quantity and quality may be implicated in the development of Alzheimer's disease and contribute to the course of the illness.

Rapid and sustained antidepressant effects of intravenous ketamine in treatment-resistant major depressive disorder and suicidal ideation: a randomized clinical trial.

BACKGROUND: Major depressive disorder (MDD) is the most disabling and burdensome mental disorder, negatively affecting an individual's quality of life and daily functioning. the current study was conducted with the aim of investigating the clinical effects of intravenous ketamine on symptoms of MDD and suicidal ideation. METHODS: The current randomized clinical trial was carried out on 64 patients diagnosed with treatment-resistant major depressive disorder between April and August 2022. The participants were randomly assigned to two groups: the intervention group received a dose of 0.5 mg/kg of ketamine, while the control group received normal saline. The Montgomery-Asberg Depression Scale and Beck's Suicidal Ideation Scale were utilized to assess depression and suicidal ideation, respectively. RESULTS: One hour after the administration of ketamine treatment, there was a notable and significant improvement in both depression symptoms (35.16 ± 8.13 vs. 14.90 ± 10.09) and suicidal ideation (6.74 ± 6.67 vs. 0.42 ± 1.52). Moreover, there were statistically significant differences in depression scores between the two groups at one hour, four hours, one day, three days, one week, one month, and two months after the administration of ketamine (p-value < 0.001). However, ketamine recipients frequently experienced side effects such as increased heart rate, headache, dizziness, and dissociative syndrome symptoms. CONCLUSION: The observed rapid onset of action and sustained effect demonstrate the potential of ketamine to provide relief from depressive symptoms in a shorter timeframe compared to traditional treatment approaches. These findings contribute to the growing body of evidence supporting the use of ketamine as a valuable therapeutic option for patients with treatment-resistant depression. IRCT REGISTRATION: IRCT registration number: IRCT20210806052096N1; IRCT URL: https://www.irct.ir/trial/62243 ; Ethical code: IR.ZUMS.REC.1400.150; Registration date: 2022-04-09.

Digital Twin Model of Electric Drives Empowered by EKF.

Digital twins, a product of new-generation information technology development, allows the physical world to be transformed into a virtual digital space and provide technical support for creating a Metaverse. A key factor in the success of Industry 4.0, the fourth industrial revolution, is the integration of cyber-physical systems into machinery to enable connectivity. The digital twin is a promising solution for addressing the challenges of digitally implementing models and smart manufacturing, as it has been successfully applied for many different infrastructures. Using a digital twin for future electric drive applications can help analyze the interaction and effects between the fast-switching inverter and the electric machine, as well as the system's overall behavior. In this respect, this paper proposes using an Extended Kalman Filter (EKF) digital twin model to accurately estimate the states of a speed sensorless rotor field-oriented controlled induction motor (IM) drive. The accuracy of the state estimation using the EKF depends heavily on the input voltages, which are typically supplied by the inverter. In contrast to previous research that used a low-precision ideal inverter model, this study employs a high-performance EKF observer based on a practical model of the inverter that takes into account the dead-time effects and voltage drops of switching devices. To demonstrate the effectiveness of the EKF digital twinning on the IM drive system, simulations were run using the MATLAB/Simulink software (R2022a), and results are compared with a set of actual data coming from a 4 kW three-phase IM as a physical entity.

A Super-Efficient GSM Triplexer for 5G-Enabled IoT in Sustainable Smart Grid Edge Computing and the Metaverse.

Global concerns regarding environmental preservation and energy sustainability have emerged due to the various impacts of constantly increasing energy demands and climate changes. With advancements in smart grid, edge computing, and Metaverse-based technologies, it has become apparent that conventional private power networks are insufficient to meet the demanding requirements of industrial applications. The unique capabilities of 5G, such as numerous connections, high reliability, low latency, and large bandwidth, make it an excellent choice for smart grid services. The 5G network industry will heavily rely on the Internet of Things (IoT) to progress, which will act as a catalyst for the development of the future smart grid. This comprehensive platform will not only include communication infrastructure for smart grid edge computing, but also Metaverse platforms. Therefore, optimizing the IoT is crucial to achieve a sustainable edge computing network. This paper presents the design, fabrication, and evaluation of a super-efficient GSM triplexer for 5G-enabled IoT in sustainable smart grid edge computing and the Metaverse. This component is intended to operate at 0.815/1.58/2.65 GHz for 5G applications. The physical layout of our triplexer is new, and it is presented for the first time in this work. The overall size of our triplexer is only 0.007 λg2, which is the smallest compared to the previous works. The proposed triplexer has very low insertion losses of 0.12 dB, 0.09 dB, and 0.42 dB at the first, second, and third channels, respectively. We achieved the minimum insertion losses compared to previous triplexers. Additionally, the common port return losses (RLs) were better than 26 dB at all channels.

Assessment of macronutrients status using digital soil mapping techniques: a case study in Maru'ak area in Lorestan Province, Iran.

The present study was conducted to compare generalized linear model (GLM), random forest (RF), and Cubist to produce available phosphorus (AP) and potassium (AK) maps and to identify the covariates that control mineral distribution in Lorestan Province, Iran. To this end, the locations for collecting 173 soil samples were determined through the conditioned Latin hypercube sampling (cLHS) method, at four different land-uses (orchards, paddy fields, agricultural, and abandoned fields). The performance of the models was assessed by coefficient of determination (R2), root-mean-square error (RMSE), and mean absolute error (MAE) indices. The results showed that the RF model fitted better than GLM and Cubist models and could explain 40 and 57% of AP and AK distribution, respectively. The R2, RMSE, and MAE of the RF model were 0.4, 2.81, and 2.43 for predicting AP and equal to 0.57, 143.77, and 116.61 for predicting AK, respectively. The most important predictors selected by the RF model were valley depth and soil-adjusted vegetation index (SAVI) for AP and AK, respectively. The maps showed higher AP and AK content in apricot orchards compared to other land-uses. No difference was observed between AP and AK content on paddy fields, agricultural, and abandoned areas. The higher AP and AK contents were related to orchard management practices, such as failure to dispose of plant residuals and fertilizer consumption. It can be concluded that the orchards (by increasing soil quality) was the best land-use in line with sustainable management for the study area. However, generalizing the results needs more detailed research.

Modeling the spatial variation of calcium carbonate equivalent to depth using machine learning techniques.

Inorganic carbon is the largest source of carbon in terrestrial surface, particularly in arid and semiarid regions, including the Chahardowli Plain in western Iran. Inorganic carbon plays an equal or greater role than organic soil carbon in these areas, although less attention has been paid in quantifying their variability. The objective of this study was to model and map calcium carbonate equivalent (CCE) presenting inorganic carbon in soil using machine learning and digital soil mapping techniques. Chahardowli Plain in foothills of the Zagros Mountains in the southeast of Kurdistan Province in Iran was taken as a case study area. CCE was measured at 0-5, 5-15, 15-30, 30-60, and 60-100 cm depths following GloalSoilMap.net project specifications. A total of 145 samples were collected from 30 soil profiles using the conditional Latin hypercube (cLHS) method of sampling. Relationships between CCE and environmental predictors were modeled using random forest (RF) and decision tree (DT) models. In general, the RF model performed slightly superior than the DT model. The mean value of CCE increased with soil depth, from 3.5% (0-5 cm) to 63.8% (30-60 cm). Remote sensing (RS) variables and terrestrial variables were equally important. The importance of RS variables was higher at the surface than terrestrial variables, and vice versa. The most significant variables were Channel Network Base Level (CNBL) variable and Difference Vegetation Index (DVI) with the same variable importance value (21.1%). In areas affected by river activities, the use of the CNBL and vertical distance to channel networks (VDCN) as variables in digital soil mapping (DSM) could increase the accuracy of soil property prediction maps. The VDCN played a principal role in soil distribution in the study area by affecting the rate of discharge and, thus, erosion and sedimentation. A high percentage of carbonate in parts of the region could exacerbate nutrient deficiencies for most crops and provide information for sustainably managing agricultural activity.

The Adsorption and Degradation of 2, 4-D Affected by Soil Organic Carbon and Clay.

More has yet to be indicated on the adsorption and degradation processes, determining herbicides recycling in the environment. The sorption and degradation of 2, 4-D, affected by organic carbon (1.92-2.81%), soil clay (20-30%) and pH of the citrus orchards of Mazandaran province, Iran was investigated using HPLC equipped with UV detector for the identification and quantification of soil 2, 4-D. The adsorption (kd) and degradation (Kdeg) coefficients were determined using Freundlich and the first-degree kinetic equations. Gardens C (2.45 mL g-1), and B (0.3 mL g-1), with the highest (8.2 g day-1) and least (2.7 g day-1) degradation coefficients, had the highest and lowest Kd values. Kd variations with pH indicated higher adsorption of 2, 4-D in acidic pH. Due to the high presence of functional groups and soil biological activities, organic carbon affected the adsorption and degradation rates more effectively, which is of economic and environmental significance.

d-Glycero-ß-d-mannoheptose Phosphate 7-O-Modifications.

Pathogen-associated molecular patterns activate the immune system via pattern recognition receptors. Recently, newly discovered pathogen-associated molecular patterns, d-glycero-ß-d-mannoheptose phosphate and d-glycero-ß-d-mannoheptose 1,7-biphosphate, were shown to induce a TRAF-interacting protein with a forkhead-associated domain-dependent immune response in human embryonic kidney cells and colonic epithelial cells. Concurrently, ADP-heptose was shown to bind α-kinase 1 and activate TIFA via phosphorylation leading to an immune cascade to ultimately activate NF-κB. These pathogen-associated molecular patterns have raised interest in the pharmaceutical industry for their potential use as immunomodulators. However, little is understood about the host cell uptake of d-glycero-ß-d-mannoheptose phosphate, d-glycero-ß-d-mannoheptose 1,7-biphosphate, and ADP-heptose in vivo and derivatives of these molecules are needed to interrogate this. In this regard, herein we describe 7-O-modifications of d-glycero-ß-d-mannoheptose phosphate to produce molecular probes toward the development of a useful toolbox for biologists. A convergent strategy that involves introduction of a substituent at O-7 before alkene oxidation was investigated and proved successful in the generation of a range of molecular probes.

Assessment of stability of sulphated lactosyl archaeol archaeosomes for use as a vaccine adjuvant.

Archaeosomes, composed of sulphated lactosyl archaeol (SLA) glycolipids, have been proven to be an effective vaccine adjuvant in multiple preclinical models of infectious disease or cancer. In addition to efficacy, the stability of vaccine components including the adjuvant is an important parameter to consider when developing novel vaccine formulations. To properly evaluate the potential of SLA glycolipids to be used as vaccine adjuvants in a clinical setting, a comprehensive evaluation of their stability is required. Herein, we evaluated the long term stability of preformed empty SLA archaeosomes prior to admixing with antigen at 4 °C or 37 °C for up to 6 months. In addition, the stability of adjuvant and antigen was evaluated for up to 1 month following admixing. Multiple analytical parameters evaluating the molecular integrity of SLA and the liposomal profile were assessed. Following incubation at 4 °C or 37 °C, the SLA glycolipid did not show any pattern of degradation as determined by mass spectroscopy, nuclear magnetic resonance (NMR) and thin layer chromatography (TLC). In addition, SLA archaeosome vesicle characteristics, such as size, zeta potential, membrane fluidity and vesicular morphology, were largely consistent throughout the course of the study. Importantly, following storage for 6 months at both 4 °C and 37 °C, the adjuvant properties of empty SLA archaeosomes were unchanged, and following admixing with antigen, the immunogenicity of the vaccine formulations was also unchanged when stored at both 4 °C and 37 °C for up to 1 month. Overall this indicates that SLA archaeosomes are highly stable adjuvants that retain their activity over an extended period of time even when stored at high temperatures.

Effects of triple combination of hydrocortisone, thiamine, and Vitamin C on clinical outcome in patients with septic shock: A single-center randomized controlled trial.

BACKGROUND: Recent studies suggest that hydrocortisone, Vitamin C, and thiamine alone or in combination may improve the clinical outcomes of patients with septic shock. The aim of this study is the effects of this combination therapy on clinical outcome and sepsis biomarkers in patients with septic shock. MATERIALS AND METHODS: Fifty-eight consecutive patients suffering septic shock were randomly assigned into two groups receiving the combination therapy of hydrocortisone (50 mg/6 h, intravenously), Vitamin C (1.5 g/6 h in 100 ml normal saline or DW5%, intravenously), and thiamine (200 mg/12 h in 50 ml normal saline or DW5%, intravenously) or placebo for up to 4 days. RESULTS: The decline in procalcitonin, lactate, and leukocyte count 72 h after the initiation of treatment was significantly greater in the intervention as compared to the control group. The intervention group has a significantly lower sequential organ failure assessment score 72 h after treatment (P < 0.001). The mean duration of vasopressor dependency was shorter in the intervention group (P = 0.039). In-hospital death occurred in 10.3% of the patients who received combination therapy and 37.9% in the control group (P = 0.014). CONCLUSION: The administration of the triple combination of hydrocortisone, thiamine, and Vitamin C appeared to be effective in improving the clinical outcomes of patients with septic shock and of reducing vasopressor requirements with a significant increase in the rate of improvement of sepsis biomarkers.

Combined Growth Factor and Gene Therapy: An Approach for Hair Cell Regeneration and Hearing Recovery.

INTRODUCTION: Fibroblast growth factor, nerve growth factor neurotrophins, and insulin-like growth factor 1 are considered 3 families of growth factors that can be involved in the process of otic neurogenesis. In this respect, otic neurons can also be connected with mechanoreceptors in the ear, the hair cells (HCs), as well as the central nervous system. As a growth factor is combined with gene transfer technology, it can be used for hair cell regeneration. Gene therapy can be similarly employed to introduce genes into a system in order to induce the expression of genes for therapeutic agents, to replace defective genes, or to re-program supporting or surrounding cells to acquire the phenotype of lost or damaged cells in order to repair or regenerate the damaged tissue. OBJECTIVE: The purpose of this review article was to investigate the epigenetic and growth factors involved in the differentiation pathway of embryonic stem cells (ESCs) into HCs and auditory neurons (ANs). METHODS: To this end, the databases of Directory of Open Access Journals, Google Scholar, PubMed (NLM), LISTA (EBSCO), as well as Web of Science were searched. RESULTS: Given the results available in the related literature, the differentiation efficacy of ESCs toward the ANs and the HCs, the important role of growth factors, and 3 different strategies of application of miRNA, epigenetic regulation, and preparation of three-dimensional (3D) environments were suggested to be taken into consideration in order to improve these studies in the future. Furthermore, the role of epige-netic mechanisms and miRNA in this differentiation process became quite obvious; hence, the utilization of such procedures in the near future would be significant. CONCLUSION: Combining several techniques with a synergic effect (such as growth factor gene therapy and 3D environments) seemed to lead to obtaining the best results as a therapeutic strategy.

On the Ability of Formaldehyde to Act as a Tethering Catalyst in Water.

The low concentration issue is a fundamental challenge when it comes to prebiotic chemistry, as macromolecular systems need to be assembled via intermolecular reactions, and this is inherently difficult in dilute solutions. This is especially true when the reactions are challenging, and reactions that proceeded more rapidly could have dictated chemical evolution. Herein we establish that formaldehyde is capable of catalyzing, via temporary intramolecularity, a challenging reaction in water at low concentrations, thus providing an alternative to other approaches that can either lead to higher concentrations or higher effective molarities.

Downregulation of miR-185 and upregulation of miR-218 expression may be potential diagnostic and prognostic biomarkers of human chondrosarcoma.

Increasing evidence has confirmed that dysregulation of microRNAs (miRNAs) can contribute to the progression and metastasis of human tumors. Chondrosarcoma is the most common primary malignant bone tumor in adults and has no effective systemic treatment, and patients with this disease have poor survival. Thus, it is important to find new diagnostic markers and improve treatment options. In the current study, we are interested to examine the role of miR-185 and miR-218 expression in patients with chondrosarcoma using real-time PCR. Moreover, the association of the two miRNAs with clinicopathological features and prognosis was evaluated. Survival and Cox proportional hazards analyses were performed to find the association of miR-185 expression and miR-218 levels with prognosis in the patients. Our results indicated that the miR-185 expression was significantly downexpressed in clinical chondrosarcoma bone tissues compared with adjacent normal tissues (P = 0.001). MiR-218 expression level was increased in clinical chondrosarcoma bone tissue than those adjacent normal tissues (P = 0.001). Decreased expression of miR-185 showed remarkable correlation with advanced tumor stage (P = 0.019), tumor grade (P < 0.001), and distant metastasis (P = 0.001). Moreover, high expression of miR-218 was strongly correlated with advanced tumor stage (P = 0.014), tumor grade (P < 0.001), and distant metastasis (P = 0.002). Kaplan-Meier survival analysis revealed that the low miR-185 expression group and the high miR-218 expression group had remarkably shorter overall survival (log-rank test P = 0.007, P = 0.004). The multivariate Cox proportional hazards model indicated that decreased expression of miR-185 and increased expression of miR-218 (P = 0.017, P = 0.012), advanced tumor stage (P = 0.006, P = 0.012), tumor grade (P = 0.032, P = 0.016), and distant metastasis (P = 0.004, P = 0.015) were independently related to overall survival in patients with chondrosarcoma. In conclusion, downregulation of miR-185 and upregulation of miR-218 can be associated with progression of chondrosarcoma and also both of them may act as tumor suppressor genes in chondrosarcoma.

Clinical outcome of en-block resection and reconstruction with nonvascularized fibular autograft for the treatment of giant cell tumor of distal radius.

BACKGROUND: Although giant cell tumor (GCT) is considered to be a primary benign bone tumor, its aggressive behavior makes its diagnosis and treatment, difficult and challenging. This is especially true in distal radius where GCT appears to be more aggressive and difficult to control locally. We report our clinical outcome of en-block resection and reconstruction with non-vascularized fibular autograft in 15 patients with distal radius GCT. MATERIALS AND METHODS: We retrospectively reviewed 15 patients with GCT (Grade 2 and 3) of distal radius who were treated with en-block resection and non-vascularized fibular autograft. Five of 15 were recurrent GCT treated initially with extended curettage; local adjuvant therapy and filling the cavity with cement or bone graft. We followed the patients for mean 7.2 years post operation (range: 4-11 years). Patients were evaluated post operation with clinical examination, plain radiography of distal radius and chest X-ray and/or computed tomography scan. Furthermore pain, function, range of motion and grip strength of the affected limb were evaluated and mMayo wrist score was assessed. RESULTS: A total of 11 patients were women and 4 were men. Mean age of patients was 29 years (range: 19-48). We had no lung metastasis and bony recurrence occurred in one patient (6.6%). Nearly 53.3% of patients had excellent or good functional wrist score, 80% of the patients were free of pain or had only occasional pain and 80% of patients returned to work. Mean range of motion of the wrist was 77° of flexion-extension and mean grip strength was 70% of the normal hand. CONCLUSION: En-block resection of distal radius GCT and reconstruction with non-vascularized fibular autograft is an effective technique for treatment in local control of the tumor and preserving function of the limb.

Optimization of the Synthesis and Conjugation of the Methyl Rhamnan Tip of Pseudomonas aeruginosa A-Band Polysaccharide and Immunogenicity Evaluation for the Continued Development of a Potential Glycoconjugate Vaccine.

Pseudomonas aeruginosa is an antimicrobial-resistant bacterium that has no vaccine approved for human use. Additionally, it has been identified by the World Health Organization as a priority pathogen for novel vaccines and therapeutic development. We previously developed a synthetic mimic of the A-band polysaccharide tip that showed promise in terms of immunogenicity for use as a glycoconjugate vaccine. In this current manuscript, we improve upon the previous work to continue the development of this glycoconjugate vaccine. Herein, we report a higher-yielding synthesis of mimics containing a handle and a spacer that improved conjugation efficiency, resulting in better carbohydrate-to-protein ratios and also good immunogenicity of these conjugates in mice and rabbits. The data suggested that perhaps only a tetrasaccharide was required to induce an immune response capable of recognizing whole cells of P. aeruginosa.

An octonion-based nonlinear echo state network for speech emotion recognition in Metaverse.

While the Metaverse is becoming a popular trend and drawing much attention from academia, society, and businesses, processing cores used in its infrastructures need to be improved, particularly in terms of signal processing and pattern recognition. Accordingly, the speech emotion recognition (SER) method plays a crucial role in creating the Metaverse platforms more usable​ and enjoyable for its users. However, existing SER methods continue to be plagued by two significant problems in the online environment. The shortage of adequate engagement and customization between avatars and users is recognized as the first issue and the second problem is related to the complexity of SER problems in the Metaverse as we face people and their digital twins or avatars. This is why developing efficient machine learning (ML) techniques specified for hypercomplex signal processing is essential to enhance the impressiveness and tangibility of the Metaverse platforms. As a solution, echo state networks (ESNs), which are an ML powerful tool for SER, can be an appropriate technique to enhance the Metaverse's foundations in this area. Nevertheless, ESNs have some technical issues restricting them from a precise and reliable analysis, especially in the aspect of high-dimensional data. The most significant limitation of these networks is the high memory consumption caused by their reservoir structure in face of high-dimensional signals. To solve all problems associated with ESNs and their application in the Metaverse, we have come up with a novel structure for ESNs empowered by octonion algebra called NO2GESNet. Octonion numbers have eight dimensions, compactly display high-dimensional data, and improve the network precision and performance in comparison to conventional ESNs. The proposed network also solves the weaknesses of the ESNs in the presentation of the higher-order statistics to the output layer by equipping it with a multidimensional bilinear filter. Three comprehensive scenarios to use the proposed network in the Metaverse have been designed and analyzed, not only do they show the accuracy and performance of the proposed approach, but also the ways how SER can be employed in the Metaverse platforms.

Patient effective dose and radiation biological risk in the chest and abdominopelvic computed tomography.

The incidence and mortality (per 100,000) rates in chest CT are highest for the lungs and breasts (incidence: lung = 116, breast = 98.64; mortality: lung = 113.43, breast = 49.72). Abdominopelvic CT scans showed the highest incidence for stomach (79.57), colon (62.86), bladder (48.69), and liver (28.63), respectively. Mortality is highest for the bladder (80.44), stomach (72.43), colon (69.02), and liver (63.78), respectively. This study helps to better understand the concept of radiation dose and the numbers reported as organ dose and effective dose and identify the probability of the stochastic effect.

Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation.

Advanced mathematical and deep learning (DL) algorithms have recently played a crucial role in diagnosing medical parameters and diseases. One of these areas that need to be more focused on is dentistry. This is why creating digital twins of dental issues in the metaverse is a practical and effective technique to benefit from the immersive characteristics of this technology and adapt the real world of dentistry to the virtual world. These technologies can create virtual facilities and environments for patients, physicians, and researchers to access a variety of medical services. Experiencing an immersive interaction between doctors and patients can be another considerable advantage of these technologies, which can dramatically improve the efficiency of the healthcare system. In addition, offering these amenities through a blockchain system enhances reliability, safety, openness, and the ability to trace data exchange. It also brings about cost savings through improved efficiencies. In this paper, a digital twin of cervical vertebral maturation (CVM), which is a critical factor in a wide range of dental surgery, within a blockchain-based metaverse platform is designed and implemented. A DL method has been used to create an automated diagnosis process for the upcoming CVM images in the proposed platform. This method includes MobileNetV2, a mobile architecture that improves the performance of mobile models in multiple tasks and benchmarks. The proposed technique of digital twinning is simple, fast, and suitable for physicians and medical specialists, as well as for adapting to the Internet of Medical Things (IoMT) due to its low latency and computing costs. One of the important contributions of the current study is to use of DL-based computer vision as a real-time measurement method so that the proposed digital twin does not require additional sensors. Furthermore, a comprehensive conceptual framework for creating digital twins of CVM based on MobileNetV2 within a blockchain ecosystem has been designed and implemented, showing the applicability and suitability of the introduced approach. The high performance of the proposed model on a collected small dataset demonstrates that low-cost deep learning can be used for diagnosis, anomaly detection, better design, and many more applications of the upcoming digital representations. In addition, this study shows how digital twins can be performed and developed for dental issues with the lowest hardware infrastructures, reducing the costs of diagnosis and treatment for patients.

Metaverse and Healthcare: Machine Learning-Enabled Digital Twins of Cancer.

Medical digital twins, which represent medical assets, play a crucial role in connecting the physical world to the metaverse, enabling patients to access virtual medical services and experience immersive interactions with the real world. One serious disease that can be diagnosed and treated using this technology is cancer. However, the digitalization of such diseases for use in the metaverse is a highly complex process. To address this, this study aims to use machine learning (ML) techniques to create real-time and reliable digital twins of cancer for diagnostic and therapeutic purposes. The study focuses on four classical ML techniques that are simple and fast for medical specialists without extensive Artificial Intelligence (AI) knowledge, and meet the requirements of the Internet of Medical Things (IoMT) in terms of latency and cost. The case study focuses on breast cancer (BC), the second most prevalent form of cancer worldwide. The study also presents a comprehensive conceptual framework to illustrate the process of creating digital twins of cancer, and demonstrates the feasibility and reliability of these digital twins in monitoring, diagnosing, and predicting medical parameters.

Vascular synthesis based on hemodynamic efficiency principle recapitulates measured cerebral circulation properties in the human brain.

Quantifying anatomical and hemodynamical properties of the brain vasculature in vivo is difficult due to limited spatiotemporal resolution neuroimaging, variability between subjects, and bias between acquisition techniques. This work introduces a metabolically inspired vascular synthesis algorithm for creating a digital representation of the cortical blood supply in humans. Spatial organization and segment resistances of a cortical vascular network were generated. Cortical folding and macroscale arterial and venous vessels were reconstructed from anatomical MRI and MR angiography. The remaining network, including ensembles representing the parenchymal capillary bed, were synthesized following a mechanistic principle based on hydrodynamic efficiency of the cortical blood supply. We evaluated the digital model by comparing its simulated values with in vivo healthy human brain measurements of macrovessel blood velocity from phase contrast MRI and capillary bed transit times and bolus arrival times from dynamic susceptibility contrast. We find that measured and simulated values reasonably agree and that relevant neuroimaging observables can be recapitulated in silico. This work provides a basis for describing and testing quantitative aspects of the cerebrovascular circulation that are not directly observable. Future applications of such digital brains include the investigation of the organ-wide effects of simulated vascular and metabolic pathologies.