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Abstract Background The most prevalent persistent parenchymatous liver alterations in healthy individuals are thought to be hepatic steatosis. The liver biopsy is the most crucial procedure for the identification and measurement of hepatic steatosis. By identifying the liver attenuation index (LAI) at CT image with fibroscan controlled attenuation parameter (CAP), hepatic steatosis can be evaluated without the risk of liver resection. Objective Using liver biopsy histological analysis as a reference standard, to examine the precision of the CT liver attenuation index (LAI) and fibroscan controlled attenuation parameter (CAP) for quantitative evaluation of macrovesicular steatosis in living related liver donors. Methods In this cross-sectional study, comparing the CT liver attenuation index & fibroscan controlled attenuation parameter with liver biopsy result for the detection of the steatosis in subject's candidate for liver living donors, 50 subjects were conducted at Ain Shams Specialized Hospital and other private hospitals over about 2 years. Results Our study reported that liver attenuation index of 9 is the cutoff value in post-contrast CT images with sensitivity 100% and specificity 80% that make it a very good method to exclude donor to have steatosis ≥ 15%, which mean that if donor had LAI index

Background and objectives. Cervical spondylosis is an age-related condition that influences the various components of the spine. Attributed to its exceptional tissue contrast, magnetic resonance imaging (MRI) is the preferred diagnostic modality for assessing cervical spondylosis. Dynamic MRI examination adds diagnostic information obtained from imaging the patient in flexion and extension. Our study had the purpose of evaluating the flexion-extension MRI’s diagnostic utility. Materials and methods. 40 patients with cervical spondylosis joined our prospective cross-sectional study. The patients were examined by flexion and extension sagittal T2 weighted images (Dynamic MRI) in addition to static MRI cervical spine protocol. The study was carried out in our department and lasted for two years. Results. Total central spinal stenosis (TCSS) was considerably higher in extension in comparison to neutral MRI (Mean ± SD =6.1± 1.45 compared to 4.7 ± 1.29) (p

Abstract The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work—a possibility that has sparked ample discussion on the integrity of student evaluation processes in the age of artificial intelligence (AI). To date, it is unclear how such tools perform compared to students on university-level courses across various disciplines. Further, students’ perspectives regarding the use of such tools in school work, and educators’ perspectives on treating their use as plagiarism, remain unknown. Here, we compare the performance of the state-of-the-art tool, ChatGPT, against that of students on 32 university-level courses. We also assess the degree to which its use can be detected by two classifiers designed specifically for this purpose. Additionally, we conduct a global survey across five countries, as well as a more in-depth survey at the authors’ institution, to discern students’ and educators’ perceptions of ChatGPT’s use in school work. We find that ChatGPT’s performance is comparable, if not superior, to that of students in a multitude of courses. Moreover, current AI-text classifiers cannot reliably detect ChatGPT’s use in school work, due to both their propensity to classify human-written answers as AI-generated, as well as the relative ease with which AI-generated text can be edited to evade detection. Finally, there seems to be an emerging consensus among students to use the tool, and among educators to treat its use as plagiarism. Our findings offer insights that could guide policy discussions addressing the integration of artificial intelligence into educational frameworks.

Summary: Pancreatic islets regulate blood glucose homeostasis through the controlled release of insulin; however, current metabolic models of glucose-sensitive insulin secretion are incomplete. A comprehensive understanding of islet metabolism is integral to studies of endocrine cell development as well as diabetic islet dysfunction. Human pluripotent stem cell-derived islets (SC-islets) are a developmentally relevant model of human islet function that have great potential in providing a cure for type 1 diabetes. Using multiple 13C-labeled metabolic fuels, we demonstrate that SC-islets show numerous divergent patterns of metabolite trafficking in proposed insulin release pathways compared with primary human islets but are still reliant on mitochondrial aerobic metabolism to derive function. Furthermore, reductive tricarboxylic acid cycle activity and glycolytic metabolite cycling occur in SC-islets, suggesting that non-canonical coupling factors are also present. In aggregate, we show that many facets of SC-islet metabolism overlap with those of primary islets, albeit with a retained immature signature.

The TYK2 gene is associated with development of type 1 diabetes. Here the authors show that TYK2 regulates β-cell development, but at the same time TYK2 inhibition in the islets prevents IFNα responses and enhances their survival against CD8+ T-cell cytotoxicity; representing a potent therapeutic target to halt T1D progression.

Type 1 diabetes (T1D) is a disease of both autoimmunity and β-cells. The β-cells play an active role in their own demise by mounting defense mechanisms that are insufficient at best, and that can become even deleterious in the long term. This complex crosstalk is important to understanding the physiological defense mechanisms at play in healthy conditions, their alterations in the T1D setting, and therapeutic agents that may boost such mechanisms. Robust protocols to develop stem-cell-derived islets (SC-islets) from human pluripotent stem cells (hPSCs), and islet-reactive cytotoxic CD8+ T-cells from peripheral blood mononuclear cells offer unprecedented opportunities to study this crosstalk. Challenges to develop in vitro β-cell killing models include the cluster morphology of SC-islets, the relatively weak cytotoxicity of most autoimmune T-cells and the variable behavior of in vitro expanded CD8+ T-cells. These challenges may however be highly rewarding in light of the opportunities offered by such models. Herein, we discuss these opportunities including: the β-cell/immune crosstalk in an islet microenvironment; the features that make β-cells more sensitive to autoimmunity; therapeutic agents that may modulate β-cell vulnerability; and the possibility to perform analyses in an autologous setting, i.e., by generating T-cell effectors and SC-islets from the same donor.

Summary: We present here a robust and reliable protocol by which to differentiate pancreatic islet-like aggregates (SC-islets) from human pluripotent stem cells. The 7-stage protocol mimics developmental patterning factors that induce endocrine lineage formation and spans monolayer, microwell, and aggregate suspension culture. The SC-islets demonstrate dynamic glucose-sensitive insulin secretion and an endocrine cell composition similar to those of primary human islets. SC-islets generated using this optimized protocol are suitable for in vitro modeling of islet cell pathophysiology and therapeutic applications.For complete details on the use and execution of this protocol, please refer to Balboa et al. (2022). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Using stochastic geometry tools, we develop a systematic framework to characterize the meta distributions of the downlink SIR/SNR and data rate of the typical device in a cellular network with coexisting sub-6GHz and millimeter wave (mm-wave) spectrums. Macro base-stations (MBSs) transmit on sub-6GHz channels (which we term “microwave” channels), whereas small base-stations (SBSs) communicate with devices on mm-wave channels. The SBSs are connected to MBSs via a microwave (μwave) wireless backhaul. The μwave channels are interference limited and mm-wave channels are noise limited; therefore, we have the meta distribution of SIR and SNR in μwave and mm-wave channels, respectively. To model the line-of-sight (LOS) nature of mm-wave channels, we use Nakagami-m fading model. To derive the meta distribution of SIR/SNR, we characterize the conditional success probability (CSP) (or equivalently reliability) and its bth moment for the typical device (a) when it associates to a μwave MBS for direct transmission, and (b) when it associates to a mm-wave SBS for dual-hop transmission (backhaul and access transmission). Performance metrics such as the mean and variance of the local delay (network jitter), mean of the CSP (coverage probability), and variance of the CSP are derived. Closedform expressions are presented for special scenarios. The extensions of the developed framework to the μwave-only network or mm-wave only networks where SBSs have mm-wave backhauls are discussed. Numerical results validate the analytical results. Insights are extracted related to the reliability, coverage probability, and latency of the considered network.

Abstract Background Chronic renal failure is one of the main health problems in Egypt. Arterio-venous fistulas, grafts, as well as conventional sites for placement of the dialysis catheters are liable to thrombosis; stenosis, and occlusions, so alternative routes are considered as life-saving ways in such cases. Transhepatic permcath is one of the new and up to date methods for inferior vena cava and right atrium catheterization. Few studies with rather limited nomber are available to evaluate transhepatic permcath. The aim of our study is to emphasize the technique, complications, and efficacy of application of percutaneous transhepatic hemodialysis catheters. Results Two hundred-ninety six chronic renal dialysis patients were included in this prospective interventional study. They include 180 males and 116 females with mean age of 53.2 years ± 11.7 years ranging from 38 to 65 years. Percutaneous transhepatic hemodialysis catheters were inserted for all patients. Technical success of the procedure was achieved in all cases (100%). Post-procedure patency and function of the catheters were followed up with mean follow-up period 750 days. Mean of primary and secondary devices service intervals were 290 and 270 days respectively. Mean time catheter in situ was 280 days. Mean cumulative duration of catheter in situ was 557 days. Catheters migration, sepsis, thrombosis, and exit site infection rates were 0.14, 0.15, 0.18, and 0.32 per 100 catheter-days respectively. Three patients had hepatic subcapsular hematoma (1%). No mortality or other complications were related to the procedure. Conclusions Combined ultrasound and fluoroscopic-guided transhepatic permanent dialysis catheter application for patients with exhausted classic venous access routes and non-functioning/thrombosed AV fistulas or grafts showed excellent technical success with good short and mid-term patency rates and low complications rates. Thus, this study encourages us to expand this promising technique for application of dialysis catheter in indicated cases.

Summary: Background: Posttraumatic dorsal hand defects with exposed tendons and/or bones represent a challenge to reconstructive surgeons. Many options are suggested ranging from local, regional, distant up to free flaps. First dorsal metacarpal artery island flap was commonly prescribed for reconstructing the thumb or first web space defects. Methods: During a 30 month's period, 23 patients, 15 males aged between 17 and 48 years and 8 females aged between 18 and 36 years presented by posttraumatic dorsal hand defects. Of them 18 had both exposed tendons and bones while 5 had exposed tendons only. The defects dimensions ranged between 3 × 4 cm and 4.5 × 6 cm. All defects were reconstructed by using a single stage first dorsal metacarpal artery island flaps. Results: All flaps survived completely without complication during the mean follow up period of 2 years. All patients were very satisfied both functionally and aesthetically by the procedure. Conclusion: Island first dorsal metacarpal artery flap is a good option for reconstructing mild to moderate dorsal hand defects with acceptable functional and cosmetic results. Keywords: Dorsal hand, Defects, Flap, Island first dorsal metacarpal, Reconstruction

Remote monitoring of a fall condition or activities and daily life (ADL) of elderly patients has become one of the essential purposes for modern telemedicine. Internet of Things (IoT) and artificial intelligence (AI) techniques, including machine and deep learning models, have been recently applied in the medical field to automate the diagnosis procedures of abnormal and diseased cases. They also have many other applications, including the real-time identification of fall accidents in elderly patients. The goal of this article is to review recent research whose focus is to develop AI algorithms and methods of fall detection systems (FDS) in the IoT environment. In addition, the usability of different sensor types, such as gyroscopes and accelerometers in smartwatches, is described and discussed with the current limitations and challenges for realizing successful FDSs. The availability problem of public fall datasets for evaluating the proposed detection algorithms are also addressed in this study. Finally, this article is concluded by proposing advanced techniques such as lightweight deep models as one of the solutions and prospects of futuristic smart IoT-enabled systems for accurate fall detection in the elderly.

Mitochondrial intermembrane space proteins CHCHD2 and CHCHD10 have roles in motor neuron diseases such as amyotrophic lateral sclerosis, spinal muscular atrophy and axonal neuropathy and in Parkinson's disease. They form a complex of unknown function. Here we address the importance of these two proteins in human motor neurons. We show that gene edited human induced pluripotent stem cells (iPSC) lacking either CHCHD2 or CHCHD10 are viable and can be differentiated into functional motor neurons that fire spontaneous and evoked action potentials. Mitochondria in knockout iPSC and motor neurons sustain ultrastructure but show increased proton leakage and respiration, and reciprocal compensatory increases in CHCHD2 or CHCHD10. Knockout motor neurons have largely overlapping transcriptome profiles compared to isogenic control line, in particular for synaptic gene expression. Our results show that the absence of either CHCHD2 or CHCHD10 alters mitochondrial respiration in human motor neurons, inducing similar compensatory responses. Thus, pathogenic mechanisms may involve loss of synaptic function resulting from defective energy metabolism.

Object tracking is one of the major tasks for mobile robots in many real-world applications. Also, artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot navigation. In contrast to previous simulation studies, this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue (RGB) colored objects in a real experimental field. Moreover, a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative (PID) schemes to achieve accurate tracking results, considering robot command delay and tolerance errors. The design of developed controllers implies some motion rules to mimic the knowledge of experienced operators. Twelve scenarios of three colored object combinations have been successfully tested and evaluated by using the developed controlled image-based robot tracker. Classical PID control failed to handle some tracking scenarios in this study. The proposed adaptive fuzzy PID control achieved the best accurate results with the minimum average final error of 13.8 cm to reach the colored targets, while our designed custom PID control is efficient in saving both average time and traveling distance of 6.6 s and 14.3 cm, respectively. These promising results demonstrate the feasibility of applying our developed image-based robotic system in a colored object-tracking environment to reduce human workloads. [ABSTRACT FROM AUTHOR]

Falling is among the most harmful events older adults may encounter. With the continuous growth of the aging population in many societies, developing effective fall detection mechanisms empowered by machine learning technologies and easily integrable with existing healthcare systems becomes essential. This paper presents a new healthcare Internet of Health Things (IoHT) architecture built around an ensemble machine learning-based fall detection system (FDS) for older people. Compared to deep neural networks, the ensemble multi-stage random forest model allows the extraction of an optimal subset of fall detection features with minimal hyperparameters. The number of cascaded random forest stages is automatically optimized. This study uses a public dataset of fall detection samples called SmartFall to validate the developed fall detection system. The SmartFall dataset is collected based on the acquired measurements of the three-axis accelerometer in a smartwatch. Each scenario in this dataset is classified and labeled as a fall or a non-fall. In comparison to the three machine learning models—K-nearest neighbors (KNN), decision tree (DT), and standard random forest (SRF), the proposed ensemble classifier outperformed the other models and achieved 98.4% accuracy. The developed healthcare IoHT framework can be realized for detecting fall accidents of older people by taking security and privacy concerns into account in future work. [ABSTRACT FROM AUTHOR]

This article introduces a new medical internet of things (IoT) framework for intelligent fall detection system of senior people based on our proposed deep forest model. The cascade multi-layer structure of deep forest classifier allows to generate new features at each level with minimal hyperparameters compared to deep neural networks. Moreover, the optimal number of the deep forest layers is automatically estimated based on the early stopping criteria of validation accuracy value at each generated layer. The suggested forest classifier was successfully tested and evaluated using a public SmartFall dataset, which is acquired from three-axis accelerometer in a smartwatch. It includes 92781 training samples and 91025 testing samples with two labeled classes, namely non-fall and fall. Classification results of our deep forest classifier demonstrated a superior performance with the best accuracy score of 98.0% compared to three machine learning models, i.e., K-nearest neighbors, decision trees and traditional random forest, and two deep learning models, which are dense neural networks and convolutional neural networks. By considering security and privacy aspects in the future work, our proposed medical IoT framework for fall detection of old people is valid for real-time healthcare application deployment. [ABSTRACT FROM AUTHOR]

Background: The most prevalent persistent parenchymatous liver alterations in healthy individuals are thought to be hepatic steatosis. The liver biopsy is the most crucial procedure for the identification and measurement of hepatic steatosis. By identifying the liver attenuation index (LAI) at an unenhanced CT image, hepatic steatosis can be evaluated without the risk of liver resection. Objective: Using liver biopsy histological analysis as a reference standard, to examine the precision of the CT liver attenuation index (LAI) and fibroscan controlled attenuation parameter (CAP) for quantitative evaluation of macro vesicular steatosis in living related liver donors. Methods: In this study comparing CT liver attenuation index & fibroscan controlled attenuation parameter with liver pathology of steatosis in subject's candidate for liver living donors 50 subjects in each two study's correlation with biopsy results, conducted at Ain Shams Shams Specialized hospital and other Private hospitals over about 2 years. Results: Our study reported that liver - spleen attenuation index of 9 is the cutoff value with sensitivity 100% and specificity 80% that make it a very good method to exclude donor to have steatosis ≥15%, which mean if donor had LS index < 9 we can safely do proceed do liver biopsy. Our study reported that CAP measurement had an AUROC OF 0.780, for detecting steatosis ≥ 15 %, with sensitivity is only 60% with specificity as CT LAI of 80%, which consider low compared to other study, that could be due to small number of donors in out study with steatosis ≥ 15 % (5 case from 50 donors) unlike the other studies. Conclusion: When used to estimate the amount of liver fat in liver donors, the examined CAP and CT indices worked equally. But according to multivariate analysis, the only factor strongly linked with hepatic steatosis in alive donors was the CT L-S attenuation index. We contend that the combination of CT L-S attenuation index and CAP allows for the detection of the degree of hepatic steatosis and can be used as an option to liver biopsy, reserving liver biopsy for those with positive steatosis donors. [ABSTRACT FROM AUTHOR]