Current Conventional Techniques Research Articles

IDMap: Leveraging AI and Data Technologies for Early Cancer Detection

Cancer screening is vital in cutting mortality rates, and containing the impact of cancer in a worldwide basis. The current conventional detection techniques including imaging and biopsy though efficient are also characterized with drawbacks like; invasive, expensive, and inaccurate. This abstract will describe the new AI and data solution in the fight against early cancer detection, which presents a massive opportunity to improve accuracy, cut down the time that it takes to deliver a diagnosis, and bring quality health care to possibly millions of patients. ML and, in particular, DL are prospective in terms of decision making upon medical data including imaging, genomic sequences, and electronic health records to detect biomarkers of cancer in early stages. The statistics show that the AI-driven systems are capable to provide better diagnostic outcomes than conventional methods in some fields including mammography for breast cancer and CT for lung. Moreover, AI’s integration in genomic studies helps in determining Cancer related genes and biomarkers hence supporting precision medicine that adapts treatment to the specific genetic information of the patient. Apart from having outlets in AI, big data analytics, cloud computing, and IoT are equally important in early cancer detection as well. Big data analysis enables the analysis of large and complicated data sets with the aid of which one may identify inklings that may point towards possible early development of cancer. The use of cloud computing in health care mainly provides meaningful platforms for the storage and management of the large volumes of medical data in a way that allows improved efficiency and high levels of security. Wearable sensors collect data on different biomarkers throughout a patient’s body, and convey real-time information regarding whether the biomarkers’ levels are approaching cancerous state. Despite this great promise, there are various issues that have to be solved: data protection, privacy, and security, problems with the algorithms’ biases, and integration into practice. Ethical questions are generally important to tackle the uncertainty surrounding data and decision-making in clinical care using A I systems. The future trends in early cancer diagnostics will involve deeper integration of the approaches as AI and big data technology, which will enable more precise prevention and treatment. The applicability of this approach can also extend to the early identification of cancer, but also the prevention of its occurrence through proper intervention. In conclusion, conversing AI and data technologies will be useful for enhancing the efficiency of the early cancer diagnosis, and that is why the perspectives for the patients’ recovery and the further decrease in the mortality rates connected with cancer are rather promising. The approaches in this area remain informative developing technologies that are likely to be integrated into clinical work as the leading organizational models for the future of oncology and preventive health.

Numerical Analysis of Aluminium Façade Components

This paper commences with a scientific literature review of current research that underlines the environmental benefits to be gained from using smaller quantities of raw materials in the construction industry, with particular emphasis on a sustainable approach to façade design. Life cycle assessment modelling is advocated to validate the sustainability of building structures to achieve optimal solutions. A real-life application of the design of an aluminium façade bracket is presented, demonstrating that a weight reduction of up to 35-45% is attainable by exploiting the post-elastic properties of a material. The work described ranges from a discussion of the current conventional numerical techniques adopted by the industry to the most recent and advanced computational methods permitted by the introduction of Eurocode 9. This code facilitates a substantial enhancement in structural performance by incorporating an evaluation of the material's elastic-hardening behaviour and allows for a noteworthy reduction in component size and increased geometric design flexibility.

Deep Learning-Inspired IoT-IDS Mechanism for Edge Computing Environments.

The Internet of Things (IoT) technology has seen substantial research in Deep Learning (DL) techniques to detect cyberattacks. Critical Infrastructures (CIs) must be able to quickly detect cyberattacks close to edge devices in order to prevent service interruptions. DL approaches outperform shallow machine learning techniques in attack detection, giving them a viable alternative for use in intrusion detection. However, because of the massive amount of IoT data and the computational requirements for DL models, transmission overheads prevent the successful implementation of DL models closer to the devices. As they were not trained on pertinent IoT, current Intrusion Detection Systems (IDS) either use conventional techniques or are not intended for scattered edge-cloud deployment. A new edge-cloud-based IoT IDS is suggested to address these issues. It uses distributed processing to separate the dataset into subsets appropriate to different attack classes and performs attribute selection on time-series IoT data. Next, DL is used to train an attack detection Recurrent Neural Network, which consists of a Recurrent Neural Network (RNN) and Bidirectional Long Short-Term Memory (LSTM). The high-dimensional BoT-IoT dataset, which replicates massive amounts of genuine IoT attack traffic, is used to test the proposed model. Despite an 85 percent reduction in dataset size made achievable by attribute selection approaches, the attack detection capability was kept intact. The models built utilizing the smaller dataset demonstrated a higher recall rate (98.25%), F1-measure (99.12%), accuracy (99.56%), and precision (99.45%) with no loss in class discrimination performance compared to models trained on the entire attribute set. With the smaller attribute space, neither the RNN nor the Bi-LSTM models experienced underfitting or overfitting. The proposed DL-based IoT intrusion detection solution has the capability to scale efficiently in the face of large volumes of IoT data, thus making it an ideal candidate for edge-cloud deployment.

First Argentine database for the accurate identification of Brucella to species level by MALDI-TOF MS

MALDI-TOF mass spectrometry (MS) has proven to be a fast and reliable method for the identification of a large number of taxonomic groups. It offers the advantage of being able to incorporate protein spectra of microorganisms that are absent or poorly represented in commercial databases, such as the genus Brucella. The aim of the study was to build the first database of protein spectra of local biological variants of Brucella in Argentina and of standard strains. First, the identification performance of a panel of 135 strains was evaluated with the Swedish database ¨Folkhälsomyndigheten¨ (containing protein spectra of several international standards of the genus Brucella) imported from the open access site https://spectra.folkhalsomyndigheten.se/spectra/. With this library 100 % of the strains were correctly identified by mass spectrometry to genus level, but not to species level.Due to the limitation found, an in-house database was designed with local Brucella isolates from Argentina and standard strains used in routine bacteriological diagnosis. For its validation, a panel of strains, different from those used to develop the extended local database (n: 177), was used to, simultaneously, challenge both libraries. The samples were processed by triplicate and the results obtained were: 177 strains correctly identified to genus and species level compared to the gold standard method (phenotypic typing), meeting the criteria accepted by the literature and the manufacturer as reliable identification. Only 2 of these isolates had score values lower than 2 (1.862) and were therefore not included in the calculation of results.According to these results, MALDI-TOF MS is a fast and reliable method for the routine identification of the different Brucella species, and even has the advantage of reducing the time of exposure to pathogenic microorganisms for laboratorians. It could be considered a valuable technique to replace, in the near future, the current conventional techniques due to the ease of transferring protein spectra, avoiding the use of reference strains that are difficult to find commercially available and commonly used in phenotypic typing.

Conventional manual technique of post placental IUD insertion versus intra-cesarean post placental introducer withdrawal IUD insertion technique: a new standardized technique for IUD insertion during cesarean section: a randomized controlled trial

BackgroundInserting IUDs during cesarean section reduces the need for more manipulation and discomfort. The current conventional manual technique for IUD insertion during cesarean section is not standardized with many modifications and high rates of expulsion, displacement, missed threads, and discontinuation. This study aims to find a standard technique for IUD insertion during cesarean section with the least possible problems, especially displacement and missed threads.MethodsA randomized controlled study was conducted at Kasr Al-Ainy Maternity Hospital, Cairo University, Egypt. The study was performed over 12 months, from September 2020 to September 2021. Two groups of patients were selected; each group included 420 patients with a desire for IUD insertion during cesarean section. Group (A) (Control group) was subjected to a post-placental intrauterine device (Copper T380) during cesarean section using a conventional manual method; Group (B) (Study group): the IUD (Copper T380) was placed at the top of the uterine fundus using a new technique (intra-cesarean post placental introducer withdrawal IUD insertion technique).ResultsThere was a significant statistical difference between the two groups regarding displacement of the IUDs at the end of puerperium, at 6 months, non-visibility of IUD threads, and continuation of use with p-value < 0.05. There was no significant statistical difference in the term of duration of surgery.ConclusionThe new technique of post-placental IUD insertion can be the standard technique of intra-cesarean section IUD insertion as it is associated with more favorable outcomes among the included women in the form of lower incidence of IUD displacement, non-visibility of IUD threads, and higher rates of continuation without increasing the duration of surgery as compared with the conventional manual technique.Trial registrationClinicalTrial.gov ID: NCT05788354, registration date: 28/03/2023 (retrospectively registered).

Unexpected decrease of full-length prion protein in macaques inoculated with prion-contaminated blood products.

The presence of prion infectivity in the blood of patients affected by variant Creutzfeldt-Jakob disease (v-CJD), the human prion disease linked to the bovine spongiform encephalopathy (BSE), poses the risk of inter-human transmission of this fatal prion disease through transfusion. In the frame of various experiments, we have previously described that several cynomolgus macaques experimentally exposed to prion-contaminated blood products developed c-BSE/v-CJD, but the vast majority of them developed an unexpected, fatal disease phenotype focused on spinal cord involvement, which does not fulfill the classical diagnostic criteria of v-CJD. Here, we show that extensive analyses with current conventional techniques failed to detect any accumulation of abnormal prion protein (PrPv-CJD) in the CNS of these myelopathic animals, i.e., the biomarker considered responsible for neuronal death and subsequent clinical signs in prion diseases. Conversely, in the spinal cord of these myelopathic primates, we observed an alteration of their physiological cellular PrP pattern: PrP was not detectable under its full-length classical expression but mainly under its physiological terminal-truncated C1 fragment. This observed disappearance of the N-terminal fragment of cellular PrP at the level of the lesions may provide the first experimental evidence of a link between loss of function of the cellular prion protein and disease onset. This original prion-induced myelopathic syndrome suggests an unexpected wide extension in the field of prion diseases that is so far limited to pathologies associated with abnormal changes of the cellular PrP to highly structured conformations.

Incorporating quartz crystal microbalance with chronoamperometry to enhance manganese detection stability in drinking water

Mn was previously considered a mere esthetic issue in drinking water; however, excessive Mn exposure has been linked to negative effects on children's neurological development. Current conventional laboratory techniques are constrained in their ability to provide real-time measurement of Mn release events, due to expensive bench-sized instrumentation and lengthy turn-around times. Herein, we developed and investigated the working principle and application of a portable and rapid electrochemical method to detect Mn2+ in drinking water. The method employs quartz crystal microbalance (QCM) integrated with chronoamperometry (CA) to measure charge transfer and weight change during Mn2+ oxidation. The deposition of MnO2 is characterized by electrochemical methods, SEM, EDS and QCM. The CA-QCM calibration curves were determined in Milli-Q water and a real drinking water sample with a detection limit of 12.9 µM in drinking water sample. Additionally, an effective cleaning procedure was developed to regenerate the sensor after use. The CA-QCM technique demonstrated higher reproducibility and interference resistance than other conventional electrochemical methods in the presence of common drinking water components, as well as an excellent recovery rate (101.7%) in a real drinking water sample.

Advanced cross-sectional imaging of cerebral aneurysms.

While the rupture rate of cerebral aneurysms is only 1% per year, ruptured aneurysms are associated with significant morbidity and mortality, while aneurysm treatments have their own associated risk of morbidity and mortality. Conventional markers for aneurysm rupture include patient-specific and aneurysm-specific characteristics, with the development of scoring systems to better assess rupture risk. These scores, however, rely heavily on aneurysm size, and their accuracy in assessing risk in smaller aneurysms is limited. While the individual risk of rupture of small aneurysms is low, due to their sheer number, the largest proportion of ruptured aneurysms are small aneurysms. Conventional imaging techniques are valuable in characterizing aneurysm morphology; however, advanced imaging techniques assessing the presence of inflammatory changes within the aneurysm wall, hemodynamic characteristics of blood flow within aneurysm sacs, and imaging visualization of irregular aneurysm wall motion have been used to further determine aneurysm instability that otherwise cannot be characterized by conventional imaging techniques. The current manuscript reviews conventional imaging techniques and their value and limitations in cerebral aneurysm characterization, and evaluates the applications, value and limitations of advanced aneurysm imaging and post-processing techniques including intracranial vessel wall MRA, 4D-flow, 4D-CTA, and computational fluid dynamic simulations.

The status of fertility control for rodents-recent achievements and future directions.

Management of overabundant rodents at a landscape scale is complex but often required to sustainably reduce rodent abundance below damage thresholds. Current conventional techniques such as poisoning are not species specific, with some approaches becoming increasingly unacceptable to the general public. Fertility control, first proposed for vertebrate pest management over 5 decades ago, has gained public acceptance because it is perceived as a potentially more species-specific and humane approach compared with many lethal methods. An ideal fertility control agent needs to induce infertility across one or more breeding seasons, be easily delivered to an appropriate proportion of the population, be species specific with minimal side-effects (behavioral or social structure changes), and be environmentally benign and cost effective. To date, effective fertility control of rodents has not been demonstrated at landscape scales and very few products have achieved registration. Reproductive targets for fertility control include disrupting the hormonal feedback associated with the hypothalamic-pituitary-gonadal axis, gonad function, fertilization, and/or early implantation. We review progress on the oral delivery of various agents for which laboratory studies have demonstrated efficacy in females and/or males and synthesize progress with the development and/or use of synthetic steroids, plant extracts, ovarian specific peptides, and immunocontraceptive vaccines. There are promising results for field application of synthetic steroids (levonorgestrel, quinestrol), chemosterilants (4-vinylcyclohexene diepoxide), and some plant extracts (triptolide). For most fertility control agents, more research is essential to enable their efficient and cost-effective delivery such that rodent impacts at a population level are mitigated and food security is improved.

Construction of reliable image captioning system for web camera based traffic analysis on road transport application

The automated captioning of natural images with appropriate descriptions is an intriguing and complicated task in the field of image processing. On the other hand, Deep learning, which combines computer vision with natural language, has emerged in recent years. Image emphasization is a record file representation that allows a computer to understand the visual information of an image in one or more words. When it comes to connecting high-quality images, the expressive process not only requires the credentials of the primary item and scene but also the ability to analyse the status, physical characteristics, and connections. Many traditional algorithms substitute the image to the front image. The image characteristics are dynamic depending on the ambient condition of natural photographs. Image processing techniques fail to extract several characteristics from the specified image. Nonetheless, four properties from the images are accurately described by using our proposed technique. Based on the various filtering layers in the convolutional neural network (CNN), it is an advantage to extract different characteristics. The caption for the image is based on long short term memory (LSTM), which comes under recurrent neural network. In addition, the precise subtitling is compared to current conventional techniques of image processing and different deep learning models. The proposed method is performing well in natural images and web camera based images for traffic analysis. Besides, the proposed algorithm leverages good accuracy and reliable image captioning.

Enhanced in vitro Shoot Regeneration and Biochemical Properties of Stevia rebaudiana using Chitosan

Stevia rebaudiana is a herbaceous perennial plant with great global demand due to its beneficial steviol glycosides(SGs) content. Current conventional breeding technique is unable to cater the need for more S. rebaudiana planting materials. Therefore, an improved in vitro shoot regeneration protocol was developed for S. rebaudiana by using chitosan. The highest fresh weight of plant (0.586 ± 0.176 g/explant), dry weight of plant (0.056 ± 0.02 g/explant) and plant height (4.94 ± 1.17 cm/explant) with maximum number of leaves (25.33 ± 6.95 /explant) were observed on explants grown in optimun treatment of MS basal medium supplemented with 1.0 mg/L of 6-benzyaminopurine (BAP) and 60 mg/L of low molecular weight (MW) chitosan after 4 weeks of culture. Scanning electron microscopy (SEM) analysis showed that new shoot primordia and shoot bud formation can be seen as early as day 3 and 5 of cultures on optimun treatment. Further biochemical assays showed that total phenolic acid content, total protein content and total hydrolyzed sugar content were recorded higher in explants cultured in optimun treatment as compared to control media. In contrast, total chlorophyll content and total flavonoids content were reduced in optimum treatment. Meanwhile, no significant difference in antioxidant activity was observed. All cultures from the optimal treatment were successfully regenerated, acclimatized and grew well with 100% survival rate. Taken together, an enhanced and efficient shoot regeneration protocol of S. rebaudiana was successfully developed which will be useful for rapid and large-scale micropropagation in future.

Oral Fixed-Dose Combination Pharmaceutical Products: Industrial Manufacturing Versus Personalized 3D Printing.

Fixed-dose combination (FDC) products containing at least two different active pharmaceutical ingredients are designed to treat more effectively different pathologies as they have demonstrated to enhance patient compliance. However, the combination of multiple drugs within the same dosage form can bring many physicochemical and pharmacodynamic interactions. The manufacturing process of FDC products can be challenging, especially when it is required to achieve different drug release profiles within the same dosage form to overcome physicochemical drug interactions. Monolithic, multiple-layer, and multiparticulate systems are the most common type of FDCs. Currently, the main manufacturing techniques utilized in industrial pharmaceutical companies rely on the use of combined wet and dry granulation, hot-melt extrusion coupled with spray coating, and compression of bilayered tablets. Nowadays, personalized medicines are gaining importance in clinical settings and 3D printing is taking a highlighted role in the manufacturing of complex and personalized 3D solid dosage forms that could not be manufactured using conventional techniques. In this review, it will be discussed in detail current marketed FDC products and their application in several diseases with an especial focus on antimicrobial drugs. Current industrial conventional techniques will be compared with 3D printing manufacturing of FDCs. Graphical Abstract.

An insight into curcumin-based photosensitization as a promising and green food preservation technology.

Consumer awareness on the side effects of chemical preservatives has increased the demand for natural preservation technologies. An efficient and sustainable alternative to current conventional preservation techniques should guarantee food safety and retain its quality with minimal side effects. Photosensitization, utilizing light and a natural photosensitizer, has been postulated as a viable and green alternative to the current conventional preservation techniques. The potential of curcumin as a natural photosensitizer is reviewed in this paper as a practical guide to develop a safe and effective decontamination tool for industrial use. The fundamentals of the photosensitization mechanism are discussed, with the main emphasis on the natural photosensitizer, curcumin, and its application to inactivate microorganisms as well as to enhance the shelf life of foods. Photosensitization has shown promising results in inactivating a wide spectrum of microorganisms with no reported microbial resistance due to its particular lethal mode of targeting nucleic acids. Curcumin as a natural photosensitizer has recently been investigated and demonstrated efficacy in decontamination and delaying spoilage. Moreover, studies have shown the beneficial impact of an appropriate encapsulation technique to enhance the cellular uptake of photosensitizers, and therefore, the phototoxicity. Further studies relating to improved delivery of natural photosensitizers with inherent poor solubility should be conducted. Also, detailed studies on various food products are warranted to better understand the impact of encapsulation on curcumin photophysical properties, photo-driven release mechanism, and nutritional and organoleptic properties of treated foods.

Challenging diagnosis of gastrointestinal tuberculosis made simpler with multi-targeted loop-mediated isothermal amplification assay.

Prompt and accurate diagnosis of gastrointestinal tuberculosis (GITB) is highly challenging. Current conventional techniques lack sensitivity and are time-consuming. Multi targeted loop-mediated isothermal amplification (LAMP) using two targets (IS6110 and MPB64) is a promising technique for rapid diagnosis of TB. LAMP test using IS6110 and MPB64 targets for M. tuberculosis complex was performed on ileocecal biopsy samples of 35 clinically suspected patients of GITB and 30 ileocecal biopsy samples of non-tuberculosis control subjects. Results of IS6110 LAMP and MPB64 LAMP were compared with IS6110 PCR and culture INFERENCE: Overall LAMP test (using any of the two targets) had a sensitivity and specificity of 100 and 100%, respectively, for confirmed GITB (five culture positive) cases and 85.71 and 100%, respectively, for clinically suspected 30 ileocecal biopsy samples of GITB. Sensitivity of IS6110 LAMP, MPB64 LAMP and IS6110 PCR for clinically suspected cases was 22 (73.33%), 24 (80%) and 21 (70%), respectively. In total 35 GITB patients, the overall sensitivity of microscopy, culture, IS6110 PCR, IS6110 LAMP, MPB64 LAMP and the multi-targeted LAMP assay (if any of the two targets were used) were 5.71, 14.28, 68.57, 74.28, 82.85 and 85.71%, respectively. Specificity of all the tests was 100%. There were three cases which were missed by IS6110 LAMP and two cases by MPB64 LAMP. Multi-targeted LAMP is a promising technique for rapid and accurate diagnosis of GITB.

Identification of Brucella spp. isolates and discrimination from the vaccine strain Rev.1 by MALDI-TOF mass spectrometry

Brucellosis' surveillance and control programs require robust laboratory techniques that can reliably identify and biotype Brucella strains and discriminate between vaccine and field infection. In the recent years, Matrix Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) has revolutionized the routine identification of several microorganisms in clinical microbiology laboratories. Nevertheless, its application on Brucella spp. identification is limited since there are no reference spectra in the commercial databases, due to the microorganism's potential bioterrorist use.In this study, a custom MALDI-TOF MS reference library was constructed and its performance on identification at species level was evaluated using 75 Brucella spp. isolates. Furthermore, distinct peak biomarkers were detected for biovar assignment and discrimination from vaccine strain Rev.1. Analysis of mass peak profiles allowed Brucella accurate identification at genus and species level (100%) with no misidentifications. Despite the high intrageneric similarity, MALDI-TOF MS database succeeded in classifying at biovar level, 47 out of 62 B. melitensis bv. 3 isolates (75.81%), whereas all B. melitensis strains, except for one, were correctly discriminated from vaccine strain Rev.1.MALDI-TOF MS appeared to be a rapid, cost-effective and reliable method for the routine identification of brucellae which reduces time consumption in pathogen identification and could replace in the near future the current conventional and molecular techniques. Its ability to differentiate vaccine from field infection could facilitate brucellosis’ monitoring systems contributing in the effective control of the disease.

A new era for sterilization based on supercritical CO2 technology.

The increasing complexity in morphology and composition of modern biomedical materials (e.g., soft and hard biological tissues, synthetic and natural-based scaffolds, technical textiles) and the high sensitivity to the processing environment requires the development of innovative but benign technologies for processing and treatment. This scenario is particularly applicable where current conventional techniques (steam/dry heat, ethylene oxide, and gamma irradiation) may not be able to preserve the functionality and integrity of the treated material. Sterilization using supercritical carbon dioxide emerges as a green and sustainable technology able to reach the sterility levels required by regulation without altering the original properties of even highly sensitive materials. In this review article, an updated survey of experimental protocols based on supercritical sterilization and of the efficacy results sorted by microbial strains and treated materials was carried out. The application of the supercritical sterilization process in materials used for biomedical, pharmaceutical, and food applications is assessed. The opportunity of supercritical sterilization of not only replace the above mentioned conventional techniques, but also of reach unmet needs for sterilization in highly sensitive materials (e.g., single-use medical devices, the next-generation biomaterials, and medical devices and graft tissues) is herein unveiled.

Development of Sialoglycan Recognizing Probes (SGRPs) With Defined Specificities: Towards Exploring the Dynamic Mammalian Sialoglycome

Abstract Dense and complex glycans on vertebrate cell surfaces and secreted molecules often terminate with sialic acids (Sias), a diverse family of sugars involved in numerous biological processes, including cell-cell interactions, immune regulation, cellular homeostasis, host-pathogen interactions and microbial pathogeneses. Due to immense structural variations, a major fraction of sialoglycans remain poorly characterized by current inadequate conventional techniques. While traditional glycomic methods are useful, they can destroy or overlook crucial aspects of Sia diversity, or fail to elucidate native structures as they exist in biological systems. To date, in situdetection and analysis of sialoglycans have been largely based on plant lectins, sialidases or antibodies whose preferences are limited and/or uncertain. We defined 9 classes of Sialoglycan Recognizing Probes (SGRPs: SGRP1- SGRP9) aiming to provide a simple and systematic approach to track mammalian sialome changes, using techniques common in most laboratories. Our approach utilizes molecules naturally evolved with maximized specificity towards sialoglycans such as bacterial adhesins, toxin subunits and viral hemagglutinin-esterases. We selected the experimentally proven best candidates for SGRPs and engineered each with a corresponding non-binding mutant as a negative control. Following sialoglycan microarray studies to confirm the binding specificity of our SGRPs, the optimized panel of SGRPs was subsequently applied in common detection methods such as ELISA, Western Blot and FACS analysis. While further work is needed to define a comprehensive suite of SGRPs, our efforts provide a reliable toolkit with specificity to track the mammalian sialoglycome.

A Novel Unbalance Compensation Method for Distribution Solid-State Transformer Based on Reduced Order Generalized Integrator

Owing to its modular construction, ability for bi-directional power flow and suitability for AC/DC grids, solid-state transformer (SST) is expected to be the backbone of the future smart grids. One of the main drawbacks of SST is the generation of negative-sequence current component at its input stage under unbalanced distribution system which causes adverse impacts on the power quality of the electricity grids. This paper is aimed at proposing a novel unbalance compensation method based on reduced order generalized integrator to suppress the negative-sequence current. Unlike the conventional sequence compensation method that is based on dual synchronous reference frames, the new proposed method does not involve complex calculation of the command current and sequence decomposition. As such, the response speed of the compensation controller is significantly improved. Additionally, the proposed method is easy to implement when compared with the current conventional compensation technique as there is no need to inject sequence components into the grid. A simulation model of three-module cascaded SST with three-phase star connection is established in Matlab/Simulink. Several case studies are carried out under different operating conditions. Simulation results validate the feasibility of the proposed method.

Apoptotic effect of Gyejibokryunghwan on uterine sarcoma cells (SK-UT-1B)

BackgroundDiagnosis of uterine sarcomais is a challenging task for clinicians because its position is not easily accessible by current conventional techniques. In addition, standardized treatment for uterine sarcoma has not yet been established due to its rarity and heterogeneity. Hypothesis/PurposeWe investigated the apoptotic cell death of uterine sarcoma cells (SK-UT-1B) induced by Gyejibokryunghwan (GBH). GBH, an herbal medicine, has been widely used for gynecological diseases in Koean medicine. MethodsSK-UT-1B cells were treated with GBH of varying concentrations from 0 to 500 µg/ml. The mechanism of cell death was investigated through multiple analysis methods, including flow cytometry, cell cycle, and western blotting. ResultsFlow cytometric analysis revealed that the number of apoptotic cells increased in a GBH dose-dependent manner. The cell populations of sub-G1 and G0/G1 phases were increased by GBH treatment, indicating apoptosisand cell arrest, while the population of S and G2/M phases decreased. With GBH, the expression levels of cleaved caspase-3, -6, and -9 were upregulated, while the expression levels of pro-caspase-3, -6, and -9 were down-regulated in SK-UT-1B cells. ConclusionThese results are the first observation of uterine sarcoma cell death induced by GBH and confirmation of the mechanism of cell death, which occurred through the intrinsic apoptotic pathway. Clinically, uterine sarcoma has a poor prognosis with no appropriate treatment. GBH may become a new treatment modality for uterine sarcoma.

Palliation of Vertebral Metastases with Radiotherapy: Exploration of Volumetric-Modulated Arc Therapy From Development to Implementation in Routine Clinical Practice

The development of volumetric-modulated arc therapy (VMAT) in radiation therapy has allowed for improved dose escalation and a decrease in radiation-induced toxicities for patients. This article will describe a single centre's experience in development and implementation of VMAT for palliation of vertebral metastases. A retrospective planning analysis of 10 cases identified that utilization of VMAT decreases overall planning time with a statistically significant improvement in target coverage when compared with the current conventional technique. PTV Dmax (P = .02), PTV V9519Gy (95%) (P = .01), dose conformation (P = 1.8e-004), and the homogeneity index (P = .019) were all superior for VMAT plans with an average PTV length of 22.46 cm. Another benefit of VMAT utilization is a significant decrease in treatment delivery time, which reduced treatment times from 9.95 minutes to 2.98 minutes. Immobilization was also carefully considered, and rotational errors were measured and fell within institutional tolerances when VMAT was delivered using simple immobilization devices. Clinical implementation of this technique, utilizing a highly conformal target volume to decrease radiation-induced toxicities and minimizing the length of time patients are required to maintain their treatment positions, aims to improve the palliative radiotherapy experience for patients with painful spinal metastases.