Anca Cardoneanu  Luana Andreea Macovei  Alexandra Maria Burlui  Ioana Ruxandra Mihai  Ioana Bratoiu  Ioana Irina Rezus  Patricia Richter  Bogdan-Ionel Tamba  Elena Rezus 《International journal of molecular sciences》2023,24(1)

The temporomandibular joint (TMJ) is a specialized synovial joint that is crucial for the movement and function of the jaw. TMJ osteoarthritis (TMJ OA) is the result of disc dislocation, trauma, functional overburden, and developmental anomalies. TMJ OA affects all joint structures, including the articular cartilage, synovium, subchondral bone, capsule, ligaments, periarticular muscles, and sensory nerves that innervate the tissues. The present review aimed to illustrate the main pathomechanisms involving cartilage and bone changes in TMJ OA and some therapeutic options that have shown potential restorative properties regarding these joint structures in vivo. Chondrocyte loss, extracellular matrix (ECM) degradation, and subchondral bone remodeling are important factors in TMJ OA. The subchondral bone actively participates in TMJ OA through an abnormal bone remodeling initially characterized by a loss of bone mass, followed by reparative mechanisms that lead to stiffness and thickening of the condylar osteochondral interface. In recent years, such therapies as intraarticular platelet-rich plasma (PRP), hyaluronic acid (HA), and mesenchymal stem cell-based treatment (MSCs) have shown promising results with respect to the regeneration of joint structures or the protection against further damage in TMJ OA. Nevertheless, PRP and MSCs are more frequently associated with cartilage and/or bone repair than HA. According to recent findings, the latter could enhance the restorative potential of other therapies (PRP, MSCs) when used in combination, rather than repair TMJ structures by itself. TMJ OA is a complex disease in which degenerative changes in the cartilage and bone develop through intricate mechanisms. The regenerative potential of such therapies as PRP, MSCs, and HA regarding the cartilage and subchondral bone (alone or in various combinations) in TMJ OA remains a matter of further research, with studies sometimes obtaining discrepant results.  相似文献   

    

Anastasiya Mamaeva  Olga Krasnova  Irina Khvorova  Konstantin Kozlov  Vitaly Gursky  Maria Samsonova  Olga Tikhonova  Irina Neganova 《International journal of molecular sciences》2023,24(1)

Human pluripotent stem cells are promising for a wide range of research and therapeutic purposes. Their maintenance in culture requires the deep control of their pluripotent and clonal status. A non-invasive method for such control involves day-to-day observation of the morphological changes, along with imaging colonies, with the subsequent automatic assessment of colony phenotype using image analysis by machine learning methods. We developed a classifier using a convolutional neural network and applied it to discriminate between images of human embryonic stem cell (hESC) colonies with “good” and “bad” morphological phenotypes associated with a high and low potential for pluripotency and clonality maintenance, respectively. The training dataset included the phase-contrast images of hESC line H9, in which the morphological phenotype of each colony was assessed through visual analysis. The classifier showed a high level of accuracy (89%) in phenotype prediction. By training the classifier on cropped images of various sizes, we showed that the spatial scale of ~144 μm was the most informative in terms of classification quality, which was an intermediate size between the characteristic diameters of a single cell (~15 μm) and the entire colony (~540 μm). We additionally performed a proteomic analysis of several H9 cell samples used in the computational analysis and showed that cells of different phenotypes differentiated at the molecular level. Our results indicated that the proposed approach could be used as an effective method of non-invasive automated analysis to identify undesirable developmental anomalies during the propagation of pluripotent stem cells.  相似文献   

    

Kristina A. Sharlo  Irina D. Lvova  Svetlana P. Belova  Ksenia A. Zaripova  Boris S. Shenkman  Tatiana L. Nemirovskaya 《International journal of molecular sciences》2023,24(1)

Muscle unloading leads to signaling alterations that cause muscle atrophy and weakness. The cellular energy sensor AMPK can regulate myofiber-type shift, calcium-dependent signaling and ubiquitin-proteasome system markers. We hypothesized that the prevention of p-AMPK downregulation during the first week of muscle unloading would impede atrophy development and the slow-to-fast shift of soleus muscle fibers, and the aim of the study was to test this hypothesis. Thirty-two male Wistar rats were randomly assigned to four groups: placebo control (C), control rats treated with metformin (C + M), 7 days of hindlimb suspension (HS) + placebo (7HS), and 7 days of HS + metformin administration (7HS + M). In the soleus of the 7HS rats, we detected a slow-to-fast fiber-type shift as well as a significant downregulation of MEF-2D and p300 in the nuclei. In the 7HS group, we also found decreases in p-ACC (AMPK target) protein level and in the expression of E3 ubiquitin ligases and p-CaMK II protein level vs. the C group. The 7-day metformin treatment for soleus muscle unloading (1) prevented slow-to-fast fiber-type shift; (2) counteracted changes in the p-ACC protein level; (3) hindered changes in the nuclear protein level of the slow myosin expression activators MEF-2D and p300, but did not affect NFATc1 signaling; and (4) attenuated the unloading-induced upregulation of MuRF-1, atrogin-1, ubiquitin and myostatin mRNA expression, but did not prevent soleus muscle atrophy. Thus, metformin treatment during muscle disuse could be useful to prevent the decrease in the percentage of slow-type fatigue-resistant muscle fibers.  相似文献   

    

Irina Buchovec  Enrika Vy ait&#x;  Kazimieras Badokas  Edita Suiedelien&#x;  Saulius Bagdonas 《International journal of molecular sciences》2023,24(1)

Acinetobacter baumannii is a dangerous hospital pathogen primarily due to its ability to form biofilms on different abiotic and biotic surfaces. The present study investigated the effect of riboflavin- and chlorophyllin-based antimicrobial photodynamic therapy, performed with near-ultraviolet or blue light on the viability of bacterial cells in biofilms and their structural stability, also determining the extent of photoinduced generation of intracellular reactive oxygen species as well as the ability of A. baumannii to form biofilms after the treatment. The efficacy of antimicrobial photodynamic therapy was compared with that of light alone and the role of the photosensitizer type on the photosensitization mechanism was demonstrated. We found that the antibacterial effect of riboflavin-based antimicrobial photodynamic therapy depends on the ability of photoactivated riboflavin to generate intracellular reactive oxygen species but does not depend on the concentration of riboflavin and pre-incubation time before irradiation. Moreover, our results suggest a clear interconnection between the inactivation efficiency of chlorophyllin-based antimicrobial photodynamic therapy and the sensitivity of A. baumannii biofilms to used light. In summary, all the analyzed results suggest that riboflavin-based antimicrobial photodynamic therapy and chlorophyllin-based antimicrobial photodynamic therapy have the potential to be applied as an antibacterial treatment against A. baumannii biofilms or as a preventive measure against biofilm formation.  相似文献   

    

A. Muthumari  J. Banumathi  S. Rajasekaran  P. Vijayakarthik  K. Shankar  Irina V. Pustokhina  Denis A. Pustokhin 《计算机、材料和连续体（英文）》2021,67(2):1863-1879

Cloud computing offers internet location-based affordable, scalable, and independent services. Cloud computing is a promising and a cost-effective approach that supports big data analytics and advanced applications in the event of forced business continuity events, for instance, pandemic situations. To handle massive information, clusters of servers are required to assist the equipment which enables streamlining the widespread quantity of data, with elevated velocity and modified configurations. Data deduplication model enables cloud users to efficiently manage their cloud storage space by getting rid of redundant data stored in the server. Data deduplication also saves network bandwidth. In this paper, a new cloud-based big data security technique utilizing dual encryption is proposed. The clustering model is utilized to analyze the Deduplication process hash function. Multi kernel Fuzzy C means (MKFCM) was used which helps cluster the data stored in cloud, on the basis of confidence data encryption procedure. The confidence finest data is implemented in homomorphic encryption data wherein the Optimal SIMON Cipher (OSC) technique is used. This security process involving dual encryption with the optimization model develops the productivity mechanism. In this paper, the excellence of the technique was confirmed by comparing the proposed technique with other encryption and clustering techniques. The results proved that the proposed technique achieved maximum accuracy and minimum encryption time.  相似文献   

    

D. Venugopal  T. Jayasankar  Mohamed Yacin Sikkandar  Mohamed Ibrahim Waly  Irina V. Pustokhina  Denis A. Pustokhin  K. Shankar 《计算机、材料和连续体（英文）》2021,68(3):2877-2893

Data fusion is one of the challenging issues, the healthcare sector is facing in the recent years. Proper diagnosis from digital imagery and treatment are deemed to be the right solution. Intracerebral Haemorrhage (ICH), a condition characterized by injury of blood vessels in brain tissues, is one of the important reasons for stroke. Images generated by X-rays and Computed Tomography (CT) are widely used for estimating the size and location of hemorrhages. Radiologists use manual planimetry, a time-consuming process for segmenting CT scan images. Deep Learning (DL) is the most preferred method to increase the efficiency of diagnosing ICH. In this paper, the researcher presents a unique multi-modal data fusion-based feature extraction technique with Deep Learning (DL) model, abbreviated as FFE-DL for Intracranial Haemorrhage Detection and Classification, also known as FFEDL-ICH. The proposed FFEDL-ICH model has four stages namely, preprocessing, image segmentation, feature extraction, and classification. The input image is first preprocessed using the Gaussian Filtering (GF) technique to remove noise. Secondly, the Density-based Fuzzy C-Means (DFCM) algorithm is used to segment the images. Furthermore, the Fusion-based Feature Extraction model is implemented with handcrafted feature (Local Binary Patterns) and deep features (Residual Network-152) to extract useful features. Finally, Deep Neural Network (DNN) is implemented as a classification technique to differentiate multiple classes of ICH. The researchers, in the current study, used benchmark Intracranial Haemorrhage dataset and simulated the FFEDL-ICH model to assess its diagnostic performance. The findings of the study revealed that the proposed FFEDL-ICH model has the ability to outperform existing models as there is a significant improvement in its performance. For future researches, the researcher recommends the performance improvement of FFEDL-ICH model using learning rate scheduling techniques for DNN.  相似文献   

    

M. S. Maharajan  T. Abirami  Irina V. Pustokhina  Denis A. Pustokhin  K. Shankar 《计算机、材料和连续体（英文）》2021,68(3):2995-3013

Wireless Sensor Networks (WSN) started gaining attention due to its wide application in the fields of data collection and information processing. The recent advancements in multimedia sensors demand the Quality of Service (QoS) be maintained up to certain standards. The restrictions and requirements in QoS management completely depend upon the nature of target application. Some of the major QoS parameters in WSN are energy efficiency, network lifetime, delay and throughput. In this scenario, clustering and routing are considered as the most effective techniques to meet the demands of QoS. Since they are treated as NP (Non-deterministic Polynomial-time) hard problem, Swarm Intelligence (SI) techniques can be implemented. The current research work introduces a new QoS aware Clustering and Routing-based technique using Swarm Intelligence (QoSCRSI) algorithm. The proposed QoSCRSI technique performs two-level clustering and proficient routing. Initially, the fuzzy is hybridized with Glowworm Swarm Optimization (GSO)-based clustering (HFGSOC) technique for optimal selection of Cluster Heads (CHs). Here, Quantum Salp Swarm optimization Algorithm (QSSA)-based routing technique (QSSAR) is utilized to select the possible routes in the network. In order to evaluate the performance of the proposed QoSCRSI technique, the authors conducted extensive simulation analysis with varying node counts. The experimental outcomes, obtained from the proposed QoSCRSI technique, apparently proved that the technique is better compared to other state-of-the-art techniques in terms of energy efficiency, network lifetime, overhead, throughput, and delay.  相似文献   

    

Marina Lesnichaya  Anastasiya Gazizova  Alla Perfileva  Olga Nozhkina  Irina Graskova  Boris Sukhov 《IET nanobiotechnology / IET》2021,15(7):585

Water‐soluble, stable nanoparticles of elemental sulphur with a size of 9‐52 nm have been synthesised using the stabilising potential of starch. Sulphide anions were used as sulphur precursors that were generated earlier from the bulk powder sulphur in the base‐reduction system NaOH‐N₂H₄·H₂O followed by their oxidation with molecular oxygen to element sulphur atoms. Using a set of modern spectral and microscopic methods (XRD, optical spectroscopy, DLS, TEM), the phase state, elemental composition of the nanocomposites and their nanomorphological characteristics have been investigated. It was found that nanocomposites are formed as sulphur particles with the shape which is nearly spherical dispersed in the polysaccharide starch matrix with a pronounced tendency to cluster into ring formations. Water solubility and stability of the obtained nanoparticles is ensured by sorption of starch macromolecules on the surface of sulphur nanoparticles, with the thickness of the stabilising shell in a range of 10‐171 nm. In vitro experiments were carried out to study the anti‐microbial activity of the obtained sulphur nanocomposite (1.6% S) using the propidium iodide fluorescent dye staining method and the diffusion method. It showed that the water solution of the starch‐capped sulphur nanoparticles at the concentration of 6.25 µg/ml had a pronounced anti‐phytopathogenic activity against the potato ring rot pathogen Clavibacter michiganensis subsp. sepedonicus.  相似文献   

    

R. Gopi  P. Muthusamy  P. Suresh  C. G. Gabriel Santhosh Kumar  Irina V. Pustokhina  Denis A. Pustokhin  K. Shankar 《计算机、材料和连续体（英文）》2022,70(3):4883-4896

Smart City Healthcare (SHC²) system is applied in monitoring the patient at home while it is also expected to react to their needs in a timely manner. The system also concedes the freedom of a patient. IoT is a part of this system and it helps in providing care to the patients. IoT-based healthcare devices are trustworthy since it almost certainly recognizes the potential intensifications at very early stage and alerts the patients and medical experts to such an extent that they are provided with immediate care. Existing methodologies exhibit few shortcomings in terms of computational complexity, cost and data security. Hence, the current research article examines SHC² security through Light Weight Cipher (LWC) with Optimal S-Box model in PRESENT cipher. This procedure aims at changing the sub bytes in which a single function is connected with several bytes’ information to upgrade the security level through Swam optimization. The key contribution of this research article is the development of a secure healthcare model for smart city using SHC² security via LWC and Optimal S-Box models. The study used a nonlinear layer and single 4-bit S box for round configuration after verifying SHC² information, constrained by Mutual Authentication (MA). The security challenges, in healthcare information systems, emphasize the need for a methodology that immovably concretes the establishments. The methodology should act practically, be an effective healthcare framework that depends on solidarity and adapts to the developing threats. Healthcare service providers integrated the IoT applications and medical services to offer individuals, a seamless technology-supported healthcare service. The proposed SHC² was implemented to demonstrate its security levels in terms of time and access policies. The model was tested under different parameters such as encryption time, decryption time, access time and response time in minimum range. Then, the level of the model and throughput were analyzed by maximum value i.e., 50 Mbps/sec and 95.56% for PRESENT-Authorization cipher to achieve smart city security. The proposed model achieved better results than the existing methodologies.  相似文献   

    

Salma Zouhair;Charlotte Clegg;Irina Valitova;Samuel March;Javith Mohammed Jailani;Vincenzo Pecunia; 《Solar RRL》2024,8(6):2300929

Carbon electrodes have gained significant attention as a cost-effective, sustainable, stable, and scalable replacement for metal electrodes in perovskite solar cells (PSCs). However, traditional carbon-electrode-based PSCs (C-PSCs) lack a hole-selective layer (HSL) due to their incompatibility with the most effective organic HSLs employed in the PSC literature. In turn, the absence of an HSL has been identified as one of the main factors hindering the performance of C-PSCs. Consequently, numerous studies have recognized the pivotal significance of the region between the perovskite absorber and the carbon electrode in C-PSCs, proposing various interfacial engineering strategies to improve the performance of these solar cells. Given the rapid evolution of this field, an up-to-date and comprehensive review of C-PSCs is in order. Key areas of focus of this review include the shift from high-temperature to low-temperature carbon electrodes, strategies to improve energetic alignment at the interface, novel approaches such as hole-selective bilayers, and alternative carbon deposition methods to reduce solvent damage. Additionally, this review presents a comprehensive meta-analysis—the first of its kind in the C-PSC literature—to assess how various interfacial modifications impact critical C-PSC performance metrics, offering valuable insights for future advancements in the field.  相似文献