This paper aimed to describe an atlas of the head of the crested porcupine (Hystrix cristata), applying advanced imaging techniques such as MRI. Furthermore, by combining the images acquired through these techniques with anatomical gross sections, we obtained an adequate description of the structures that form the CNS and associated structures of this species. This anatomical information could serve as a valuable diagnostic tool for the clinical evaluation of different pathological processes in porcupines such as abscesses, skull malformations, fractures, and neoplasia.

In order to improve real-time performance of gesture recognition by micro-Doppler map of mmWave Radar, the point cloud based gesture recognition for mmWave Radar is proposed in this paper.Two steps are carried out for mmWave Radar based gesture recognition. The first step is to estimate the point cloud of the gestures by 3D-FFT and the peak grouping. The second step is to train the TRANS-CNN model by combining the multi-head self-attention and the 1D-convolutional network, so as to extract the features in the point cloud data at a deeper level to categorize the gestures. In the experiments, TI mmWave Radar sensor IWR1642 is used as benchmark to evaluate the feasibility of the proposed approach. The results show that the accuracy of the gesture recognition reaches 98.5%. In order to prove the effectiveness of our approach, a simply 2Tx2Rx Radar sensor is developed in our lab and the accuracy of recognition reaches 97.1%. The results show that our proposed gesture recognition approach achieves the best performance in real-time with limited training data, in comparison with the existing methods.

The root system plays an irreplaceable role in plant growth. Its improvement can increase crop productivity. However, such system is still mysterious for us. The underlying mechanism has not been fully uncovered. The investigation on proteins related to the root system is an important means to complete this task. In the previous time, lack of root-related proteins makes it impossible to adopt machine learning methods for designing efficient models for the discovery of novel root-related proteins. Recently, a public database on root-related proteins was set up and machine learning methods can be applied in this field. In this study, we proposed a machine learning based model, named Graph-Root, for identification of root-related proteins. The features derived from protein sequences and one network were extracted, where the former features were processed by graph convolutional neural network and multi-head attention, and the later features abstracted the linkage between proteins. These features were fed into the fully connected layer to make prediction. The 5-fold cross-validation and independent tests suggested its good performance. It also outperformed the only one previous model, SVM-Root. Furthermore, the importance of each feature type and component in the proposed model was investigated.

A simple and rapid method for the extraction of D-series resolvins (RvD1, RvD2, RvD3, RvD4, RvD5) released into Leibovitz's L-15 complete medium by head kidney cells from Atlantic salmon and further liquid chromatography triple quadrupole mass spectrometry determination is proposed. A three-level factorial design was proposed to select the optimal concentrations of internal standards that were used in the evaluation of the performance parameters such as linear range (0.1-50 ng/mL), limits of detection and quantification (0.05 and 0.1 ng/mL, respectively) and recovery values (98.99±0.00). The optimized method was used to determine the stimulated production of resolvins by head kidney cells exposed to docosahexaenoic acid, and the results indicated that it is possible that the production was controlled by circadian responses.

(1) Background: P-cadherin (CDH3) is a transmembrane protein that plays a crucial role in maintaining the structural integrity of epithelial tissue and homeostasis. Its role in carcinogenesis remains a subject of debate, as its behavior can vary depending on the molecular context and the specific tumor cell model under study. In this study, we explored the role of P-cadherin in head and neck squamous cell carcinoma (HNSCC) and the mechanism underlying its function. (2) Methods: We analyzed P-cadherin expression in HNSCC patients using The Cancer Genome Atlas (TCGA) database. For in vitro functional analysis, we conducted proliferation, migration, invasion, and western blot assays after either suppressing or overexpressing P-cadherin. For in vivo functional analysis, we utilized mouse xenograft models. (3) Results: P-cadherin was significantly overex-pressed in tumor samples compared to normal samples in the TCGA-HNSCC cohort. P-cadherin knockdown resulted in decreased proliferation, migration, and invasion compared to control cells, while P-cadherin overexpression increased cell proliferation and migration in HNSCC cells. We discovered that c-Met functioned as an upstream regulator of P-cadherin. Surprisingly, we found that P-cadherin knockdown increased the phosphorylation of c-Met and STAT3. Combining P-cadherin siRNA with the c-Met inhibitor SU11274 resulted in a more effective reduction in HNSCC cell growth, both in vitro and in vivo, compared to either treatment alone. (4) Conclusions: Our study uncovered a previously unknown aspect of P-cadherin-mediated c-Met regulation. The enhanced activation of c-Met/STAT3 following P-cadherin inhibition could be responsible for the survival of resistant tumor cells. Therefore, dual inhibition of P-cadherin and c-Met may be a potentially effective approach for treating HNSCC.

The delineation of the clinical target volumes (CTVs) for radiation therapy is time-consuming, requires intensive training and shows high inter-observer variability. Supervised deep learning methods depend heavily on consistent training data, thus state-of-the-art research focuses on making CTV labels more homogeneous and strictly bounding them to current standards. International consensus expert guidelines standardize CTV delineation by conditioning the extension of the clinical target volume on surrounding anatomical structures. Training strategies that directly following the construction rules given in the expert guidelines or the possibility to quantify the conformance of manually drawn contours with the guidelines are still missing. 71 anatomical structures that are relevant for CTV delineation in head and neck cancer patients according to the expert guidelines were segmented on 104 CT scans to assess the possibility to automate their segmentation by state-of-the-art deep learning methods. nnU-Net models were trained to automatically segment those 71 structures on planning CT scans. We report the DICE, HD and sDICE for 71 + 5 anatomical structures for most of which no previous segmentation accuracies have been reported. For those structures, for that prediction values have been reported, our segmentation accuracy matched or exceeded the reported values. The predictions from our models were always better than those predicted by the TotalSegmentator. The sDICE with 2mm margin was larger than 80% for almost all structures. Individual structures with decreased segmentation accuracy are analyzed and discussed with respect to their impact on the CTV delineation following the expert guidelines. No deviation is expected to affect the rule-based automation of the CTV delineation.

This study aimed to investigate the influence of cranio-cervical position on the electromyographical activity of the core muscles during the prone plank exercise. Twenty healthy participants were enrolled in this study. Muscle activation was registered using surface electromyography (sEMG) in the rectus abdominis (RA), external oblique (EO), internal oblique (IO) and lumbar portion of erector spinae (LES). Three prone plank conditions were randomly evaluated, varying the position of the cranio-cervical segment during the prone plank performance (NEUTRAL, FLEXION and EXTENSION). sEMG signals of each individual muscle, Total Intensity (TI) and ratings of perceived exertion (RPE) were analysed with statistical significance set at P<0.05. FLEXION revealed significantly higher TI values compared to NEUTRAL and EXTENSION (p = 0.000; effect size (ES) > 0.90). The RA presented larger activation in FLEXION compared to the other variations (p < 0.05; ES >0.70). FLEXION elicited a greater response compared to NEUTRAL for both sides of EO when compared to EXTENSION, and also for both sides of IO compared to the other conditions. Both FLEXION and EXTENSION reported higher RPE values compared to NEUTRAL. Cranio-cervical segment position influenced the electromyographical activation of core musculature, showing highest values when performing prone plank in a cranio-cervical flexion.

Keywords: head-and-neck cancer; chemoradiation; cisplatin; carboplatin; loco-regional control; metastases-free survival; overall survival; toxicity.

Traumatic Brain Injury represents a significant public health concern due to its role in traumatic death and disability, often caused by head impacts or rapid accelerations. Despite advancements in Finite Element Head Models, existing models primarily represent adult males, neglecting anatomical and physiological differences between genders and age groups. Additionally, the mechanistic roles of specific intracranial tissues, such as the dura mater, have conventionally been overlooked. To better understand the mechanical behavior of the brain and its injured regions in the context of TBI, including the dura mater, this study proposes the development of a Female Finite Element Head Model. This model, representative of a middle-aged female subject, was developed using medical image-derived geometry and finite element modeling techniques. The validation results demonstrate a similarity between the numerical displacement curves and those obtained experimentally. In the model with dura mater, the numerical results show analogous behavior to the experimental results, despite minimal variations in the amplitude of the curves. These advancements highlight the significance of including the dura mater in biomechanical brain modeling. Incorporating the dura mater in Finite Element Head Models produces more realistic results than models without it. This emphasizes the importance of enhancing biomechanical models to better represent anatomical complexity.

Head and neck squamous cell carcinoma (HNSCC) takes the sixth place among the most common cancers in the world. Abnormal methylation can be one of the reasons for this cancer. The aim of this study was to investigate the DNA promotor methylation status of cancer-associated genes (ATM, APC, CDO1, RB1, TP53, WIF1) in patients with HNSCC. Bisulfite Conversion and Methylation-Sensitive High-Resolution Melting was used for analysis of the DNA methylation level of normal and tumor tissues in 44 patients. There were significant differences in DNA methylation level between patient’s tumor and normal tissues for CDO1 and WIF1 genes in all subjects and subgroups (p<0.05). In T3 subgroup there was significant correlation between CDO1 gene methylation and age in the normal tissue. The same correlation was detected also for the WIF1 gene methylation in tumor tissue samples in the subgroup with T3 and in normal tissue samples in the subgroup with T4 (p<0,05). In all genes no significant differences were found between the subgroups (T2, T3, T4 stage, primary/recurrent lesion, non-keratinizing/keratinizing SCC, age before/ after 50, smokers/non-smokers) of the patients. Thus, changes in the expression of the CDO1 and WIF1 genes can affect mechanisms of the occurrence and development of HNSCC.

The proliferation of deep learning in natural language processing (NLP) has led to the development and release of innovative technologies capable of understanding and generating human language with remarkable proficiency. Atinuke, a Transformer-based neural network, optimises performance across various language tasks by utilising a unique configuration. The architecture interweaves layers for processing sequential data with attention mechanisms to draw meaningful affinities between inputs and outputs. Due to the configuration of its topology and hyperparameter tuning, it can emulate human-like language by extracting features and learning complex mappings. Atinuke is modular, extensible, and integrates seamlessly with existing machine learning pipelines. Advanced matrix operations like softmax, embeddings, and multi-head attention enable nuanced handling of textual, acoustic, and visual signals. By unifying modern deep learning techniques with software design principles and mathematical theory, the system achieves state-of-the-art results on natural language tasks whilst remaining interpretable and robust.

Background: Approximately 75% of all head and neck cancer patients are treated with radiotherapy (RT). RT to the oral cavity results in acute and late adverse events which can be severe and detrimental to a patient’s quality of life and function. The purpose of this study was to explore associations between RT dose to a defined oral cavity organ at risk (OAR) avoidance structure, provider and patient reported outcomes (PROs), opioid use, and hospitalization. Methods: This was a retrospective analysis of prospectively obtained outcomes using multivariable modeling. The study included 196 patients treated with RT involving the oral cavity for a head and neck tumor. A defined oral cavity OAR avoidance structure was used in all patients for RT treatment planning. Validated PROs were collected prospectively. Opioid use and hospitalization were abstracted electronically from medical records. Results: Multivariable modeling revealed the mean dose to the oral cavity OAR was significantly associated with opioid use (p=0.0082) and hospitalization (p=0.0356) during and within 30 days of completing RT. Conclusion: The findings of this study may be valuable in RT treatment planning for patients with tumors of the head and neck region to reduce the need for opioid use and hospitalization during treatment.

Cytokines are mediators of inflammation that could lead to fibrosis. The aim was to monitor cytokine levels in saliva and serum after locally fractionated radiotherapy of the head and neck in mice and investigate associations with salivary gland fibrosis and hyposalivation. C57BL/6 mice were randomized to sham or X-ray irradiation of 66 Gy in 10 fractions over 5 days. Blood and saliva were collected on day -7, 5, 35, 80 and 105 with following cytokine analysis. The harvested submandibular salivary gland was assessed for presence of fibrosis. Decision tree regression analysis was used to investigate whether cytokine levels could predict late endpoints in terms of hyposalivation or fibrosis. Significant formation of fibrosis in gland tissue and reduced saliva production was found after irradiation. The pro-inflammatory cytokines IL-1α, TNF, TIMP1, G-CSF, KC and MIP-1α showed increased levels in saliva in irradiated mice and strong correlation with late endpoints. The decision tree analysis largely separated controls from irradiated animals with IL-1α being the strongest predictor. Pro-inflammatory cytokines in saliva, but not in serum, were associated with late endpoints. This indicates that cytokine expression in saliva is a good biomarker for local salivary gland damage with IL-1α as the strongest single predictor.

Passive dynamics is an aspect of locomotion which is entirely dependent on the mechanical configuration and linkages of adjacent body segments. Tension distribution along mechanical linkages enables execution of movement patterns with reduced need for complex neurological pathways and may play a role in reestablishing postural stability following external disturbances. Here we demonstrate a uni-directional mechanical relationship between the equine forelimb, head and neck, which may have implications for balance and forelimb loading in the horse. These observations suggest that forelimb, head and neck movement coordination (observed in the horse during unrestrained locomotion) is largely controlled by the mechanical linkages between body segments, rather than being entirely dependent on neurological input as previously thought. This highlights the potential significance of research directed at investigating passively induced movements in understanding common locomotory patterns. Additionally, it suggests a mode of postural control which may provide instantaneous adjustments to postural disturbances, thus promoting rapid and efficient locomotion.

Chronic traumatic encephalopathy (CTE) is a unique neurodegenerative disease that is associated with repetitive head impacts (RHI) in both civilian and military settings. In 2014, the research criteria for the clinical manifestation of CTE, traumatic encephalopathy syndrome (TES) were proposed to improve the clinical identification and understanding of the complex neuropathological phenomena underlying CTE. This review provides a comprehensive overview of the current understanding of the neuropathological and clinical features of CTE, proposed biomarkers of traumatic brain injury (TBI) in both research and clinical settings, and a range of treatments based on previous preclinical and clinical research studies. Due to the heterogeneity of TBI, there is no universally agreed-upon serum, CSF, or neuroimaging marker for its diagnosis. However, as our understanding of this complex disease continues to evolve, it is likely that there will be more robust, early diagnostic methods and effective clinical treatments. This is especially important given the increasing evidence of a correlation between TBI and neurodegenerative conditions, such as Alzheimer's disease and CTE¹. As public awareness of these conditions grows, it is imperative to prioritize both basic and clinical research, as well as the implementation of necessary safe and preventative measures.

Vein blood sampling is one of the methods of mass blood sampling, and is an act of drawing blood from a vein for blood type discrimination, confirmation of various physiological indicators, disease diagnosis, and the like, and is the most commonly used blood sampling method. An important point in vein blood sampling is to search for the exact location of the vein and insert the blood sampling. This is influenced by the patient's obesity, skin and blood vessel conditions, and the experience of the clinical technologist, nurse, and resident who performs the blood sampling. It is required to perform blood sampling technique practice. However, due to many limitations of the practice room or laboratory, there is a problem of using only a limited environment and model for clinical practice. As a result, many medical educational institutions have situations in which only fragmentary clinical practices are performed, and it is difficult to per-form a large number of blood sampling skills practices, so they do not provide enough experience to understand the actual skill field. In this paper, we propose a method for developing a virtual reality-based vein blood sampling simulator to practice a large number of blood sampling techniques without restrictions. The proposed vein blood sampling simulator can operate a 3D model related to vein blood sampling using HMD Controller and Haptic in a virtual space for vein blood sampling practice by wearing an HMD (Head mounted display), and can perform vein blood sampling practice through interaction with the patient 3D model. there is. In addition, the effectiveness of the simulator developed for dental students was verified, and as a result of the verification, the potential of the proposed vein blood sampling simulator was confirmed.

The Atlantic puffin is a medium-sized seabird with black and white plumage and orange feet. It is distributed mainly along the northern Atlantic Ocean and due, among other reasons, to human activities, it is in a threatened situation and classified as a vulnerable species according to the International Union of Conservation of Nature (IUCN). In this study, we used a total of 20 carcasses of juvenile Atlantic puffins to perform anatomical cross sections and magnetic resonance images. Thus, an adequate description of the head was made, providing valuable information that could be helpful as a diagnostic tool for veterinary clinicians, who increasingly treat these birds in zoos, rehabilitation centers and even in the wild.

Taxanes, particularly docetaxel (DTX), has been widely used for combination therapy of head and neck squamous cell carcinoma (HNSCC). For locally advanced unresectable HNSCC, DTX combined with cisplatin and 5-fluorouracil as a revolutionary treatment revealed an advantage in improvement of patient outcome. In addition. DTX plus immune check inhibitors (ICIs) showed low toxicity and increased response of patients with recurrent or metastatic HNSCC (R/M HNSCC). Accumulating data indicate that taxanes not only function as antimitotics but also impair diverse oncogenic signalings including angiogenesis, inflammatory response, ROS production, and apoptosis induction. However, despite an initial response, development of resistance remains a major obstacle to treatment response. Taxane resistance could result from intrinsic mechanisms such as enhanced DNA/RNA damage repair, increased drug efflux, and apoptosis inhibition, and extrinsic effects such as angiogenesis and interactions between tumor cells and immune cells. This review provides an overview of taxanes therapy applied in different stages of HNSCC and describe the mechanisms of taxane resistance in HNSCC. Through a detailed understanding the mechanisms of resistance may help developing the potential therapeutic methods and the effective combination strategies to overcome drug resistance.

In the past decade, it has been discovered that intestinal flora can influence various organ-specific cancers by altering the body's energy balance, increasing obesity, synthesizing genetic toxins and small signaling molecules, initiating and modulating immune responses, and metabolizing indigestible dietary components, exogenous substances, and drugs. In this review, we will focus on elucidating the role of gut flora based on its molecular mechanisms and its potential therapeutic implications in head and neck tumors in the near future.

Synthetic Aperture Radar (SAR) is an active sensor that uses microwave for sense, it is unrestricted by weather and illumination conditions, and it can observe targets all day and weather. Aircraft targets are important monitoring objects in military and civilian fields, and how to efficiently detect and recognize aircraft targets is an important topic in the field of SAR image interpretation. Based on the features of SAR images, such as complex background, high resolution, and multi-scale, we proposed an improved method based on YOLOv5s. Firstly, this paper proposed the structure of the multi-scale receptive field and channel attention fusion, which is applied to the shallow layer of the backbone of YOLOv5s, it can adjust the weights of the multi-scale receptive field during the training process to enhance the extraction ability of feature information. Secondly, we proposed four de-coupled detection heads to replace the original part in YOLOv5s, which can improve the efficiency and accuracy of SAR image interpretation for small targets. Thirdly, in the case of the limited amount of SAR images, this paper proposed multi methods of data augmentation, which can enhance the diversity and generalization of the network. Fourthly, this paper proposed the K-means++ to re-place the original K-means to improve the network convergence speed and detection accuracy. Finally, Experiments demonstrate that the improved YOLOv5s can enhance the accuracy of SAR image interpretation by 9.3%, and the accuracy of small targets is improved more obviously, reaching 13.1%.

Radiotherapy and cisplatin-based chemotherapy belong to the main treatment modalities for head and neck squamous cell carcinoma (HNSCC), and induce cancer cell death by generating DNA damage, including the most severe double strand breaks (DSBs). Alterations in DSB response and repair genes may affect individual DNA repair capacity and treatment sensitivity, contributing to therapy resistance and poor prognosis often observed in HNSCC. In this study, we investigated the association of a panel of single nucleotide polymorphisms (SNPs) in 20 DSB signaling and repair genes with therapy results and prognosis in 505 HNSCC patients treated non-surgically with DNA damage-inducing therapies. In the multivariate analysis, there were a total of 14 variants associated with overall, locoregional recurrence-free or metastasis-free survival. Moreover, we identified 10 of these SNPs as independent predictors of therapy failure and unfavorable prognosis in the whole group or in two treatment subgroups. They were MRE11A rs2155209, XRCC5 rs828907, RAD51 rs1801321, rs12593359, LIG4 rs1805388, CHEK1 rs558351, TP53 rs1042522, ATM rs1801516, XRCC6 rs2267437 and NBS1 rs2735383. Only CHEK1 rs558351 remained statistically significant after correction for multiple testing. These results suggest that specific germline variants related to DSB response and repair may be potential genetic modifiers of therapy effects and disease progression in HNSCC treated with radiotherapy and cisplatin-based chemoradiation.

Researchers achieved high torque volume ratios in magnetorheological (MR) fluid braking devices by introducing multiple layers and multiple poles concepts. The number of magnetic poles, pole geometry and placement have a significant effect on these multi-pole MR brake performances. This research work focused on the effect of the pole head geometry in a multi-pole dual-disc MR brake for the enhancement of braking torque. The magnetic field generated by the electromagnetic coil has to penetrate through pole heads and travel orthogonally through the rotor and MR fluid layers to achieve maximum brake torque. This flow depends on the profiles of the magnetic pole head area and corresponding core dimensions. This study considered pentagon, square, hexagon, trapezoid and ellipse pole head profiles in place of the conventional circular pole and the best possible core dimensions were used for each geometry. A three-dimensional electromagnetic analysis of the MR brake is conducted to simulate the brake performance. Results showed that the hexagonal and elliptical pole heads are having better magnetic field area, magnetic intensity distribution and higher magnetic flux lines piercing through the MR fluid perpendicularly than the circular and square pole heads. An increment of 3.88% for braking torque performance is obtained, and the braking torque is significantly enhanced.

Human papillomavirus (HPV) is one the most common sexually transmitted infections (STI), spreading through direct sexual contact to oropharynx and anogenital regions. Although most infected individuals may be asymptomatic and naturally undergo viral clearance, in some individuals’ HPV infection causes carcinogenesis of the infected epithelia. HPV now accounts for over 70% of oropharyngeal carcinomas (OPC). Over 90% of these OPC are associated with HPV 16, one of the 14 high-risk subtypes. In recent years, HPV positive (HPV+) OPC has been one of the most rapidly rising cancers, by new cancer incidence rates, especially among men. They present some unique infection driven cellular and molecular features, in comparison to other head and neck carcinomas (HNC), constituting distinct preventive, therapeutic and prognostic strategies - with significant strides made in this area. However, HPV+OPC are routinely detected at a later stage, adding to the disease burden and overall survival. In this review, we provide a summary of HPV from a STI to malignant transformation, while also parsing through the immune response environment. We further collate key literature around infection sites, diagnostics and clinical management, while throwing light on the current state of epidemiology, transmission, screening and prevention strategies. Indeed, our improving understanding of the disease’s molecular biology has added some success to the prognostic outcomes of certain HPV+OPC across clinical trials examining targeted therapeutics and immunotherapy. This work is directed towards improving our current understanding of HPV and associated oncogenic landscape, to guide screening, early detection, triaging and further prevention and management strategies.

BACKGROUND: Head and Neck Sarcomas (HNSs) are rare malignant tumors derived from mesenchymal cells characterized by rapid growth, local aggressive behavior, and multiple re-lapses. The Rhabdomyosarcoma (RMS) and the Osteosarcoma (OS) are the more frequent HNS. The present study aims to evaluate the clinical impact of multimodal treatment in patients diagnosed with HNS. METHODS: A retrospective analysis of medical records from patients diagnosed with HNS multimodal treated, four groups were formed: a) surgery and chemotherapy (CTX); b) surgery, CTX, and RT; c) surgery and RT; d) CTX and RT exclusively. The overall survival (OSS), disease-free survival (DFS) and progression-free survival (PFS) rates were calculated using the Kaplan-Meier test. RESULTS: Among 39 patients, 23.1% were diagnosed with RMS , 66.7% with OS and 10.3% with other subtypes of HNS. Moreover, 59% showed initial clinical staging (T1/T2) and of those 35.9% were T1. Surgery was performed in 87.2% patients, RT in 35.9% and CTX in 84.7%. RT performed showed not statistically significant clinical role regarding OSS (p=0.74), DFS (p=0.09) and PFS (p=0.90) rates independent of histological subtype. Finally, OSS (p=0.89), DFS (p=0.13) and PFS (p=0.50) rates were not statistically different for patients treated with monotherapy or multimodal therapy. CONCLUSION: RT has not showed a clinically important role referred to improve OSS, DFS and PFS rates in patients with HNS, regardless of the histological subtype of the primary tumor. Multimodal treatment could influence in survival rates and locoregional control of the disease; however, longitudinal studies such as randomized clinical trials must be conducted.

Single Nucleotide Polymorphisms (SNPs) are the most common type of genetic variation found in individual’s DNA sequences. SNPs can occur in both coding and non-coding regions of the genome and can affect gene expression, protein function, and disease susceptibility. In this systematic review we evaluate the influence of SNPs as a biomarker in the assessment of oral mucositis (OM) in head and neck cancer (HNC) patients. The study selection process involved screening 66 articles from different platforms, and after removing duplicates and excluding irrelevant articles, 23 articles were included for full-text evaluation. The main characteristics and findings of the selected articles are presented and discussed. We conclude that SNPs can be used as a reliable biomarker for the assessment of OM in HNC patients, and further research is needed to explore the potential of SNPs in personalized medicine for HNC treatment.

Background: Metastatic tumors to the oro-facial tissues are rare, with an incidence ranging between 1% and 8% of all oral malignant tumors. Generally reported with a peak of incidence in the 5th–7th decades, but possibly occurring at any age, metastases may represent the first sign of an occult cancer or manifest in patient with an already known history of a primary carcinoma, mostly from the lungs, kidney, prostate, and colon-rectum in males, or uterus, breast, lung, and ovary in females. In the oro-facial tissues the sites mostly involved are the oral mucosa, gingiva/jawbones, tongue, and the salivary glands. Methods: A systemic Review of the literature on the oro-facial metastases from Renal Cell Carcinoma has been conducted by searching the most used databases, also focusing the attention on the Clear Cell histological variant, representing the most frequent one. Results: Among the 160 analyzed studies, 211 cases of oral metastases of renal cancer were found (148 in males, 70.1%; 63 in females, 29.8%), with an average age of 59.8 years. In almost 40% of cases, metastasis represented the first clinical manifestation of the primary tumor and 122 were histologically diagnosed as ccRCCs (57.8%). The tongue was involved in most of the cases (26% - 55 cases), followed by mandible (18.9% - 40 cases), gingiva (18.4% - 39 cases), maxilla (10.9% - 23 cases), parotid gland (10.4% - 22 cases), buccal mucosa (5.2% - 11 cases), lips (3.3% - 7 cases), hard palate (2.8% - 6 cases), soft palate, masticatory space and submandibular gland (0.9% - 2 cases), lymph nodes, tonsil and oral floor (0.4% - 1 case). Among the 122 ccRCCs (84 were males, 68.8 %; 38 females, 31.1%), with an average age of 60.8 years and representing in 33.6% the first clinical manifestation, the tongue remained the most involved site (25.4% - 31 cases), followed by the gingiva (17.2% - 21 cases), parotid gland (13,1% - 16 cases), mandibular bone (12.2% - 15 cases), maxillary bone (11.4% - 14 cases), buccal mucosa and lips (4.9% - 6 cases), hard palate (4% - 5 cases), submandibular gland and soft palate (1.6% - 2 cases), lymph nodes, tonsil, oral floor and masticatory space (0.8%. 1 case). The clinical presentation in soft tissues was represented by a fast-growing exophytic mass, sometimes accompanied by pain. Instead inn bone appeared as radiolucent lesions, with ill-defined borders and cortical erosion. Conclusions: Our data focus the attention on the incidence of Renal cancer Metastases in the oro-facial tissues. Their early identification surely represents a diagnostic challenge, especially when the clinical work-up is limited to the cervico-facial region. Nevertheless, early diagnosis and recently introduced adjuvant therapies may represent the key for better outcomes. Therefore, general guidelines about clinical and radiological identification of oro-facial potentially malignant lesions should be part of the cultural background of any dentists.

Predatory research field in science is when an emerging scientific topic destroys current topics and characterizes a main scientific change. Predatory research field can be a basic driver of scientific and technological change that generates a 'creative destruction' in science and society in contexts of knowledge-based competition and rapid changes. The prediction of proposed theory of predatory research fields is that it destroys with a fast growth other research fields. The theoretical approach is tested here in research fields of large language models (LLM) by analyzing the transformers (a deep learning architecture based on the multi-head attention mechanism) proposed in 2017 and from November 2022 started main applications in generative artificial intelligence with innovations of BERT, ChatGPT, Microsoft Copilot (launched on February 7, 2023) and other natural language processing tools driven by AI technology for engaging conversations, gain insights, automate tasks, etc., etc. Statistical evidence suggests that growth rate of transformer technologies is 80.58%, a high level compared to all other research fields in machine learning (having a growth rate of 13.83%). Moreover, predatory research field of transformers has a destructive power such that all other domains in LLM from 2021 to 2023 have a general reduction of scientific growth. The impact of transformers is much more drastic of previous radical technologies such as CNN having a temporal growth rate of 0.16%, lower than 0.38% by transformers, ceteris paribus. These analysis reveals that transformers have characteristics to generate a radical scientific and technological change in a not-too-distant future. Overall, then, the study suggests that predatory research field on emerging topics and technologies can generate path-breaking innovations and the examination here can clarify the essential elements of the science dynamics for a better theory of scientific and technological change, providing also main implications for knowledge policy to support promising research fields and technologies to guide economic and social change.

Background: This study investigated the incidence, characteristics and functional outcomes associated with unplanned Acute Care Unit Readmissions (ACUR) during inpatient traumatic brain injury (TBI) rehabilitation in an Asian cohort. Methods: Retrospective review of electronic medical records from single rehabilitation unit was conducted from 1 Jan 2012 to 31 Dec 2014. Inclusion criteria were first TBI, aged &gt;18 years, admitted &lt; 6 months of TBI. ACUR were characterized into either of neurological, medical or neurosurgical subtypes. The main outcome measure was discharge Functional Independence Measure (FIM). Secondary outcomes included rehabilitation length of stay (RLOS). Results: Of 121 eligible TBI records, the incidence of ACUR was 14% (n=17), comprising neurologic (76.5%) and medical (23.5%) subtypes, occurring at median of 13 days (IQR 6, 28.5) after rehabilitation admission. Patients without ACUR had significantly higher admission mean (SD) FIM score compared to those with ACUR (FIM ACUR-negative 63.4 (21.1) vs FIM ACUR-positive 50.53(25.4), P =0.026). Significantly lower discharge FIM was noted in those with ACUR compared to those without. (FIM ACUR-positive 65.8(31.4) vs FIM ACUR-negative 85.4 (21.1), P = 0.023) Furthermore, a significant near-doubling of RLOS was noted in ACUR patients compared to non-ACUR counterparts [ACUR-positive median 55 days (IQR 34.50, 87.50) vs ACUR-negative median 28 days (IQR 16.25, 40.00), P = 0.002]. Conclusion: This study highlights the significant negative functional impact and lengthening of rehabilitation duration of ACUR on inpatient rehabilitation outcome for TBI.

The metastatic disease is a complex and sequential process that involves the migration of tumor cells from the primary site to distant areas. This metastatic pathway is not always predictable. Therefore, this paper presents three rare cases of unusual metastases, due to their primary site: two metastases of a clear cell renal cell carcinoma, one gingival and one nasal, as well as a mandibular metastasis of a hepatocellular carcinoma. In all cases, an incisional biopsy was performed in order to sign out the diagnosis. After microscopical examination of morphological Hematoxylin and Eosin stained slides, for all cases, immunohistochemical reactions were performed to support the primary tumor site. Two cases had a previous histopathological diagnosis of a primary tumor, while for the third case, the metastatic lesion represented the first manifestation of the neoplastic disease, with an unfavorable prognosis.

Background: Infantile hemangiomas (IHs) are the most common benign vascular tumors of infancy. Methods: We report our experience of 248 patients with head and neck IHs. Results: The median age on admission was 4 months, and female/male ratio was 2.17. Among the cases, 45% were followed without treatment. No local complications were observed in any of these patients. Propranolol was given to all patients who received medical treatment. The median duration of treatment was 12 months (1-30 months), and the median follow-up period of all patients was 14 months (0-118 months). The treatment response was 98%. Complication rate was 17% and children aged between 3 and 9 months accounted for 60% of patients who developed complications. Most of the complications were local complications such as bleeding, ulcer, and infection. Conclusion: Although most of them regress spontaneously, complications may occur. Propranolol alone is an effective treatment option, and early treatment initiation increases success rates.

(1) Background: The goal of the study was to evaluate psychological tolerance and health-related quality of life (QOL) in head and neck (HN) cancer patients treated with definitive accelerated radiotherapy (DART); (2) Methods: Seventy-six recurrence-free patients eligible for the study, who were treated with DART in the CAIR-2 phase III clinical study (median of follow-up=47 months), completed EORTC QLQ-C30 with H&amp;N35 module, Hospital Anxiety and Depression Scale (HADS) and Visual–Analog Scales (VAS) of pain in HN and the neck / arm area.; (3) Results: The most dominating symptoms measured with QLQ-C30 were: fatigue (44/100), sleeplessness (39/100), financial problems (38/100) and pain (32/100). Within H&amp;N35 the highest scores were reported on the subscales of sticky saliva (60/100), mouth dryness (65/100) and increased intake of painkillers (50/100). Pain (VAS) was reported by 87% (HN area) and 78% (shoulder) of the patients, with a mean score of 3/10. One-third reported depressive mood (HADS≥15 points) with an average score of 12.5/42 p. The depressed group, who smoked more as compared to non-depressed before DART (96% vs 78%) and required steroids treatment (85% vs 58%) during DART, also scored significantly worse on 23 of 35 subscales of QLQ-C30 and H&amp;N35 and experienced more intense pain (VAS). Women, and less advanced patients scored better in several aspects of the quality of life; (4) Conclusions: Patients treated with DART struggle with low quality of life and persisting treatment-related symptoms including constant pain. HNC survivors, especially those, who are depressed, may require additional psychosocial, rehabilitation and medical intervention programs..

The incidence of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) is rising in the West, but little is known in Asia. This study elucidated changes in the incidence and HPV-positive portion of OPSCC in Hong Kong. Data from population-based cancer registry were used to analyze the incidence of OPSCC in associate with other head and neck cancers. Archived tumour tissues were tested for HPV. From 1986 to 2020, there was a marked decrease in the incidence of nasopharyngeal and laryngeal cancers, but a persistent increase in OPSCC from 36 cases in 1986 to 116 cases in 2020. The average positive rate for high-risk HPV was 36.1% (112/310) among OPSCC diagnosed in 2010-2020. The HPV positive rate in recent years was significantly higher than earlier cases (tonsil SCC: 64.7% (55/85) in 2016-2020 vs. 40.4% (19/47) in 2010-2015, P = 0.007). Patients with HPV-positive tonsil cancers were significantly younger than those negative (mean [SD]: 58.9 [9.9] vs. 64.3 [13.3] years, P = 0.006), but no significant difference between genders. A persistent increase in the incidence of oropharyngeal cancer over the last few decades was observed in Hong Kong, which can be explained by the remarkable increase in HPV-positive tonsil cancers.

This is a retrospective chart review of outcomes of maxillofacial microvascular free flap reconstructions in pediatric and adolescent patients. A single head and neck surgical team performed all the included 136 procedures. Demographic and surgical patient data were recorded. Type of transfer performed in each recipient site and major complications were analyzed. Relevant influencing factors, such as age, gender and etiology of defect were determined using the ANOVA test and χ² test of independence. Results indicate a 90% success rate. No significant relation was found between the incidence of total flap loss and patient age, etiology or graft source. The maxillary reconstructions showed a higher incidence of total flap loss compared to mandibular ones (11 vs. 3 cases). Despite the high success rate, the findings underline the necessity for further research to validate these observations and enhance surgical methods for pediatric and adolescent patients.

Head trauma or any traumatic injury can cause damage to parts of the brain. The most important part regulating the body are the hormones and the two centers of brain which are main ones for this regulation are the most prone to getting injured. The hypothalamus and pituitary regulate a lot many functions and the loss of these organs can cause Adrenal Insufficiency, SIADH, Diabetes Insipidus, and many more.

Using traditional methods based on detection rules written by human security experts, there is a significant challenge in accurately detecting many network threats that are increasingly becoming sophisticated. In order to deal with the limitation of the traditional methods, network threat detection techniques utilizing artificial intelligence technologies such as machine learning are being extensively studied. Research has also been conducted on analyzing various string patterns in network packet payloads through natural language processing techniques to detect attack intent. However, due to the nature of packet payloads containing binary data as well as text data, a new approach is needed that goes beyond typical natural language processing techniques. In this paper, we study a token extraction method optimized for payloads using n-gram and byte pair encoding techniques. Furthermore, we generate embedding vectors that can understand the context of the packet payload using algorithms such as Word2Vec and FastText. We also compute the embedding of various header data associated with packets, such as IP addresses and ports. Given the combination of these features, we ensemble a text 1D-CNN and a multi-head attention network in a novel fashion. We validated the effectiveness of our classification technique with the CICIDS2017 open dataset and over half a million data collected by The Education Cyber Security Center (ECSC) currently operating in South Korea. The proposed model showed remarkable progress compared to previous studies, demonstrating a highly accurate classification performance with an F1-Score of 0.998. Our model can also preprocess and classify 150,000 network threats per minute to help security agents in the field divert their time to analyzing more complex attack patterns.

Introduction and objectives Obstructive sleep apnea (OSA) is defined as a cause of daytime sleepiness, as well as a clinical manifestation of sleep-disordered breathing. In the literature, there are numerous controversial studies regarding the etiology of this condition, but it is universally accepted that a significant role in its onset is played by the reduced activity of the upper airway muscles. Additionally, OSA has been associated with a series of comorbidities, such as type II diabetes, metabolic syndrome, cardiovascular and pulmonary conditions, as well as head and neck tumors, especially oropharyngeal and laryngeal tumors. The purpose of this review is to examine and demonstrate the prevalence of OSA in patients with associated pathologies, especially in patients with head and neck tumors, as well as the role of surgical and non-surgical therapeutic methods in improving the quality of life. Material and methods Taking into consideration the stated objective, a systematic analysis of the available literature was conducted, encompassing PubMed, Medline and Scopus databases. The evaluation was based on several keywords, including head and neck cancer, diabetes, diabetic, overlap syndrome, cardiovascular conditions, laryngeal neoplasm, radiotherapy, chemotherapy, as well as the concept of quality of life in laryngectomized patients and patients with OSA. Results Our results demonstrate the involvement of OSA in the presence of comorbidities and also, an increased incidence of OSA in patients with laryngeal cancer. It is important to note that surgical and post-surgical treatment can play a significant role in triggering OSA in these patients. Conclusions The clinician must recognize the increased prevalence of OSA in patients with head and neck cancer, as well as the coexistence of OSA with certain comorbidities. They should actively engage in early diagnosis and establish optimal treatment methods to improve the quality of life for patients with associated conditions such as head and neck tumors or cardiovascular pathology.

This study aims to categorize the morphological changes during cabbage (B. oleracea ssp. capitata) development: seedling, rosette, folding, and heading and to elucidate the cellular mechanisms of leaf curvature, essential for the formation of the leafy head. We followed the growth of two cabbage morphotypes with distinct head shapes (round and pointed); we phenotyped the size and volume of the whole-plant as well as the size, shape, and curvature of the leaves during growth. By integrating these phenotypic data, we determined the four vegetative stages for both cabbages. Cytological phenotypes of microtome sections from five distinct leaf positions of the rosette, folding, and heading leaves at two timepoints during leaf growth were quantified and revealed variations in cellular parameters among leaf types, between leaf positions, and between the adaxial and abaxial sides. We identified two synergistic cellular mechanisms contributing to the curvature of heading leaves: differential growth across the leaf blade, with increased growth at the leaf's centre relative to the margins; and increased expansion of the spongy parenchyma layer compared to the palisade parenchyma layer, resulting in the direction of the curvature, which is inwards. These two processes together contribute to the typical leafy heads of cabbages.

Arthroscopic capsular release (ACR) is used for persistent shoulder stiffness after an index surgery. No cases of post-ACR humeral head osteonecrosis have been reported to date. A 56-year-old male patient underwent open reduction and internal fixation using a hook plate for acromioclavicular joint dislocation. Despite hardware removal, the patient presented with unresolved shoulder pain and range-of-motion (ROM) limitation. He had a history of hypertension, chronic hepatitis B infection, and alcohol consumption. Preoperative ROM was forward flexion 90°and internal rotation sacral level. Preoperative functional status was visual analog scale (VAS) score 4, American Shoulder and Elbow Surgeons (ASES) score 51, and Constant–Murley (CMS) score 48, and normal radiography and magnetic resonance imaging. Standard ACR was performed with 360° release of the joint capsule via electrocautery ablation. Six-months post-ACR, ROM (forward flexion: 135°, abduction: 135°, external rotation: 70°, internal rotation: T10 vertebra) and functional outcomes (VAS 2; ASES79; CMS 75) were significantly improved, without interval change in radiographic assessment. However, 21 months later, he had recurrent shoulder pain and decreased ROM. Radiography revealed humeral head osteonecrosis. Patients with intrinsic or extrinsic risk factors related to humeral head circulation disturbance should be monitored for humeral head osteonecrosis post-ACR.

Abstract. Leiomyoma is a benign tumour of smooth muscle cells classified into three groups: solid leiomyoma, angioleiomyoma and leiomyoblastoma. Angioleiomyoma arises from the tunica media of veins and arteries of vascular smooth muscle.Nasal cavity, paranasal sinus and oral cavity are the most frequent locations in Head and Neck region. Here we present the case of a tongue base angioleiomyoma with an emphasis on clinical data, pathologic findings and surgical approach. The patient complained about a one-month of globus sensation, dysphagia and hemoptysis without other systemic symptoms. Laryngoscopy revealed the presence of a 2 cm solitary submucosal mass located on the left tongue base covered with normal mucosa. The patient underwent direct laryngoscopy to perform a biopsy for the purpose of achieving the conclusive diagnosis. Treatment options were discussed, included surgical resection. Transoral robot-assisted resection was performed without complications. Clearly the description of our case does not want to have a purpose in terms of indications but wants to describe the possibility of considering TORS in the case of benign tumours of the tongue base, especially in cases like this where a standard technique can difficulty be achieved. Current literature review was provided and discussed.

Introduction: Obstructive sleep apnea (OSA) is not only common in the general population but even more so in patients with tumors of the head and neck region. Untreated, it leads to reduced quality of life, increased daytime sleepiness, and other comorbidities. The aim of this study was to determine the difference in the occurrence of OSA in the patient population with head and neck tumors compared to the general population as represented by the Trend cohort of the Study of Health in Pomerania (SHIP) , and to assess the influence of tumor treatment. Methods: Between July 2018 and December 2021, preoperative polysomnography was conducted in 47 patients with histologically confirmed squamous cell carcinoma in the oropharynx, hypo-pharynx, or larynx. A follow-up polysomnography was performed in 23 patients 2-11 months af-ter completing treatment. The collected data was correlated with tumor treatment and tumor size. Results: Of the included patients, 43 were male and four were female. Age ranged from 54 to 90 years. The pretherapeutic measurement found no significant difference in the prevalence of a pathologically elevated apnea-hypopnea index (AHI) in our patients compared to the SHIP-Trend cohort. In the follow-up measurement after treatment completion, a significant deterioration in AHI was observed. Initially, 70 % of patients had an AHI > 5, after therapy this increased to 87 %. The effect was particularly pronounced in the group of patients with advanced tumor stages who had received primary chemoradiation. Conclusion: OSA is a relevant condition in patients with head and neck cancer. Tumor treatment can lead to an increased occurrence of sleep-related breathing disorders, especially in patients with advanced tumor stages undergoing primary chemoradiation. Additional studies are neces-sary to better understand the exact mechanism involved.

Abstract Purpose Despite a considerable amount of literature on dual-energy-CT(DECT) iodine uptake of the head and neck, the physiologic iodine uptake of this region has not been defined yet. This study aims to establish reference values for the iodine uptake of healthy organs to facilitate clinical application. Material and Methods: Consecutive venous DECT scans of head and neck were reviewed, and unremarkable exams were included (n=617). 35 region of interest measurements were performed in 16 anatomical regions. Iodine uptake was compared among different organs/tissues and subgroup analysis was performed (male [n=403] vs female [n=214]; young [n=207] vs middle-aged [n=206] vs old [n=204]; normal weight [n=314] vs overweight [n=196] vs obese [n=107]]). Results: Overall mean iodine uptake values ranged between 0.5 and 9.4mg/ml. Women showed higher iodine concentration in the cervical vessels and higher uptake for the parotid gland, masseter muscle, submandibular glands, sublingual glands, palatine tonsils, tongue body, thyroid gland, and the sternocleidomastoid muscle than men (p0.04). With increasing age, intravascular iodine concentrations increased as well as iodine uptake for cerebellum and thyroid gland, while values for tongue and palatine tonsils were lower compared to younger subjects (p0.03). Iodine concentrations for parotid glands and sternocleidomastoid muscles decreased with higher BMI (p0.004), while normal-weighted patients showed higher iodine values inside the jugular veins, other cervical glands, and tonsils versus patients with higher BMI (p0.04). Conclusion: Physiologic iodine uptake values of cervical organs and tissues show gender-, age-, and BMI-related differences, which should be considered in clinical routine of head and neck DECT.

In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issue caused by near-duplicate videos is becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can be helpful to uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which are difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and clustering initial center under a condition that prior distribution is unknown, which seriously affect the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-headed attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing works, simulation results demonstrate that the performance of the proposed method.

Previously, pseudomyogenic hemangioendothelioma (PMHE) is regarded as epithelioid sarcoma-like hemangioendothelioma due to significant histologic overlapping and diffuse cytokeratin expression since the first description in 1992. After considerable controversy and long-term debating, it is currently defined as a distinct intermediate malignant, rarely metastasizing neoplasm with vascular/endothelial differentiation in nature. PMHE is characterized by young age (typically < 40 years old) and extremity location (approximately ~80%) with t(7:19) SERPINE1-FOSB fusion as the most common molecular alteration. Here we reported a 59-year-old male presenting with multifocal lesions, including right temporalis muscle, right frontoparietal calvarium, right pterygoid muscles, and right mandibular condyle. Histologic examination of the lesion from right temporal mass revealed a multinodular biphasic lesion composed of sheets and fascicles of elongated spindle cells, and epithelioid small round to ovoid cells infiltrating into the adjacent skeletal muscle admixed with abundant neutrophilic infiltration. No rhabdomyoblast-like cells, prominent nuclear pleomorphism and mitosis were identified. IHC staining showed that the tumor cells were diffusely and strongly positive for FOSB, pan-cytokerain (AE1/AE3), CD31, ERG, and molecular testing further demonstrated a t(9:19) EGFL7::FOSB fusion mRNA. This constellation of morphological, IHC and molecular findings was consistent with the diagnosis of PMHE. This is the first reported case of multiple PMHEs with EGFL7::FOSB fusion in a patient aged more than 50 years old in the head and neck area. Since the vast majority of the differential diagnoses of PMHE are high-grade malignancies with aggressive clinical behavior and PMHE is rarely reported in the head and neck region, awareness of this tumor will avoid misdiagnosis and over-treatments of this entity.

Ensuring the accuracy of wind power prediction is paramount for the reliable and stable operation of power systems. This study introduces a novel approach aimed at enhancing the precision of wind power prediction through the development of a multiscale hybrid model. This model integrates advanced methodologies including Improved Intrinsic Mode Function with Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), Permutation Entropy(PE), Least Squares Support Vector Regression (LSSVR), Regularized Extreme Learning Machine(RELM), Multi-head Attention (MHA), and Bidirectional Gated Recurrent Unit (BiGRU). Firstly, the ICEEMDAN technique is employed to decompose the non-stationary raw wind power data into multiple relatively stable sub-modes, while concurrently utilizing PE to assess the complexity of each sub-mode. Secondly, the dataset is reconstituted into three distinct components: high-frequency, mid-frequency, and low-frequency, to alleviate data complexity. Following this, the LSSVR, RELM, and MHA-BiGRU models are individually applied to predict the high, mid,and low-frequency components, respectively. Thirdly, the parameters of the low-frequency prediction model are optimized utilizing the Dung Betele Optimizer(DBO) algorithm. Ultimately, the predicted results of each component are aggregated to derive the final prediction. Empirical findings illustrate the exceptional predictive performance of the multiscale hybrid model incorporating LSSVR, RELM,and MHA-BiGRU. In comparison to other benchmark models, the proposed model exhibits a reduction in Root Mean Square Error(RMSE) values of over 10%, conclusively affirming its superior predictive accuracy.

A special vibration damper is proposed for material property identification through a scratching process on a vibrating object. This paper presents the design and working principle of a scratching damper based on a scratch test device. A non-contact electromagnetic shaker is used to generate the shaking force for the vibration of the tested object. The required pressure on the scratched material during the scratching process is generated by a compression spring and adjusted by changing the amount of compression of the spring. The proposed damper is designed and tested on extruded aluminum samples for the determination of its Young’s modulus and hardness and validated by using the standard test instruments. Observations of physical dimensions of the scratching tracks are determined by microscope and were utilized to compute the scratching energy factor. Load curves are obtained at different pressure of the scratching process. The hysteresis loop energy during the scratching process of the tested object is measured and used for the determination of material properties of the object. Furthermore, energy conservation law, scratch energy release rate and loop energy release rate are used to determine the Young’s modulus and hardness of the sample. The measurement accuracy of the modulus and hardness of the tested sample is evaluated. The proposed method of material testing has several advantages over the traditional methods such as low cost and high repeatability, and may be used as an alternative to the standard modulus and hardness testers.

With the development of deep learning, several Graph Neural Networks (GNN)-based approaches have been utilized for text classification. However, GNNs encounter challenges in capturing contextual text information within a document sequence. To address this, a novel text classification model RB-GAT is proposed by combining RoBERTa-BiGRU embedding and a multi-head Graph ATtention Network (GAT). First, the pre-trained RoBERTa model is exploited to learn word and text embeddings in different contexts. Second, the Bidirectional Gated Recurrent Unit (BiGRU) is employed to capture long-term dependencies and bidirectional sentence information from the text context. Next, the multi-head graph attention network is applied to analyze this information, which serves as a node feature for the document. Finally, the classification results are generated through a Softmax layer. Experimental results on three benchmark datasets demonstrate that our method can achieve an accuracy of 71.48%, 98.45%, and 80.32% on Ohsumed, R8, and MR, which is superior to the existing nine text classification approaches.

Artificial intelligence (AI), deep learning (DL) or machine learning (ML) is the ability of computer systems, machines and enginery to work devise procedures like humans. These technologies provide opportunities and possibilities to advance diagnostics and in planning also in the field of human medicine and dentistry. The purpose of this literature review was to ascertain the applicability and significance of AI, as well as to highlight its uses in maxillofacial surgery. The primary inclusion criterion for this publication was an original paper written in English focusing on the use of AI, DL or ML in maxillofacial surgery. The sources of information were PubMed, Scopus and Web of Science, and the queries were made on 31st of December 2023. The search strings used were “artificial intelligence maxillofacial surgery”, “machine learning maxillofacial surgery” and “deep learning maxillofacial surgery”. Following the removal of duplicates, all remaining publications that were returned by the searches and were screened by three independent operators to minimize the risk of bias. The analysis of publications from 1992 to 2023 identified certain records, of which 324 were finally selected. These were calculated according to the year of publication with a continuous increase (excluding 2012 and 2013) of R2 = 0.9295. Generally, in orthognathic dentistry and maxillofacial surgery, artificial intelligence and machine learning have gained popularity over the past few decades. When we included the keywords "planning in maxillofacial surgery" and "planning in orthognathic surgery", the set of published papers significantly increased to the number of 7535 publications. The first publication appeared in 1965, with an increasing trend (excluding 2014-2018), with an R2 value of 0.8642. These tools have been found useful for diagnosis, treatment planning in head and neck surgical oncology, cosmetic and aesthetic surgery, and in oral pathology. In orthognathic surgery, they have been utilised for diagnosis, treatment planning, assessment of treatment needs, cephalometric analyses, and orthognathic surgeries, among other applications. The review confirms that the current use of artificial intelligence and machine learning in maxillofacial surgery is focused mainly on the evaluation of digital diagnostic methods especially radiology, treatment plans and postoperative results. However, as these technologies are integrated in maxillofacial surgery and robotic surgery in head and neck region, it is expected that in the future they will be gradually utilized to plan and comprehensively evaluate the success of maxillofacial surgeries.

Background: The accurate diagnosis of regional lymph node metastasis is critical for guiding treatment decisions in head and neck cancer patients. Despite advances in imaging techniques, detecting nodal metastasis remains challenging, leading to potential undertreatment or overtreatment. This systematic review aims to identify molecular markers associated with occult metastasis in Head and Neck Squamous Cell Carcinoma (HNSCC) patients. Methods: The present research was conducted following PRISMA guidelines. Prospero registration nr. CRD42024522985. Results: Through a comprehensive literature search and review process, 634 articles were considered, 103 of them were finally included. Conclusions: Several promising markers were identified, including miR-205, DSG3, pan-CK AE1/AE3, HPV-16, Activin-A, Cyclin D1, and NPL that demonstrated effectiveness across multiple studies. Future research should focus on exploring combination scoring systems to improve diagnostic precision and optimize treatment selection in HNSCC patients.