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Abstract Spindle epithelial tumor with thymus-like elements (SETTLE) is a rare malignant neoplasm of the thyroid gland which is believed to arise from intrathyroidal thymic tissue. It predominantly affects young adults and children presenting with a thyroid mass of variable duration and rarely occurs in adults. It has a high overall survival with a tendency for delayed metastasis. SETTLE is a biphasic lobulated tumor composed of spindle shaped cells along with glandular formations seen on histopathological examination. Despite its typical morphology it is commonly misdiagnosed on histopathology due to its rarity and overlapping morphology with other close mimics such as a carcinoma, synovial sarcoma and thymoma. Herein we report such a case occurring in a middle aged female presenting with a neck mass. She had an initial diagnosis of metastatic poorly differentiated squamous cell carcinoma possibly with an orophayngeal primary in view of co expression of CK, p40 and p16 on immunohistochemistry. The patient underwent surgical resection with modified neck dissection. On review at our hospital it was diagnosed as SETTLE and she remains disease free after a follow-up period of 1 year. Diligent histopathological examination espoused with a judicious panel of IHC markers in conjunction with clinicoradiological findings forms the mainstay of diagnosis. Diffuse and strong p16 immunoexpression has not been documented or evaluated in literature so far, and needs to be explored for its diagnostic utility in this rare entity.

For medical fraternity, health system and policymakers to undertake effective countermeasures, a comprehensive assessment of the prevalence of anxiety among older adults is required; hence, we conducted a systematic review and meta-analysis using data pooled from surveys across the country. The search strategy was developed using medical subject headings (MeSH) terms and free-text keywords. We searched PubMed and Scopus for articles to report the prevalence of anxiety among older adults. The appraisal tool for cross-sectional studies was used for quality assessment. Prevalence from different studies was pooled together using the inverse variance heterogeneity method. Sensitivity analyses were performed to assess the impact of included studies’ methodological quality on pooled results and to investigate potential causes of heterogeneity. Twenty-three studies were included in this systematic review. The overall pooled estimate of the prevalence of anxiety in older adults was 18.7% (95% CI: 2.4, 38.8). The studies had a high degree of heterogeneity. Publication bias was assessed using a Doi plot which showed an luis furuya-kanamori (LFK) index of 1.21 indicating minor asymmetry. Like other parts of the world, India has witnessed a rise in the number of elderly due to lower fertility rates, higher life expectancies and a shift in illness patterns from communicable to non-communicable. The number of elderly people suffering from diseases of mental health is expected to rise dramatically. This review consolidates the existing evidence to showcase anxiety as an upcoming public health problem requiring due focus from policymakers and health systems.

Advanced Non-Small Cell Lung Carcinoma (NSCLC) patients with ROS1 gene rearrangement have shown significant therapeutic responses to tyrosine kinase inhibitors approved by the US Food and Drug Administration, with approximately 40 fusion partners documented in the existing literature. Our report highlights a novel fusion partner of ROS1 that has demonstrated a conclusive response to the current standard of treatment.

Background: Cervical cancer is a public health problem, and nursing personnel are crucial for successful implementation of low-cost cervical cancer screening approaches in low-resource settings. The following study assessed and compared the knowledge, attitude, and practices regarding cervical cancer and its screening among female nursing staff at different levels of health care facilities in western Rajasthan, India. Methodology: An anonymous pre-validated, structured questionnaire was used as the study tool among 233 female nursing personnel of primary, secondary, and tertiary care health facilities. Multiple logistic regression was performed to determine the association between level of knowledge with level of health care and other demographic variables. Results: The nursing staff of the tertiary care health facility demonstrated significantly higher knowledge compared to those working at primary and secondary levels [adjusted odds ratio (95% confidence interval) 11.01 (3.80–32.40)]. At tertiary care, the practices of the nursing professionals were not found significantly associated with any socio-demographic variable including age, marital status, or level of health care facility. Conclusion: The overall knowledge of cervical cancer was poor, especially among staff nurses at primary and secondary levels of health care. In order to implement a successful population-based screening program in India, it is important to update the nursing curriculum and start in-service trainings at primary and secondary levels of health care facilities.

The present study attempted for the first time an investigation on the effect of deep cryogenic treatment in liquid nitrogen (LN) on magnesium–cerium oxide (Mg/2wt.%CeO2) composites containing equal amounts of different length scales (micron and nanosize) cerium oxide (CeO2) particles. The disintegrated melt deposition method was used to synthesize Mg-2CeO2 micro- and nanocomposites, followed by hot extrusion as the secondary processing. Further liquid nitrogen treatment was performed at a cryogenic temperature of −196 °C. The combined effects of cryogenic treatment and reinforcement length scale on physical, mechanical, and thermal behaviors were studied. The results indicate that LN-treated micro- and nanocomposite samples exhibit, in common, a reduction in porosity, similar grain size, and a limited effect on the original texture of the matrix. However, microhardness, 0.2% Compressive Yield Strength (CYS), failure strain, and energy absorbed increased for both micro- and nanocomposite samples. Overall, results clearly indicate the capability of deep cryogenic treatment with LN to positively diversify the properties of both micro- and nanocomposite samples.

Introduction: Popularly, teletherapy (telecobalt/LA) equipment is based on a C-arm gantry system. Recently, a fast O-ring gantry system introduced a medical linear accelerator (LA) to smoothen the workflow of treatment of cancer patients because of the increasing trend of the number of cancer cases over the past few years. This study aimed to analyze the commissioning parameters and validation of the O-ring gantry-based LA for improved radiotherapy techniques. Material and Methods: Three-dimensional (3D) radiation field analyzer (RFA) used to commission HalcyonTM LA. It is used for measuring percent depth dose (PDD), profiles, and output factors. Results: TPS data was validated by comparing it with our measured data. Plans per the TG-119 protocol showed good agreement between treatment planning systems (TPS) calculated and measured doses. For patient-specific, QA plans showed good agreement with gamma evaluation criteria. Conclusion: Commissioning and validation of O-ring gantry system HalcyonTM LA was performed successfully.

Hyperbaric Oxygen Therapy (HBOT) utilizes 100% oxygen at high atmospheric pressure for clinical applications. HBOT has proven to be an effective supplementary treatment for a variety of clinical and pathological disorders. HBOT’s therapeutic results are based on the physiological effects of increased tissue oxygenation, or improved oxygen bioavailability. HBOT’s current indications in illnesses like as wound healing, thermal or radiation burns, and tissue necrosis point to its function in facilitating the regeneration process. Various research has revealed that HBOT plays a function in vascularization, angiogenesis, and collagen production augmentation. Individual regeneration capacity is influenced by both environmental and genetic factors. Furthermore, the regenerating ability of different types of tissues varies, and this ability declines with age. HBOT affects physiological processes at the genetic level by altering gene expression, delaying cell senescence, and assisting in telomere length enhancement. The positive results in a variety of indications, ranging from tissue regeneration to better cognitive function, indicate that it has enormous potential in regenerative and anti-aging therapy.

This paper introduces an innovative methodology to disrupt deep-learning (DL) surveillance systems by implementing an adversarial framework strategy, inducing misclassification in live video objects and extending attacks to real-time models. Focusing on the vulnerability of image-categorization models, the study evaluates the effectiveness of face mask surveillance against adversarial threats. A real-time system, employing the ShuffleNet V1 transfer-learning algorithm, was trained on a Kaggle dataset for face mask detection accuracy. Using a white-box Fast Gradient Sign Method (FGSM) attack with epsilon at 0.13, the study successfully generated adversarial frames, deceiving the face mask detection system and prompting unintended video predictions. The findings highlight the risks posed by adversarial attacks on critical video surveillance systems, specifically those designed for face mask detection. The paper emphasizes the need for proactive measures to safeguard these systems before real-world deployment, crucial for ensuring their robustness and reliability in the face of potential adversarial threats.

Contemporary culture presents a substantial obstacle for cyber security experts in the shape of software vulnerabilities, which, if taken advantage of, can jeopardize the Confidentiality, Integrity, and Availability (CIA) of any system. Data-driven and modern threat intelligence tools can enhance cyber security, bolster resilience, and foster innovation across cloud, multi-cloud, and hybrid platforms. As a result, performance evaluation and accuracy verification have become essential for Security Information and Event Management (SIEM) to prevent cyber threats. The SIEM system offers threat intelligence, reporting, and security incident management through the collection and analysis of event logs and other data sources that are specific to events and their context. We propose a hybrid strategy to address threat intelligence, reporting, and security incident management consisting of two layers that utilize a predefined set of characteristics. Here, we use RStudio to assess how well a hybrid intrusion detection system (HIDS) handles the CIC-Bell-DNS-EXF-2021 dataset. Furthermore, we have incorporated our developed model into Multi-Criteria Decision Analysis Methods (MCDM) to enhance the methods’ ability to identify complex DNS exfiltration attacks using machine learning algorithms: RF-AHP (RA), KNN-TOPSIS (KT), GBT-VIKOR (GV), and DT-Entropy-TOPSIS (DET). We consider several factors during the work, including accuracy, absolute error, weighted average recall, weighted average precision, kappa value, logistic loss, and root mean square deviation (RMSD). We use the Machine-Automated Model function to integrate and validate the models. According to the findings, GV has the highest level of accuracy, with a rate of 99.52%, while KT has the lowest level of authenticity, with a rate of 93.65%. Furthermore, these findings illustrate enhanced performance metrics for multiclass classification in comparison to previous approaches.

Abstract Topological slow light exhibits potential to achieve stopped light by virtue of its widely known robust and non-reciprocal behaviours. Conventional approach for achieving topological slow light often involves flat-band engineering without disentangling the underlying physical mechanism. Here, we unveil the presence of counter-propagating waves within valley kink states as the distinctive hallmark of the slow light topological photonic waveguides. These counter-propagating waves, supported by topological vortices along glide-symmetric interface, provide significant flexibility for controlling the slowness of light. We tune the group velocity of light by changing the spatial separation between vortices adjacent to the glide-symmetric interface. We also dynamically control the group delay by introducing a non-Hermitian defect using photoexcitation to adjust the relative strength of the counter-propagating waves. This study introduces active slow light topological photonic device on a silicon chip, opening new horizons for topological photon transport through defects, topological light-matter interactions, nonlinear topological photonics, and topological quantum photonics.

Sentiment analysis has received incremental growth in recent years for emerging applications, including human-robot integration, social platforms monitoring, and decision-support systems. Several neural or transformer model-based solutions have been provided in the field of sentiment analysis that relies on the decision of a single classifier or neural model. These are erroneous to encode contextual information into appropriate dialogues and increase extra computational cost and time. Hence, we proposed a compact and parameter-effective Particle Swarm Optimization-based Ensemble Fusion Voting Model (PSO-EFVM) that exploited the combined properties of four ensemble techniques, namely Adaptive-Boost, Gradient-Boost, Random-Forest, and Extremely-Randomized Tree with Particle Swarm Optimization (PSO)-based hyperparameter selection. The proposed model is investigated on five cross-domain datasets after applying the foremost initialization and feature extraction using Information Gain (IG). It employs adaptive and gradient learning to incorporate the automatic attribute selection with the arbitrary loss function optimization. In short, a generalized two-block composite classifier is designed to perform context compositionality and sentiment classification. A population-based meta-heuristic optimization PSO is applied to each base ensemble learner that calculates weights for the best parameter selection. Comprehensive investigations of different domains reveal the superiority of the proposed PSO-EFVM over established baselines and the latest state-of-the-art models.

Ball milling is an effective method for developing a homogenous and refined microstructure for composites. In this study, we synthesized ultrahigh strength Al7075/xZrO2 alloy nanocomposites. These nanocomposites were specially fabricated by the in-situ powder metallurgy technique from high-purity elemental powders through a multi-step process, which included ball milling, uniaxial cold compaction, traditional sintering in an inert atmosphere, and hot extrusion. The ZrO2 nanoparticles with varying volume percentages (x vol.% = 0, 1.25, 2.53, 3.84, and 5.19) were used as a reinforcement. Ball milling was performed to mechanically alloy the elemental powders that reduce the grain size of the powder and homogeneously disperse the nano ZrO2 in the matrix. The physical, mechanical, microstructural, and tribological properties of the nanocomposites were determined. The results showed that adding 2.53 vol.% ZrO2 nanoparticles considerably improved the mechanical and tribological properties. The tensile strength and yield strength of the 2.53 vol.% alloy nanocomposites increased significantly. The wear resistance of the nanocomposite increased up to 5.19 vol.% ZrO2. The results obtained from the newly developed composites were compared with those of Al7075 alloy composites produced earlier.

Metal matrix composites (MMCs) are dynamic and fascinating materials as they can be designed to suit the end property requirements for any present and futuristic application [...]

The deep learning method (DLM) is one way to fix issues in optical nonorthogonal multiple access (O-NOMA) systems that are caused by signals that overlap and interfere with each other. NOMA increases the optical framework's spectrum efficiency, allowing several users to share the same time-frequency resources. However, NOMA-DLM-based detection's complicated interference patterns and variable channel conditions are challenging for conventional detection methods to manage. By utilizing deep neural networks' advantages, these methods are able to overcome these challenges and improve detection performance. An overview of the main features and advantages of DLM detection in massive multiple input and output (M-MIMO) O-NOMA systems is given in this article. It describes the essential elements, such as the training procedure and the network design. In order to process the sent symbols or decode data streams, DLM networks are built to process the incoming signal, power allocation coefficients, and extra information. Gradient descent optimization is used to update the network parameters iteratively while training the network, and a diverse and representative dataset is created. Additionally, the challenges of detecting deep learning in O-NOMA systems are examined. It recognizes that in order to get the best results, significant computational resources, a large amount of training data, and careful model design are required. It looks at and compares the 16 × 16, 32 × 32, and 64 × 64 M-MIMO-NOMA models in terms of bit error rate (BER), complexity, and power spectral density (PSD). The suggested DLM algorithms have been demonstrated to perform better than traditional methods by achieving an excellent BER of 10-3 at 4.1 dB and PSD (−2500) performance with low complexity.

The widespread dissemination of false information across various online platforms has emerged as a matter of paramount concern due to the potential harm it poses to individuals, communities, and entire nations. Substantial efforts are currently underway in the research community to combat this issue. A burgeoning area of study gaining significant traction is the development of fake news identification techniques. However, this field faces formidable challenges primarily stemming from limited resources, including access to comprehensive datasets, computational resources, and evaluation tools. To overcome these challenges, researchers are exploring various methodologies. One promising approach involves the use of feature abstraction and vectorization techniques. In this context, we highly recommend utilizing the Python sci-kit-learn module, which offers many invaluable tools such as the Count Vectorizer and Tiff Vectorizer. These tools enable the efficient handling of text data by converting it into numerical representations, thereby facilitating subsequent analysis. Once the text data is appropriately transformed, the next crucial step involves feature selection. To achieve optimal results, researchers often employ feature selection methods based on misperception matrices. These methods allow for the exploration and selection of the most suitable features, which are essential for achieving the highest accuracy in fake news identification.

The detrimental effects of PM2.5 on the health of urban populations, especially in developing countries, are being carefully addressed by governments worldwide. To mitigate the adverse health effects of air pollution, this paper presents a case study and suggests a three-phase plan for implementing a prediction and control approach in the Thai metro region of Nakhon Ratchasima (NRM). A data-driven assessment of the region's air pollution situation is conducted in the initial phase, which is then followed by an analysis of the health risks related to PM2.5 concentrations. It is therefore imperative to determine which machine learning model has the best capabilities to estimate PM2.5 concentration. With the help of this advanced predictive capability, decision-makers will have an important window of opportunity to put preventive measures in place to safeguard the population from the adverse effects of air pollution. The study showed that there were respiratory diseases in the NRM area because of high concentrations of PM2.5 particles, primarily from vehicle exhaust, which far exceeded Thailand's threshold of 15 μg m−3. A total of 10,379 people, or 16.91% of the affected population, lived in zones with PM2.5 concentrations >38 μg m−3 in 2019. Another 741 people, or 1.21% of the population, lived in zones with PM2.5 values between 36 and 37 μg m−3. The study finds that Extra-Trees regression combined with AdaBoost has the best-predicting capacity for PM2.5 ambient concentration in the NRM area out of the 13 machine-learning regression models examined. This case study presents an additional tool for policymakers to employ in controlling adverse health effects in urban areas.

Abundant {10–12} twins appeared in an extruded Mg-2.8Y (wt. %) sheet with rare-earth (RE) texture under compression along the transverse direction (TD). Twinning-detwinning behavior during compression-tension loading was quantitatively investigated via quasi-in-situ EBSD observation. The evolution of deformation mechanisms was quantitatively studied by calculation of the plastic strain fraction of twinning, detwinning, and dislocation slip. Twinning and detwinning were the dominant deformation modes in compression and reverse tension, respectively, owing to their relatively higher Schmid factors (SF) and lowest activation stresses (τ). Twin variants with SF ranking 1st and 2nd were activated preferentially while detwinning with low SF ranking showed high activation. The impact of texture and load path on variant selection was systematically discussed. Moreover, short twin chains only passing through two or three grains caused by twinning transfer were observed. Grain boundary misorientation angle (GBMA) and geometric compatibility factor (m’) were introduced to analyze the crystallographic characteristics of twinning transfer. GBMA ≤34.5° or m’ ≥ 0.80 is a necessary condition for most twinning transfer events. RE texture as well as the nearly uniform distribution of GBMA gave rise to short twin chains and restricted the formation of long twin bands. The relationship between GBMA and m’ was also discussed.

This study for the first time reports that insights into microstructure and thermal and compressive responses can be best achieved following exposure to different cryogenic temperatures and that the lowest cryogenic temperature may not always produce the best results. In the present study, a Mg-SiO2 biocompatible and environment-friendly nanocomposite was synthesized by using the Disintegrated Melt Deposition method followed by hot extrusion. Subsequently, it was subjected to four different sub-zero temperatures (−20 °C, −50 °C, −80 °C, and −196 °C). The results reveal the best densification at −80 °C, marginally improved ignition resistance at 50 °C, the best damping response at −80 °C, the best microhardness at −50 °C, and the best compressive response at −20 °C. The results clearly indicate that the cryogenic temperature should be carefully chosen depending on the property that needs to be particularly enhanced governed by the principal requirement of the end application.

Fatigue refers to the progressive and localized structural damage that occurs when a material is subjected to repeated loading and unloading, typically at levels below its ultimate strength. Several failure mechanisms have been observed in practical scenarios, encompassing high-cycle, low-cycle, thermal, surface, corrosion, and fretting fatigue. Fatigue, connected to the failure of numerous engineered products, stands out as a prevalent cause of structural failure in service. Conducting research on the advancement and application of fatigue analysis technologies is crucial because fatigue analysis plays a critical role in determining the service life of components and mitigating the risk of failure. This study compiles data from a wide range of sources and offers a thorough summary of the state of fatigue analysis. It focuses on the effects of different parameters, including hardness, temperature, residual stresses, and hardfacing, on the fatigue life of different materials and their alloys. The fatigue life of alloys is typically high at low temperatures, but it is significantly reduced at high temperatures or under high-stress conditions. One of the main causes of lower fatigue life is residual stress. High-temperature conditions and hardfacing processes cause the development of tensile residual stresses, which in turn decreases fatigue life. But, if the hardness of the material significantly increases due to hardfacing, then the fatigue life also increases. This manuscript focuses on reviewing the research on fatigue-life prediction methods, shortcomings, and recommendations.

Magnesium-based biomaterials have recently been in the research spotlight in the field of biomedical engineering owing to their properties, such as density and biocompatibility that closely align with those of human bone. However, poor strength and rapid degradation impede their application as bone support fixtures. The present research aims to tailor the properties of Mg by using a novel ultrasonic-assisted rheo-squeeze casting approach. To satisfy the demand, pure Mg (Mg), MHA (Mg/5%HA), MZHA (Mg-1%Zn/5%HA/), and MSHA (Mg-1%Sn/5%HA) were fabricated, and various mechanical tests were conducted to assess the composite’s mechanical properties, including its microhardness, tensile strength, compressive strength, flexural strength, and impact strength. The microstructural and fractured morphology of the composites was examined by scanning electron microscopy (SEM), whereas their elemental composition was analyzed by field emission scanning electron microscopy (FESEM) equipped with elemental mapping. Comparing the MZHA, MHA, and pure Mg samples, the mechanical behavior of MSHA is significantly superior. This is due to composites containing Sn that possess finer-grained materials, which act as barriers to dislocation motion while increasing the strength of the materials. From the observed results, there is a significant improvement in the microhardness of MSHA of 64.5% when compared to that of pure Mg, and 42.7% compared to MHA. Furthermore, MSHA composites possess noticeable enhancements in tensile and compression performance of 80.8% and 58.3%, respectively, and 19% and 22.4% compared to MHA. Additionally, the impact and flexural performance of MSHA composites exhibit higher performance (41% and 42%) than pure Mg and 8% and 7% against the MHA composite.

Magnesium-based multicomponent alloys with different compositions, namely Mg60Al20Zn5Cu10Mn5 (Mg60 alloy), Mg70Al15Zn5Cu5Mn5 (Mg70 alloy), and Mg80Al5Cu5Mn5Zn5 (Mg 80) alloys, were prepared using the disintegrated melt deposition technique. The DMD technique is a distinctive method that merges the benefits from gravity die casting and spray forming. This approach facilitates high solidification rates, process yields, and reduced metal wastage, resulting in materials with a fine microstructure and minimal porosity. Their potential as biodegradable materials was assessed through corrosion in different simulated body fluids (SBFs), microstructure, and cytotoxicity tests. It was observed that the Mg60 alloy exhibited low corrosion rates (~× 10−5 mm/year) in all SBF solutions, with a minor amount of corrosive products, and cracks were observed. This can be attributed to the formation of the Mg32(AlZn)49 phase and to its stability due to Mg(OH)2 film, leading to excellent corrosion resistance when compared to the Mg70 and M80 alloys. Conversely, the Mg80 alloy exhibited high corrosion rates, along with more surface degradation and cracks, due to active intermetallic phases, such as Al6Mn, Al2CuMg, and Al2Cu phases. The order of corrosion resistance for the Mg alloy was found to be ASS > HBSS > ABP > PBS. Further, in vitro cytotoxicity studies were carried out using MDA-MB-231 tumor cells. By comparing all three alloys, in terms of proliferation and vitality, the Mg80 alloy emerged as a promising material for implants, with potential antitumor activity.

Herein, ZrO2 and Si + ZrO2 composite coatings on AZ91D alloys are deposited at a constant voltage of 8 kV and 1 Å/s deposition rate using the electron beam physical vapor deposition (EBPVD) method. Further, the samples are examined for surface morphology, phase analysis, adhesion, corrosion, and antibacterial properties, as per ASTM standards. The adhesion strength of the composite (Si + ZrO2) coating nominally dropped (9%) compared to the ZrO2 coating even when the coating thickness increased by 18%. However, the composite (Si + ZrO2) coating improved wettability because silanol promotes hydrogen bonding with water molecules, which elevates the surface energy of the silica and increases its hydrophilic nature. Further, increased wettability and surface roughness have the potential to improve cell adhesion and proliferation. The corrosion potential (Ecorr) values of the coated samples exhibited a positive shift in the potentiodynamic polarization curve, indicating a substantial increase in their corrosion resistance in the artificial blood plasma (ABP) electrolyte. Similarly, SEM images of both coated corroded samples are less affected in the ABP solution, indicating that the coating mitigated heavy cracks and micropores, protecting them from corrosion. The Si + ZrO2 coatings exhibited exceptional performance in preventing bacterial infiltration by Staphylococcus aureus, thus inhibiting the subsequent formation of biofilms. In addition, these coatings demonstrate improved vitality among fibroblast cells, enabling better cellular spreading and proliferation.

Introduction: Cancer impacts not only people living with cancer but also their caregivers. In hospital, caregivers always have pressure on them and their personal and private lives are disrupted during the caring process. Aim: To identify the various factors affecting the Quality Of Life (QOL) among caregivers of cancer patients. Materials and Methods: This quantitative study with an exploratory research design was conducted in oncology Outpatient Department (OPD) of All India Institute of Medical Sciences, Rishikesh, India, from November 2019 to February 2020. A total of 256 caregivers of cancer patients, who were visiting various oncology units were included. Data regarding caregiver’s sample characteristics, clinical variables and caregiver’s Oncology Quality of Life questionnaire (CarGOQoL) were collected. Statistical analysis was done using Chi-square test and Fisher-exact tests were used to study variables. Results: Majority, 94 (37%) belonged to 41-50 years age group, 143 (56%) were females, and 142 (56%) lived in rural areas. Patients’ diagnoses were breast cancer in 94 (37%), Stage-III in 133 (52%), symptoms lasting more than 6-12 months in 103 (40%), and were partial dependent in 172 (67%). A total of 123 (48%) of caregivers scored less in the CarGOQoL questionnaire, so about half of the caregivers had a poor QOL. Caregiver coping (43%) and the private life domain were enormously affected in 193 (37%). Significant relationships with caregivers’ QOL were seen for variables like female gender (p-value=0.037), educational level of patients (p-value=0.018), caregivers with co-morbidities (p-value=0.05), and the number of earning members in the family (p-value=0.022). Conclusion: Care burden always has an impact on the caregiver’s overall QOL. It mainly affected their psychological well-being, burdens, and private lives. Therefore, comprehensive attention should be given to patients as well as caregivers.

Multidisciplinary teams decrease the likelihood of adverse pregnancy outcomes in high-risk pregnant cardiac patients. We present the case of a patient with complex congenital heart disease and a mechanical mitral valve, whose treatment included warfarin until delivery despite the discovery of placental hematomas. A multidisciplinary approach mitigated both maternal and fetal adverse pregnancy outcomes.

The present study investigates the effect of nanoindentation on single-crystal magnesium specimens using the embedded-atom method potential in molecular dynamics simulation. Analyses are done under dynamic loading where the load-bearing capacity and change in the structural configuration are studied on the basal (Z–direction) and two prismatic planes (X– and Y–directions) with varying indenter velocities. The investigation of structural evolution is done using atomic displacement analyses to measure the net magnitude of displacement, atomic strain analyses to evaluate the shear strain developed in the process, and Wigner–Seitz defect analyses to calculate the total vacancies at varied timesteps. Furthermore, Voronoi analyses are done when indented on the basal plane to identify the cluster distribution at different planar depths of the specimen. From the analyses, it has been observed that the load-bearing capacity of the specimen varies with the indentation velocity and the direction of indentation on the specimen. Additionally, it is seen that the observed shear and total atomic displacement in the Z–direction is the least in comparison to the other two axes. The partial dislocation 1/3 is seen to be majorly present and the population of dislocation loops is more abundant for lower indenter velocities. Furthermore, clusters and are the major indices developed during nanoindentation on the basal plane where they exhibit symmetrical distribution as observed from the Z–direction.

Abstract Background Despite the high prevalence of locally advanced head and neck cancer, treatment failure in the form of a cutaneous deposit in the treatment field during radiation is not common. There has never been a cytology-proven published case of marginal treatment failure in the cutaneous region during radiotherapy. Case presentation A 51-year-old male patient was diagnosed with squamous cell carcinoma of the left tonsillar fossa. After a partial response to induction chemotherapy, the patient was treated with definitive chemo-radiotherapy. After the 23rd fractionation of radiotherapy, there was a clinical progression in the form of a solitary skin nodule within the treatment field, which was further treated with an electron boost to a total dose of 70 Gy followed by palliative chemotherapy. Conclusion During definitive chemoradiotherapy, failure outside the high-dose radiation field is not common, and a skin nodule during treatment had never been described. Our case demonstrates the importance of performing thorough clinical examinations on a weekly basis, not only for toxicity assessment but also for treatment response.

The second-phase particles in magnesium alloys could affect the mechanical properties of the material significantly. In this work, 3D finite element models with explicit incorporation of second-phase particles are established. The simulations are calibrated with the experimental results of the Mg-1Gd alloy. The influences of factors, such as the particle distribution, size, and orientation of cylindrical particles, on precipitation hardening are investigated in detail. Three interface conditions between particles and the matrix—perfect bonding and high- and low-strength bonding—are studied at the same time. The interface conditions are shown to exert a stronger influence on precipitation hardening compared to the factors of particle distribution and size. In contrast, the influence of the orientation of cylindrical particles at grain boundaries outweighs the effect of interface property. When second-phase particles are relatively large and all located at grain boundaries, the hardening effect can be improved, and the magnesium alloy shows relatively high flow stress. However, the high hardening effect from the second-phase particles could result in high local stress concentration and possible early failure or low ductility of Mg alloys.

A magnesium-based metal matrix composite, Mg-5Se-2Zn-2SiO2, was synthesized using the Disintegrated Melt Deposition (DMD) method followed by hot extrusion. Elemental analysis revealed that the material experienced selenium loss which was attributed to the evaporation of selenium at high temperatures. Superior damping characteristics were exhibited while retaining similar Young’s modulus, and significant grain refinement also resulted in decisively superior mechanical properties such as hardness (32% increase), fracture strain (39% increase), as well as yield and ultimate compressive strength (157% and 54% increase, respectively). These were a consequence of SiO2 addition as well as presence of Mg2Si (and MgSe) intermetallic phases which were detected by X-ray characterization. Furthermore, while the material had lower corrosion resistance than pure magnesium, it retained acceptable corrosion resistance as well as structural integrity after the full immersion duration of 28 days. Overall, the material exhibits promising potential for applications in the biomedical field, especially in development of smaller and lighter implants where mechanical properties are paramount, with key lessons learned for the synthesis of Mg-materials containing selenium for the future.

The current study focused on developing a biodegradable implant composite material that could work in a multitude of applications. The fabricated composite showcases a porous matrix of Mg–hydroxyapatite developed through the spacer-holder technique. The composite was incorporated with a natural medicinal plant, i.e., Aloe barbadensis miller, commonly known as the Aloe vera plant. The final composite was enveloped under a thin layer of PLA to work as an encapsulated drug as well as a composite material for implant applications. Further, the mechanical and microstructural properties were analyzed along with corrosion analysis through the weight loss method and pH change. The experiments showed an improvement in the corrosion rate when tested under cell culture medium. The antibacterial rates were experimented with under different aloe vera concentrations against Gram-positive B. subtilis and Gram-negative E. coli, and finally, a minimum inhibitory value was formulated for further experimentations. Hemocompatibility and surface wettability tests were also performed, which revealed improved surface hydrophilicity with a reduced hemolysis rate. An in vitro cell viability analysis was performed against the MG63 osteoblast cell line to indicate the cytotoxicity and cytocompatibility of the samples. This research proposed a novel composite material that provides antibacterial and non-toxic properties and retains its strength under a physiological environment.

Extramedullary hematopoiesis (EMH) is a rare entity most often associated with primary myelofibrosis, chronic myeloproliferative neoplasms, chronic hemolytic states, such as thalassemia, sickle cell anemia and certain solid tumors. Various theories have been postulated as the mechanism for occurrence of EMH. Iron deposition and/or fatty infiltration along with increased density of liver and spleen may be observed on imaging. Also, organs may show diffuse involvement or mass like foci of hematopoiesis on imaging. Treatment includes transfusion, surgery, hydroxyurea and radiation. In this review we narrate the clinicopathological features, radiological imaging and treatment strategies of non hepatosplenic Extramedullary hematopoiesis.

The purpose of this research work is to present a numerical study through artificial neural networks (ANNs) to solve a SIQ-based COVID-19 mathematical model using the effects of lockdown. The effects of lockdown are considered to the three-dimensional mathematical model, “susceptible”, “infective” and “quarantined”, i.e. the SIQ system. ANNs and Levenberg–Marquardt backpropagation (LMB) are used to present the numerical analyses of the SIQ system-based COVID-19. Three different types of authentications, testing and training as sample data are applied to solve the SIQ system. Statistical ratios for the SIQ-based COVID-19 mathematical model are selected – 80% for training and 10% for both testing and authentication. The obtained numerical results of the SIQ mathematical system have been compared with the reference dataset, which is constructed through Adams solutions. The obtained numerical performances of the nonlinear SIQ dynamical model are testified with a reduction of the error in mean square sense in the range of 10−9 to 10−12.

Abstract Introduction Brain metastases (BM) are associated with dismal prognosis as they cause significant morbidity and affect the quality of life of patients. Management of BM depends on the following factors: age, patient performance, size and the number of lesions, location of the tumor, comorbidities, primary tumor type, and extracranial disease burden. In the present study, the pattern of occurrence, clinical characteristics, treatment outcome of brain metastases, and factors, tumor characteristics, and treatment that may impact BM patients’ overall survival were analyzed. Methods Retrospective analysis of medical records of 116 patients with histologically proven primary site solid tumors with brain metastases was done in the present study. Clinicoradiological and pathological parameters were documented. The relationship between variables and outcome was assessed by univariate analysis using the Cox proportional regression model to reach a significance of p < 0.05, to determine independent predictors of overall survival. Results One hundred sixteen patients of BM from various solid malignancies were included. Age ranged from 18 to 81 years (median 53.5). One hundred four patients received WBRT with a dose range of 8–40Gy/1–15fr, 7 received SRS with a dose of 18–24Gy depending on the size of the metastatic lesion, and 2 received SRT 27–33Gy/3fr. At the time of final analysis, 47 patients with BM had expired, 60 were lost to follow-up, and 9 were alive. Median survival was 8.25 (0.5–32.5 months) months. Female gender (χ 2 = 8.423; p = 0.015), RPA I (χ 2 = 9.353; p = 0.05), and metachronous BM (χ 2 = 3.793; p = 0.03) were associated with better survival. Patients with age 41–50 years, adenocarcinoma lung histology, and supratentorial location survived more than 2 years but did not show any statistical significance. Conclusion Brain metastases portend a very dismal prognosis. Certain clinicoradiological and pathologic factors have been identified to affect survival. More prospective multicentric trials, with a larger sample size, need to be conducted to assess the benefit of radiation in patients with limited life expectancy and identify prognostic and predictive factors for survival.

6G communication requires high-speed and advanced functionalities on-chip. Here the authors demonstrate broadband phototunable topological waveguide and demultiplexing chip with record single-channel 160 Gbit/s communication link and excellent channel isolation for 300 GHz band.

In this study, the Mg-15Se binary system was, for the first time, investigated and synthesized using the powder metallurgy (PM) method, including microwave sintering and hot extrusion. The resulting material was shown to possess visible pores with a porosity of 2.91%, higher than other Mg materials synthesized using this method in the literature. Despite this, the material not only exhibited a comparable corrosion response with pure Mg but also a significantly superior mechanical response (76% greater damping capacity, 57% increase in hardness, and increases of 21%, 50%, and 51% for compressive yield strength, ultimate compressive strength, and fracture strain, respectively). Thus, this not only opens the door for future work concerning the addition of medicinal Se to nutritional Mg element and the optimization of process parameters but also could potentially be making inroads into the biomedical field with the use of selenium as a biomedical-oriented alloying element.

Magnesium and its composites have been used in various applications owing to their high specific strength properties and low density. However, the application is limited to room-temperature conditions owing to the lack of research available on the ability of magnesium alloys to perform in sub-zero conditions. The present study attempted, for the first time, the effects of two cryogenic temperatures (−20 °C/253 K and −196 °C/77 K) on the physical, thermal, and mechanical properties of a Mg/2wt.%CeO2 nanocomposite. The materials were synthesized using the disintegrated melt deposition method followed by hot extrusion. The results revealed that the shallow cryogenically treated (refrigerated at −20 °C) samples display a reduction in porosity, lower ignition resistance, similar microhardness, compressive yield, and ultimate strength and failure strain when compared to deep cryogenically treated samples in liquid nitrogen at −196 °C. Although deep cryogenically treated samples showed an overall edge, the extent of the increase in properties may not be justified, as samples exposed at −20 °C display very similar mechanical properties, thus reducing the overall cost of the cryogenic process. The results were compared with the data available in the open literature, and the mechanisms behind the improvement of the properties were evaluated.

The most effective and cutting-edge method for achieving a 0.004 mm precision on a typical material is to employ die-sinking electrical discharge machining (EDM). The material removal rate (MRR), tool wear rate (TWR), residual stresses, and crater depth were analyzed in the current study in an effort to increase the productivity and comprehension of the die-sinking EDM process. A parametric design was employed to construct a two-dimensional model, and the accuracy of the findings was verified by comparing them to prior research. Experiments were conducted utilizing the EDM machine, and the outcomes were assessed in relation to numerical simulations of the MRR and TWR. A significant temperature disparity that arises among different sections of the workpiece may result in the formation of residual strains throughout. As a consequence, a structural model was developed in order to examine the impacts of various stress responses. The primary innovations of this paper are its parametric investigation of residual stresses and its use of Haynes 25, a workpiece material that has received limited attention despite its numerous benefits and variety of applications. In order to accurately forecast the output parameters, a deep neural network model, more precisely, a multilayer perceptron (MLP) regressor, was utilized. In order to improve the precision of the outcomes and guarantee stability during convergence, the L-BFGS solver, an adaptive learning rate, and the Rectified Linear Unit (ReLU) activation function were integrated. Extensive parametric studies allowed us to determine the connection between key inputs, including the discharge current, voltage, and spark-on time, and the output parameters, namely, the MRR, TWR, and crater depth.

A magnesium-based multi-component alloy (MCA), Mg70Al18Zn6Ca4Y2, was successfully synthesized using the Turning-Induced Deformation (TID) method, with promising improvements in multiple properties such as damping capabilities, hardness (11% to 34% increase), and strength (5% to 15% increase) over its conventional cast and extruded equivalent which has already been established as a high-performance MCA exhibiting superior mechanical properties over other Mg-based materials while retaining acceptable ductility. This new TID-based MCA comes only at a slight compromise in the aspects of ductility, ignition resistance, and corrosion resistance, which was previously observed in other TID-based materials. In addition, the general microstructure and secondary phases of this MCA were retained even when using the TID method, with only minimal porosity (70Al18Zn6Ca4Y2 remained very high at 915 °C, positioning it as a potential Mg-based material suitable for aerospace applications with a high ignition resistance. This is tantamount to a successful application of TID to yet another class of Mg-based materials and opening the door to future explorations of such materials.

Recently, the physics of J=3/2 electrons on a honeycomb lattice has received attention with the suggestion of hosting an SU(8) Dirac semimetallic state. Motivated by this, in this work we provide a systematic study of the interplay of various hopping pathways and atomic spin-orbit coupling for the low-energy electrons in candidate d^{1} transition-metal halides MX_{3} (M=Ti,Zr,Hf; X=F,Cl,Br). By combining first-principles calculations and a minimal hopping Hamiltonian, we uncover the role of dominant direct metal-metal hopping on top of indirect metal-halide-metal hopping. This sets up a hierarchy of hopping pathways that centrally modify the SU(8) picture for the above materials. These hopping interactions, along with the spin-orbit coupling, lead to a plethora of exactly compensated metals instead of the SU(8) Dirac semimetal. Remarkably, the same can be understood as descendants of a topological insulator obtained by gapping out the SU(8) Dirac semimetallic phase. The resultant compensated metals have varied Fermi surface topology and are separated by Lifshitz phase transitions. We discuss the implications of the proximate Lifshitz transition, which may be accessed via strain, in the context of the relevant materials.

Magnesium-based biodegradable implant materials for the osteosynthesis process (fixation or stabilizing of a fractured bone) are on the verge of being used clinically. However, the rapid degradation of magnesium-based materials in the physiological environment results in a loss of mechanical integrity before the complete healing of the fracture site. To address this issue, the present study used Silicon Nitride (Si3N4) nanoparticles to improve the in-vitro degradation resistance along with the mechanical strength and ductility of Magnesium. The Si3N4 nanoparticles were homogeneously reinforced in the pure Magnesium matrix through the ultrasonic-assisted stir casting method. Moreover, the effect of Si3N4 nanoparticles on microstructure, mechanical, in-vitro corrosion and bioactivity response of Mg/Si3N4 nanocomposites was studied. Notably, the inclusion of 1.0 vol% Si3N4 nanoparticles increased tensile strength by 1.4 times and ductility by two times. In addition, the elastic modulus of Mg/Si3N4 nanocomposites is within the range of local cortical bone elastic modulus. In-vitro immersion experiments in simulated physiological fluids revealed a 2.2-fold reduction in degradation rate compared to pure Magnesium. Moreover, the addition of Si3N4 nanoparticles enhanced the in-vitro bioactivity, as the surface of the nanocomposites showed a high needle-like Ca–P apatite layer with a 1.41 Ca/P ratio of the deposited layer close to hydroxyapatite's Ca/P ratio (1.64). Overall, this study provides the basis for the fabrication of stable yet completely biodegradable Mg/Si3N4 nanocomposite bone implants for the osteosynthesis process.

Objectives: The aim of the study was to compare the stress distribution of magnesium alloy and titanium fracture fixation plates using 3 different designs of fixation plates (Straight plate with interval, Straight plate without interval, and Circular bar) used in simple unilateral mandibular angle fracture and to analyze the stresses acting within the screws used to stabilize the plates. Methods: Finite element models of 3 fixation screw designs (Straight plate with interval, Straight plate without interval, and Circular bar) were developed to simulate the biomechanics of mandibular fixation devices. Material properties of mandibular bone, magnesium and titanium alloy (Titanium alloys) was incorporated. Fracture lines were created on the angle of mandible and loads of 100–500 N were applied in sequence on the mandibular premolar/molar region of the normal side. Von Mises stresses and the magnitude of displacement on the fixation plates and screws were calculated. Results: For 300 N of applied load the straight plate with interval showed stress values in the range of 2.3 MPa–505 MPa (Magnesium alloys) and 3 MPa–533 MPa (Titanium alloys). The straight plate without interval showed Von Mises stress values in the range of 0.9 MPa–431 MPa (Magnesium alloys) and 2.3 MPa–460 MPa (Titanium alloys). However, the Von mises stress values for Circular bar were in the range of 3 MPa–345 MPa (Magnesium alloys) and 3 MPa–353 MPa (Titanium alloys). The displacement of the fixations plates for all the designs were less than 1 mm. The von mises stress values for Circular bar showed less stresses acting within the prosthesis compared to the straight plate with interval, and straight plate without interval.

Abstract Cytotoxicity of any biomedical material needs to be investigated for successful application within the human tissues. In this study, manganese in low amounts of 0.3, 0.5 and 0.7 (wt.%) was added to Mg2Zn1Ca alloy using Disintegrated Melt Deposition (DMD) followed by hot extrusion and the extruded alloys were tested for in vitro cytocompatibility using cell viability assays (CCK-8, LDH enzyme release assay, cell cytoskeleton and cell morphology) and in vitro osteogenic potential was evaluated using ALP, Alizarin Red and RT-PCR assays. Addition of manganese improved the cell viability and osteogenic potential in variable concentrations. The Mg2Zn1Ca /0.3 Mn and Mg2Zn1Ca /0.5 Mn alloys showed increased cell viability percentage compared to Mg2Zn1Ca alloys. The cytotoxicity percentage at the end of 24 h culture for Mg2Zn1Ca /0.3 Mn alloys showed lesser cytotoxicity percentage (~ 8%) when compared to the Mg2Zn1Ca /0.5 Mn (~ 13%) and Mg2Zn1Ca /0.7 Mn (~ 16%) samples. All the alloys showed good initial cell attachment, osteogenic potential and cell spreading. The results of this study validates great potential of Mg2Zn1Ca alloys with manganese addition and exhibited great potential for to be used as temporary implant materials in craniofacial reconstruction.

Metallic biomaterials have been widely used in the field of medical implants for replacement purposes and/or for regeneration of tissue. Metals such as stainless steel (316 L), cobalt-chromium alloys and titanium alloys (Ti-6Al-4 V) are widely used as metallic implants today. However, they often exhibit unsatisfactory results such as stress shielding, the release of toxic ions and are often permanent and invasive – where a second surgery is required to remove the implant once the bone is fully healed. Magnesium as a biomaterial have attracted much attention recently due to its excellent biocompatibility, similar mechanical properties to bone and biodegradability. Unlike other metals and bio ceramics, the ability for magnesium alloys to undergo biodegradation eliminates the requirement for a second surgery to remove the implant. Additionally, the degradation of magnesium releases Mg2+ ions, which stimulates metabolism as they are a cofactor in numerous numbers of enzymes. Despite the advantages of magnesium alloys, the rapid degradation of magnesium proved to be challenging as the implant is unable to retain its structural integrity sufficiently enough to act as an implant. To improve the corrosion resistance of magnesium alloys, researchers have been working on the synthesis and characterization of Mg-based bulk metallic glasses, which can significantly improve the corrosion resistance of Mg-based alloys. This paper is a comprehensive review that compiles, analyzes and critically discusses the recent literature on the latest understanding of the processing, mechanical and biological characteristics of Mg-based bulk metallic glasses.

Thermal management devices such as heat exchangers and heat pipes are integral to safe and efficient performance in multiple engineering applications, including lithium-ion batteries, electric vehicles, electronics, and renewable energy. However, the functional designs of these devices have until now been created around conventional manufacturing constraints, and thermal performance has plateaued as a result. While 3D printing offers the design freedom to address these limitations, there has been a notable lack in high thermal conductivity materials beyond aluminium alloys. Recently, the 3D printing of pure copper to sufficiently high densities has finally taken off, due to the emergence of commercial-grade printers which are now equipped with 1 kW high-power lasers or short-wavelength lasers. Although the capabilities of these new systems appear ideal for processing pure copper as a bulk material, the performance of advanced thermal management devices are strongly dependent on topology-optimised filigree structures, which can require a very different processing window. Hence, this article presents a broad overview of the state-of-the-art in various additive manufacturing technologies used to fabricate pure copper functional filigree geometries comprising thin walls, lattice structures, and porous foams, and identifies opportunities for future developments in the 3D printing of pure copper for advanced thermal management devices.

The present investigation highlights the development of high-performance materials in the construction materials industry, with a special focus on the production of aluminium matrix composites (AMCs) containing titanium carbide (TiC) particles. The stir casting method with ultrasonic assistance was employed to enhance the mechanical and tribological properties. ASTM standards were employed to evaluate the influence of TiC particles on density, hardness (VHN), ultimate tensile strength (UTS), and wear resistance at various TiC weight fraction percentages (0.0 wt.%, 2.0 wt.%, 4.0 wt.%, 6.0 wt.%, and 8.0 wt.%). Field emission scanning electron microscopy (FESEM) and X-ray diffraction (XRD) analysis were performed to analyse the microstructural changes and elemental phases present in the synthesised composite. Results revealed that the incorporation of 8 wt.% TiC reinforcement in the metal matrix composites demonstrated significant improvements compared to the base alloy. In particular, a substantial enhancement in hardness by 32%, a notable increase of 68% in UTS, and a significant 80% rise in yield strength were observed when contrasted with the pure aluminium alloy. The tensile fracture analysis of the specimens revealed the presence of dimples, voids, and cracks, suggesting a brittle nature. To assess the wear characteristics of the composites, dry sliding wear experiments were performed using a pin-on-disc wear tester. Incorporation of TiC particles resulted in a lower coefficient of friction than the base alloy, with the lowest friction coefficient being recorded at 0.266 for 6 wt.% TiC, according to the data. FESEM and energy-dispersive X-ray spectroscopy (EDXS) were used to examine the surfaces of the worn pin. Overall, the inclusion of TiC reinforcement particles in the matrix alloy greatly enhanced the wear resistance and friction coefficient of the Al-6TiC composites. Ploughing and adhesion under lower loads and delamination under higher loads were the wear mechanisms observed in the wear test.

Development of metallic glasses is hindered by the difficulties in manufacturing bulk parts large enough for practical applications. Spark plasma sintering (SPS) has emerged as an effective consolidation technique in the formation of bulk metallic glasses (BMGs) from melt-spun ribbons. In this study, Mg65Zn30Ca5 melt-spun ribbons were sintered at prolonged sintering times (15 min to 180 min) via SPS under a pressure of 90 MPa and at a temperature of 150 °C (which is below the crystallization temperature), to provide an insight into the influence of sintering time on the consolidation, structural, and biodegradation behavior of Mg-BMGs. Scanning Electron Microscopy was used to characterize the microstructure of the surface, while the presence of the amorphous phase was characterized using X-ray diffraction and Electron Backscatter Diffraction. Pellets 10 mm in diameter and height with near-net amorphous structure were synthesized at 150 °C with a sintering time of 90 min, resulting in densification as high as 98.2% with minimal crystallization. Sintering at extended durations above 90 min achieved higher densification and resulted in a significant amount of local and partial devitrification. Mechanical properties were characterized via compression and microhardness testing. Compression results show that increased sintering time led to better structural integrity and mechanical properties. Notably, SPS150_90 displayed ultimate compressive strength (220 MPa) that matches that of the cortical bone (205 MPa). Corrosion properties were characterized via potentiodynamic polarization with Phosphate Buffered Solution (PBS). The results suggest that the sintered samples have significantly better corrosion resistance compared to the crystalline form. Overall, SPS150_90 was observed to have a good balance between corrosion properties (10× better corrosion resistance to as-cast alloy) and mechanical properties.

Background: Extranodal extension (ENE) has been included as a factor for the staging of head-and-neck cancer (HNC) considering its prognostic value. Aim: The present study aimed to find out the percentage of patients with HNC getting upstaged because of ENE and their treatment outcome. Patients and Methods: A retrospective analysis of all patients with HNC registered in the Department of Radiation Oncology, All India Institute of Medical Sciences, Rishikesh, India, between January 2018 and January 2019. American Joint Committee on Cancer (AJCC) criteria were used for defining clinical and radiological ENE. The site, subsite, stage and presence of ENE were documented. The clinical outcome of all these patients was collected and analysed. Results: A total of 562 patients were registered with HNC. Among them 45 patients were identified to have ENE (8%). The majority of the cases were oral cavity (44.4%) and oropharyngeal tumours (26.8%). Thirty-three patients had clinically documented ENE and 11 were radiological and one patient had pathological ENE. Among those who got upstaged to N3b disease due to ENE, 29 patients (64.4%) had N2 disease as per the 7th edition AJCC. When stage grouping was considered, 28 patients (62.2%) who got upstaged had stage Isovaleric acidaemia (IVA) disease as per the AJCC 7th Edition. Twelve patients were treated with radical intent and 16 received palliative treatment and rest did not complete the treatment or defaulted. Overall, the outcomes of these patients remained poor. Conclusion: A significant proportion of HNC patients got upstaged when ENE was included in the staging. Patients with ENE had a poor prognosis irrespective of the treatment modality.

SMARCA4/BRG1-deficient lung adenocarcinoma (SD-LUAD) is being recognized as a distinct subtype based on subtle differences in its clinical, morphological, and immunophenotypic attributes compared to other non–small cell lung carcinomas. We present here a case of SD-LUAD with curious thyroid transcription factor 1 (TTF1) expression in a morphologically heterogenous lung adenocarcinoma. The better differentiated area showed preservation of TTF1 expression, and a poorly differentiated tumor had loss of TTF1 expression with universal BRG1 loss.