Hybrid deep spatial and statistical feature fusion for accurate MRI brain tumor classification.

The classification of medical images is crucial in the biomedical field, and despite attempts to address the issue, significant challenges persist. To effectively categorize medical images, collecting and integrating statistical information that accurately describes the image is essential. This study proposes a unique method for feature extraction that combines deep spatial characteristics with handmade statistical features. The approach involves extracting statistical radiomics features using advanced techniques, followed by a novel handcrafted feature fusion method inspired by the ResNet deep learning model. A new feature fusion framework (FusionNet) is then used to reduce image dimensionality and simplify computation. The proposed approach is tested on MRI images of brain tumors from the BraTS dataset, and the results show that it outperforms existing methods regarding classification accuracy. The study presents three models, including a handcrafted-based model and two CNN models, which completed the binary classification task. The recommended hybrid approach achieved a high F1 score of 96.12 ± 0.41, precision of 97.77 ± 0.32, and accuracy of 97.53 ± 0.24, indicating that it has the potential to serve as a valuable tool for pathologists.

Bayesian-Edge system for classification and segmentation of skin lesions in Internet of Medical Things.

BACKGROUND: Skin diseases are severe diseases. Identification of these severe diseases depends upon the abstraction of atypical skin regions. The segmentation of these skin diseases is essential to rheumatologists in risk impost and for valuable and vital decision-making. Skin lesion segmentation from images is a crucial step toward achieving this goal-timely exposure of malignancy in psoriasis expressively intensifies the persistence ratio. Defies occur when people presume skin diseases they have without accurately and precisely incepted. However, analyzing malignancy at runtime is a big challenge due to the truncated distinction of the visual similarity between malignance and non-malignance lesions. However, images' different shapes, contrast, and vibrations make skin lesion segmentation challenging. Recently, various researchers have explored the applicability of deep learning models to skin lesion segmentation. MATERIALS AND METHODS: This paper introduces a skin lesions segmentation model that integrates two intelligent methodologies: Bayesian inference and edge intelligence. In the segmentation model, we deal with edge intelligence to utilize the texture features for the segmentation of skin lesions. In contrast, Bayesian inference enhances skin lesion segmentation's accuracy and efficiency. RESULTS: We analyze our work along several dimensions, including input data (datasets, preprocessing, and synthetic data generation), model design (architecture, modules), and evaluation aspects (data annotation requirements and segmentation performance). We discuss these dimensions from seminal works and a systematic viewpoint and examine how these dimensions have influenced current trends. CONCLUSION: We summarize our work with previously used techniques in a comprehensive table to facilitate comparisons. Our experimental results show that Bayesian-Edge networks can boost the diagnostic performance of skin lesions by up to 87.80% without incurring additional parameters of heavy computation.

Timing of development of osteoradionecrosis post head and neck radiotherapy: does a safe time interval exist for dental extraction?

INTRODUCTION: Risk factors for developing osteoradionecrosis (ORN) are well known, but less is known about factors influencing the interval between radiotherapy and the onset of ORN. Also, it is unknown whether there is any specific period post-radiotherapy with a reduced probability of ORN when irradiated teeth require extraction. PURPOSE: The primary aim of this study was to identify factors influencing the interval in developing ORN in the following subgroups of patients: (1) patients who spontaneously developed ORN, (2) surgical-intervention-related ORN with a particular focus on patients after mandibulectomy. The secondary aim was to attempt to identify a possible time for safer dental intervention after primary treatment. MATERIALS AND METHODS: The authors retrospectively analysed 1608 head and neck cancer (HNC) patients treated in a single centre. Time intervals were measured from the end of radiotherapy to the development of ORN and further analysed in the subgroups listed above. RESULTS: In all, 141 patients (8.8%) developed intra-oral ORN. Median time from radiotherapy to ORN development in the whole cohort was 9 months. Median interval for spontaneous ORN was 8 months, 6.5 months for intervention-related ORN, and 15 months for patients post-mandibulectomy. In patients who required dental extraction preradiotherapy, median interval of ORN onset was 5 months. CONCLUSION: In our study, a slightly higher proportion of patients with intervention developed ORN earlier in comparison with spontaneous ORN. The period from 12-18 months after radiotherapy was identified as having the highest probability of developing ORN in patients after mandibulectomy. A time for safer dental intervention after primary treatment was not identified.

Locally advanced nasopharyngeal carcinoma in adolescents treated with tomotherapy: Experience at King Faisal Specialist Hospital and Research Centre.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a rare disease worldwide; To the best of our knowledge, there is no established standard of care specifically tailored for the adolescent population. The majority of existing research relies on retrospective data analysis. OBJECTIVE: Evaluate clinical features, treatment results, prognostic factors and late toxicities of locally advanced NPC patients treated with tomotherapy. DESIGN: Retrospective. SETTINGS: Tertiary care hospital. PATIENTS AND METHODS: Between January 2007 and January 2020, we treated patients with NPC, aged between 14 and 21 years, with concomitant chemoradiotherapy using tomotherapy at our institution. We prospectively collected details of clinical characteristics, treatment modalities, outcomes and prognostic factors of these patients and then analysed them retrospectively. MAIN OUTCOME MEASURES: 3-5 years overall survival (OS), 3-5 years locoregional control rate, 3-5 years disease-free survival (DFS), prognostic factors. SAMPLE SIZE: 51 patients. RESULTS: There were 26 male and 25 female patients included in our study. The mean age was 16.5 years, 5 (9.8%) patients with stage III, and 46 (90.2%) with stage IVa according to the American Joint Committee on Cancer, 8th edition staging system. Most patients (98%) received two or more cycles of induction chemotherapy. All patients received concomitant chemoradiotherapy. The median total dose of radiotherapy delivered was 6600 cGy (range 4800-7000). With a median follow-up of 73 months (range 9-168 months), a 5-year locoregional control rate, 5-year OS and 5-year DFS rates were 100%, 86.8% and 71.7%, respectively. Five years later, disease control was 71.7%. Ten (19.6%) patients had disease recurrence in the form of distant metastases during the follow up. CONCLUSIONS: Helical tomotherapy has an excellent late toxicity profile without compromising clinical outcome for patients with NPC. Radiotherapy remains the mainstay of treatment of nasopharyngeal carcinoma to achieve remarkable local control rates. LIMITATIONS: Single institution experience, small number of patients, and retrospective design.

Altering electronic structure of nickel foam supported CoNi-based oxide through Al ions modulation for efficient oxygen evolution reaction.

Developing highly active and durable non-precious metal-based electrocatalysts for the oxygen evolution reaction (OER) is crucial in achieving efficient energy conversion. Herein, we reported a CoNiAl0.5O/NF nanofilament that exhibits higher OER activity than previously reported IrO2-based catalysts in alkaline solution. The as-synthesized CoNiAl0.5O/NF catalyst demonstrates a low overpotential of 230 mV at a current density of 100 mA cm-2, indicating its high catalytic efficiency. Furthermore, the catalyst exhibits a Tafel slope of 26 mV dec-1, suggesting favorable reaction kinetics. The CoNiAl0.5O/NF catalyst exhibits impressive stability, ensuring its potential for practical applications. Detailed characterizations reveal that the enhanced activity of CoNiAl0.5O/NF can be attributed to the electronic modulation achieved through Al3+ incorporation, which promotes the emergence of higher-valence Ni metal, facilitating nanofilament formation and improving mass transport and charge transfer processes. The synergistic effect between nanofilaments and porous nickel foam (NF) substrate significantly enhances the electrical conductivity of this catalyst material. This study highlights the significance of electronic structures for improving the activity of cost-effective and non-precious metal-based electrocatalysts for the OER.

Enhancing brain tumor classification in MRI scans with a multi-layer customized convolutional neural network approach.

Background: The necessity of prompt and accurate brain tumor diagnosis is unquestionable for optimizing treatment strategies and patient prognoses. Traditional reliance on Magnetic Resonance Imaging (MRI) analysis, contingent upon expert interpretation, grapples with challenges such as time-intensive processes and susceptibility to human error. Objective: This research presents a novel Convolutional Neural Network (CNN) architecture designed to enhance the accuracy and efficiency of brain tumor detection in MRI scans. Methods: The dataset used in the study comprises 7,023 brain MRI images from figshare, SARTAJ, and Br35H, categorized into glioma, meningioma, no tumor, and pituitary classes, with a CNN-based multi-task classification model employed for tumor detection, classification, and location identification. Our methodology focused on multi-task classification using a single CNN model for various brain MRI classification tasks, including tumor detection, classification based on grade and type, and tumor location identification. Results: The proposed CNN model incorporates advanced feature extraction capabilities and deep learning optimization techniques, culminating in a groundbreaking paradigm shift in automated brain MRI analysis. With an exceptional tumor classification accuracy of 99%, our method surpasses current methodologies, demonstrating the remarkable potential of deep learning in medical applications. Conclusion: This study represents a significant advancement in the early detection and treatment planning of brain tumors, offering a more efficient and accurate alternative to traditional MRI analysis methods.

Community-Acquired Meningitis Complicated With Pyogenic Ventriculitis and Hydrocephalus in a Patient With Haematological Malignancy: A Case Report and Literature Review.

Meningitis, an infection of the meninges of the central nervous system (CNS), can advance quickly and carries a mortality rate reaching 30% among affected patients. It may become complicated by conditions such as hydrocephalus, ventriculitis, and cerebral abscess. Here, we describe a case of meningitis that was complicated by pyogenic ventriculitis and hydrocephalus in a patient with diffuse large B-cell lymphoma (DLBCL) who underwent chemotherapy and radiotherapy. The patient presented with acute change in mental status and high-grade fever, with few episodes of non-bloody vomiting. Blood culture and cerebrospinal fluid (CSF) culture grew Streptococcus pneumoniae, which was sensitive to ceftriaxone. CT scan of the head showed ventriculomegaly, pansinusitis, and a large left mastoid effusion. MRI of the brain showed layering in ventricles, hydrocephalus, and dural enhancement consistent with pachymeningitis. She was treated with ceftriaxone for 21 days with a meaningful outcome. She was discharged home with near-baseline mental capacity for further physical therapy.

Synthesis and Investigation of Mechanical Properties of the Acrylonitrile Butadiene Styrene Fiber Composites Using Fused Deposition Modeling.

Additive manufacturing is becoming a global phenomenon due to its versatile properties and numerous benefits, which is not possible by conventional machining processes. Fused deposition modeling (FDM) shows a huge potential of shift from rapid prototyping toward the rapid manufacturing. Nowadays, the strength of the FDM-printed parts is very important to consider along with all the printing parameters, which affect the strength of these parts. This study includes the investigation of printing parameters (infill density, layer thickness, and shell count) on the strength of FDM-printed parts of acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS (ABS-CF). These printing parameters directly affect the quality as well as the strength of the 3D-printed parts through FDM. Tensile tests were performed on the universal testing machine on both types of printed parts. The optimized parameters for the 3D-printed samples of the pristine ABS are found to be 0.1045 mm of layer thickness, 57.72% of infill density, and 7.63 numbers of shell count, while the optimum parameters obtained for ABS-CF are 0.2780 mm of layer thickness, 28.37% of infill density, and 9.88 numbers of shell count. The results show that the layer thickness and shell count have a significant effect on the ultimate tensile strength of the 3D-printed parts.

Predicting short-term thromboembolic risk following Roux-en-Y gastric bypass using supervised machine learning.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) is a widely recognized bariatric procedure that is particularly beneficial for patients with class III obesity. It aids in significant weight loss and improves obesity-related medical conditions. Despite its effectiveness, postoperative care still has challenges. Clinical evidence shows that venous thromboembolism (VTE) is a leading cause of 30-d morbidity and mortality after RYGB. Therefore, a clear unmet need exists for a tailored risk assessment tool for VTE in RYGB candidates. AIM: To develop and internally validate a scoring system determining the individualized risk of 30-d VTE in patients undergoing RYGB. METHODS: Using the 2016-2021 Metabolic and Bariatric Surgery Accreditation Quality Improvement Program, data from 6526 patients (body mass index ≥ 40 kg/m2) who underwent RYGB were analyzed. A backward elimination multivariate analysis identified predictors of VTE characterized by pulmonary embolism and/or deep venous thrombosis within 30 d of RYGB. The resultant risk scores were derived from the coefficients of statistically significant variables. The performance of the model was evaluated using receiver operating curves through 5-fold cross-validation. RESULTS: Of the 26 initial variables, six predictors were identified. These included a history of chronic obstructive pulmonary disease with a regression coefficient (Coef) of 2.54 (P < 0.001), length of stay (Coef 0.08, P < 0.001), prior deep venous thrombosis (Coef 1.61, P < 0.001), hemoglobin A1c > 7% (Coef 1.19, P < 0.001), venous stasis history (Coef 1.43, P < 0.001), and preoperative anticoagulation use (Coef 1.24, P < 0.001). These variables were weighted according to their regression coefficients in an algorithm that was generated for the model predicting 30-d VTE risk post-RYGB. The risk model's area under the curve (AUC) was 0.79 [95% confidence interval (CI): 0.63-0.81], showing good discriminatory power, achieving a sensitivity of 0.60 and a specificity of 0.91. Without training, the same model performed satisfactorily in patients with laparoscopic sleeve gastrectomy with an AUC of 0.63 (95%CI: 0.62-0.64) and endoscopic sleeve gastroplasty with an AUC of 0.76 (95%CI: 0.75-0.78). CONCLUSION: This simple risk model uses only six variables to assist clinicians in the preoperative risk stratification of RYGB patients, offering insights into factors that heighten the risk of VTE events.

Acute pancreatitis associated with pembrolizumab-induced hypertriglyceridemia.

INTRODUCTION: Acute pancreatitis (AP) following drug-induced hypertriglyceridemia is a rare clinical phenomenon. Immune checkpoint inhibitors have revolutionized treatment for a variety of solid organ and hematological malignancies. Pembrolizumab is a programmed cell death receptor-1 (PD-1) inhibitor that has shown promising responses in many advanced cancers. However, a constellation of immune-related adverse events has also been described. There are reports of pembrolizumab-induced hypertriglyceridemia, but AP as a result of this side effect remains an exceedingly rare clinical sequela. CASE REPORT: We delineate a case of a patient with stage IVB non-small-cell lung cancer who developed progressive abdominal pain and nausea following administration of pembrolizumab for four months. Laboratory studies revealed increased serum lipase and triglyceride levels at 12,562 IU/L and 16,901 mg/dL, respectively. The diagnosis of AP was made based on the revised Atlanta classification criteria. After ruling out alternative causes, pembrolizumab-induced hypertriglyceridemia was considered the likely etiology of AP. MANAGEMENT AND OUTCOME: The patient was transferred to the medical intensive care unit for close monitoring. Treatment was initiated with intravenous fluids, pain medications, and an insulin infusion. However, her hypertriglyceridemia levels remained persistently elevated, necessitating therapeutic apheresis. She recovered well with no complications after triglyceride apheresis. DISCUSSION: AP following pembrolizumab-associated hypertriglyceridemia remains a rare clinicopathologic entity. Given the widespread clinical use of immune checkpoint inhibitors, knowledge of such rare adverse events is crucial. Evaluation of serum triglyceride levels before and after initiating pembrolizumab therapy may be mandated, especially in patients with metabolic comorbidities.

The multifaceted potential of fenugreek seeds: From health benefits to food and nanotechnology applications.

The present lifestyle, dietary patterns, psychological pressure, environmental factors, and the widespread exploitation of processed substances in food production and farming have collectively contributed to a substantial expediting in the development of various health problems. Globally, researchers have been seeking natural pharmaceutical substances with the potential to be employed in treating lifestyle-related diseases or delaying their onset. Fenugreek seeds have gained significant attention in various fields, including health, nutrition, and cutting-edge nanotechnology applications, due to their versatile qualities. The current investigation offers a comprehensive discussion of the nutritional composition and therapeutic potential of fenugreek seeds, with an emphasis on their plentiful reservoir of bioactive compounds. This seed demonstrates promising medicinal potential in addressing a wide range of health issues. Significantly, these findings indicate noteworthy properties, such as antidiabetic, antioxidant, anti-obesity, hypocholesterolemic, anticancer, and cardioprotective effects. Moreover, the components of fenugreek seeds are important in the development of a multitude of foods, which is the reason why they are used extensively in the area of food research. In addition to their nutritional value, their exploration of nanotechnology reveals a promising domain, utilizing the distinctive characteristics of seeds for many purposes, such as nanoparticle synthesis and oil for edible films and nanoemulsions. This review article focuses on a comprehensive analysis of fenugreek seeds, examining their wide-ranging applications in the fields of health, nutrition, food, and nanotechnology.

Lanthanide complexes facilitate wound healing by promoting fibroblast viability, migration and M2 macrophage polarization.

A tridentate ligand LH3 ((2-hydroxy-3-methoxybenzylidene)-2-(hydroxyimino)propanehydrazide) comprising o-vanillin, hydrazone and oxime donor groups has been employed to prepare a series of tetranuclear Ln(III) complexes. The reaction of ligand LH3 with Ln(NO3)3 [Ln = Sm, Eu, Gd, Tb, Dy, Ho, Er] in MeOH yielded Ln4(LH)6(MeOH)2 (Ln = Sm(1), Eu(2), Gd(3), Tb(4), Ho (6) and Er (7))] whereas the corresponding reaction with Dy(NO3)3 afforded Dy4(LH)4(LH2)2(OH)2 (5). All complexes were characterized by various analytical techniques including single crystal X-ray diffraction, IR spectroscopy, UV-Vis spectroscopy, and elemental analysis. To investigate the potential of these lanthanide complexes for wound healing applications, their effects on fibroblast viability, migration, and M2 macrophage polarization were evaluated. The cytotoxicity assessment revealed that complexes 2(Eu), 4(Tb), 5(Dy), and 7(Er) significantly enhanced fibroblast viability compared to the negative control (NC). In vitro wound healing assay demonstrated that complexes 2(Eu) and 7(Eu) substantially promoted fibroblast migration compared to the NC. Moreover, complex 2(Eu) exhibited significant anti-inflammatory effects by reducing the phagocytic ability of lipopolysaccharide (LPS)-stimulated macrophage cells and attenuating nitric oxide (NO) production. In conclusion, among the series of complexes tested, complex 2(Eu) displayed the most potent anti-inflammatory effect on macrophage cells, while simultaneously promoting fibroblast viability and migration. This unique combination of properties renders complex 2 (Eu) highly promising for wound healing applications.

Human T-cell Lymphotropic Virus Type 1 (HTLV-1)-Associated Adult T-cell Leukemia/Lymphoma in a Patient Previously Treated for Strongyloidiasis.

Adult T-cell leukemia/lymphoma (ATLL) is a rare form of T-cell lymphoma with poor median survival time and limited response to chemotherapy. We present a 45-year-old female from Ghana with generalized body rash, hypercalcemia, lymphadenopathy, and lytic bone lesions. She had a history of strongyloidiasis, treated two years ago, and her serology was positive for the human T-cell lymphotropic virus type 1 (HTLV-1). Histopathology of cervical lymph node and abdominal rash biopsy revealed T-cell lymphoma. We present a literature review on the topic and the challenges of diagnosis. We emphasize the importance of considering HTLV-1-associated ATLL in patients who have been treated for strongyloidiasis in the past and are presenting with rash or lymphadenopathy.

A classifier model for prostate cancer diagnosis using CNNs and transfer learning with multi-parametric MRI.

Prostate cancer (PCa) is a major global concern, particularly for men, emphasizing the urgency of early detection to reduce mortality. As the second leading cause of cancer-related male deaths worldwide, precise and efficient diagnostic methods are crucial. Due to high and multiresolution MRI in PCa, computer-aided diagnostic (CAD) methods have emerged to assist radiologists in identifying anomalies. However, the rapid advancement of medical technology has led to the adoption of deep learning methods. These techniques enhance diagnostic efficiency, reduce observer variability, and consistently outperform traditional approaches. Resource constraints that can distinguish whether a cancer is aggressive or not is a significant problem in PCa treatment. This study aims to identify PCa using MRI images by combining deep learning and transfer learning (TL). Researchers have explored numerous CNN-based Deep Learning methods for classifying MRI images related to PCa. In this study, we have developed an approach for the classification of PCa using transfer learning on a limited number of images to achieve high performance and help radiologists instantly identify PCa. The proposed methodology adopts the EfficientNet architecture, pre-trained on the ImageNet dataset, and incorporates three branches for feature extraction from different MRI sequences. The extracted features are then combined, significantly enhancing the model's ability to distinguish MRI images accurately. Our model demonstrated remarkable results in classifying prostate cancer, achieving an accuracy rate of 88.89%. Furthermore, comparative results indicate that our approach achieve higher accuracy than both traditional hand-crafted feature techniques and existing deep learning techniques in PCa classification. The proposed methodology can learn more distinctive features in prostate images and correctly identify cancer.

Comparison of Pedicle Coagulation Hemorrhoidectomy With LigaSure Versus Conventional Milligan Morgan Hemorrhoidectomy in Reducing Post-operative Pain: A Randomized Controlled Trial.

Background Hemorrhoids refer to the abnormal enlargement of the anal cushions. They are a common anorectal problem with a prevalence of 5% in the general population aged greater than 40 years. The objective of this study was to compare Milligan-Morgan open hemorrhoidectomy with pedicle ligation with LigaSure (Medtronic, Dublin, Ireland) in terms of postoperative pain on day 1 and day 7. It is important to assess the technique that is associated with lower postoperative pain because both of these techniques are still practiced in the developing world. Methods It was a randomized controlled trial conducted in the Department of Surgery, Rawalpindi, Pakistan. A total of 100 patients were selected and were allotted into the two groups by lottery method. Patients aged from 15 to 60 years who presented with symptomatic third and fourth-degree hemorrhoids were included after taking informed consent. Patients who had a previous or concomitant anorectal disease, patients who had undergone previous surgery for hemorrhoids, and those who were anesthetically unfit for surgery (American Society of Anesthesiologists (ASA) class 3 or above) were excluded from the study. Pain was assessed using the Visual Analogue scale (VAS). Data was entered and analyzed using SPSS v. 23.0 (IBM Corp., Armonk, USA). Chi-square tests were applied. P-value <0.05 was taken as statistically significant. Results Out of 100 patients, 68 (68%) were males while 32 (32%) were females. The mean age was 40.56±9.24 years. Postoperative pain at day 1 was 9.24±0.51 in the Milligan-Morgan group while that in the LigaSure group was 8.44±0.64 (p<0.0001). Postoperative pain at day 7 was 5.00±0.85 in the Milligan-Morgan group while it was 3.04±1.08 in the LigaSure group (p<0.0001). Conclusion LigaSure is a newer technique that helps to reduce complications as compared to other traditional hemorrhoidectomy procedures. Many patients avoid hemorrhoidectomy as it is associated with painful postoperative recovery. Pedicle coagulation with LigaSure was better than conventional Milligan-Morgan hemorrhoidectomy in terms of reducing the mean postoperative pain on 1st day and 7th day. Reducing the postoperative pain helps in greater patient satisfaction and lesser requirement of analgesia among patients of 3rd and 4th-degree hemorrhoids undergoing hemorrhoidectomy.

Efficacy and Safety of RET-Specific Kinase Inhibitors in RET-Altered Cancers: A Systematic Review.

RET proto-oncogene encodes receptor tyrosine kinase. Selpercatinib and pralsetinib are the only RET-specific tyrosine kinase inhibitors approved by FDA in RET-altered tumors. We searched PubMed, Embase, Cochrane, WOS, and Clinicaltrials.gov. Objective-response, complete-response, and partial-response were 60-89%, 0-11%, and 55-89%, respectively, with the use of RET-specific drugs. ≥Grade 3 adverse events were seen in 28-53% of the patients, with hypertension, change in ALT, QT prolongation, neutropenia, and pneumonitis among the common side effects. Hence, selpercatinib and pralsetinib were effective and well tolerated by most of the patients with RET-altered tumors.

P176S Mutation Rewires Electrostatic Interactions That Alter Maspin Functionality.

Maspin is known to regress tumors by inhibiting angiogenesis; however, its roles have been reported to be context- and sequence-dependent. Various proteins and cofactors bind to maspin, possibly explaining its conflicting roles. Moreover, polymorphic forms of maspin have also been linked to tumor regression and survival; for instance, maspin with Ser at 176 (maspin-S176) promotes tumors, while maspin with Pro at 176 (maspin-P176) has opposing roles in cancer pathogenesis. With the help of long molecular dynamics simulations, a possible link between polymorphic forms and tumor progression has been established. First, maspin is dynamically stable with either amino acid at the 176 position. Second, differential contacts have been observed among various regions; third, these contacts have significantly altered the electrostatic energetics of various residues; finally, these altered electrostatics of maspin-S176 and maspin-P176 rewire the polar contacts that abolished the allosteric control of the protein. By combining these factors, the altered electrostatics substantially affect the localization and preference of maspin-binding partners, thus culminating in a different maspin-protein(cofactor)-interaction landscape that may have been manifested in previous conflicting reports. Here, the underlying reason has been highlighted and discussed, which may be helpful for better therapeutic manipulation.

A Case of Post-COVID-19 Rhino-Cerebral Mucormycosis in an Immunocompromised Patient.

Mucormycosis is a fulminant angioinvasive fungal infection that occurs in an immunocompromised condition, most commonly in diabetic patients. Rhino-cerebral and pulmonary infections are common but may also lead to disseminated disease associated with a high mortality rate (almost 100%). Here we report on an elderly diabetic lady presented with a headache and altered level of consciousness and peri-orbital swelling following coronavirus disease 2019 (COVID-19). Imaging studies revealed a single large space-occupying lesion in the frontal lobe extending to the left orbit and sinusitis. An excisional biopsy was taken from the middle meatus of the nasal cavity and histopathology findings were broad aseptate hyphae branching at the right angle which suggests mucormycosis. Liposomal amphotericin B was started but the patient developed acute kidney injury (AKI) and bi-cytopenia (thrombocytopenia and anemia) followed by sepsis resulting in death. Though this is a rapidly progressing disease with a high mortality rate, a strong level of suspicion and early diagnosis can save lives.

From Euphoria to Emergency: Exploring the Role of K2/Spice in Diffuse Alveolar Hemorrhage.

Marijuana or cannabis has been one of the most widely used recreational drugs, in the United States. However, a sinister counterpart has emerged in recent times: K2/Spice, a synthetic rendition of tetrahydrocannabinol (THC), capturing increasing popularity. Alarming reports have linked this synthetic compound to a multitude of life-threatening complications, ranging from acute kidney injury (AKI) from direct nephrotoxicity to cardiac arrest. Here we present the case of a 34-year-old man who presented with hemoptysis, later found to have diffuse alveolar hemorrhage (DAH) on the investigation after smoking K2/Spice successfully treated with a course of intravenous steroids. The case presented underscores the urgent need for increased awareness about the potential complications associated with synthetic compounds like K2/Spice, such as diffuse alveolar hemorrhage, and the importance of developing effective treatment strategies.

Tissue characterization of benign cardiac tumors by cardiac magnetic resonance imaging, a review of core imaging protocol and benign cardiac tumors.

Generally, cardiac masses are initially suspected on routine echocardiography. Cardiac magnetic resonance (CMR) imaging is further performed to differentiate tumors from pseudo-tumors and to characterize the cardiac masses based on their appearance on T1/T2-weighted images, detection of perfusion and demonstration of gadolinium-based contrast agent uptake on early and late gadolinium enhancement images. Further evaluation of cardiac masses by CMR is critical because unnecessary surgery can be avoided by better tissue characterization. Different cardiac tissues have different T1 and T2 relaxation times, principally owing to different internal biochemical environments surrounding the protons. In CMR, the signal intensity from a particular tissue depends on its T1 and T2 relaxation times and its proton density. CMR uses this principle to differentiate between various tissue types by weighting images based on their T1 or T2 relaxation times. Generally, tumor cells are larger, edematous, and have associated inflammatory reactions. Higher free water content of the neoplastic cells and other changes in tissue composition lead to prolonged T1/T2 relaxation times and thus an inherent contrast between tumors and normal tissue exists. Overall, these biochemical changes create an environment where different cardiac masses produce different signal intensity on their T1- weighted and T2- weighted images that help to discriminate between them. In this review article, we have provided a detailed description of the core CMR imaging protocol for evaluation of cardiac masses. We have also discussed the basic features of benign cardiac tumors as well as the role of CMR in evaluation and further tissue characterization of these tumors.