Assessment of hydrocarbon degradation capacity and kinetic modeling of Chlorella vulgaris and Scenedesmus quadricauda for crude oil phycoremediation under mixotrophic conditions.

Crude oil spills imperil aquatic ecosystems globally, prompting innovative solutions such as microalgae-based bioremediation. This study explores the potential of Chlorella vulgaris and Scenedesmus quadricauda, for crude oil spill phycoremediation under mixotrophic conditions and varying crude oil concentrations (0.5-2%). C. vulgaris demonstrated notable resilience, thriving up to 1% crude oil exposure, while S. quadricauda adapted to lower concentrations. Optimal growth for both was observed at 0.5% exposure. Chlorophyll a content in C. vulgaris increases at 0.5% exposure but declines above 1%, while a decline was noticeable in chlorophyll b in treatment groups above 1%. Carotenoid levels varied, displaying the highest levels at higher concentrations above 1.5%. Similarly, S. quadricauda showed increased chlorophyll a content at 0.5% exposure, with stable carotenoid levels and a decline in chlorophyll b content at higher concentrations. GC/MS analyses indicated C. vulgaris efficiently degraded aliphatic compounds like decane and tridecane, surpassing S. quadricauda in degrading both aliphatic and aromatic hydrocarbons. Growth kinetics was best represented by the modified Gompertz and logistic models. These findings highlight the species-specific adaptability and optimal concentration for microalgae to degrade crude oil effectively, advancing phycoremediation processes and strategies critical for environmental restoration.

This study marks the first exploration of both Chlorella vulgaris and the previously unexplored Scenedesmus quadricauda for crude oil phycoremediation potential under mixotrophic conditions. Additionally, it pioneers the modeling and study of algae growth kinetics in response to crude oil exposure. Notably, this research demonstrated the adaptability and efficiency of C. vulgaris in degrading crude oil components under mixotrophic conditions up to a level of 1%, while S. quadricauda showed similar capabilities at a concentration of 0.5%.

Mathematical modeling of heat transfer in tissues with skin tumor during thermotherapy.

The study of thermal therapy to tumors and the response of living cells to this therapy used to treat tumor is very important due to the complexity of heat transfer in biological tissues. In the past few years, there has been a growing interest among clinicians, mathematicians, and engineers regarding the use of computational and mathematical methods to simulate biological systems. Numerous medical proceedings also employ mathematical modeling and engineering techniques as a means to guarantee their safety and evaluate the associated risks effectively. This manuscript provides an analytical solution used for the first time to study the mechanism of biological thermal response during heat therapy on spheroidal skin tumor. The proposed method used a generalized thermoelasticity model with one relaxation time. The influence of relaxation times on the responses of diseased and healthy tissues is studied and interpreted graphically. Also, the impact of different laser irradiance on the thermal profile of the malignant tumor cells over a period of 2 minutes is interpreted graphically. To investigate the transfer of heat within biological tissues during the thermal therapy, the Laplace transform and inverse Laplace transform methods were applied. A comparison of the present generalized thermoelasticity model and different models based on Pennes bioheat transfer PBT shows that our proposed model yields more realistic and accurate predictions. The current model can be used to explain various therapeutic methods.

The Role of AI in Drug Discovery.

The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This review paper elucidates the multifaceted applications of AI across various stages of drug development, highlighting significant advancements and methodologies. It delves into AI's instrumental role in drug design, polypharmacology, chemical synthesis, drug repurposing, and the prediction of drug properties such as toxicity, bioactivity, and physicochemical characteristics. Despite AI's promising advancements, the paper also addresses the challenges and limitations encountered in the field, including data quality, generalizability, computational demands, and ethical considerations. By offering a comprehensive overview of AI's role in drug discovery, this paper underscores the technology's potential to significantly enhance drug development, while also acknowledging the hurdles that must be overcome to fully realize its benefits.

SKping cell cycle regulation: role of ubiquitin ligase SKP2 in hematological malignancies.

SKP2 (S-phase kinase-associated protein 2) is a member of the F-box family of substrate-recognition subunits in the SCF ubiquitin-protein ligase complexes. It is associated with ubiquitin-mediated degradation in the mammalian cell cycle components and other target proteins involved in cell cycle progression, signal transduction, and transcription. Being an oncogene in solid tumors and hematological malignancies, it is frequently associated with drug resistance and poor disease outcomes. In the current review, we discussed the novel role of SKP2 in different hematological malignancies. Further, we performed a limited in-silico analysis to establish the involvement of SKP2 in a few publicly available cancer datasets. Interestingly, our study identified Skp2 expression to be altered in a cancer-specific manner. While it was found to be overexpressed in several cancer types, few cancer showed a down-regulation in SKP2. Our review provides evidence for developing novel SKP2 inhibitors in hematological malignancies. We also investigated the effect of SKP2 status on survival and disease progression. In addition, the role of miRNA and its associated families in regulating Skp2 expression was explored. Subsequently, we predicted common miRNAs against Skp2 genes by using miRNA-predication tools. Finally, we discussed current approaches and future prospective approaches to target the Skp2 gene by using different drugs and miRNA-based therapeutics applications in translational research.

Natural compounds targeting YAP/TAZ axis in cancer: Current state of art and challenges.

Cancer has become a burgeoning global healthcare concern marked by its exponential growth and significant economic ramifications. Though advancements in the treatment modalities have increased the overall survival and quality of life, there are no definite treatments for the advanced stages of this malady. Hence, understanding the diseases etiologies and the underlying molecular complexities, will usher in the development of innovative therapeutics. Recently, YAP/TAZ transcriptional regulation has been of immense interest due to their role in development, tissue homeostasis and oncogenic transformations. YAP/TAZ axis functions as coactivators within the Hippo signaling cascade, exerting pivotal influence on processes such as proliferation, regeneration, development, and tissue renewal. In cancer, YAP is overexpressed in multiple tumor types and is associated with cancer stem cell attributes, chemoresistance, and metastasis. Activation of YAP/TAZ mirrors the cellular "social" behavior, encompassing factors such as cell adhesion and the mechanical signals transmitted to the cell from tissue structure and the surrounding extracellular matrix. Therefore, it presents a significant vulnerability in the clogs of tumors that could provide a wide window of therapeutic effectiveness. Natural compounds have been utilized extensively as successful interventions in the management of diverse chronic illnesses, including cancer. Owing to their capacity to influence multiple genes and pathways, natural compounds exhibit significant potential either as adjuvant therapy or in combination with conventional treatment options. In this review, we delineate the signaling nexus of YAP/TAZ axis, and present natural compounds as an alternate strategy to target cancer.

Dynamic interplay of nuclear receptors in tumor cell plasticity and drug resistance: Shifting gears in malignant transformations and applications in cancer therapeutics.

Recent advances have brought forth the complex interplay between tumor cell plasticity and its consequential impact on drug resistance and tumor recurrence, both of which are critical determinants of neoplastic progression and therapeutic efficacy. Various forms of tumor cell plasticity, instrumental in facilitating neoplastic cells to develop drug resistance, include epithelial-mesenchymal transition (EMT) alternatively termed epithelial-mesenchymal plasticity, the acquisition of cancer stem cell (CSC) attributes, and transdifferentiation into diverse cell lineages. Nuclear receptors (NRs) are a superfamily of transcription factors (TFs) that play an essential role in regulating a multitude of cellular processes, including cell proliferation, differentiation, and apoptosis. NRs have been implicated to play a critical role in modulating gene expression associated with tumor cell plasticity and drug resistance. This review aims to provide a comprehensive overview of the current understanding of how NRs regulate these key aspects of cancer biology. We discuss the diverse mechanisms through which NRs influence tumor cell plasticity, including EMT, stemness, and metastasis. Further, we explore the intricate relationship between NRs and drug resistance, highlighting the impact of NR signaling on chemotherapy, radiotherapy and targeted therapies. We also discuss the emerging therapeutic strategies targeting NRs to overcome tumor cell plasticity and drug resistance. This review also provides valuable insights into the current clinical trials that involve agonists or antagonists of NRs modulating various aspects of tumor cell plasticity, thereby delineating the potential of NRs as therapeutic targets for improved cancer treatment outcomes.

Lipid metabolism and its implications in tumor cell plasticity and drug resistance: what we learned thus far?

Metabolic reprogramming, a hallmark of cancer, allows cancer cells to adapt to their specific energy needs. The Warburg effect benefits cancer cells in both hypoxic and normoxic conditions and is a well-studied reprogramming of metabolism in cancer. Interestingly, the alteration of other metabolic pathways, especially lipid metabolism has also grabbed the attention of scientists worldwide. Lipids, primarily consisting of fatty acids, phospholipids and cholesterol, play essential roles as structural component of cell membrane, signalling molecule and energy reserves. This reprogramming primarily involves aberrations in the uptake, synthesis and breakdown of lipids, thereby contributing to the survival, proliferation, invasion, migration and metastasis of cancer cells. The development of resistance to the existing treatment modalities poses a major challenge in the field of cancer therapy. Also, the plasticity of tumor cells was reported to be a contributing factor for the development of resistance. A number of studies implicated that dysregulated lipid metabolism contributes to tumor cell plasticity and associated drug resistance. Therefore, it is important to understand the intricate reprogramming of lipid metabolism in cancer cells. In this review, we mainly focused on the implication of disturbed lipid metabolic events on inducing tumor cell plasticity-mediated drug resistance. In addition, we also discussed the concept of lipid peroxidation and its crucial role in phenotypic switching and resistance to ferroptosis in cancer cells. Elucidating the relationship between lipid metabolism, tumor cell plasticity and emergence of resistance will open new opportunities to develop innovative strategies and combinatorial approaches for the treatment of cancer.

Nicotine sensing behavior of nickel(II) complexes catalyzed oxidation and coupling reactions.

One of the main source of demise during the next ten years will be coronary heart disease and stroke, which are brought on by smoking (nicotine). To identify the percentage (%) of nicotine consumption by electrocatalytic sensor towards nicotine for target-specific prevent stroke, four uninuclear Ni2+ complexes of substituted butanimidamide Schiff base ligands [H2L1-4] was prepared. All the complexes were thoroughly analyzed by using several spectroscopic techniques such as CHNS analysis, FT-IR, NMR (1H & 13C) UV-Vis and NMR. The analyses showed tetradentate binding mode of ligand around nickel(II) metal ion leads to the structure of square planar with N2X2 (X = O, S) donor fashion. In addition, the well-defined nickel(II) complexes were utilized for oxidation of various alcohols such as cyclohexanol, and benzyl alcohol were produced to the assorted oxidized products with high yield respectively using greener co-oxidant (molecular oxygen). In addition, Nickel(II) complexes was further utilized as catalyst for aryl-aryl coupling reaction via Suzuki-Mayura method to obtain biphenyl compound. Furthermore, nickel(II) complexes were exploited for electrochemical detection of nicotine sensing in µM concentration.

Therapeutic potential of tocotrienols as chemosensitizers in cancer therapy.

Chemoresistance is the adaptation of cancer cells against therapeutic agents. When exhibited by cancer cells, chemoresistance helps them to avoid apoptosis, cause relapse, and metastasize, making it challenging for chemotherapeutic agents to treat cancer. Various strategies like dosage modification of drugs, nanoparticle-based delivery of chemotherapeutics, antibody-drug conjugates, and so on are being used to target and reverse chemoresistance, one among such is combination therapy. It uses the combination of two or more therapeutic agents to reverse multidrug resistance and improve the effects of chemotherapy. Phytochemicals are known to exhibit chemosensitizing properties and are found to be effective against various cancers. Tocotrienols (T3) and tocopherols (T) are natural bioactive analogs of vitamin E, which exhibit important medicinal value and potential curative properties apart from serving as an antioxidant and nutrient supplement. Notably, T3 exhibits a variety of pharmacological activities like anticancer, anti-inflammatory, antiproliferative, and so on. The chemosensitizing property of tocotrienol is exhibited by modulating several signaling pathways and molecular targets involved in cancer cell survival, proliferation, invasion, migration, and metastasis like NF-κB, STATs, Akt/mTOR, Bax/Bcl-2, Wnt/ß-catenin, and many more. T3 sensitizes cancer cells to chemotherapeutic drugs including cisplatin, doxorubicin, and paclitaxel increasing drug concentration and cytotoxicity. Discussed herewith are the chemosensitizing properties of tocotrienols on various cancer cell types when combined with various drugs and biological molecules.

Delineating the role of nuclear receptors in colorectal cancer, a focused review.

Colorectal cancer (CRC) stands as one of the most prevalent form of cancer globally, causing a significant number of deaths, surpassing 0.9 million in the year 2020. According to GLOBOCAN 2020, CRC ranks third in incidence and second in mortality in both males and females. Despite extensive studies over the years, there is still a need to establish novel therapeutic targets to enhance the patients' survival rate in CRC. Nuclear receptors (NRs) are ligand-activated transcription factors (TFs) that regulate numerous essential biological processes such as differentiation, development, physiology, reproduction, and cellular metabolism. Dysregulation and anomalous expression of different NRs has led to multiple alterations, such as impaired signaling cascades, mutations, and epigenetic changes, leading to various diseases, including cancer. It has been observed that differential expression of various NRs might lead to the initiation and progression of CRC, and are correlated with poor survival outcomes in CRC patients. Despite numerous studies on the mechanism and role of NRs in this cancer, it remains of significant scientific interest primarily due to the diverse functions that various NRs exhibit in regulating key hallmarks of this cancer. Thus, modulating the expression of NRs with their agonists and antagonists, based on their expression levels, holds an immense prospect in the diagnosis, prognosis, and therapeutical modalities of CRC. In this review, we primarily focus on the role and mechanism of NRs in the pathogenesis of CRC and emphasized the significance of targeting these NRs using a variety of agents, which may represent a novel and effective strategy for the prevention and treatment of this cancer.

Exploring the nexus of nuclear receptors in hematological malignancies.

Hematological malignancies (HM) represent a subset of neoplasms affecting the blood, bone marrow, and lymphatic systems, categorized primarily into leukemia, lymphoma, and multiple myeloma. Their prognosis varies considerably, with a frequent risk of relapse despite ongoing treatments. While contemporary therapeutic strategies have extended overall patient survival, they do not offer cures for advanced stages and often lead to challenges such as acquisition of drug resistance, recurrence, and severe side effects. The need for innovative therapeutic targets is vital to elevate both survival rates and patients' quality of life. Recent research has pivoted towards nuclear receptors (NRs) due to their role in modulating tumor cell characteristics including uncontrolled proliferation, differentiation, apoptosis evasion, invasion and migration. Existing evidence emphasizes NRs' critical role in HM. The regulation of NR expression through agonists, antagonists, or selective modulators, contingent upon their levels, offers promising clinical implications in HM management. Moreover, several anticancer agents targeting NRs have been approved by the Food and Drug Administration (FDA). This review highlights the integral function of NRs in HM's pathophysiology and the potential benefits of therapeutically targeting these receptors, suggesting a prospective avenue for more efficient therapeutic interventions against HM.

Harnessing Sulforaphane Potential as a Chemosensitizing Agent: A Comprehensive Review.

Recent advances in oncological research have highlighted the potential of naturally derived compounds in cancer prevention and treatment. Notably, sulforaphane (SFN), an isothiocyanate derived from cruciferous vegetables including broccoli and cabbage, has exhibited potent chemosensitizing capabilities across diverse cancer types of bone, brain, breast, lung, skin, etc. Chemosensitization refers to the enhancement of cancer cell sensitivity to chemotherapy agents, counteracting the chemoresistance often developed by tumor cells. Mechanistically, SFN orchestrates this sensitization by modulating an array of cellular signaling pathways (e.g., Akt/mTOR, NF-κB, Wnt/ß-catenin), and regulating the expression and activity of pivotal genes, proteins, and enzymes (e.g., p53, p21, survivin, Bcl-2, caspases). When combined with conventional chemotherapeutic agents, SFN synergistically inhibits cancer cell proliferation, invasion, migration, and metastasis while potentiating drug-induced apoptosis. This positions SFN as a potential adjunct in cancer therapy to augment the efficacy of standard treatments. Ongoing preclinical and clinical investigations aim to further delineate the therapeutic potential of SFN in oncology. This review illuminates the multifaceted role of this phytochemical, emphasizing its potential to enhance the therapeutic efficacy of anti-cancer agents, suggesting its prospective contributions to cancer chemosensitization and management.

Combination Therapy with Enalapril and Paricalcitol Ameliorates Streptozotocin Diabetes-Induced Testicular Dysfunction in Rats via Mitigation of Inflammation, Apoptosis, and Oxidative Stress.

BACKGROUND: As the impacts of diabetes-induced reproductive damage are now evident in young people, we are now in urgent need to devise new ways to protect and enhance the reproductive health of diabetic people. The present study aimed to evaluate the protective effects of enalapril (an ACE inhibitor) and paricalcitol (a vitamin D analog), individually or in combination, on streptozotocin (STZ)-diabetes-induced testicular dysfunction in rats and to identify the possible mechanisms for this protection. MATERIAL AND METHODS: This study was carried out on 50 male Sprague-Dawley rats; 10 normal rats were allocated as a non-diabetic control group. A total of 40 rats developed diabetes after receiving a single dose of STZ; then, the diabetic rats were divided into four groups of equivalent numbers assigned as diabetic control, enalapril-treated, paricalcitol-treated, and combined enalapril-and-paricalcitol-treated groups. The effects of mono and combined therapy with paricalcitol and enalapril on testicular functions, sperm activity, glycemic state oxidative stress, and inflammatory parameters, as well as histopathological examinations, were assessed in comparison with the normal and diabetic control rats. RESULTS: As a result of diabetes induction, epididymal sperm count, sperm motility, serum levels of testosterone, follicle-stimulating hormone (FSH) as well as luteinizing hormone (LH), and the antioxidant enzyme activities, were significantly decreased, while abnormal sperm (%), insulin resistance, nitric oxide (NO), malondialdehyde (MDA), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were significantly increased, along with severe distortion of the testicular structure. Interestingly, treatment with paricalcitol and enalapril, either alone or in combination, significantly improved the sperm parameters, increased antioxidant enzyme activities in addition to serum levels of testosterone, FSH, and LH, reduced insulin resistance, IL-6, and TNF-α levels, and finally ameliorated the diabetes-induced testicular oxidative stress and histopathological damage, with somewhat superior effect for paricalcitol monotherapy and combined therapy with both drugs compared to monotherapy with enalapril alone. CONCLUSIONS: Monotherapy with paricalcitol and its combination therapy with enalapril has a somewhat superior effect in improving diabetes-induced testicular dysfunction (most probably as a result of their hypoglycemic, antioxidant, anti-inflammatory, and anti-apoptotic properties) compared with monotherapy with enalapril alone in male rats, recommending a synergistic impact of both drugs.

Synthesis and characterization of mesoporous bioactive glass nanoparticles loaded with peganum harmala for bone tissue engineering.

Globally, there is an increase in a number of bone disorders including osteoarthritis (OA), osteomyelitis, bone cancer, and etc., which has led to a demand for bone tissue regeneration. In order to take use of the osteogenic potential of natural herbs, mesoporous bioactive glass nanoparticles (MBGNs) have the ability to deliver therapeutically active chemicals locally. MBGNs influence bioactivity and osteointegration of materials making them suitable for bone tissue engineering (BTE). In the present study, we developed Peganum Harmala (P. harmala) loaded MBGNs (PH-MBGNs) synthesized via modified Stöber process. The MBGNs were analyzed in terms of surface morphology, chemical make-up, amorphous nature, chemical interaction, pore size, and surface area before and after loading with P. harmala. A burst release of drug from PH-MBGNs was observed within 8 h immersion in phosphate buffer saline (PBS). PH-MBGNs effectively prevented Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) from spreading. Furthermore, PH-MBGNs developed a hydroxyapatite (HA) layer in the presence of simulated body fluid (SBF) after 21 days, which confirmed the in-vitro bioactivity of MBGNs. In conclusion, PH-MBGNs synthesized in this work are potential candidate for scaffolding or a constituent in the coatings for BTE applications.

Crosstalk between Non-Coding RNAs and Wnt/ß-Catenin Signaling in Head and Neck Cancer: Identification of Novel Biomarkers and Therapeutic Agents.

Head and neck cancers (HNC) encompass a broad spectrum of neoplastic disorders characterized by significant morbidity and mortality. While contemporary therapeutic interventions offer promise, challenges persist due to tumor recurrence and metastasis. Central to HNC pathogenesis is the aberration in numerous signaling cascades. Prominently, the Wnt signaling pathway has been critically implicated in the etiology of HNC, as supported by a plethora of research. Equally important, variations in the expression of non-coding RNAs (ncRNAs) have been identified to modulate key cancer phenotypes such as cellular proliferation, epithelial-mesenchymal transition, metastatic potential, recurrence, and treatment resistance. This review aims to provide an exhaustive insight into the multifaceted influence of ncRNAs on HNC, with specific emphasis on their interactions with the Wnt/ß-catenin (WBC) signaling axis. We further delineate the effect of ncRNAs in either exacerbating or attenuating HNC progression via interference with WBC signaling. An overview of the mechanisms underlying the interplay between ncRNAs and WBC signaling is also presented. In addition, we described the potential of various ncRNAs in enhancing the efficacy of chemotherapeutic and radiotherapeutic modalities. In summary, this assessment posits the potential of ncRNAs as therapeutic agents targeting the WBC signaling pathway in HNC management.

Effect and mechanism of nano-materials on plant resistance to cadmium toxicity: A review.

Cadmium (Cd), one of the most toxic heavy metals, has been extensively studied by environmental scientists because of its detrimental effects on plants, animals, and humans. Increased industrial activity has led to environmental contamination with Cd. Cadmium can enter the food chain and pose a potential human health risk. Therefore, reducing the accumulation of Cd in plant species and enhancing their detoxification abilities are crucial for remediating heavy metal pollution in contaminated areas. One innovative technique is nano-phytoremediation, which employs nanomaterials ranging from 1 to 100 nm in size to mitigate the accumulation and detrimental effects of Cd on plants. Although extensive research has been conducted on using nanomaterials to mitigate Cd toxicity in plants, it is important to note that the mechanism of action varies depending on factors such as plant species, level of Cd concentration, and type of nanomaterials employed. This review aimed to consolidate and organize existing data, providing a comprehensive overview of the effects and mechanisms of nanomaterials in enhancing plant resistance to Cd. In particular, its deep excavation the mechanisms of detoxification heavy metals of nanomaterials by plants, including regulating Cd uptake and distribution, enhancing antioxidant capacity, regulating gene expression, and regulating physiological metabolism. In addition, this study provides insights into future research directions in this field.

Enhanced brain tumor classification using graph convolutional neural network architecture.

The Brain Tumor presents a highly critical situation concerning the brain, characterized by the uncontrolled growth of an abnormal cell cluster. Early brain tumor detection is essential for accurate diagnosis and effective treatment planning. In this paper, a novel Convolutional Neural Network (CNN) based Graph Neural Network (GNN) model is proposed using the publicly available Brain Tumor dataset from Kaggle to predict whether a person has brain tumor or not and if yes then which type (Meningioma, Pituitary or Glioma). The objective of this research and the proposed models is to provide a solution to the non-consideration of non-Euclidean distances in image data and the inability of conventional models to learn on pixel similarity based upon the pixel proximity. To solve this problem, we have proposed a Graph based Convolutional Neural Network (GCNN) model and it is found that the proposed model solves the problem of considering non-Euclidean distances in images. We aimed at improving brain tumor detection and classification using a novel technique which combines GNN and a 26 layered CNN that takes in a Graph input pre-convolved using Graph Convolution operation. The objective of Graph Convolution is to modify the node features (data linked to each node) by combining information from nearby nodes. A standard pre-computed Adjacency matrix is used, and the input graphs were updated as the averaged sum of local neighbor nodes, which carry the regional information about the tumor. These modified graphs are given as the input matrices to a standard 26 layered CNN with Batch Normalization and Dropout layers intact. Five different networks namely Net-0, Net-1, Net-2, Net-3 and Net-4 are proposed, and it is found that Net-2 outperformed the other networks namely Net-0, Net-1, Net-3 and Net-4. The highest accuracy achieved was 95.01% by Net-2. With its current effectiveness, the model we propose represents a critical alternative for the statistical detection of brain tumors in patients who are suspected of having one.

A 47-Year-Old Woman with a Retained Central Venous Catheter Line Guidewire Presenting with a Right Atrial Thrombus Requiring Removal During Open Heart Surgery: A Case Report.

BACKGROUND A central venous catheter (CVC) is an indwelling catheter that is inserted into a large central vein for different purposes, including hemodynamic monitoring and administration of fluids and medications. This report is of a 47-year-old woman with a retained CVC line guidewire presenting with a large right atrial thrombus requiring removal during open heart surgery. CVC insertion is one of the most frequently attempted procedures in intensive care units, emergency departments, and operation rooms, especially for critically ill patients. Possible complications range from failure to place the catheter to cardiac arrest. One of the rarest complications is missing the guidewire after insertion, which is usually discovered early after inserting it. CASE REPORT We report the case of a 47-year-old woman who had a CVC line inserted following complicated open cholecystectomy. A few years later, she developed shortness of breath, with an incidental finding of a huge right atrial thrombus and a wire shown on transthoracic echocardiography. The right atrial thrombus required open heart surgery to excise the thrombus and the wire, which was done successfully. The thrombus was histopathologically and clinically proven to be an organized right atrial thrombus formed around the CVC guidewire. CONCLUSIONS This case report presents a rare complication of CVC insertion. Because this procedure is increasingly used, clinicians should be aware of the potential complications of retained CVC lines. Moreover, this report outlines different techniques to prevent such fatal complications and emphasizes the significance of radiography after insertion.

Patterns, procedures, and indications for pediatric surgery in a Tanzanian Refugee Camp: a 20-year experience.

Background: There are 103 million displaced people worldwide, 41% of whom are children. Data on the provision of surgery in humanitarian settings are limited. Even scarcer is literature on pediatric surgery performed in humanitarian settings, particularly protracted humanitarian settings. Methods: We reviewed patterns, procedures, and indications for pediatric surgery among children in Nyarugusu Refugee Camp using a 20-year retrospective dataset. Results: A total of 1221 pediatric surgical procedures were performed over the study period. Teenagers between the ages of 12 and 17 years were the most common age group undergoing surgery (n=991; 81%). A quarter of the procedures were performed on local Tanzanian children seeking care in the camp (n=301; 25%). The most common procedures performed were cesarean sections (n=858; 70%), herniorrhaphies (n=197; 16%), and exploratory laparotomies (n=55; 5%). Refugees were more likely to undergo exploratory laparotomy (n=47; 5%) than Tanzanian children (n=7; 2%; p=0.032). The most common indications for exploratory laparotomy were acute abdomen (n=24; 44%), intestinal obstruction (n=10; 18%), and peritonitis (n=9; 16%). Conclusions: There is a significant volume of basic pediatric general surgery performed in the Nyarugusu Camp. Services are used by both refugees and local Tanzanians. We hope this research will inspire further advocacy and research on pediatric surgical services in humanitarian settings worldwide and illuminate the need for including pediatric refugee surgery within the growing global surgery movement.

NAMSTCD: A Novel Augmented Model for Spinal Cord Segmentation and Tumor Classification Using Deep Nets.

Spinal cord segmentation is the process of identifying and delineating the boundaries of the spinal cord in medical images such as magnetic resonance imaging (MRI) or computed tomography (CT) scans. This process is important for many medical applications, including the diagnosis, treatment planning, and monitoring of spinal cord injuries and diseases. The segmentation process involves using image processing techniques to identify the spinal cord in the medical image and differentiate it from other structures, such as the vertebrae, cerebrospinal fluid, and tumors. There are several approaches to spinal cord segmentation, including manual segmentation by a trained expert, semi-automated segmentation using software tools that require some user input, and fully automated segmentation using deep learning algorithms. Researchers have proposed a wide range of system models for segmentation and tumor classification in spinal cord scans, but the majority of these models are designed for a specific segment of the spine. As a result, their performance is limited when applied to the entire lead, limiting their deployment scalability. This paper proposes a novel augmented model for spinal cord segmentation and tumor classification using deep nets to overcome this limitation. The model initially segments all five spinal cord regions and stores them as separate datasets. These datasets are manually tagged with cancer status and stage based on observations from multiple radiologist experts. Multiple Mask Regional Convolutional Neural Networks (MRCNNs) were trained on various datasets for region segmentation. The results of these segmentations were combined using a combination of VGGNet 19, YoLo V2, ResNet 101, and GoogLeNet models. These models were selected via performance validation on each segment. It was observed that VGGNet-19 was capable of classifying the thoracic and cervical regions, while YoLo V2 was able to efficiently classify the lumbar region, ResNet 101 exhibited better accuracy for sacral-region classification, and GoogLeNet was able to classify the coccygeal region with high performance accuracy. Due to use of specialized CNN models for different spinal cord segments, the proposed model was able to achieve a 14.5% better segmentation efficiency, 98.9% tumor classification accuracy, and a 15.6% higher speed performance when averaged over the entire dataset and compared with various state-of-the art models. This performance was observed to be better, due to which it can be used for various clinical deployments. Moreover, this performance was observed to be consistent across multiple tumor types and spinal cord regions, which makes the model highly scalable for a wide variety of spinal cord tumor classification scenarios.