Emerging trends to replace pesticides with nanomaterials: Recent experiences and future perspectives for ecofriendly environment.

Despite the widespread usage to safeguard crops and manage pests, pesticides have detrimental effects on the environment and human health. The necessity to find sustainable agricultural techniques and meet the growing demand for food production has spurred the quest for pesticide substitutes other than traditional ones. The unique qualities of nanotechnology, including its high surface area-to-volume ratio, controlled release, and better stability, have made it a promising choice for pest management. Over the past ten years, there has been a noticeable growth in the usage of nanomaterials for pest management; however, concerns about their possible effects on the environment and human health have also surfaced. The purpose of this review paper is to give a broad overview of the worldwide trends and environmental effects of using nanomaterials in place of pesticides. The various types of nanomaterials, their characteristics, and their possible application in crop protection are covered. The limits of the current regulatory frameworks for nanomaterials in agriculture are further highlighted in this review. Additionally, it describes how standard testing procedures must be followed to assess the effects of nanomaterials on the environment and human health before their commercialization. In order to establish sustainable and secure nanotechnology-based pest control techniques, the review concludes by highlighting the significance of taking into account the possible hazards and benefits of nanomaterials for pest management and the necessity of an integrated approach. It also emphasizes the importance of more investigation into the behavior and environmental fate of nanomaterials to guarantee their safe and efficient application in agriculture.

Enhancing brain tumor diagnosis: an optimized CNN hyperparameter model for improved accuracy and reliability.

Hyperparameter tuning plays a pivotal role in the accuracy and reliability of convolutional neural network (CNN) models used in brain tumor diagnosis. These hyperparameters exert control over various aspects of the neural network, encompassing feature extraction, spatial resolution, non-linear mapping, convergence speed, and model complexity. We propose a meticulously refined CNN hyperparameter model designed to optimize critical parameters, including filter number and size, stride padding, pooling techniques, activation functions, learning rate, batch size, and the number of layers. Our approach leverages two publicly available brain tumor MRI datasets for research purposes. The first dataset comprises a total of 7,023 human brain images, categorized into four classes: glioma, meningioma, no tumor, and pituitary. The second dataset contains 253 images classified as "yes" and "no." Our approach delivers exceptional results, demonstrating an average 94.25% precision, recall, and F1-score with 96% accuracy for dataset 1, while an average 87.5% precision, recall, and F1-score, with accuracy of 88% for dataset 2. To affirm the robustness of our findings, we perform a comprehensive comparison with existing techniques, revealing that our method consistently outperforms these approaches. By systematically fine-tuning these critical hyperparameters, our model not only enhances its performance but also bolsters its generalization capabilities. This optimized CNN model provides medical experts with a more precise and efficient tool for supporting their decision-making processes in brain tumor diagnosis.

Significance of Estrogen/Progesterone Receptor Expression in Metaplastic Breast Carcinoma.

Introduction: Metaplastic breast carcinoma (MBC) is a rare subgroup of breast neoplasms associated with adverse outcomes because of its aggressive nature. Typically, MBCs show triple-negative hormone receptor (HR) status. Determining the HR status of breast cancer is an integral part because it is an important prognostic factor and helps in the treatment course of the disease. This study aimed to determine the HR status of MBC, its significance, and its association with various clinicopathological parameters. Methods: This was a retrospective study conducted at the Department of Histopathology, Liaquat National Hospital. A total of 140 biopsy-proven cases of MBC were enrolled in the study. Clinical and pathological data were retrieved from the institutes' archives. Immunohistochemical studies were conducted to determine the estrogen receptor (ER) and progesterone receptor (PR) status. Results: The mean age of MBC in our population was found to be 52.18 ± 12.19 years. The HR positivity rate in our population was found to be 32.9%. A significant association was found between HR status and tumor laterality, tumor size, tumor grade, tumor stage, and recurrence. ER/PR-negative MBCs were most probably associated with higher grade and higher tumor stage and were larger in size (6.62 ± 3.43 cm) than ER/PR-positive MBCs (4.20 ± 1.88 cm). Moreover, ER/PR-positive MBCs showed a higher recurrence rate than ER/PR-negative MBCs (43.5% vs. 25.5%, respectively). No statistically significant relationship was found between HR status and patient age, histological subtype, or survival rate. Conclusion: MBC is a rare breast neoplasm. MBC was found to be triple negative in most cases, but a significant percentage were HR (ER/PR) positive. Moreover, we found an association between HR status and various clinicopathological features, indicating that HR status is a significant predictor of MBC prognosis.

Advancing brain tumor detection: harnessing the Swin Transformer's power for accurate classification and performance analysis.

The accurate detection of brain tumors through medical imaging is paramount for precise diagnoses and effective treatment strategies. In this study, we introduce an innovative and robust methodology that capitalizes on the transformative potential of the Swin Transformer architecture for meticulous brain tumor image classification. Our approach handles the classification of brain tumors across four distinct categories: glioma, meningioma, non-tumor, and pituitary, leveraging a dataset comprising 2,870 images. Employing the Swin Transformer architecture, our method intricately integrates a multifaceted pipeline encompassing sophisticated preprocessing, intricate feature extraction mechanisms, and a highly nuanced classification framework. Utilizing 21 matrices for performance evaluation across all four classes, these matrices provide a detailed insight into the model's behavior throughout the learning process, furthermore showcasing a graphical representation of confusion matrix, training and validation loss and accuracy. The standout performance parameter, accuracy, stands at an impressive 97%. This achievement outperforms established models like CNN, DCNN, ViT, and their variants in brain tumor classification. Our methodology's robustness and exceptional accuracy showcase its potential as a pioneering model in this domain, promising substantial advancements in accurate tumor identification and classification, thereby contributing significantly to the landscape of medical image analysis.

Enhanced Regularized Ensemble Encoderdecoder Network for Accurate Brain Tumor Segmentation.

BACKGROUND: Segmenting tumors in MRI scans is a difficult and time-consuming task for radiologists. This is because tumors come in different shapes, sizes, and textures, making them hard to identify visually. OBJECTIVE: This study proposes a new method called the enhanced regularized ensemble encoder-decoder network (EREEDN) for more accurate brain tumor segmentation. METHODS: The EREEDN model first preprocesses the MRI data by normalizing the intensity levels. It then uses a series of autoencoder networks to segment the tumor. These autoencoder networks are trained using back-propagation and gradient descent. To prevent overfitting, the EREEDN model also uses L2 regularization and dropout mechanisms. RESULTS: The EREEDN model was evaluated on the BraTS 2020 dataset. It achieved high performance on various metrics, including accuracy, sensitivity, specificity, and dice coefficient score. The EREEDN model outperformed other methods on the BraTS 2020 dataset. CONCLUSION: The EREEDN model is a promising new method for brain tumor segmentation. It is more accurate and efficient than previous methods. Future studies will focus on improving the performance of the EREEDN model on complex tumors.

Koetjapic acid: unveiling its potential as a saviour in the realm of biological and medicinal properties, with a focus on anticancer mechanism of action.

Scientists have been compelled to search for alternative treatments due to the increasing prevalence of chemoresistance as well as the agonising and distressing side effects of both chemotherapy and radiation. Plant extracts have been exploited to treat various medical conditions for ages. Considering this fact, the main focus of various recent studies that are being conducted to find new and potent anticancer drugs involves the identification and utilisation of potential therapeutic chemicals present in plant extracts. Koetjapic acid (KJA), which belongs to the family of triterpenes, is primarily isolated from Sandoricum koetjape. Ongoing investigations into its therapeutic applications have revealed its tendency to impede the growth and proliferation of cancer cells. Koetjapic acid activates the intrinsic apoptotic pathway and promotes the death of cancer cells. Moreover, it inhibits angiogenesis and the dissemination of tumour (metastasis) by targeting the VEGF signalling cascade. Therefore, this study aims to elucidate the underlying mechanism of anticancer activity of koetjapic acid, providing significant insight into the compound's potential as an anticancer agent.

Diagnostic accuracy of intraoperative frozen section for margin evaluation of oral cavity squamous cell carcinoma.

OBJECTIVES: Intraoperative frozen-section evaluation is a valuable technique for detecting positive margins intraoperatively for oral squamous cell carcinoma. We conducted this study to determine the diagnostic accuracy of frozen section in detecting margin status and the effect of tumor grade and stage on diagnostic accuracy. RESULTS: A total of 251 biopsy-proven cases of oral squamous cell carcinoma were included in this study. The tissue specimen resected during surgery was sent to the laboratory for frozen section evaluation. The frozen section results were then compared with the permanent section results to determine the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy. The mean age of the patients included in the study was 51.65 ± 10.03 years, with male predominance (55.4%). The overall sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of frozen section were 88.81%, 94.84%, 95.20%, 88.10%, and 91.63%, respectively. We conclude that frozen section is a useful technique in determining the margin status intraoperatively in oral cancers, with high diagnostic accuracy. Moreover, certain clinical parameters such as age, gender, disease duration, and tumor stage and grade appear to affect the diagnostic accuracy of frozen section.

Fungal empyema thoracis, a rare but an emerging entity: a retrospective case series from Pakistan.

Background and objective: Fungal empyema is a rare entity which is associated with high mortality. It is mostly seen in immune-compromised hosts. However, there is limited data available on fungal empyema from developing countries regarding risk factors, treatment, and outcome. This study was conducted to determine the risk factors, clinical features, treatment, and outcome of fungal empyema. Methods: A retrospective observational study was performed on proven fungal empyema cases, admitted at Aga Khan University Hospital, Karachi, Pakistan during January 2018 to May 2021. We excluded all those patients with polymicrobial bacterial and fungal empyema or with negative pleural fluid cultures. A preformed questionnaire was filled out for each case. Results: A total of 26 patients were diagnosed with fungal empyema with a mean age of 43.6 ± 20.3 years. Of these, 16 (61.5%) patients were male. Diabetes mellitus was the most frequent comorbidity (n = 11, 42.3%), followed by hypertension (n = 9, 34.6%), malignancy (n = 6, 23.1%), and asthma (n = 1, 3.8%). Ten (38.5%) patients had multiple comorbidities. Candida spp. was isolated in 21 (80.8%) patients and Aspergillus spp. in 7 (26.9%) patients. Fusarium spp. was isolated from one (3.9%) patient. Video-assisted thoracoscopy surgery was done in 14 (53.8%) patients and 12 (46.1%) patients were managed with tube thoracostomy. Twenty-one (80.8%) patients received antifungal agents. Overall, in-hospital mortality was 38.5% (n = 10) and all patients developed respiratory failure. Clinical improvement was seen in 16 (61.5%) patients. Conclusion: Our data suggest that fungal empyema has a poor outcome as almost one-third of our patients died. Early diagnosis and intervention can improve outcome.

Fungal Empyema; A Case series from Pakistan • This study was carried out as there are limited data available globally on fungal empyema. • We conducted a retrospective case study of 26 patients and our findings suggest that the fungal empyema has a poor outcome. • One third of our patients died during hospital stay. • Early diagnosis and treatment are important in fungal empyema. • Diabetes mellitus was found as a possible risk factor for fungal empyema, which should be evaluated further in future studies.

Theabrownin: a dietary nutraceutical with diverse anticancer mechanisms.

Cancer, a highly deadly disease, necessitates safe, cost-effective, and readily accessible treatments to mitigate its impact. Theabrownin (THBR), a polyphenolic pigment found in Pu-erh tea, has garnered attention for its potential benefits in memory, liver health, and inflammation control. By observing different biological activities of THBR, recently researchers have unveiled THBR's promising anticancer properties across various human cancer types. By examining existing studies, it is evident that THBR demonstrates substantial potential in inhibiting cell proliferation and reducing tumour size with minimal harm to normal cells. These effects are achieved through the modulation of key molecular markers such as Bcl-2, Bax, various Caspases, Poly (ADP-ribose) polymerase cleavage (Cl-PARP), and zinc finger E box binding homeobox 1 (ZEB 1). This review aims to provide in-depth insights into THBR's role in cancer research. This review also elucidates the underlying anticancer mechanisms of THBR, offering promise as a novel anticancer drug to alleviate the global cancer burden.

Next-Gen brain tumor classification: pioneering with deep learning and fine-tuned conditional generative adversarial networks.

Brain tumor has become one of the fatal causes of death worldwide in recent years, affecting many individuals annually and resulting in loss of lives. Brain tumors are characterized by the abnormal or irregular growth of brain tissues that can spread to nearby tissues and eventually throughout the brain. Although several traditional machine learning and deep learning techniques have been developed for detecting and classifying brain tumors, they do not always provide an accurate and timely diagnosis. This study proposes a conditional generative adversarial network (CGAN) that leverages the fine-tuning of a convolutional neural network (CNN) to achieve more precise detection of brain tumors. The CGAN comprises two parts, a generator and a discriminator, whose outputs are used as inputs for fine-tuning the CNN model. The publicly available dataset of brain tumor MRI images on Kaggle was used to conduct experiments for Datasets 1 and 2. Statistical values such as precision, specificity, sensitivity, F1-score, and accuracy were used to evaluate the results. Compared to existing techniques, our proposed CGAN model achieved an accuracy value of 0.93 for Dataset 1 and 0.97 for Dataset 2.

Successful Management of Recurrent Cholangitis Post Cholecystectomy in a Primary Care Hospital.

Cholangitis, a pathological disease characterized by inflammation of the biliary system, often occurs in conjunction with gallstone blockage and may lead to various problems, persisting for extended periods after cholecystectomy. The present report provides a comprehensive account of a clinical case involving a 35-year-old female patient who had undergone cholecystectomy three years before and is now experiencing symptoms consistent with cholangitis. The individual was originally given conservative therapy, which included the administration of intravenous ceftriaxone antibiotics, analgesics, fluids, and gastrointestinal treatment. Subsequently, they were sent to a tertiary care hospital for the performance of endoscopic retrograde cholangiopancreatography (ERCP) and the placement of a stent. Following a period of seven days, laboratory tests showed a return to normalcy, showing a positive outcome in response to the use of conservative management strategies. The patient made the decision to have an elective laparoscopic cholecystectomy, resulting in a favorable recuperation and a hospitalization period of 24 hours. The aforementioned results jointly demonstrate the efficacy of conservative therapy in treating cholangitis and the potential for eventual elective surgery in individuals experiencing prolonged gallbladder problems. In conclusion, this case underscores the need to maintain a state of alertness with respect to complications associated with cholecystectomy, such as cholangitis. It also emphasizes the effectiveness of conservative treatment approaches and the probable necessity for elective surgical intervention.

Multi-Method Analysis of Histopathological Image for Early Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning and Hybrid Techniques.

Oral cancer is a fatal disease and ranks seventh among the most common cancers throughout the whole globe. Oral cancer is a type of cancer that usually affects the head and neck. The current gold standard for diagnosis is histopathological investigation, however, the conventional approach is time-consuming and requires professional interpretation. Therefore, early diagnosis of Oral Squamous Cell Carcinoma (OSCC) is crucial for successful therapy, reducing the risk of mortality and morbidity, while improving the patient's chances of survival. Thus, we employed several artificial intelligence techniques to aid clinicians or physicians, thereby significantly reducing the workload of pathologists. This study aimed to develop hybrid methodologies based on fused features to generate better results for early diagnosis of OSCC. This study employed three different strategies, each using five distinct models. The first strategy is transfer learning using the Xception, Inceptionv3, InceptionResNetV2, NASNetLarge, and DenseNet201 models. The second strategy involves using a pre-trained art of CNN for feature extraction coupled with a Support Vector Machine (SVM) for classification. In particular, features were extracted using various pre-trained models, namely Xception, Inceptionv3, InceptionResNetV2, NASNetLarge, and DenseNet201, and were subsequently applied to the SVM algorithm to evaluate the classification accuracy. The final strategy employs a cutting-edge hybrid feature fusion technique, utilizing an art-of-CNN model to extract the deep features of the aforementioned models. These deep features underwent dimensionality reduction through principal component analysis (PCA). Subsequently, low-dimensionality features are combined with shape, color, and texture features extracted using a gray-level co-occurrence matrix (GLCM), Histogram of Oriented Gradient (HOG), and Local Binary Pattern (LBP) methods. Hybrid feature fusion was incorporated into the SVM to enhance the classification performance. The proposed system achieved promising results for rapid diagnosis of OSCC using histological images. The accuracy, precision, sensitivity, specificity, F-1 score, and area under the curve (AUC) of the support vector machine (SVM) algorithm based on the hybrid feature fusion of DenseNet201 with GLCM, HOG, and LBP features were 97.00%, 96.77%, 90.90%, 98.92%, 93.74%, and 96.80%, respectively.

Clinicopathological Parameters Predicting Malignancy in Phyllodes Tumor of the Breast.

Introduction Phyllodes tumor (PT) is an uncommon fibroepithelial neoplasm of the breast. It is a biphasic tumor with stromal and epithelial components, with a tendency to recur. Because of its wide range of disease manifestations, it has been subclassified into three categories, i.e., benign, borderline, and malignant, based on several histological parameters. This study was conducted to evaluate the clinicopathological features associated with malignancy in breast PTs. Methods We conducted a retrospective study at the Department of Histopathology at Liaquat National Hospital, Karachi, Pakistan. A total of 146 biopsy-proven cases of PTs were enrolled in the study. Clinical data were obtained from the clinical referral forms. Specimens were obtained from either lumpectomy or simple mastectomy. The specimens obtained were received at the laboratory where after gross examination, paraffin-embedded tissue blocks were prepared, which were sectioned, stained, and studied by a senior histopathologist. Pathological features, such as mitotic count, necrosis, stromal atypia, stromal overgrowth, and heterologous elements, were observed. Based on these features, the PTs were classified into benign, borderline, and malignant tumors. Results The mean age of the PTs in our setup was 40.65 ± 12.17 years with a mean size of 9.40 ± 6.49 cm. Malignant PT was found to be the most prevalent in our population, accounting for 63 (43.2%) cases, followed by borderline (51, 34.9%) and benign (32, 21.9%). A significant association was found between the tumor subtype and patient age, i.e., patients diagnosed with malignant and borderline PTs were found to be of older age (mean 42.82 ± 12.94 and 42.05 ± 11.31 years, respectively) than those diagnosed with benign PTs (mean age 34.12 ± 9.75 years). Moreover, malignant PTs were associated with larger tumor size (mean 11.46 ± 6.08) compared with the other two subtypes. Conclusion We found a significant association among patient age, tumor size, and PT subtype. Therefore, apart from the usual histological parameters, patient age and tumor size are important parameters for predicting the behavior of breast PT and should be considered for management.

TP53 and its Regulatory Genes as Prognosis of Cutaneous Melanoma.

The present study was the first comprehensive investigation of genetic mutation and expression levels of the p53 signaling genes in cutaneous melanoma through various genetic databases providing large datasets. The mutational landscape of p53 and its signaling genes was higher than expected, with TP53 followed by CDKN2A being the most mutated gene in cutaneous melanoma. Furthermore, the expression analysis showed that TP53, MDM2, CDKN2A, and TP53BP1 were overexpressed, while MDM4 and CDKN2B were under-expressed in cutaneous melanoma. Overall, TCGA data revealed that among all the other p53 signaling proteins, CDKN2A was significantly higher in both sun and non-sun-exposed healthy tissues than in melanoma. Likewise, MDM4 and TP53BP1 expressions were markedly greater in non-sun-exposed healthy tissues compared to other groups. However, CDKN2B expression was higher in the sun-exposed healthy tissues than in other tissues. In addition, various genes were expressed significantly differently among males and females. In addition, CDKN2A was highly expressed in the SK-MEL-30 skin cancer cell line, whereas, Immune cell type expression analysis revealed that the MDM4 was highly expressed in naïve B-cells. Furthermore, all six genes were significantly overexpressed in extraordinarily overweight or obese tumor tissues compared to healthy tissues. MDM2 expression and tumor stage were closely related. There were differences in gene expression across patient age groups and positive nodal status. TP53 showed a positive correlation with B cells, MDM2 with CD8+T cells, macrophages and neutrophils, and MDM4 with neutrophils. CDKN2A/B had a non-significant correlation with all six types of immune cells. However, TP53BP1 was positively correlated with all five types of immune cells except B cells. Only TP53, MDM2, and CDKN2A had a role in cutaneous melanoma-specific tumor immunity. All TP53 and its regulating genes may be predictive for prognosis. The results of the present study need to be validated through future screening, in vivo, and in vitro studies.

Non-cystic fibrosis bronchiectasis: a retrospective review of clinical, radiological, microbiological and lung function profile at a tertiary care center of low-middle income country.

Non-cystic fibrosis (non-CF) bronchiectasis has emerged as a significant respiratory disease in developing countries. Given the variation in causes and clinical characteristics across different regions, it is necessary to conduct studies in regions with limited data such as low-middle income countries (LMIC). The aim of the study was to investigate the underlying causes, clinical presentation, etiology, lung function and imaging in patients with bronchiectasis who sought treatment at a tertiary care hospital in a LMIC. We conducted retrospective observational study at the Aga Khan University, Pakistan. Adult patients diagnosed with non-CF bronchiectasis on high-resolution computed tomography scan between 2000 and 2020 were included. We evaluated the etiology, clinical characteristics, microbiology, radiology and spirometric pattern of these patients. A total of 340 patients were included with 56.5% being female and 44.7% aged over 60 years. Among them, 157 (46.2%) had experienced symptoms for 1-5 years. The most common spirometric pattern observed was obstructive impairment (58.1%). Previous tuberculosis (TB) (52.94%) was the most common etiology followed by allergic bronchopulmonary aspergillosis (7.64%). Bilateral lung involvement on HRCT scan was found in 63.2% of patients. Pseudomonas aeruginosa was the most frequently identified organism (38.75%) among 240 patients with available specimens. Patients with P. aeruginosa infections had a significantly higher number of exacerbations (p=0.016). There was a significant difference (p<0.001) in P. aeruginosa growth among different etiologies. In conclusion, post-TB bronchiectasis was the most common cause of non-CF bronchiectasis in our study population. P. aeruginosa was the predominant organism, and 63.2% of the patients exhibited bilateral lung involvement. Since P. aeruginosa growth and extensive lung involvement have been associated with poor prognosis and increased mortality risk, we recommend close follow ups of these patients to improve quality of life and survival in developing countries like Pakistan.

LncRNA SNHG6 role in clinicopathological parameters in cancers.

RNA sequencing has revealed that a substantial portion of the human genome undergoes transcription, yet a minimal fraction of these transcripts translates into proteins. LncRNAs, RNA molecules less than 200 nt in length, once deemed as transcriptional noise, have now emerged as crucial regulators of numerous cellular processes. This review focuses on the lncRNA SNHG6, aiming to elucidate its biogenesis, the pivotal roles it plays, and its mechanisms in facilitating the hallmarks of cancer. A comprehensive literature review and analysis were undertaken to delve into the biogenesis of SNHG6, its roles in cellular processes, and the mechanisms through which it contributes to the hallmarks of cancer. SNHG6 is a notable lncRNA, observed to be overexpressed in various cancer types; its perturbation has been linked to tumor progression, emphasizing its significance in oncogenesis. This lncRNA contributes to a range of cellular aberrations, influencing transcriptional, post-transcriptional, and epigenetic processes of mRNA, ultimately driving cancerous transformations. LncRNA SNHG6 serves as a potential biomarker and therapeutic target due to its association with tumorigenesis. Understanding its mechanism and role in cancer can pave the way for novel diagnostic and therapeutic strategies.

Mismatch Repair Deficient (dMMR) Colorectal Carcinoma in a Pakistani Cohort: Association With Clinical and Pathological Parameters.

Introduction Microsatellite instability (MSI) is an important pathway in colorectal carcinoma (CRC) pathogenesis. MSI occurs due to mutations in mismatch repair (MMR) genes that include MutL protein homolog 1 (MLH1), postmeiotic segregation increased 2 (PMS2), MutS homolog 2 (MSH2), and MutS homolog 6 (MSH6). CRC with MSI is termed MMR deficient (dMMR) CRC. Conversely, CRC with intact MMR genes is called microsatellite stable (MSS) or MMR proficient (pMMR). In this study, we compared the clinicopathological features of dMMR CRC with pMMR CRC. Methods It was a retrospective study conducted in the Department of Histopathology, Liaquat National Hospital, Karachi, Pakistan, from March 2020 to February 2022, over a duration of two years. Biopsy-proven cases of CRC with upfront surgical resection were included in the study. Microscopic examination was performed to evaluate tumor type, grade, and extent of invasion, presence of necrosis, perineural invasion (PNI), lymphovascular invasion (LVI), peritumoral lymphocytes (PTL), intratumoral lymphocytes (ITL), and nodal metastasis. Immunohistochemical staining was performed using antibodies, namely, MLH1, PMS2, MSH2, and MSH6. Any loss of nuclear expression in tumor cells was termed dMMR or microsatellite instable, whereas the intact nuclear expression in tumor cells was labeled as MSS or pMMR. Results A total of 135 cases of CRC were included in the study. The mean age at diagnosis was 46.76 ± 17.74 years, with female predominance (60.7%). The loss of MLH1, PMS2, MSH2, and MSH6 expression was noted in 39.3%, 34.1%, 17.8%, and 16.3% cases, respectively. Overall, 59.3% of CRCs were pMMR, while 40.7% were dMMR. A significant association of MMR status was noted with respect to age, PNI, LVI, tumor grade, tumor (T) and nodal (N) stage, mucinous differentiation, and ITL. dMMR CRC was significantly above 50 years than pMMR CRC. The frequency of PNI and LVI was lower in dMMR CRC than in pMMR CRC. Conversely, the higher grade (grade 3) and higher T-stage (T4) were associated with dMMR CRC. Alternatively, the frequency of higher N stage (N2b) was more commonly seen in pMMR CRC. Moreover, mucinous differentiation and ITL were significantly associated with dMMR CRC. Conclusion A significant proportion of CRC patients in our population demonstrated dMMR status. dMMR CRC had a higher histological grade with a higher frequency of mucinous differentiation and higher T-stage. Conversely, the presence of LVI, PNI, and higher N stages were associated with pMMR CRC.

Zinc Foliar Application Mitigates Cadmium-Induced Growth Inhibition and Enhances Wheat Growth, Chlorophyll Contents, and Yield.

Cadmium (Cd) is a toxic heavy metal that significantly threatens plants and the environment. Its toxicity in plants can result in various adverse effects, including reduced growth, altered metabolism, and cell damage. Cadmium can also interfere with nutrient uptake, particularly zinc (Zn), leading to Zn deficiency and further exacerbating Cd toxicity. On the other hand, foliar application of zinc might be a useful strategy to mitigate cadmium (Cd) toxicity in plants. Hence, a pot experiment was conducted with three replications. The wheat plants were treated with various concentrations of Zn as a foliar spray (control, 0.1, 0.2, 0.4, and 0.5%) in Cd-spiked soil in pots. The results showed that foliar use of Zn at 0.4 or 0.5% resulted in higher plant height, grain yield, and dry matter yield than the control group. Using Zn as foliar spray enriched shoot and grain Zn content while reducing Cd content in the shoot and grain. The leaf's electrolyte leakage (EL) decreased by 15.4, 29.8, 40.7, and 45.9% in the Zn 0.1%, Zn 0.2%, Zn 0.4%, and Zn 0.5% treatments, respectively, compared to the control treatment. Regarding superoxide dismutase (SOD) activity, Zn 0.5% treatment showed a decrease of 42.9% over control. Specifically, the Zn 0.1% showed a 27.2%, Zn 0.2% showed a 56.8%, Zn 0.4% showed a 91.1%, and Zn 0.5% showed a 133.7% increase in total chlorophyll content than control. Based on the results, it is recommended that 0.4% Zn solution may be used for foliar application for enhancing crop productivity and Zn concentration in plants under high Cd stress. Additionally, continued research on the mechanisms of cadmium uptake, transport, and detoxification in plants may lead to the identification of new targets for intervention.

Advancing Brain Tumor Classification through Fine-Tuned Vision Transformers: A Comparative Study of Pre-Trained Models.

This paper presents a comprehensive study on the classification of brain tumor images using five pre-trained vision transformer (ViT) models, namely R50-ViT-l16, ViT-l16, ViT-l32, ViT-b16, and ViT-b32, employing a fine-tuning approach. The objective of this study is to advance the state-of-the-art in brain tumor classification by harnessing the power of these advanced models. The dataset utilized for experimentation consists of a total of 4855 images in the training set and 857 images in the testing set, encompassing four distinct tumor classes. The performance evaluation of each model is conducted through an extensive analysis encompassing precision, recall, F1-score, accuracy, and confusion matrix metrics. Among the models assessed, ViT-b32 demonstrates exceptional performance, achieving a high accuracy of 98.24% in accurately classifying brain tumor images. Notably, the obtained results outperform existing methodologies, showcasing the efficacy of the proposed approach. The contributions of this research extend beyond conventional methods, as it not only employs cutting-edge ViT models but also surpasses the performance of existing approaches for brain tumor image classification. This study not only demonstrates the potential of ViT models in medical image analysis but also provides a benchmark for future research in the field of brain tumor classification.

Early-Onset/Young-Onset Colorectal Carcinoma: A Comparative Analysis of Morphological Features and Biomarker Profile.

Introduction Colorectal carcinoma (CRC) is one of the most common cancers that involve the human body. Young-onset CRC (YO-CRC) or early-onset CRC (EO-CRC) is defined as CRC that develops before the age of 50 years, as opposed to CRC that is diagnosed after the age of 50, referred to as late-onset CRC (LO-CRC). EO-CRC is sparsely studied in our population. Therefore, in this study, we evaluated the clinicopathological parameters and biomarker profile of EO-CRC and compared them with those of LO-CRC. Methods This was a retrospective study conducted at the Department of Histopathology, Liaquat National Hospital, Karachi, Pakistan. A total of 254 biopsy-proven cases of CRC, reported over a period of nine years, were enrolled in the study. The specimens collected during surgery were sent to the laboratory for histopathological and immunohistochemical (IHC) status examinations. IHC staining of the specimens was performed using antibodies, namely, MutL protein homolog 1 (MLH1), postmeiotic segregation increased 2 (PMS2), MutS homolog 2 (MSH2), MutS homolog 6 (MSH6), and human epidermal growth factor receptor 2 (HER2/neu), on representative tissue blocks. A comparison of morphological and biomarker profiles between EO-CRC and LO-CRC was performed. Results The mean age at diagnosis was 46.27±17.75 years, with female predominance (59.8%). A significant difference between the two groups (EO-CRC and LO-CRC) was noted with respect to laterality, tumor site, tumor grade, tumor type, presence of pre-existing polyps, perineural invasion (PNI), lymphovascular invasion (LVI), and IHC markers. EO-CRC (as opposed to LO-CRC) significantly affected the left colon (92.6% vs. 72.9%, p<0.001), with the rectosigmoid being the most common site in the majority of cases (72.1% in EO-CRC vs. 61% in LO-CRC). EO-CRC showed a higher frequency of PNI and LVI than LO-CRC (42.6% vs. 23.7%, p=0.001; 29.4% vs. 18.6%, p=0.046, respectively). A significantly higher proportion of EO-CRCs were mucinous (42.6%) and medullary carcinoma (11.8%). Although the majority (54.4%) of cases of EO-CRC were grade 2 tumors at the time of diagnosis, a significantly higher proportion of them were grade 3 (44.1%) compared with LO-CRC. IHC comparisons between the two age groups showed that a significantly higher proportion of cases of EO-CRC showed positive HER2/neu expression (27.1%) compared with LO-CRC (13.2%). Conversely, the loss of expression of microsatellite instability (MSI) markers was more commonly seen in LO-CRS compared with EO-CRC. Conclusions We found a relatively higher frequency of EO-CRC in our population. Moreover, compared with LO-CRCs, EO-CRCs were associated with prognostically poor histological parameters, such as mucinous and medullary carcinoma, high-grade, PNI, and LVI. Similarly, EO-CRC had a higher positive expression of HER2/neu with intact MSI markers compared with AO-CRC; all these characteristics indicate poor biological behavior in EO-CRC.