PFP-HOG: Pyramid and Fixed-Size Patch-Based HOG Technique for Automated Brain Abnormality Classification with MRI.

Detecting neurological abnormalities such as brain tumors and Alzheimer's disease (AD) using magnetic resonance imaging (MRI) images is an important research topic in the literature. Numerous machine learning models have been used to detect brain abnormalities accurately. This study addresses the problem of detecting neurological abnormalities in MRI. The motivation behind this problem lies in the need for accurate and efficient methods to assist neurologists in the diagnosis of these disorders. In addition, many deep learning techniques have been applied to MRI to develop accurate brain abnormality detection models, but these networks have high time complexity. Hence, a novel hand-modeled feature-based learning network is presented to reduce the time complexity and obtain high classification performance. The model proposed in this work uses a new feature generation architecture named pyramid and fixed-size patch (PFP). The main aim of the proposed PFP structure is to attain high classification performance using essential feature extractors with both multilevel and local features. Furthermore, the PFP feature extractor generates low- and high-level features using a handcrafted extractor. To obtain the high discriminative feature extraction ability of the PFP, we have used histogram-oriented gradients (HOG); hence, it is named PFP-HOG. Furthermore, the iterative Chi2 (IChi2) is utilized to choose the clinically significant features. Finally, the k-nearest neighbors (kNN) with tenfold cross-validation is used for automated classification. Four MRI neurological databases (AD dataset, brain tumor dataset 1, brain tumor dataset 2, and merged dataset) have been utilized to develop our model. PFP-HOG and IChi2-based models attained 100%, 94.98%, 98.19%, and 97.80% using the AD dataset, brain tumor dataset1, brain tumor dataset 2, and merged brain MRI dataset, respectively. These findings not only provide an accurate and robust classification of various neurological disorders using MRI but also hold the potential to assist neurologists in validating manual MRI brain abnormality screening.

Development of Debiasing Technique for Lung Nodule Chest X-ray Datasets to Generalize Deep Learning Models.

Screening programs for early lung cancer diagnosis are uncommon, primarily due to the challenge of reaching at-risk patients located in rural areas far from medical facilities. To overcome this obstacle, a comprehensive approach is needed that combines mobility, low cost, speed, accuracy, and privacy. One potential solution lies in combining the chest X-ray imaging mode with federated deep learning, ensuring that no single data source can bias the model adversely. This study presents a pre-processing pipeline designed to debias chest X-ray images, thereby enhancing internal classification and external generalization. The pipeline employs a pruning mechanism to train a deep learning model for nodule detection, utilizing the most informative images from a publicly available lung nodule X-ray dataset. Histogram equalization is used to remove systematic differences in image brightness and contrast. Model training is then performed using combinations of lung field segmentation, close cropping, and rib/bone suppression. The resulting deep learning models, generated through this pre-processing pipeline, demonstrate successful generalization on an independent lung nodule dataset. By eliminating confounding variables in chest X-ray images and suppressing signal noise from the bone structures, the proposed deep learning lung nodule detection algorithm achieves an external generalization accuracy of 89%. This approach paves the way for the development of a low-cost and accessible deep learning-based clinical system for lung cancer screening.

Estimation of the proportion of true null hypotheses under sparse dependence: Adaptive FDR controlling in microarray data.

The proportion of non-differentially expressed genes is an important quantity in microarray data analysis and an appropriate estimate of the same is used to construct adaptive multiple testing procedures. Most of the estimators for the proportion of true null hypotheses based on the thresholding, maximum likelihood and density estimation approaches assume independence among the gene expressions. Usually, sparse dependence structure is natural in modelling associations in microarray gene expression data and hence it is necessary to develop methods for accommodating the sparse dependence well within the framework of existing estimators. We propose a clustering based method to put genes in the same group that are not coexpressed using the estimated high dimensional correlation structure under sparse assumption as dissimilarity matrix. This novel method is applied to three existing estimators for the proportion of true null hypotheses. Extensive simulation study shows that the proposed method improves an existing estimator by making it less conservative and the corresponding adaptive Benjamini-Hochberg algorithm more powerful. The proposed method is applied to a microarray gene expression dataset of colorectal cancer patients and the results show gain in terms of number of differentially expressed genes. The R code is available at https://github.com/aniketstat/Proportiontion-of-true-null-under-sparse-dependence-2021.

Deep Mining Generation of Lung Cancer Malignancy Models from Chest X-ray Images.

Lung cancer is the leading cause of cancer death and morbidity worldwide. Many studies have shown machine learning models to be effective in detecting lung nodules from chest X-ray images. However, these techniques have yet to be embraced by the medical community due to several practical, ethical, and regulatory constraints stemming from the "black-box" nature of deep learning models. Additionally, most lung nodules visible on chest X-rays are benign; therefore, the narrow task of computer vision-based lung nodule detection cannot be equated to automated lung cancer detection. Addressing both concerns, this study introduces a novel hybrid deep learning and decision tree-based computer vision model, which presents lung cancer malignancy predictions as interpretable decision trees. The deep learning component of this process is trained using a large publicly available dataset on pathological biomarkers associated with lung cancer. These models are then used to inference biomarker scores for chest X-ray images from two independent data sets, for which malignancy metadata is available. Next, multi-variate predictive models were mined by fitting shallow decision trees to the malignancy stratified datasets and interrogating a range of metrics to determine the best model. The best decision tree model achieved sensitivity and specificity of 86.7% and 80.0%, respectively, with a positive predictive value of 92.9%. Decision trees mined using this method may be considered as a starting point for refinement into clinically useful multi-variate lung cancer malignancy models for implementation as a workflow augmentation tool to improve the efficiency of human radiologists.

Apigenin-Loaded PLGA-DMSA Nanoparticles: A Novel Strategy to Treat Melanoma Lung Metastasis.

The flavone apigenin (APG), alone as well as in combination with other chemotherapeutic agents, is known to exhibit potential anticancer effects in various tumors and inhibit growth and metastasis of melanoma. However, the potential of apigenin nanoparticles (APG-NPs) to prevent lung colonization of malignant melanoma has not been well investigated. APG-loaded PLGA-NPs were surface-functionalized with meso-2,3-dimercaptosuccinic acid (DMSA) for the treatment of melanoma lung metastasis. DMSA-conjugated APG-loaded NPs (DMSA-APG-NPs) administered by an oral route exhibited sustained APG release and showed considerable enhancement of plasma half-life, Cmax value, and bioavailability compared to APG-NPs both in plasma and the lungs. DMSA-conjugated APG-NPs showed comparably higher cellular internalization in B16F10 and A549 cell lines compared to that of plain NPs. Increased cytotoxicity was observed for DMSA-APG-NPs compared to APG-NPs in A549 cells. This difference between the two formulations was lower in B16F10 cells. Significant depolarization of mitochondrial transmembrane potential and an enhanced level of caspase activity were observed in B16F10 cells treated with DMSA-APG-NPs compared to APG-NPs as well. Western blot analysis of various proteins was performed to understand the mechanism of apoptosis as well as prevention of melanoma cell migration and invasion. DMSA conjugation substantially increased accumulation of DMSA-APG-NPs given by an intravenous route in the lungs compared to APG-NPs at 6 and 8 h. This was also corroborated by scintigraphic imaging studies with radiolabeled formulations administered by an intravenous route. Conjugation also allowed comparatively higher penetration as evident from an in vitro three-dimensional tumor spheroid model study. Finally, the potential therapeutic efficacy of the formulation was established in experimental B16F10 lung metastases, which suggested an improved bioavailability with enhanced antitumor and antimetastasis efficacy of DMSA-conjugated APG-NPs following oral administration.

A Review of Models Used for Investigating Barriers to Healthcare Access in Australia.

Understanding barriers to healthcare access is a multifaceted challenge, which is often highly diverse depending on location and the prevalent surroundings. The barriers can range from transport accessibility to socio-economic conditions, ethnicity and various patient characteristics. Australia has one of the best healthcare systems in the world; however, there are several concerns surrounding its accessibility, primarily due to the vast geographical area it encompasses. This review study is an attempt to understand the various modeling approaches used by researchers to analyze diverse barriers related to specific disease types and the various areal distributions in the country. In terms of barriers, the most affected people are those living in rural and remote parts, and the situation is even worse for indigenous people. These models have mostly focused on the use of statistical models and spatial modeling. The review reveals that most of the focus has been on cancer-related studies and understanding accessibility among the rural and urban population. Future work should focus on further categorizing the population based on indigeneity, migration status and the use of advanced computational models. This article should not be considered an exhaustive review of every aspect as each section deserves a separate review of its own. However, it highlights all the key points, covered under several facets which can be used by researchers and policymakers to understand the current limitations and the steps that need to be taken to improve health accessibility.

Microfilaria Infection in Metastatic Node in a Case of Breast Carcinoma.

Filariasis is a major public health problem in tropical and subtropical countries such as India. It is caused by nematodes, principally Wuchereria bancrofti and Brugia malayi and is transmitted by the Culex mosquito. W.bancrofti accounts for 90% of cases of lymphatic filariasis. Filaria of the breast with axillary lymphadenopathy and lymphedema, mimicking breast carcinoma has been previously reported. Microfilariae have also been previously observed as coincidental findings with various inflammatory and neoplastic lesions. Few examples are hemangiomas of the liver, meningiomas, intracranial hemangioblastomas, uterine cervix, pharyngeal, urinary bladder, preputial and metastatic carcinomas, melanomas, and leukemia.Here, we report an unusual case of filarial infection of a metastatic axillary node in a case of invasive breast carcinoma, observed in a modified radical mastectomy specimen. Previous cases reported in literature have reported microfilaria in metastatic axillary node detected on cytology specimens; histological diagnosis, though reported, is rare.

Polymorphisms in ADH1B and ALDH2 genes associated with the increased risk of gastric cancer in West Bengal, India.

BACKGROUND: Gastric cancer (GC) is one of the most frequently diagnosed digestive tract cancers and carries a high risk of mortality. Acetaldehyde (AA), a carcinogenic intermediate of ethanol metabolism contributes to the risk of GC. The accumulation of AA largely depends on the activity of the major metabolic enzymes, alcohol dehydrogenase and aldehyde dehydrogenase encoded by the ADH (ADH1 gene cluster: ADH1A, ADH1B and ADH1C) and ALDH2 genes, respectively. This study aimed to evaluate the association between genetic variants in these genes and GC risk in West Bengal, India. METHODS: We enrolled 105 GC patients (cases), and their corresponding sex, age and ethnicity was matched to 108 normal individuals (controls). Genotyping for ADH1A (rs1230025), ADH1B (rs3811802, rs1229982, rs1229984, rs6413413, rs4147536, rs2066702 and rs17033), ADH1C (rs698) and ALDH2 (rs886205, rs968529, rs16941667 and rs671) was performed using DNA sequencing and RFLP. RESULTS: Genotype and allele frequency analysis of these SNPs revealed that G allele of rs17033 is a risk allele (A vs G: OR = 3.67, 95% CI = 1.54-8.75, p = 0.002) for GC. Significant association was also observed between rs671 and incidence of GC (p = 0.003). Moreover, smokers having the Lys allele of rs671 had a 7-fold increased risk of acquiring the disease (OR = 7.58, 95% CI = 1.34-42.78, p = 0.009). CONCLUSION: In conclusion, rs17033 of ADH1B and rs671 of ALDH2 SNPs were associated with GC risk and smoking habit may further modify the effect of rs671. Conversely, rs4147536 of ADH1B might have a protective role in our study population. Additional studies with a larger patient population are needed to confirm our results.

Iron-Catalyzed Mild and Selective Hydrogenative Cross-Coupling of Nitriles and Amines To Form Secondary Aldimines.

The first example of a base-metal-catalyzed homogeneous hydrogenative coupling of nitriles and amines to selectively form secondary cross-imines is reported. The reaction is catalyzed under mild conditions by a well-defined (iPr-PNP)Fe(H)Br(CO) pincer pre-catalyst and catalytic tBuOK.

Z-Selective (Cross-)Dimerization of Terminal Alkynes Catalyzed by an Iron Complex.

Efficient iron-catalyzed homocoupling of terminal alkynes and cross-dimerization of aryl acetylenes with trimethylsilylacetylene is reported. The complex [Fe(H)(BH4 )(iPr-PNP)] (1) catalyzed the (cross-)dimerization of alkynes at room temperature, with no need for a base or other additives, to give the corresponding dimerized products with Z selectivity in excellent yields (79-99 %).

Unprecedented iron-catalyzed selective hydrogenation of activated amides to amines and alcohols.

The first example of hydrogenation of amides homogeneously catalyzed by an earth-abundant metal complex is reported. The reaction is catalyzed by iron PNP pincer complexes. A wide range of secondary and tertiary N-substituted 2,2,2-trifluoroacetamides were hydrogenated to form amines and trifluoroethanol.

Selective hydrogenation of nitriles to primary amines catalyzed by a novel iron complex.

Hydrogenation of nitriles to primary amines constitutes an atom-efficient and environmentally benign synthetic reaction. Herein we present a novel complex based on earth-abundant iron, and its application in the catalytic homogeneous hydrogenation of (hetero)aromatic, benzylic, and aliphatic nitriles to selectively form primary amines.

Antitumor and antimicrobial activity of some cyclic tetrapeptides and tripeptides derived from marine bacteria.

Marine derived cyclo(Gly-l-Ser-l-Pro-l-Glu) was selected as a lead to evaluate antitumor-antibiotic activity. Histidine was chosen to replace the serine residue to form cyclo(Gly-l-His-l-Pro-l-Glu). Cyclic tetrapeptides (CtetPs) were then synthesized using a solution phase method, and subjected to antitumor and antibiotic assays. The benzyl group protected CtetPs derivatives, showed better activity against antibiotic-resistant Staphylococcus aureus in the range of 60-120 µM. Benzyl group protected CtetPs 3 and 4, exhibited antitumor activity against several cell lines at a concentration of 80-108 µM. However, shortening the size of the ring to the cyclic tripeptide (CtriP) scaffold, cyclo(Gly-l-Ser-l-Pro), cyclo(Ser-l-Pro-l-Glu) and their analogues showed no antibiotic or antitumor activity. This phenomenon can be explained from their backbone structures.

Mass-independent oxygen isotopic partitioning during gas-phase SiO2 formation.

Meteorites contain a wide range of oxygen isotopic compositions that are interpreted as heterogeneity in solar nebula. The anomalous oxygen isotopic compositions of refractory mineral phases may reflect a chemical fractionation process in the nebula, but there are no experiments to demonstrate this isotope effect during particle formation through gas-phase reactions. We report experimental results of gas-to-particle conversion during oxidation of silicon monoxide that define a mass-independent line (slope one) in oxygen three-isotope space of (18)O/(16)O versus (17)O/(16)O. This mass-independent chemical reaction is a potentially initiating step in nebular meteorite formation, which would be capable of producing silicate reservoirs with anomalous oxygen isotopic compositions.

Primary bilateral small lymphocytic lymphoma of ocular adnexal origin: Imprint cytology suggests the intraoperative diagnosis.

Ocular adnexal lymphomas (OAL) involve the peri-global soft tissues like orbit, eyelid, conjunctiva, lacrimal gland. We describe a rare case of primary bilateral OAL, histomorphologically small lymphocytic lymphoma, B cell phenotype of lacrimal gland origin. Rapid intraoperative diagnosis can be suggested on imprint cytology; subsequent histology and immunohistochemistry are helpful for confirmation and further line of management. Since no preformed lymphoid structures are expected within the orbit or lacrimal gland, any lymphoid mass here should be critically evaluated as a lymphoproliferative lesion.

Secondary signet ring cell carcinoma of prostate.

True metastases to prostate from solid tumors are reported only in 0.2% of all surgical prostatic specimens and 2.9% of all male postmortems. Clinical context, morphological features, and immunohistochemical localization of prostate specific antigen (PSA) are supposed to clarify the differential diagnosis between a secondary and a primary tumor. We report an unusual and rare case of secondary signet ring cell carcinoma (SRCC) of prostate in which the clinical data and signet ring cell morphology pointed toward the diagnosis of a primary SRCC. Immunohistochemistry (IHC) for PSA not only proved the case to be a secondary SRCC but also initiated the process for diagnosis of the occult primary malignancy in the patient's stomach.

Juvenile xanthogranuloma-diagnostic challenge on fine-needle aspiration cytology.

Juvenile xanthogranuloma (JXG) is a rare cutaneous lesion with paucity of literature on its cytological features. We report one such case which on fine-needle aspiration cytology yielded a mixed population of foamy histiocytes, multinucleated giant cells and variable admixture of lymphocytes and eosinophils causing diagnostic dilemma with other differentials, especially Langerhans cell histiocytosis. However, clinical correlation followed by histopathology confirmed the diagnosis. Hence, JXG has characteristic and diagnostic cytologic features.

Ovarian tumors in pediatric age group - A clinicopathologic study of 10 years' cases in West Bengal, India.

BACKGROUND AND OBJECTIVES: Objective in this retrospective study is to find out the incidence of different ovarian tumors of girls up to 20 years of age observed in last ten years in North Bengal Medical College and to correlate clinical and gross findings with histopathologic findings and to compare the incidence with other studies and follow-up of patients with malignant ovarian tumors. MATERIALS AND METHODS: Findings were retrieved from records of different pathological reports and clinical reports. RESULTS: Total 151 cases of ovarian tumors were received in pathology department in which 34 cases were malignant (22.6%). Amongst malignant cases, 66% are of germ-cell origin-dysgerminoma being the commonest. Strikingly we got 9 cases of malignant surface epithelial tumor. As per follow-up records most of the dysgerminoma came in stage IA and recovered fully following chemotherapy and radiotherapy. Amongst other malignant tumors, few lost the follow-up management and others expired due to metastasis. CONCLUSIONS: Patients from hilly areas of North Bengal and low socio-economic status led to lower detection rate of ovarian tumors in early stage which are absolutely necessary for proper guidelines of management to reduce mortality.

Retroperitoneal tumours--a ten years retrospective study.

In a ten-year retrospective study (1985-95), 42 cases of retroperitoneal tumours were analysed. All cases were treated surgically. Among the relevant investigations CT scan and fine needle aspiration cytology were found to be most helpful to have a pre-operative idea regarding the best course of therapy. The highest incidence of retroperitoneal tumours were found in the 4th decade of life with roughly equal sex incidence. Malignant tumours were double in comparison to benign tumours and lymphoma was found to be the most common malignant tumour. Though complete resection should be the aim to treat them it may lead to sacrifice of other vital organs like kidney, spleen and part of large gut in advanced cases. Complication may be always for a heroic surgery leading to inadvertent injury to other structures, causing high mortality up to 19.1%.