Thiacalix[4]arene-Protected Silver Nanoclusters Encapsulating Different Two-Electron Superatom Oligomers.

The subvalent silver kernel represents the nascent state of silver cluster formation, yet the growth mechanism has long been elusive. Herein, two silver nanoclusters (Ag30 and Ag34) coprotected by TC4A4- (H4TC4A = p-tert-butylthiacalix[4]arene) and TBPMT- (TBPMTH = 4-tert-butylbenzenemethanethiol) containing 6e and 4e silver kernels are synthesized and characterized. The trimer of the 2e superatom Ag14 kernel in Ag30 is built from a central Ag6 octahedron sandwiched by two orthogonally oriented Ag5 trigonal bipyramids through sharing vertexes, whereas a double-octahedral Ag10 kernel in Ag34 is a dimer of 2e superatoms. They manifest disparate polyhedron fusion growth patterns at the beginning of the silver cluster formation. Their excellent solution stabilities are contributed by the multisite and multidentate coordination fashion of TC4A4- and the special valence electron structures. This work demonstrates the precise control of silver kernel growth by the solvent strategy and lays a foundation for silver nanocluster application in photothermal conversion.

Influence of planting dates and fertilizer modules on yield of chrysanthemum and soil health.

BACKGROUND: Optimum planting date and appropriate fertilizer module are essential facets of chrysanthemum cultivation, to enhance quality yield, and improve soil health. A field-based study was undertaken over multiple growing seasons in 2022 and 2023, where six different planting dates, viz., P1:June 15, P2:June 30, P3:July 15, P4:July 30, P5:August 15 and P6:August 30 and two fertilizer modules, FM1:Jeevamrit @ 30 ml plant-1 and FM2:NPK @ 30 g m-2 were systematically examined using a Randomized Block Design (factorial), replicated thrice. RESULTS: P6 planting resulted in early bud formation (44.03 days) and harvesting stage (90.78 days). Maximum plant height (79.44 cm), plant spread (34.04 cm), cut stem length (68.40 cm), flower diameter (7.83 cm), stem strength (19.38˚), vase life (14.90 days), flowering duration (24.08 days), available soil N (314 kg ha-1), available P (37 kg ha-1), available K (347 kg ha-1), bacterial count (124.87 × 107 cfu g-1 soil), actinomycetes count (60.72 × 102 cfu g-1 soil), fungal count (30.95 × 102 cfu g-1 soil), microbial biomass (48.79 µg g-1 soil), dehydrogenase enzyme (3.64 mg TPF h-1 g-1 soil) and phosphatase enzyme (23.79 mol PNP h-1 g-1 soil) was recorded in P1 planting. Among the fertilization module, minimum days to bud formation (74.94 days) and days to reach the harvesting stage (120.95 days) were recorded with the application of NPK @30 g m-2. However, maximum plant height (60.62 cm), plant spread (23.10 cm), number of cut stems m-2 (43.88), cut stem length (51.34 cm), flower diameter (6.92 cm), stem strength (21.24˚), flowering duration (21.75 days), available soil N (317 kg ha-1), available P (37 kg ha-1) and available K (349 kg ha-1) were also recorded with the application of NPK @300 kg ha-1. Maximum vase life (13.87 days), OC (1.13%), bacterial count (131.65 × 107 cfu g-1 soil), actinomycetes count (60.89 × 102 cfu g-1 soil), fungal count (31.11 × 102 cfu g-1 soil), microbial biomass (51.27 µg g-1 soil), dehydrogenase enzyme (3.77 mg TPF h-1 g-1 soil) and phosphatase enzyme (21.72 mol PNP h-1 g-1 soil) were observed with the application of Jeevamrit @ 30 ml plant-1. CONCLUSION: Early planting (P1) and inorganic fertilization (NPK @ 30 g m-2) resulted in improved yield and soil macronutrient content. The soil microbial population and enzymatic activity were improved with the jeevamrit application. This approach highlights the potential for improved yield and soil health in chrysanthemum cultivation, promoting a more eco-friendly and economically viable agricultural model.

Automatic removal of large blood vasculature for objective assessment of brain tumors using quantitative dynamic contrast-enhanced magnetic resonance imaging.

The presence of a normal large blood vessel (LBV) in a tumor region can impact the evaluation of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and tumor classification. Hence, there is a need for automatic removal of LBVs from brain tissues including intratumoral regions for achieving an objective assessment of tumors. This retrospective study included 103 histopathologically confirmed brain tumor patients who underwent MRI, including DCE-MRI data acquisition. Quantitative DCE-MRI analysis was performed for computing various parameters such as wash-out slope (Slope-2), relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), blood plasma volume fraction (Vp), and volume transfer constant (Ktrans). An approach based on data-clustering algorithm, morphological operations, and quantitative DCE-MRI maps was proposed for the segmentation of normal LBVs in brain tissues, including the tumor region. Here, three widely used data-clustering algorithms were evaluated on two types of quantitative maps: (a) Slope-2, and (b) a new proposed combination of rCBV and Slope-2 maps. Fluid-attenuated inversion recovery-MRI hyperintense lesions were also automatically segmented using deep learning-based architecture. The accuracy of LBV segmentation was qualitatively assessed blindly by two experienced observers, and Likert scoring was also obtained from each individual and compared using Cohen's Kappa test, and multiple statistical features from quantitative DCE-MRI parameters were obtained in the segmented tumor. t-test and receiver operating characteristic (ROC) curve analysis were performed for comparing the effect of removal of LBVs on parameters as well as on tumor grading. k-means clustering exhibited better accuracy and computational efficiency. Tumors, in particular high-grade gliomas (HGGs), showed a high contrast compared with normal tissues (relative % difference = 18.5%) on quantitative maps after the removal of LBVs. Statistical features (95th percentile values) of all parameters in the tumor region showed a statistically significant difference (p < 0.05) between with and without LBV maps. Similar results were obtained for the ROC curve analysis for differentiation between low-grade gliomas and HGGs. Moreover, after the removal of LBVs, the rCBV, rCBF, and Vp maps show better visualization of tumor regions.

Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values.

Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnormalities, and it provides baseline tissue characterization. Post-contrast T1 mapping enhances tissue differentiation, enables extracellular volume (ECV) calculation, and improves myocardial viability assessment. Accurate and precise segmenting of the left ventricular (LV) myocardium on T1 maps is crucial for assessing myocardial tissue characteristics and diagnosing cardiovascular diseases (CVD). This study presents a deep learning (DL)-based pipeline for automatically segmenting LV myocardium on T1 maps and automatic computation of radial T1 and ECV values. The study employs a multicentric dataset consisting of retrospective multiparametric MRI data of 332 subjects to develop and assess the performance of the proposed method. The study compared DL architectures U-Net and Deep Res U-Net for LV myocardium segmentation, which achieved a dice similarity coefficient of 0.84 ± 0.43 and 0.85 ± 0.03, respectively. The dice similarity coefficients computed for radial sub-segmentation of the LV myocardium on basal, mid-cavity, and apical slices were 0.77 ± 0.21, 0.81 ± 0.17, and 0.61 ± 0.14, respectively. The t-test performed between ground truth vs. predicted values of native T1, post-contrast T1, and ECV showed no statistically significant difference (p > 0.05) for any of the radial sub-segments. The proposed DL method leverages the use of quantitative T1 maps for automatic LV myocardium segmentation and accurately computing radial T1 and ECV values, highlighting its potential for assisting radiologists in objective cardiac assessment and, hence, in CVD diagnostics.

Global treatment of haemorrhoids-A worldwide snapshot audit conducted by the International Society of University Colon and Rectal Surgeons.

AIM: There is no universally accepted treatment consensus for haemorrhoids, and thus, management has been individualized all over the world. This study was conducted to assess a global view of how surgeons manage haemorrhoids. METHODS: The research panel of the International Society of University Colon and Rectal Surgeons (ISUCRS) developed a voluntary, anonymous questionnaire evaluating surgeons' experience, volume and treatment approaches to haemorrhoids. The 44 multiple-choice questionnaire was available for one month via the ISUCRS email database and the social media platforms Viber and WhatsApp. RESULTS: The survey was completed by 1005 surgeons from 103 countries; 931 (92.6%) were in active practice, 819 (81.5%) were between 30 and 60 years of age, and 822 (81.8%) were male. Detailed patient history (92.9%), perineal inspection (91.2%), and digital rectal examination (91.1%) were the most common assessment methods. For internal haemorrhoids, 924 (91.9%) of participants graded them I-IV, with the degree of haemorrhoids being the most important factor considered to determine the treatment approach (76.3%). The most common nonprocedural/conservative treatment consisted of increased daily fibre intake (86.9%), increased water intake (82.7%), and normalization of bowel habits/toilet training (74.4%). Conservative treatment was the first-line treatment for symptomatic first (92.5%), second (72.4%) and third (47.3%) degree haemorrhoids; however, surgery was the first-line treatment for symptomatic fourth degree haemorrhoids (77.6%). Rubber band ligation was the second-line treatment in first (50.7%) and second (47.2%) degree haemorrhoids, whereas surgery was the second-line treatment in third (82.9%) and fourth (16.7%) degree symptomatic haemorrhoids. Rubber band ligation was performed in the office by 645(64.2%) of the participants. The most common surgical procedure performed for haemorrhoids was an excisional haemorrhoidectomy for both internal (87.1%) and external (89.7%) haemorrhoids - with 716 (71.2%) of participants removing 1, 2 or 3 sectors as necessary. CONCLUSION: Although there is no global haemorrhoidal treatment consensus, there are many practice similarities among the different cultures, resources, volume and experience of surgeons around the world. With additional studies, a consensus statement could potentially be developed.

Spinal astroblastoma, MN1 altered in 3-year-old child: An uncommon tumor at an unusual site.

Astroblastoma is an uncommon circumscribed glial tumor mostly involving the cerebral hemisphere. The characteristic molecular alteration is meningioma (disrupted in balanced translocation) 1 (MN1) rearrangement. No definite World Health Organization grade has been assigned as both low- and high-grade tumors are known to occur. Tumors in the spine are extremely rare; to date only three cases have been reported in the literature. A vigilant microscopy and ancillary testing aid in diagnosis when the tumors present in unusual locations, as in our case. The prompt differentiation of this tumor from its mimickers is a mandate as modalities of management are different and not clearly established.

Comparative assessment of microbiome and resistome of influent and effluent of sewage treatment plant and common effluent treatment plant located in Delhi, India using shotgun approach.

Antimicrobial resistance (AMR) is a significant threat that demands surveillance to identify and analyze trends of the emerging antibiotic resistance genes (ARGs) and potential microbial carriers. The influent of the wastewater treatment plants (WWTPs) reflects the microbes derived from the population and effluent being the source of dissemination of potential pathogenic microbes and AMR. The present study aimed to monitor microbial communities and antibiotic resistance genes in WWTPs employing a whole metagenome shotgun sequencing approach. The samples were collected from a sewage treatment plant (STP) and a common effluent treatment plant (CETP) in Delhi, India. The results showed the influent of STP to be rich in Bifidobacterium, Bacteroides, Escherichia, Arcobacter, and Pseudomonas residents of gut microbiota and known to cause diseases in humans and animals; whereas the CETP sample was abundant in Aeromonas, Escherichia, and Shewanella known to be involved in the degradation of different compounds. Interestingly, the effluent samples from both STPs and CETP were rich in microbial diversity, comprising organic and xenobiotic compound degrading and disease-causing bacteria, indicating the effluent being the source of dissemination of concerning bacteria to the environment. The functional profile at both sites displayed similarity with an abundance of housekeeping function genes as analyzed by Clusters of Orthologous Genes (COG), KEGG Orthology (KO), and subsystem databases. Resistome profiling by MEGARes showed the dominance of ARGs corresponding to beta-lactams having relative abundance ranging from 16% to 34% in all the metagenome datasets, followed by tetracycline (8%-16%), aminoglycosides (7%-9%), multi-drug (5%-9%), and rifampin (3%-9%). Also, AMR genes oxa, ant3-DPRIME, and rpoB, which are of clinical importance were predominantly and most prevalently present in all the samples. The presence of AMR in effluents from both types of treatment plants indicates that wastewater from both sources contributes to the spread of pathogenic bacteria and resistance genes, increasing the environmental AMR burden and therefore requires tertiary treatment before discharge. This work will facilitate further research towards the identification of suitable biomarkers for monitoring antibiotic resistance.

Microhabitat influences on phage-bacteria dynamics in an abandoned mine for ecorestoration.

Understanding the complex interactions between bacteriophages (phages) and bacteria within varied environmental niches is critical yet underexplored for improving microbe-assisted ecological restoration. This study investigates the influence of microhabitat heterogeneity within an abandoned mine on phage-bacteria interaction patterns, focusing on Pseudomonas-enriched bacterial communities. By isolating viral communities and purifying bacteria from soils of three distinct microhabitats, we assessed the regulatory role of environmental factors on these interactions, crucial for bacterial success in environmental applications. We characterized microhabitat variability by analyzing soil particle size fractions, minerals composition, and elemental content using X-ray diffraction and energy-dispersive X-ray analyses. 16S rRNA sequencing and cross-infection assays revealed that although bacterial communities across different microhabitats are taxonomically similar, their interaction patterns with phages are distinct. Phage communities showed nonselective infectivity across soil types, while bacterial communities exhibited selective adaptation, facilitating colonization across diverse microhabitats. Minerals such as mica, kaolinite, and hematite were found to increase phage infectivity, whereas mixed-layer clay correlated with early lysis. Additionally, higher levels of iron (Fe) and potassium (K) were linked to bacterial resistance strategies. Our findings highlight the importance of understanding asymmetric adaptive strategies between bacteria and phages, driven by microhabitat heterogeneity, for enhancing microbial-mediated nature-based restoration of degraded ecosystems.

Dicarboxylic Acids Induced Tandem Transformation of Silver Nanocluster.

Structural transformation of metal nanoclusters (NCs) is of great ongoing interest regarding their synthesis, stability, and reactivity. Although sporadic examples of cluster transformations have been reported, neither the underlying transformation mechanism nor the intermediates are unambiguous. Herein, we have synthesized a flexible 54-nuclei silver cluster (Ag54) by combining soft (tBuC≡C-) and hard (nPrCOO-) ligands. The existence of weakly coordinated nPrCOO- enhances the reactivity of Ag54, thus facilitating the dicarboxylic acid to induce structural transformation. X-ray structural analyses reveal that Ag54 transforms to Ag28 cluster-based 2D networks (Ag28a and Ag28b) induced by H2suc (succinic acid) and H2glu (glutaric acid), whereas with H2pda (2,2'-(1,2-phenylene)diacetic acid), a discrete Ag28 cluster (Ag28c) is isolated. The key intermediate Ag17 that emerges during the self-dissociation of Ag54 was isolated by using cryogenic recrystallization and characterized by X-ray crystallography. The "tandem transformation" mechanism for the structure evolution from Ag54 to Ag28a is established by time-dependent electrospray ionization mass spectrometry (ESI-MS) and UV-vis spectroscopy. In addition, the catalytic activity in the 4-nitrophenol reduction follows the sequence Ag28c > Ag28b > Ag28a > Ag54 due to more bare silver sites on the surface of the Ag28 cluster unit. Our findings not only open new avenues to the synthesis of silver NCs but also shed light on a better understanding of the structural transformation mechanism from one cluster to another or cluster-based metal-organic networks induced by dicarboxylates.

Pangenome-driven insights into nitrogen metabolic characteristics of Citrobacter portucalensis strain AAK_AS5 associated with wastewater nitrogen removal.

Nitrogen metabolism in the genus Citrobacter is very poorly studied despite its several implications in wastewater treatment. In the current study, Citrobacter portucalensis strain AAK_AS5 was assessed for remediation of simulated wastewater supplemented with different inorganic nitrogen sources. Combination of (NH4)2SO4 with KNO3 was the most preferred for achieving high growth density followed by (NH4)2SO4 and KNO3 alone. This was in agreement with highest ammonical nitrogen removal of 92.9% in the presence of combined nitrogen sources and the corresponding nitrate nitrogen removal of 93% in the presence of KNO3. Furthermore, these removal capacities were validated by investigating the uniqueness and the spread of metabolic features through pan-genomic approach that revealed the largest number of unique genes (2097) and accessory genes (705) in strain AAK_AS5. Of the total 44 different types of nitrogen metabolism-related genes, 39 genes were associated with the core genome, while 5 genes such as gltI, nasA, nasR, nrtA, and ntrC uniquely belonged to the accessory genome. Strain AAK_AS5 possessed three major nitrate removal pathways viz., assimilatory and dissimilatory nitrate reduction to ammonia (ANRA & DNRA), and denitrification; however, the absence of nitrification was compensated by ammonia assimilation catalyzed by gene products of the GDH and GS-GOGAT pathways. narGHIJ encoding the respiratory nitrate reductase was commonly identified in all the studied genomes, while genes such as nirK, norB, and nosZ were uniquely present in the strain AAK_AS5 only. A markedly different genetic content and metabolic diversity between the strains reflected their adaptive evolution in the environment thus highlighting the significance of C. portucalensis AAK_AS5 for potential application in nitrogen removal from wastewater.

In Silico Genomic Characterization of Bacillus velezensis Strain AAK_S6 for Secondary Metabolite and Biocontrol Potential.

This study reports the draft genome sequence of Bacillus velezensis strain AAK_S6 as a valuable biocontrol agent with high genetic potential to harbor broad-spectrum secondary metabolite producing capacity. A genome data of 4,430,946 bp were generated with a GC content of 46.4% that comprised a total of 4861 genes including a total of 4757 coding sequences (CDS), 104 rRNAs, 85 tRNAs and 80 pseudo-genes. Based on the overall genome-based relatedness indices (OGRI), the strain AAK_S6 has been reassigned to its correct taxonomic position. The strain shared > 99% OrthoANI, > 98% ANIb, > 99% ANIm, > 0.9900 TETRA, > 93% dDDH and 0.08% GC content difference with model strains B. velezensis FZB42T and B. velezensis NRRL B-41580T thus delineating them as closely related species. The genome was mined for strain-specific secondary metabolites that revealed 20 gene clusters for the biosynthesis of several cyclic lipopeptides, saccharides, polyketides along with bacilysin. Thus, the comparative genome analysis of strain AAK_S6 with members of the genus Bacillus by phylogenomic approach revealed that the genomes were almost similar genetically and contained the core genome for B. velezensis. Genomic data strongly supported that the strain AAK_S6 represented an excellent potential candidate for the production of secondary metabolites that could serve as a basis for developing new biocontrol agents, plant growth promoters, and microbial fertilizers.

Direct Detection of Fluoroquinolone Resistance in Sputum Samples from Tuberculosis Patients by High Resolution Melt Curve Analysis.

Multidrug-resistant tuberculosis (MDR-TB) requires treatment with fluoroquinolone (FLQ) drugs, however, the excessive use of FLQ has led to the rise of extensively drug-resistant TB. In 2019, ~ 20% of total MDR-TB cases were estimated to be resistant to FLQ drugs. In the present study, we developed and evaluated the utility of high-resolution melt curve analysis (HRM) for the rapid detection of FLQ-resistant Mycobacterium tuberculosis for the first time directly from sputum samples. A reference plasmid library was generated for the most frequently observed mutations of gyrA gene and was used to discriminate between mutant and wild-type samples in the FLQ-HRM assay. The developed assay was evaluated on n = 25 MDR M. tuberculosis clinical isolates followed by validation on archived sputum DNA (n = 88) using DNA sequencing as a gold standard. The FLQ-HRM assay showed a 100% sensitivity [95% Confidence Interval (CI): 71.5 to 100] and specificity (95% CI: 39.7 to 100) in smear-positive category, and a sensitivity of 88.9% (95% CI: 77.3 to 95.8) with 84.2% (95% CI: 60.4 to 96.6) specificity in smear-negative category. The assay showed a high level of concordance of ~ 90% (κ = 0.74) with DNA sequencing, however, we were limited by the absence of phenotypic drug susceptibility testing data. In conclusion, HRM is a rapid, cost-effective (INR 150/USD 1.83) and closed-tube method for direct detection of FLQ resistance in sputum samples including direct smear-negative samples.

Naringenin improves ovarian health by reducing the serum androgen and eliminating follicular cysts in letrozole-induced polycystic ovary syndrome in the Sprague Dawley rats.

Polycystic ovary syndrome (PCOS) is most common in women of reproductive age, giving rise to androgen excess and anovulation, leading to infertility and non-reproductive complications. We explored the ameliorating effect of naringenin in PCOS using the Sprague Dawley (SD) rat model and human granulosa cells. Letrozole-induced PCOS rats were given either naringenin (50 mg/kg/day) alone or in combination with metformin (300 mg/kg/day), followed by the estrous cycle, hormonal analysis, and glucose sensitivity test. To evaluate the effect of naringenin on granulosa cell (hGC) steroidogenesis, we treated cells with naringenin (2.5 µM) alone or in combination with metformin (1 mM) in the presence of forskolin (10 µM). To determine the steroidogenesis of CYP-17A1, -19A1, and 3ßHSD2, the protein expression levels were examined. Treatment with naringenin in the PCOS animal groups increased ovulation potential and decreased cystic follicles and levels of androgens. The expression levels of CYP-17A1, -19A1, and 3ßHSD2, were seen restored in the ovary of PCOS SD rats' model and in the human ovarian cells in response to the naringenin. We found an increased expression level of phosphorylated-AKT in the ovary and hGCs by naringenin. Naringenin improves ovulation and suppress androgens and cystic follicles, involving AKT activation.

Role of intra-operative squash cytology in rosette-forming glioneuronal tumor of the fourth ventricle: a case report.

Rosette-forming glioneuronal tumor (RGNT) of the 4th ventricle is a newly described WHO grade I brain tumor included in recent WHO classification of CNS tumors. It is a biphasic tumor thought to originate from pluripotent progenitor cells of subependymal plate. Intra-operative diagnosis plays an important role, as complete surgical excision is the treatment of choice. We are reporting a case of RGNT in a 19 years-old young male emphasizing the intra-operative pathological pointers and their role in accurate diagnosis for the suitable surgical intervention.

Competency-based medical curriculum: Exploring the preclinical medical teachers' pedagogical and technical readiness levels.

Background The medical curriculum for undergraduates was revised by the Medical Council of India in 2019, after 21 years. We did this study to determine teachers' pedagogical and technical readiness to implement the competency-based curriculum in medical colleges and determine factors that affect readiness, from their perspective. Methods We conducted a cross-sectional survey in the form of an online questionnaire. The qualitative data were coded numerically and were analysed using frequencies and proportions. Pearson Chi-square test was used to study the association among variables. Results The majority (85%) of respondents had attended a curriculum implementation training programme; 62.2% with experience <5 years, 56.1% with experience 5-10 years and a minority of 13.3% with >10 years' experience were ready to a 'great extent' to implement the new curriculum; 54.1% agreed to re-frame lectures and 64.9% possessed technological skills to suit the needs of a competency-based curriculum. About 77% agreed that it will provide a rich learning environment, inspire self-directed learning while 52% believed it will promote scientific thinking and provide better learning outcomes in the long run. Conclusion Medical teachers had a positive attitude towards implementation of the new curriculum. However, numerous factors such as low teacher-student ratio, textbooks designed according to the traditional curriculum, limited teachers' training and cumbersome paperwork may hinder its successful implementation. Updation of teachers' knowledge and skills through seminars/workshops is recommended to facilitate delivery of the new curriculum. Like any other ongoing reforms in medical education, competency-based curriculum is a work in process.

Edible insects as emerging food products-processing and product development perspective.

Edible insects (EI) are also becoming as a part of the diet due to their nutritional value and health benefits in many regions of the world. These EI are inexhaustible sources accessible by garnering from the wild with high feed conversion efficiency. Appreciating the budding of EI in justifiable food production, enlightening food security and biodiversity conversion, is promising a sufficient supply of the insect resource for future food to the world. These insects are processed to develop new products, improve organoleptic and nutritional parameters as well as the extension of shelf life. In this review, we discuss the edible insect characteristics, the potential application of EI in food industry, processing, pretreatments, drying, extraction of edible compounds like protein, lipid and chitin various food products formulation, safety regulation. Availability of broad nutritional spectrum of EI includes protein, mono and poly unsaturaturated fatty acids, amino acids, vitamins, amino aids and minerals has been used as an ingredient in development of various forms of food products such as flours in the form of whole insect powder, protein isolate, canned products, extruded products, hard candies, spreads, liquor infusion, cookies and other products.

Characterization of breast tumors using machine learning based upon multiparametric magnetic resonance imaging features.

Magnetic resonance imaging (MRI) is playing an important role in the classification of breast tumors. MRI can be used to obtain multiparametric (mp) information, such as structural, hemodynamic, and physiological information. Quantitative analysis of mp-MRI data has shown potential in improving the accuracy of breast tumor classification. In general, a large set of quantitative and texture features can be generated depending upon the type of methodology used. A suitable combination of selected quantitative and texture features can further improve the accuracy of tumor classification. Machine learning (ML) classifiers based upon features derived from MRI data have shown potential in tumor classification. There is a need for further research studies on selecting an appropriate combination of features and evaluating the performance of different ML classifiers for accurate classification of breast tumors. The objective of the current study was to develop and optimize an ML framework based upon mp-MRI features for the characterization of breast tumors (malignant vs. benign and low- vs. high-grade). This study included the breast mp-MRI data of 60 female patients with histopathology results. A total of 128 features were extracted from the mp-MRI tumor data followed by features selection. Five ML classifiers were evaluated for tumor classification using 10-fold crossvalidation with 10 repetitions. The support vector machine (SVM) classifier based on optimum features selected using a wrapper method with an adaptive boosting (AdaBoost) technique provided the highest sensitivity (0.96 ± 0.03), specificity (0.92 ± 0.09), and accuracy (94% ± 2.91%) in the classification of malignant versus benign tumors. This method also provided the highest sensitivity (0.94 ± 0.07), specificity (0.80 ± 0.05), and accuracy (90% ± 5.48%) in the classification of low- versus high-grade tumors. These findings suggest that the SVM classifier outperformed other ML methods in the binary classification of breast tumors.

Clinico-pathological characteristics of obstructing colorectal cancer and its management outcomes at a tertiary referral center of Eastern Nepal.

BACKGROUND: The aim of this study is to explore the treatment strategies being followed for patients with obstructing colorectal cancer (OCRC) at our institute and to know the management outcomes. METHODS: This study included 28 patients who were diagnosed with obstructing colorectal cancer (OCRC) either preoperatively or intraoperatively over a period of 5 years. RESULTS: Most were in the younger age group with mean age of 49.78 ± 15.96 years with 1/4th of the patients being younger than 40. There was no difference in incidence of OCRC among genders. It was found to be common in rural areas of the eastern Nepal, 16(57%) patients from such areas. 21.4% patients had complete bowel obstruction at presentation. The investigating modalities used were abdominal X-ray, ultrasonoghraphy of abdomen/pelvis, abdominal CT-scan, colonoscopy, serum CEA, punch biopsy and Faecal occult blood test. The anatomical shift to the right was observed with 54% lesions in the proximal colon. Majority were in advanced stage (stage 3:53.6%, stage 4:32.1%) with histologically adenocarcinoma (100%) and a higher incidence of synchronous lesion (28.6%). Patients averaged 13.82 days in the hospital with post-operative mortality rate of 3.6%. The 1-year and 2-years disease free survivals were 89.3% and 82.1% while overall survivals were 92.8% and 82.1% respectively. CONCLUSION: In developing countries like ours, relatively younger patients present to health center with obstructive colorectal cancer with anatomical shift to the right sided lesions. The treatments provided at our center and their outcomes are not inferior to that of the developed world.

Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation.

PURPOSE: Primary objective of this study was to retrospectively evaluate the potential of a range of qualitative and quantitative multiparametric features assessed on T2, post-contrast T1, DWI, DCE-MRI, and susceptibility-weighted-imaging (SWI) in differentiating evenly sampled cohort of primary-central-nervous-system-lymphoma (PCNSL) vs glioblastoma (GB) with pathological validation. METHODS: The study included MRI-data of histopathologically confirmed ninety-five GB and PCNSL patients scanned at 3.0 T MRI. A total of six qualitative features (three from T2 and post-contrast T1, three from SWI: thin-linear-uninterrupted-intra-tumoral-vasculature, broken-intra-tumoral-microvasculature, hemorrhage) were analyzed by three independent radiologists. Ten quantitative features from DWI and DCE-MRI were computed using in-house-developed algorithms. For qualitative features, Cohen's Kappa-interrater-variability-analysis was performed. Z-test and independent t-tests were performed to find significant qualitative and quantitative features respectively. Logistic-regression (LR) classifiers were implemented for evaluating performance of individual and various combinations of features in differentiating PCNSL vs GB. Performance evaluation was done via ROC-analysis. Pathological validation was performed to verify disintegration of vessel walls in GB and rim of viable neoplastic lymphoid cells with angiocentric-pattern in PCNSL. RESULTS: Three qualitative SWI features and four quantitative DCE-MRI features (rCBVcorr, Kep, Ve, and necrosis-volume-percentage) were significantly different (p < 0.05) between PCNSL and GB. Best diagnostic performance was observed with LR classifier using SWI features (AUC-0.99). The inclusion of quantitative features with SWI feature did not improve the differentiation accuracy. CONCLUSIONS: The combination of three qualitative SWI features using LR provided the highest accuracy in differentiating PCNSL and GB. Thin-linear-uninterrupted-intra-tumoral-vasculature in PCNSL and broken-intra-tumoral-microvasculature with hemorrhage in GB are the major contributors to the differentiation.

Mining the landfill soil metagenome for denitrifying methanotrophic taxa and validation of methane oxidation in microcosm.

In the present study, the microbial community residing at different depths of the landfill was characterized to assess their roles in serving as a methane sink. Physico-chemical characterization revealed the characteristic signatures of anaerobic degradation of organic matter in the bottom soil (50-60 cm) and, active process of aerobic denitrification in the top soil (0-10 cm). This was also reflected from the higher abundance of bacterial domain in the top soil metagenome represented by dominant phyla Proteobacteria and Actinobacteria which are prime decomposers of organic matter in landfill soils. The multiple fold higher relative abundances of the two most abundant genera; Streptomyces and Intrasporangium in the top soil depicted greater denitrifying taxa in top soil than the bottom soil. Amongst the aerobic methanotrophs, the genera Methylomonas, Methylococcus, Methylocella, and Methylacidiphilum were abundantly found in the top soil metagenome that were essential for oxidizing methane generated in the landfill. On the other hand, the dominance of archaeal domain represented by Methanosarcina and Methanoculleus in the bottom soil highlighted the complete anaerobic digestion of organic components via acetoclasty, carboxydotrophy, hydrogenotrophy, methylotrophy. Functional characterization revealed a higher abundance of methane monooxygenase gene in the top soil and methyl coenzyme M reductase gene in the bottom soil that correlated with the higher relative abundance of aerobic methanotrophs in the top soil while methane generation being the active process in the highly anaerobic bottom soil in the landfill. The activity dependent abundance of endogenous microbial communities in the different zones of the landfill was further validated by microcosm studies in serum bottles which established the ability of the methanotrophic community for methane metabolism in the top soil and their potential to serve as sink for methane. The study provides a better understanding about the methanotrophs in correlation with their endogenous environment, so that these bacteria can be used in resolving the environmental issues related to methane and nitrogen management at landfill site.