A Note on the Impact of the Canada-India Diplomatic Standoff on the Performance of Canadian Mutual Funds Investments in India

On June 18, 2023, Mr. Hardeep Singh Nijjar, a Canadian citizen of Indian origin, was killed in Canada. On September 18, 2023, the Canadian Prime Minister, Mr. Justin Trudeau, accused the Indian Government of involvement in killing Mr. Nijjar in the Canadian Parliament. This accusation preceded and succeeded by other events, led to a significant diplomatic standoff that is still ongoing. We examine the impact of this event chain on the performance of daily returns of mutual funds based in Canada that are predominantly invested in Indian securities. Our results, controlled for general stock market returns, fund size, expense ratio, and interest rates, indicate that the events negatively impacted fund performance. Our study adds to the existing literature on the benefits of international diversification of mutual funds in disconnected markets. The findings of this paper suggest that political discord between two distinct and unrelated economies may impact profits and negate the advantages of international diversification. Our study is significant to professionals, particularly mutual fund managers, as it demonstrates the role of two countries’ political ties in affecting mutual fund returns

Fusion of B‐mode and shear wave elastography ultrasound features for automated detection of axillary lymph node metastasis in breast carcinoma

Abstract: In this study, we evaluate and compare the diagnostic performance of ultrasound for non‐invasive axillary lymph node (ALN) metastasis detection. The study was based on fusing shear wave elastography (SWE) and B‐mode ultrasonography (USG) images. These images were subjected to pre‐processing and feature extraction, based on bi‐dimensional empirical mode decomposition and higher order spectra methods. The resulting nonlinear features were ranked according to their p‐value, which was established with Student's t‐test. The ranked features were used to train and test six classification algorithms with 10‐fold cross‐validation. Initially, we considered B‐mode USG images in isolation. A probabilistic neural network (PNN) classifier was able to discriminate positive from negative cases with an accuracy of 74.77% using 15 features. Subsequently, only SWE images were used and as before, the PNN classifier delivered the best result with an accuracy of 87.85% based on 47 features. Finally, we combined SWE and B‐mode USG images. Again, the PNN classifier delivered the best result with an accuracy of 89.72% based on 71 features. These three tests indicate that SWE images contain more diagnostically relevant information when compared with B‐mode USG. Furthermore, there is scope in fusing SWE and B‐mode USG to improve non‐invasive ALN metastasis detection

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Acute Hepatitis E Infection Accounts for Some Cases of Suspected Drug-Induced Liver Injury

The diagnosis of drug-induced liver injury relies upon exclusion of other causes, including viral hepatitis A, B, and C. Hepatitis E virus (HEV) infection has been proposed as another cause of suspected drug-induced liver disease. We assessed the frequency of HEV infection among patients with drug-induced liver injury in the United States

Low-Spin Heme b3 in the Catalytic Center of Nitric Oxide Reductase from Pseudomonas nautica

Biochemistry, 2011, 50 (20), pp 4251–4262 DOI: 10.1021/bi101605pRespiratory nitric oxide reductase (NOR) was purified from membrane extract of Pseudomonas (Ps.) nautica cells to homogeneity as judged by polyacrylamide gel electrophoresis. The purified protein is a heterodimer with subunits of molecular masses of 54 and 18 kDa. The gene encoding both subunits was cloned and sequenced. The amino acid sequence shows strong homology with enzymes of the cNOR class. Iron/heme determinations show that one heme c is present in the small subunit (NORC) and that approximately two heme b and one non-heme iron are associated with the large subunit (NORB), in agreement with the available data for enzymes of the cNOR class. Mössbauer characterization of the as-purified, ascorbate-reduced, and dithionite-reduced enzyme confirms the presence of three heme groups (the catalytic heme b(3) and the electron transfer heme b and heme c) and one redox-active non-heme Fe (Fe(B)). Consistent with results obtained for other cNORs, heme c and heme b in Ps. nautica cNOR were found to be low-spin while Fe(B) was found to be high-spin. Unexpectedly, as opposed to the presumed high-spin state for heme b(3), the Mössbauer data demonstrate unambiguously that heme b(3) is, in fact, low-spin in both ferric and ferrous states, suggesting that heme b(3) is six-coordinated regardless of its oxidation state. EPR spectroscopic measurements of the as-purified enzyme show resonances at the g ∼ 6 and g ∼ 2-3 regions very similar to those reported previously for other cNORs. The signals at g = 3.60, 2.99, 2.26, and 1.43 are attributed to the two charge-transfer low-spin ferric heme c and heme b. Previously, resonances at the g ∼ 6 region were assigned to a small quantity of uncoupled high-spin Fe(III) heme b(3). This assignment is now questionable because heme b(3) is low-spin. On the basis of our spectroscopic data, we argue that the g = 6.34 signal is likely arising from a spin-spin coupled binuclear center comprising the low-spin Fe(III) heme b(3) and the high-spin Fe(B)(III). Activity assays performed under various reducing conditions indicate that heme b(3) has to be reduced for the enzyme to be active. But, from an energetic point of view, the formation of a ferrous heme-NO as an initial reaction intermediate for NO reduction is disfavored because heme [FeNO](7) is a stable product. We suspect that the presence of a sixth ligand in the Fe(II)-heme b(3) may weaken its affinity for NO and thus promotes, in the first catalytic step, binding of NO at the Fe(B)(II) site. The function of heme b(3) would then be to orient the Fe(B)-bound NO molecules for the formation of the N-N bond and to provide reducing equivalents for NO reduction

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Learning from Poverty: Why Business Schools Should Address Poverty, and How They Can Go About It.

In the past few years, business schools have begun to address poverty issues in their teaching, learning and curricula. While this is a positive development, the arguments for reconfiguring educational programs to address such matters remain undeveloped, with much of the impetus for such endeavors rooted in calls for social responsibility in the United Nations Millennium Development Goals, the Social Compact, the Principles for Responsible Management Education and benchmarks such as ISO 26000. This article seeks to clarify the pedagogical grounds for integrating poverty issues in management education by examining the intellectual and personal development benefits of doing so. By critically examining four modes of business involvement in poverty reduction, the article shows how such initiatives can be used as intellectual lenses through which to view the complex and often paradoxical interconnections between socioeconomic and environmental systems. It is thus concluded that a consideration of poverty issues is not a marginal matter, but is key to grasping the 21st century complexities of global business and management

Between Hope and Hype: Traditional Knowledge(s) Held by Marginal Communities

Traditional Knowledge (TK) systems have always been integral to the survival and adaptation of human societies. Yet, they enjoy a fairly recent recognition and popularization by scientists, the media, politicians, corporates and the wider public. In this paper we present a typology of key driving forces behind the popularization of TK held by marginal communities: an equality preference motive, a value motive, a compliance motive, a scarcity motive and a strategic motive. Secondly, through the use of a simple model, we discuss the hype's impact on marginal communities. Moreover, we critically assess the outcome of a number of policy instruments that intend, in part, to protect traditional knowledge bases of such communities. Our analysis primarily draws upon secondary literature; policy documents and case studies within economics, the social sciences, conservation biology and legal studies. We argue that whilst the public and institutional hype around TK may have resulted in its prioritization within international conventions and frameworks, its institutionalization may have adversely impacted marginalized communities, and in particular contexts, unintentionally led to the creation of 'new' marginals. We purport that the traditional innovation incentive motive does not hold for protecting TK within a private property regime. Instead we identify a conservation incentive motive and a distribution motive that justify deriving policy instruments that focus on TK to protect marginal communities