On the Synthesis of new four-layered Aurivillius compound Bi2MNa2Nb4O15 (M= Ca, Sr, Ba)

The aim of the project was to synthesize Bi2MNa2Nb4O15 (M= Ca, Sr, Ba) by the Oxalate route. The detailed analysis of the DSC-TG plot depicted that the working range of calcination must be within 1000°C. However due to presence of competing secondary phases like BiNbO4, the synthesis of pure phase material was not possible. The detailed analysis that favored this fact was supported by powder X-ray diffraction (XRD). The precursor powder obtained was calcined at 800°C, 900°C, 1000°C, 1050°C and 1100°C, respectively. And the XRD analysis showed that as long as there was BiNbO4 in the system there were very negligible chances of preparation of the desired phase

Spinal Cord Compression Secondary to Metastatic Sinonasal Undifferentiated Carcinoma

Sinonasal undifferentiated carcinoma (SNUC) is a rare malignancy of the upper airways and anterior skull base that carries a poor prognosis. The tumor is known to be invasive into the surrounding structures of the skull base and brain. To date, there is only one existing case report documenting drop metastasis to the intradural extramedullary spinal cord. To the best of our knowledge, we present the second case of metastatic SNUC to the spine. This report describes a 59-year-old male with a history of head and neck SNUC who presented with thoracic back pain and bilateral lower extremity paresis. Neuroimaging demonstrated an extradural thoracic mass with severe spinal cord compression. The patient underwent thoracic laminectomy and fusion for decompression of the spinal cord and internal stabilization. The pathology returned as SNUC. The patient was subsequently lost to follow-up from our institution. Metastatic SNUC is rare. We discuss the relevant clinical imaging and review the literature. Such a malignancy portends a very poor prognosis

The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has parallelly emerged as a by-product, posing significant concerns. While some recent endeavors have been made to identify and mitigate different types of hallucination, there has been a limited emphasis on the nuanced categorization of hallucination and associated mitigation methods. To address this gap, we offer a fine-grained discourse on profiling hallucination based on its degree, orientation, and category, along with offering strategies for alleviation. As such, we define two overarching orientations of hallucination: (i) factual mirage (FM) and (ii) silver lining (SL). To provide a more comprehensive understanding, both orientations are further sub-categorized into intrinsic and extrinsic, with three degrees of severity - (i) mild, (ii) moderate, and (iii) alarming. We also meticulously categorize hallucination into six types: (i) acronym ambiguity, (ii) numeric nuisance, (iii) generated golem, (iv) virtual voice, (v) geographic erratum, and (vi) time wrap. Furthermore, we curate HallucInation eLiciTation (HILT), a publicly available dataset comprising of 75,000 samples generated using 15 contemporary LLMs along with human annotations for the aforementioned categories. Finally, to establish a method for quantifying and to offer a comparative spectrum that allows us to evaluate and rank LLMs based on their vulnerability to producing hallucinations, we propose Hallucination Vulnerability Index (HVI). We firmly believe that HVI holds significant value as a tool for the wider NLP community, with the potential to serve as a rubric in AI-related policy-making. In conclusion, we propose two solution strategies for mitigating hallucinations

The oral microbiota in colorectal cancer is distinctive and predictive

Background and aims: Microbiota alterations are linked with colorectal cancer (CRC) and notably higher abundance of putative oral bacteria on colonic tumours. However, it is not known if colonic mucosa-associated taxa are indeed orally derived, if such cases are a distinct subset of patients or if the oral microbiome is generally suitable for screening for CRC. Methods: We profiled the microbiota in oral swabs, colonic mucosae and stool from individuals with CRC (99 subjects), colorectal polyps (32) or controls (103). Results: Several oral taxa were differentially abundant in CRC compared with controls, for example, Streptococcus and Prevotellas pp. A classification model of oral swab microbiota distinguished individuals with CRC or polyps from controls (sensitivity: 53% (CRC)/67% (polyps); specificity: 96%). Combining the data from faecal microbiota and oral swab microbiota increased the sensitivity of this model to 76% (CRC)/88% (polyps). We detected similar bacterial networks in colonic microbiota and oral microbiota datasets comprising putative oral biofilm forming bacteria. While these taxa were more abundant in CRC, core networks between pathogenic, CRC-associated oral bacteria such as Peptostreptococcus, Parvimonas and Fusobacterium were also detected in healthy controls. High abundance of Lachnospiraceae was negatively associated with the colonisation of colonic tissue with oral-like bacterial networks suggesting a protective role for certain microbiota types against CRC, possibly by conferring colonisation resistance to CRC-associated oral taxa and possibly mediated through habitual diet. Conclusion: The heterogeneity of CRC may relate to microbiota types that either predispose or provide resistance to the disease, and profiling the oral microbiome may offer an alternative screen for detecting CRC

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors1,2, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Stage-Specific Changes in Plasmodium Metabolism Required for Differentiation and Adaptation to Different Host and Vector Environments

Malaria parasites (Plasmodium spp.) encounter markedly different (nutritional) environments during their complex life cycles in the mosquito and human hosts. Adaptation to these different host niches is associated with a dramatic rewiring of metabolism, from a highly glycolytic metabolism in the asexual blood stages to increased dependence on tricarboxylic acid (TCA) metabolism in mosquito stages. Here we have used stable isotope labelling, targeted metabolomics and reverse genetics to map stage-specific changes in Plasmodium berghei carbon metabolism and determine the functional significance of these changes on parasite survival in the blood and mosquito stages. We show that glutamine serves as the predominant input into TCA metabolism in both asexual and sexual blood stages and is important for complete male gametogenesis. Glutamine catabolism, as well as key reactions in intermediary metabolism and CoA synthesis are also essential for ookinete to oocyst transition in the mosquito. These data extend our knowledge of Plasmodium metabolism and point towards possible targets for transmission-blocking intervention strategies. Furthermore, they highlight significant metabolic differences between Plasmodium species which are not easily anticipated based on genomics or transcriptomics studies and underline the importance of integration of metabolomics data with other platforms in order to better inform drug discovery and design