Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection.

BACKGROUND: Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. METHODS: We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. RESULTS: We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. CONCLUSIONS: This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Inhibition of protein translational machinery in triple-negative breast cancer as a promising therapeutic strategy.

Y-box binding protein-1 (YB-1) is a proto-oncogenic protein associated with protein translation regulation. It plays a crucial role in the development and progression of triple-negative breast cancer (TNBC). In this study, we describe a promising approach to inhibit YB-1 using SU056, a small-molecule inhibitor. SU056 physically interacts with YB-1 and reduces its expression, which helps to restrain the progression of TNBC. Proteome profiling analysis indicates that the inhibition of YB-1 by SU056 can alter the proteins that regulate protein translation, an essential process for cancer cell growth. Preclinical studies on human cells, mice, and patient-derived xenograft tumor models show the effectiveness of SU056. Moreover, toxicological studies have shown that SU056 treatment and dosing are well tolerated without any adverse effects. Overall, our study provides a strong foundation for the further development of SU056 as a potential treatment option for patients with TNBC by targeting YB-1.

Designing, implementing and testing an intervention of affective intelligent agents in nursing virtual reality teaching simulations-a qualitative study.

Emotions play an important role in human-computer interaction, but there is limited research on affective and emotional virtual agent design in the area of teaching simulations for healthcare provision. The purpose of this work is twofold: firstly, to describe the process for designing affective intelligent agents that are engaged in automated communications such as person to computer conversations, and secondly to test a bespoke prototype digital intervention which implements such agents. The presented study tests two distinct virtual learning environments, one of which was enhanced with affective virtual patients, with nine 3rd year nursing students specialising in mental health, during their professional practice stage. All (100%) of the participants reported that, when using the enhanced scenario, they experienced a more realistic representation of carer/patient interaction; better recognition of the patients' feelings; recognition and assessment of emotions; a better realisation of how feelings can affect patients' emotional state and how they could better empathise with the patients.

Influence of Sodium Chloride on Human Bitter Taste Receptor Responses.

In the past, taste interactions between sodium chloride (NaCl) and bitter tastants were investigated in human sensory studies, and the suppression of bitterness by sodium was observed. It is currently not clear if this phenomenon occurs predominantly peripherally or centrally and if the effect is general or only particular bitter compounds are blocked. Therefore, the influence of NaCl at the receptor level was tested by functional expression assays using four out of ∼25 human bitter taste receptors together with prototypical agonists. It was observed that NaCl affected only the responses of particular bitter taste receptor-compound pairs, whereas other bitter responses remained unchanged upon variations of the sodium concentrations. Among the tested receptors, TAS2R16 showed a reduction in signaling in the presence of NaCl. This demonstrates that for some receptor-agonist pairs, NaCl reduces the activation at the receptor level, whereas central effects may dominate the NaCl-induced bitter taste inhibition for other substances.

Recent advancements in nanomaterial-mediated ferroptosis-induced cancer therapy: Importance of molecular dynamics and novel strategies.

Ferroptosis is a novel type of controlled cell death resulting from an imbalance between oxidative harm and protective mechanisms, demonstrating significant potential in combating cancer. It differs from other forms of cell death, such as apoptosis and necrosis. Molecular therapeutics have hard time playing the long-acting role of ferroptosis induction due to their limited water solubility, low cell targeting capacity, and quick metabolism in vivo. To this end, small molecule inducers based on biological factors have long been used as strategy to induce cell death. Research into ferroptosis and advancements in nanotechnology have led to the discovery that nanomaterials are superior to biological medications in triggering ferroptosis. Nanomaterials derived from iron can enhance ferroptosis induction by directly releasing large quantities of iron and increasing cell ROS levels. Moreover, utilizing nanomaterials to promote programmed cell death minimizes the probability of unfavorable effects induced by mutations in cancer-associated genes such as RAS and TP53. Taken together, this review summarizes the molecular mechanisms involved in ferroptosis along with the classification of ferroptosis induction. It also emphasized the importance of cell organelles in the control of ferroptosis in cancer therapy. The nanomaterials that trigger ferroptosis are categorized and explained. Iron-based and noniron-based nanomaterials with their characterization at the molecular and cellular levels have been explored, which will be useful for inducing ferroptosis that leads to reduced tumor growth. Within this framework, we offer a synopsis, which traverses the well-established mechanism of ferroptosis and offers practical suggestions for the design and therapeutic use of nanomaterials.

State-of-the-art review on energy sharing and trading of resilient multi microgrids.

Independently run single microgrids (MGs) encounter difficulties with inadequate self-consumption of local renewable energy and frequent power exchange with the grid. Combining numerous MGs to form a multi-microgrid (MMG) is a viable approach to enhance smart distribution networks' operational and financial performance. However, the correlation and coordination of intermittent power generation within each MG network pose many techno-economic challenges for energy sharing and trading. This review offers a comprehensive analysis of these challenges within the framework of MMG operations. It examines state-of-the-art methodologies for optimizing multi-energy dispatch and scrutinizes contemporary strategies within energy markets that contribute to the resilience of power systems. The discourse extends to the burgeoning role of blockchain technology in revolutionizing decentralized market frameworks and the intricacies of MMG coordination for reliable and cost-effective energy distribution. Overall, this study provides ample inspiration for theoretical and practical research to the new entrants and experts alike to develop new concepts for energy markets, scheduling and novel operating models for future resilient multi-energy networked systems/MMGs.

Antecedents of rapport and its mediating role on relational cohesion in patient-physician interaction.

Increasing competition in healthcare services, it is imperative that physicians and family-care practitioners seek ways to attract and retain patients. Building relationships with existing patients is one sure way to continued patronage and increased clientele. The purpose of this paper is to examine antecedents of rapport and its influence on perceived relationships in the context of patient-physician interaction. Study using cross-sectional survey method with structured questionnaire was used for data collection. Structural Equation Modeling was used for analyzing the data collected from 326 patients residing in Karnataka, India. The finding suggests that respect, responsibility and understanding have significant influence on relational cohesion with rapport acting as mediating variable. The results add to the empirical validity of the relationship among rapport, respect & relationship, as it is required to understand studied in Indian context. The finding provides new directions for both healthcare professionals and institutions in their endeavor of building relationships with their customers (Patients) by emphasizing the need for developing 'rapport' as an integral part of service interaction. Future research like longitudinal and experimental studies can provide more conclusive evidence regarding the influence of service behaviour on rapport.

The Diverse Utility of Contrast Media Delivery and Dosing During Computed Tomography: An International Assessment of Knowledge and Practices.

BACKGROUND: Despite the escalated production rate, the Iodinated Contrast Media (ICM) shortage continues, and demand outweighs supply. AIM: The aim of this study is to investigate the knowledge and practice of ICM delivery in computed tomography (CT) among radiographers and radiologic technologists worldwide. METHODS: An IRB-approved cross-sectional survey used Google Forms for data collection. It involved 94 CT radiographers from 27 countries and was divided into five sections. The first section gathered demographic information, followed by sections on experience, self-assessment of ICM reactions, and delivery technique. The third section explored ICM knowledge and its relation to CT parameters. The fourth and fifth sections focus on practices during pulmonary angiography CT and renal CT scans. Data analysis involved descriptive statistics, the Chi- Square test, and ANOVA. RESULTS: Knowledge was assessed with seven questions, and a score of at least 3.5 was needed for categorization. The median score was two, indicating low knowledge. Specifically, 64.9% of the participants scored lower than the two scores. Years of experience are strongly correlated with the level of knowledge, with 51.6% of radiographers having more than 10 years of experience demonstrating adequate knowledge. 41.7% of respondents demonstrated adequate knowledge when their duty was focused on CT. Furthermore, wide practice variability exists in all CT pulmonary angiography protocols among radiographers with adequate and inadequate knowledge. CONCLUSION: Inexperienced individuals showed knowledge gaps, leading to varied practices and highlighting the need for educational programs. The study underscores establishing standardized Protocols and Practice Guidelines (PPGs) for contrast media administration in Radiology Departments. Additionally, it emphasizes the importance of regular training programs, and international knowledge sharing. The potential for self-selection bias in the online survey sample is highlighted.

The role, relevance and management of immune exhaustion in bovine infectious diseases.

Immune exhaustion is a state of immune cell dysfunction that occurs most commonly following chronic exposure to an antigen which persists after the immune response fails to remove it. Exhaustion has been studied most thoroughly with several cancers, but has also been observed in several chronic infectious diseases. The topic has mainly been studied with CD8+ T cells, but it can also occur with CD4+ T cells and other immune cell types too. Exhaustion is characterized by a hierarchical loss of effector cell functions, up-regulation of immuno-inhibitory receptors, disruption of metabolic activities, and altered chromatin landscapes. Exhaustion has received minimal attention so far in diseases of veterinary significance and this review's purpose is to describe examples where immune exhaustion is occurring in several bovine disease situations. We also describe methodology to evaluate immune exhaustion as well as the prospects of controlling exhaustion and achieving a more suitable outcome of therapy in some chronic disease scenarios.

Neurosonographic Findings in Infants with Rhesus Hemolytic Disease of Newborn: A Prospective Observational Study.

We estimated the incidence of intraventricular hemorrhage (IVH) and/or periventricular leukomalacia/echogenicity (PVL/E) in Rhesus isoimmunized infants. Seventy-one infants underwent cranial ultrasound within the first 3 days of life or discharge, whichever was earlier. Of these, 27 (38%) infants had IVH/ PVL/E. On multivariate analysis, lower gestational age (P = 0.035), small for gestational age [aOR (95% CI) 10.6 (1.9, 58.9)], and sepsis [aOR (95% CI) 4.5 (1.1, 18.4)] were independently associated with IVH/PVL.

Does volunteering impact refugee women's life satisfaction, empowerment, and wellbeing? Experimental evidence, local knowledge, and causal reasoning.

BACKGROUND: There are gaps in the evidence base addressing whether volunteering programs enhance the wellbeing, empowerment, and life satisfaction of individual volunteers. Program impacts are seldom rigorously evaluated, whilst construct meanings remain largely unspecified, especially in the Middle East. This study tested the impacts of We Love Reading, a program training volunteers to read aloud in their local communities. It also mapped local knowledge representation. METHODS: We conducted a mixed-method program evaluation based on a randomized cluster trial with 105 Syrian refugee women from poor households in Amman, Jordan. At three time points (baseline, 5-month and 12-month-follow-up), we implemented a survey to measure levels of life satisfaction (Cantril), psychological empowerment (PE), and psychological wellbeing (PWB). We used regression models on panel data to estimate individual-level impacts, adjusting for women's characteristics and the moderating effects of their social networks. We also conducted net-mapping sessions to clarify local concepts and their causal connections, generating thematic analyses and fuzzy cognitive maps (FCMs) to represent local knowledge and causal influences. RESULTS: Life satisfaction was the only outcome variable showing a significant impact for We Love Reading (Cantril, ß = 3.00, p = 0.002). Thematic analyses and FCMs made explicit the multi-dimensional aspects of lived experiences: emphasis was placed on reaching goals, having "the full right to act," the freedom to take decisions, willingness and determination. Women explained that building their empowerment and agency was a main driver of life satisfaction, and that volunteering boosted the resolve of "not giving up" on life goals. CONCLUSION: This program evaluation integrates scientifically-rigorous and culturally-relevant methodologies to identify impacts, local knowledge systems, and causal pathways of influence. This helps clarify how and why volunteering works in real-life situations across cultural contexts, calling attention to what programs seek to achieve, how they avoid volunteer burden, and why they generate social change.

Empowering Radiographers: A Call for Integrated AI Training in University Curricula.

Background: Artificial intelligence (AI) applications are rapidly advancing in the field of medical imaging. This study is aimed at investigating the perception and knowledge of radiographers towards artificial intelligence. Methods: An online survey employing Google Forms consisting of 20 questions regarding the radiographers' perception of AI. The questionnaire was divided into two parts. The first part consisted of demographic information as well as whether the participants think AI should be part of medical training, their previous knowledge of the technologies used in AI, and whether they prefer to receive training on AI. The second part of the questionnaire consisted of two fields. The first one consisted of 16 questions regarding radiographers' perception of AI applications in radiology. Descriptive analysis and logistic regression analysis were used to evaluate the effect of gender on the items of the questionnaire. Results: Familiarity with AI was low, with only 52 out of 100 respondents (52%) reporting good familiarity with AI. Many participants considered AI useful in the medical field (74%). The findings of the study demonstrate that nearly most of the participants (98%) believed that AI should be integrated into university education, with 87% of the respondents preferring to receive training on AI, with some already having prior knowledge of AI used in technologies. The logistic regression analysis indicated a significant association between male gender and experience within the range of 23-27 years with the degree of familiarity with AI technology, exhibiting respective odds ratios of 1.89 (COR = 1.89) and 1.87 (COR = 1.87). Conclusions: This study suggests that medical practices have a favorable attitude towards AI in the radiology field. Most participants surveyed believed that AI should be part of radiography education. AI training programs for undergraduate and postgraduate radiographers may be necessary to prepare them for AI tools in radiology development.

Protocol for conducting advanced cyclic tests in lithium-ion batteries to estimate capacity fade.

Using advanced cyclic testing techniques improves accuracy in estimating capacity fade and incorporates real-world scenarios in battery cycle aging assessment. Here, we present a protocol for conducting cyclic tests in lithium-ion batteries to estimate capacity fade. We describe steps for implementing strategies for accounting for variations in rest periods, charge-discharge rates, and temperatures. We also detail procedures for validating tests experimentally within a climate-controlled chamber and for developing an empirical model to estimate capacity fading under various testing objectives. For complete details on the use and execution of this protocol, please refer to Mulpuri et al.1.

Integrated Proteomics Characterization of NLRP3 Inflammasome Inhibitor MCC950 in Monocytic Cell Line Confirms Direct MCC950 Engagement with Endogenous NLRP3.

Inhibition of the NLRP3 inflammasome is a promising strategy for the development of new treatments for inflammatory diseases. MCC950 is a potent and selective small-molecule inhibitor of the NLRP3 pathway and has been validated in numerous species and disease models. Although the capacity of MCC950 to block NLRP3 signaling is well-established, it is still critical to identify the mechanism of action and molecular targets of MCC950 to inform and derisk drug development. Quantitative proteomics performed in disease-relevant systems provides a powerful method to study both direct and indirect pharmacological responses to small molecules to elucidate the mechanism of action and confirm target engagement. A comprehensive target deconvolution campaign requires the use of complementary chemical biology techniques. Here we applied two orthogonal chemical biology techniques: compressed Cellular Thermal Shift Assay (CETSA) and photoaffinity labeling chemoproteomics, performed under biologically relevant conditions with LPS-primed THP-1 cells, thereby deconvoluting, for the first time, the molecular targets of MCC950 using chemical biology techniques. In-cell chemoproteomics with inlysate CETSA confirmed the suspected mechanism as the disruption of inflammasome formation via NLRP3. Further cCETSA (c indicates compressed) in live cells mapped the stabilization of NLRP3 inflammasome pathway proteins, highlighting modulation of the targeted pathway. This is the first evidence of direct MCC950 engagement with endogenous NLRP3 in a human macrophage cellular system using discovery proteomics chemical biology techniques, providing critical information for inflammasome studies.

Binary image encryption with a QR code-encoded optical beam having an array of vortices.

In recent years, optical information processing has become increasingly important due to its ability to handle large amounts of data efficiently. Amplitude, phase, spatial frequency, wavelength, and polarization are the physical dimensions used for information encoding into the light beam. Information encoding using orbital angular momentum (OAM) carried by a vortex beam is gaining interest in this regard. Such beams provide high-dimensional orthogonal states for encoding and have shown more stability in turbulent media than Gaussian beams, especially in the case of free space propagation. This study demonstrates an image encryption method utilizing an array of OAM light modes. The approach uses a non-interferometric intensity recording-based encoding scheme, which offers ease of implementation. Quick response codes have been utilized for encoding to avoid information loss from non-uniform distribution of light and aberrations. The encryption scheme is highly secure because the encrypted light beam contains only partial information about the object, preventing complete information retrieval without proper key information.

ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data.

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

Identification of a novel drug molecule for neurodegenerative disease from marine algae through in-silico analysis.

Cognitive functions are lost due to the rapid hydrolysis of acetylcholine including Acetylcholinesterase (AChE) and Butyrylcholinesterase (BChE). Marine algae-derived compounds were reported for their neuroprotective activities and hence they can be utilised for treating neurodegenerative ailments like Alzheimer's Disease and Parkinson's Disease which are due to the loss of cognitive functions. Major attention is currently paid to seaweeds due to their health benefits and high nutritional values. Sea weeds are of a rich sense of natural bioactive compounds which antioxidants, pharmaceutical compounds, flavonoids and alkaloids. They also contain a high amount of vitamins A, D, E, C and Ca, K, Mg and Fe. Regular consumption of a marine algae-based diet may boost immunities. In searching for natural cholinesterase inhibitors, the present study is focussed on some marine bioactive compounds reported from brown, red and green algae. Molecular docking studies have been carried out along with molecular dynamics simulations studies and binding energy calculations resulting in three best bioactive compounds when AChE is used as the target. The results are compared with cocrystal studies. Two best compounds, namely, Diphlorethohydroxycarmalol and Phlorofucofuroeckol from the brown seaweeds are identified as the potential lead compounds for neurodegenerative diseases, Alzheimer's and Parkinson's.Communicated by Ramaswamy H. Sarma.

Advances in two-dimensional transition metal dichalcogenides-based sensors for environmental, food, and biomedical analysis: A review.

Transition metal dichalcogenides (TMDCs) are versatile two-dimensional (2D) nanomaterials used in biosensing applications due to their excellent physical and chemical properties. Due to biomaterial target properties, biosensors' most significant challenge is improving their sensitivity and stability. In environmental analysis, TMDCs have demonstrated exceptional pollutant detection and removal capabilities. Their high surface area, tunable electronic properties, and chemical reactivity make them ideal for sensors and adsorbents targeting various contaminants, including heavy metals, organic pollutants, and emerging contaminants. Furthermore, their unique electronic and optical properties enable sensitive detection techniques, enhancing our ability to monitor and mitigate environmental pollution. In the food analysis, TMDCs-based nanomaterials have shown remarkable potential in ensuring food safety and quality. These nanomaterials exhibit high specificity and sensitivity for detecting contaminants, pathogens, and adulterants in various food matrices. Their integration into sensor platforms enables rapid and on-site analysis, reducing the reliance on centralized laboratories and facilitating timely interventions in the food supply chain. In biomedical studies, TMDCs-based nanomaterials have demonstrated significant strides in diagnostic and therapeutic applications. Their biocompatibility, surface functionalization versatility, and photothermal properties have paved the way for novel disease detection, drug delivery, and targeted therapy approaches. Moreover, TMDCs-based nanomaterials have shown promise in imaging modalities, providing enhanced contrast and resolution for various medical imaging techniques. This article provides a comprehensive overview of 2D TMDCs-based biosensors, emphasizing the growing demand for advanced sensing technologies in environmental, food, and biomedical analysis.

Sphingolipid diversity in Candida auris: unraveling interclade and drug resistance fingerprints.

In this study, we explored the sphingolipid (SL) landscape in Candida auris, which plays pivotal roles in fungal biology and drug susceptibility. The composition of SLs exhibited substantial variations at both the SL class and molecular species levels among clade isolates. Utilizing principal component analysis, we successfully differentiated the five clades based on their SL class composition. While phytoceramide (PCer) was uniformly the most abundant SL class in all the isolates, other classes showed significant variations. These variations were not limited to SL class level only as the proportion of different molecular species containing variable number of carbons in fatty acid chains also differed between the isolates. Also a comparative analysis revealed abundance of ceramides and glucosylceramides in fluconazole susceptible isolates. Furthermore, by comparing drug-resistant and susceptible isolates within clade IV, we uncovered significant intraclade differences in key SL classes such as high PCer and low long chain base (LCB) content in resistant strains, underscoring the impact of SL heterogeneity on drug resistance development in C. auris. These findings shed light on the multifaceted interplay between genomic diversity, SLs, and drug resistance in this emerging fungal pathogen.