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Summary: Changes in taste have been perceived as a common side effect of different cancers and may lead to malnutrition. Hence, the importance of understanding cancer patients' sensory taste perceptions and its impact on nutritional status, quality of life (QoL), and oral nutrition supplements (ONS) compliance becomes crucial. This qualitative study involved semi-structured, in-depth interviews with 24 adults (15 with multiple myeloma and 9 with head & neck cancer). The interviews were transcribed and the data analysis was conducted using reflexive thematic analysis and template analysis. This guided the development of four themes: 1. Taste and smell changes, 2. Impact on nutritional status and quality of life, 3. Information and help available for people experiencing changes in their taste, and 4. ONS and its compliance. Our findings show significant negative impact of chemosensory changes on nutritional status, quality of life and ONS compliance. Patient's experience with the level of support received for the management of taste changes during cancer treatment varied widely. Providing adequate information and support in a timely manner about changes in taste during treatment can improve patients' coping strategies and maintain their nutritional status. Overall, the findings highlight the importance of addressing taste changes and ONS compliance for people with multiple myeloma and head and neck cancer undergoing treatment. Specifically, the taste changes and its impact experienced by people with head and neck cancer were found to be more severe than those experienced by multiple myeloma patients. This study provides an understanding of changes in sensory taste perception experienced by cancer patients and its impact on nutritional status and QoL. This understanding can provide insight into ways to improve ONS consumption and compliance for preventing malnutrition. It is crucial to further conduct ONS sensory evaluations that cater to the specific needs of this cohort to help prevent malnutrition among cancer patients.

This auto-ethnographic essay draws upon Foucault's Archaeology of Knowledge to discuss the condition of Indian women in the Humanities in academia today. While acknowledging the encouragingly gender-inclusive projections in India's National Education Policy vision statement from 2020, I argue for more probing engagement with the concrete reality of being a woman teacher and researcher in the increasingly competitive and corporatized milieu of higher education. My methodology has been a close reading of the NEP's vision statement to analyze recurrences of terms and concepts as pointers to its discursive field. I argue that this policy statement implicitly envisions an empowered new-age Indian woman teacher, notionally mother to all her pupils, aiding their awakening intuitively from the very heart of her experiences, skills, and memories. Against this somewhat idealized feminine ecology of the NEP in principle and spirit, I juxtapose the actual everyday choices and struggles of women in academic positions. Does the decolonization of education in spirit also impart actual transformative agency to women academics? Will women be listened to? Not one essential woman, but heterogeneous women--women across different strata, identities, professional spaces, and ideologies? Above all, my essay probes the challenges and dividends of transitioning to a more home-grown teaching and research methodology derived from current Western academic models. For instance, what forms and lines of interdisciplinarity could best serve the interest of quality control in research and teaching? In the third and last section, I argue that women are equal contributors in the discourse of academics in the future. We are committed stakeholders that can help enhance collective performance and efficiency in ways that are commensurate and compatible with our particular needs, contexts, restraints, aptitudes, and encumbrances. I conclude my essay by urging colleagues in academia, women and men, to recognize that we can truly deliver on this challenge only in a spirit of intellectual, ethical, and interpersonal collaboration and collegiality. Keywords: Higher education, Women workers, India, Collegiality, Gender, Michel Foucault, Auto-ethnography, National Education Policy, Introduction In this informally longitudinal study, I shall be mining my own personal two-decades-long journey as teacher of literature and culture for share-worthy insights about the condition of women in [...]

Early innate immune responses play an important role in determining the protective outcome of Mycobacterium tuberculosis (Mtb) infection. Nuclear factor κB (NF-κB) signaling in immune cells regulates the expression of key downstream effector molecules that mount early antimycobacterial responses. Using conditional knockout mice, we studied the effect of abrogation of NF-κB signaling in different myeloid cell types and its impact on Mtb infection. Our results show that the absence of IKK2-mediated signaling in all myeloid cells resulted in increased susceptibility to Mtb infection. In contrast, the absence of IKK2-mediated signaling in CD11c+ myeloid cells induced early proinflammatory cytokine responses, enhanced the recruitment of myeloid cells, and mediated early resistance to Mtb. Abrogation of IKK2 in MRP8-expressing neutrophils did not affect disease pathology or Mtb control. Thus, we describe an early immunoregulatory role for NF-κB signaling in CD11c-expressing phagocytes and a later protective role for NF-κB in LysM-expressing cells during Mtb infection. [ABSTRACT FROM AUTHOR]

The ADP ribosyltransferases (PARPs 1-17) regulate diverse cellular processes, including DNA damage repair. PARPs are classified on the basis of their ability to catalyze poly-ADP-ribosylation (PARylation) or mono-ADP-ribosylation (MARylation). Although PARP9 mRNA expression is significantly increased in progressive tuberculosis (TB) in humans, its participation in host immunity to TB is unknown. Here, we show that PARP9 mRNA encoding the MARylating PARP9 enzyme was upregulated during TB in humans and mice and provide evidence of a critical modulatory role for PARP9 in DNA damage, cyclic GMP-AMP synthase (cGAS) expression, and type I IFN production during TB. Thus, Parp9-deficient mice were susceptible to Mycobacterium tuberculosis infection and exhibited increased TB disease, cGAS and 2'3'-cyclic GMP-AMP (cGAMP) expression, and type I IFN production, along with upregulation of complement and coagulation pathways. Enhanced M. tuberculosis susceptibility is type I IFN dependent, as blockade of IFN a receptor (IFNAR) signaling reversed the enhanced susceptibility of [Parp9.sup.-/-] mice. Thus, in sharp contrast to PARP9 enhancement of type I IFN production in viral infections, this member of the MAR family plays a protective role by limiting type I IFN responses during TB., Introduction Mycobacterium tuberculosis infects approximately 25% of the world's population and causes tuberculosis (TB), a leading infectious disease that results in approximately 1.3 million deaths annually. Although a majority of [...]

Simple Summary: Some cancer survivors, especially breast cancer survivors, may face the issue of lymphedema. Although it tends to be incurable, there are some methods to manage lymphedema. Exercise was thought to aggravate lymphedema severity in cancer survivors until a completely opposite view was proposed in 1998. Since then, an increasing number of studies have been carried out to investigate the effects of exercise on cancer survivors with lymphedema. Currently, exercise is widely considered safe and beneficial. However, the formulation of exercise prescriptions for patients with lymphedema has been under exploration. The aim of this literature review is to extract information from existing studies to provide some advice for the design of exercise prescriptions in terms of reducing lymphedema severity. The findings of this literature may help patients reduce the severity of lymphedema and improve their quality of life. It may also help reduce healthcare costs and improve affordability. Exercise has been repeatedly shown to be safe and beneficial for cancer survivors. However, there is no normative guideline for exercise prescription, and it is still under exploration. Therefore, this literature review aims to provide some advice for the formulation of exercise prescriptions for patients with breast cancer-related lymphedema (BCRL) from the perspective of reducing lymphedema severity. A review of relevant studies published before November 2023 was conducted using three scientific databases: PubMed, Embase, and Scopus. A total of 2696 articles were found. Eventually, 13 studies fulfilled the inclusion criteria and were included in this literature review. We concluded that daily, or nearly daily, exercise at home can be recommended. Moreover, reduced lymphedema severity may not be maintained after ceasing the exercise program, so exercise should be a lifelong practice. [ABSTRACT FROM AUTHOR]

Magnetometer measurements are one of the critical components necessary to improve our understanding of the intricate physical processes coupling mass, momentum, and energy within near-Earth space and throughout our solar system. However, these measurements are often contaminated by stray magnetic fields from the spacecraft hosting the magnetic field sensors, and the data often requires the application of interference mitigation algorithms prior to scientific use. Rigorous numerical validation of these techniques can be challenging when they are applied to in-situ spaceflight data, as a ground truth for the local magnetic field is often unavailable. This manuscript introduces and details the generation of an open-source dataset designed to facilitate the assessment of interference mitigation techniques for magnetic field data collected during spaceflight missions. The dataset contains over 100 hours of magnetic field data comprising mixtures of near-DC trends, physically-synthesized interference, and pseudo-geophysical phenomena. These constituent source signals have been independently captured by four synchronized magnetometers sampling at high cadence and combined into 30-minute intervals of data representative of events and interference seen in historic missions. The physical location of the four magnetometers relative to the interference sources enables researchers to test their interference mitigation algorithms with various magnetometer suite configurations, and the dataset also provides a ground truth for the underlying interference signals, enabling rigorous quantification of the results of past, present, and future interference mitigation efforts. [ABSTRACT FROM AUTHOR]

X-box binding protein 1 (XBP1) is a transcription factor that plays a crucial role in the unfolded protein response (UPR), a cellular stress response pathway involved in maintaining protein homeostasis in the endoplasmic reticulum (EnR). While the role of XBP1 in UPR is well-characterised, emerging evidence suggests its involvement in endocrine resistance in breast cancer. The transcriptional activity of spliced XBP1 (XBP1s) is a major component of its biological effects, but the targets of XBP1s in estrogen receptor (ER)-positive breast cancer are not well understood. Here, we show that the expression of miR-378 and PPARGC1B (host gene of miR-378) is downregulated during UPR. Using chemical and genetic methods, we show that XBP1s is necessary and sufficient for the downregulation of miR-378 and PPARGC1B. Our results show that overexpression of miR-378 significantly suppressed cell growth, colony formation, and migration of ER-positive breast cancer cells. Further, we found that expression of miR-378 sensitised the cells to UPR-induced cell death and anti-estrogens. The expression of miR-378 and PPARGC1B was downregulated in breast cancer, and higher expression of miR-378 is associated with better outcomes in ER-positive breast cancer. We found that miR-378 upregulates the expression of several genes that regulate type I interferon signalling. Analysis of separate cohorts of breast cancer patients showed that a gene signature derived from miR-378 upregulated genes showed a strong association with improved overall and recurrence-free survival in breast cancer. Our results suggest a growth-suppressive role for miR-378 in ER-positive breast cancer where downregulation of miR-378 by XBP1 contributes to endocrine resistance in ER-positive breast cancer. [ABSTRACT FROM AUTHOR]

This auto-ethnographic essay draws upon Foucault's Archaeology of Knowledge to discuss the condition of Indian women in the Humanities in academia today. While acknowledging the encouragingly gender-inclusive projections in India's National Education Policy vision statement from 2020, I argue for more probing engagement with the concrete reality of being a woman teacher and researcher in the increasingly competitive and corporatized milieu of higher education. My methodology has been a close reading of the NEP's vision statement to analyze recurrences of terms and concepts as pointers to its discursive field. I argue that this policy statement implicitly envisions an empowered new-age Indian woman teacher, notionally mother to all her pupils, aiding their awakening intuitively from the very heart of her experiences, skills, and memories. Against this somewhat idealized feminine ecology of the NEP in principle and spirit, I juxtapose the actual everyday choices and struggles of women in academic positions. Does the decolonization of education in spirit also impart actual transformative agency to women academics? Will women be listened to? Not one essential woman, but heterogeneous women--women across different strata, identities, professional spaces, and ideologies? Above all, my essay probes the challenges and dividends of transitioning to a more home-grown teaching and research methodology derived from current Western academic models. For instance, what forms and lines of interdisciplinarity could best serve the interest of quality control in research and teaching? In the third and last section, I argue that women are equal contributors in the discourse of academics in the future. We are committed stakeholders that can help enhance collective performance and efficiency in ways that are commensurate and compatible with our particular needs, contexts, restraints, aptitudes, and encumbrances. I conclude my essay by urging colleagues in academia, women and men, to recognize that we can truly deliver on this challenge only in a spirit of intellectual, ethical, and interpersonal collaboration and collegiality. [ABSTRACT FROM AUTHOR]

C/EBP homologous protein (CHOP), also known as growth arrest and DNA damage-inducible protein 153 (GADD153), belongs to the CCAAT/enhancer-binding protein (C/EBP) family. CHOP expression is induced by unfolded protein response (UPR), and sustained CHOP activation acts as a pivotal trigger for ER stress-induced apoptosis. MicroRNA-616 is located within an intron of the CHOP gene. However, the regulation of miR-616 expression during UPR and its function in breast cancer is not clearly understood. Here we show that the expression of miR-616 and CHOP (host gene of miR-616) is downregulated in human breast cancer. Both miR-5p/-3p arms of miR-616 are expressed with levels of the 5p arm higher than the 3p arm. During conditions of ER stress, the expression of miR-616-5p and miR-616-3p arms was concordantly increased primarily through the PERK pathway. Our results show that ectopic expression of miR-616 significantly suppressed cell proliferation and colony formation, whereas knockout of miR-616 increased it. We found that miR-616 represses c-MYC expression via binding sites located in its protein coding region. Furthermore, we show that miR-616 exerted growth inhibitory effects on cells by suppressing c-MYC expression. Our results establish a new role for the CHOP locus by providing evidence that miR-616 can inhibit cell proliferation by targeting c-MYC. In summary, our results suggest a dual function for the CHOP locus, where CHOP protein and miR-616 can cooperate to inhibit cancer progression. [ABSTRACT FROM AUTHOR]

Objectives: Odontogenic lesions include a broad range of pathologies that depend upon an inductive process toward odontogenesis before hamartomatous/neoplastic growth. The epithelium and stroma have an imperative role in pathogenesis and biological behavior. Hence, the study aims to evaluate the biology of the epithelium and stroma in odontogenic cysts (OCs). Material and Methods: Histochemical analysis was done (Hematoxylin and Eosin stain, Papanicolaou stain, toluidine blue, and picrosirius red) to determine the presence of keratin, epithelial thickness, mast cells (MCs), and the nature of collagen in OCs. Results: Keratin was absent in highly inflamed cases. MCs play a crucial role in cyst pathogenesis. In addition, polarizing microscopy helps in depicting the pattern of collagen fibers. Conclusion: The epithelium and the nature of stroma have an imperative role in the biological behavior of OCs. [ABSTRACT FROM AUTHOR]

Active sonar target classification remains an ongoing area of research due to the unique challenges associated with the problem (unknown target parameters, dynamic oceanic environment, different scattering mechanisms, etc.). Many feature extraction and classification techniques have been proposed, but there remains a need to relate and explain the classifier results in the physical domain. This work examines convolutional neural networks trained on simulated data with a known ground truth projected onto two time-frequency representations (spectrograms and scalograms). The classifiers were trained to discriminate the target material type, geometry, and internal fluid filling, while the hyperparameters were tuned to the classification task using Bayesian optimization. The trained networks were examined using an explainable artificial intelligence technique, gradient-weighted class activation mapping, to uncover the informative features used in discrimination. This analysis resulted in visual representations that allowed the CNN choices to be related to the physical domain. It was found that the scalogram representation provided a negligible classification accuracy increase compared with the spectrograms. Networks trained to discriminate between target geometries resulted in the highest accuracy, and the networks trained to discriminate the internal fluid of the target resulted in the lowest accuracy. [ABSTRACT FROM AUTHOR]

Automated target recognition is an important task in the littoral warfare domain, as distinguishing mundane objects from mines can be a matter of life and death. This is initial work towards the application of convolutional autoencoding to the littoral sonar space, with goals of disentangling the reflection noise prevalent in underwater acoustics and allowing recognition of the shape and material of targets. The autoencoders were trained on magnitude Fourier transforms of the TREX13 dataset. Clusters in the encoding space representing the known variable of measurement distance between the target and the sensor were found. An encoding vector space of around 16 dimensions appeared sufficient, and the space was shown to generalize well to unseen data. [ABSTRACT FROM AUTHOR]

Sonar target recognition remains an active area of research due to the complex entanglement of features from various acoustic scatterers, background clutter, and distortion by waveguide propagation effects. An equally challenging issue is due to different acoustic echoes returned from the target (including different target elements) itself. This work investigates the sonar target classification problem from a statistical perspective and aims to extract salient target feature vectors. Specifically, a multivariate statistical method is employed, canonical correlation analysis (CCA), as a feature extraction technique prior to multi-class classification of active sonar field data. The intuition behind using CCA is that persistent features slowly morph over time due to the changing aspect angles and platform positions and can be represented by maximally correlated projections of consecutive pings. CCA is applied using a sliding window, and the projections are used as feature vectors to train a neural network classifier. The smallest increase in classification accuracy when comparing the projection feature vectors to unprocessed feature vectors was 10%. The largest increase was 34%. The results are further examined through the use of confusion matrices and layer-wise relevance propagation, which distributes the trained networks output score to the input layer. [ABSTRACT FROM AUTHOR]

There was an average of 45,753 cancer diagnoses each year in Ireland from 2018 to 2020. Estimates state that by the year 2045, this average could increase by 50-100%. There are over 170,000 cancer survivors living in Ireland. Cancer-related fatigue (CRF) is a prevalent and debilitating side effect of cancer and cancer treatment. Research has demonstrated that exercise is an effective intervention to combat CRF. This review will examine the scope of CRF and critically analyse exercise interventions to combat CRF in cancer patients undergoing treatment. Aerobic exercise interventions and multimodal exercise (aerobic exercise, resistance exercise and flexibility exercise) interventions have been shown to improve symptoms of fatigue in cancer patients undergoing treatment. The effect of resistance training on CRF in cancer patients during treatment is not well understood. Aerobic exercise and multimodal exercise appear to combat CRF by improving one or more of the following health-related fitness parameters; aerobic capacity, muscular strength and endurance, flexibility, and body composition. A standardized process of recording the intensity and volume of aerobic, resistance and flexibility exercise should be developed. Future studies should investigate in greater detail the role of resistance training in reducing CRF among cancer patients. Qualitative methods should be developed to investigate the role the group dynamic has on cancer patients during group-based interventions. These qualitative methods may be able to determine the importance the delivery of exercise plays in reducing CRF. Biomarkers of CRF should be investigated and examined in relation to the specific dose of exercise that patients perform. [ABSTRACT FROM AUTHOR]

The joint successive interference cancellation technique (JSIC) is capable of jointly detecting consecutive users in an ordered set. Results suggest that the proposed JSIC is capable of achieving higher performance with an increase in complexity.

Background: Premature Ejaculation is a common sexual disorder which negatively affects men's life. Premature Ejaculation estimate prevalence is 20-30 %. It affects to overall quality of life and associated with anxiety, stress, and other psychological factors. Objective: The purpose of the study was to conduct a review of alternative therapy in the management of Premature ejaculation (PME). Method: A review was conducted using search terms Premature Ejaculation, Yoga Therapy, Alternative therapyand all the probable term in national and international data repositories such as PubMed, Scopus, science direct, google scholar, web of science in English language. Result: The review of alternative therapies in the management of Premature ejaculation suggests that most of the studies used Selective serotonin reuptake inhibitors (SSRIs), phosphodiesterase type 5 inhibitors (PDE5) and physical activity. There are very few studies conducted in relation to yoga and Premature ejaculation. Further, most of the studies explored effect of alternative therapies on psychological outcomes. Conclusion: Evidence suggests that Pharmacological clinical trial is effective with side effect, Cognitive behaviour therapy and Pharmacological Drugs separately both are less effective. One evidencebased study with integrated yoga therapy should be considered in the management of Premature ejaculation. Higherquality trial with yogic approach needed to first line management of patients presenting with Premature ejaculation. [ABSTRACT FROM AUTHOR]

Converting a vaccine into a thermostable dry powder is advantageous as it reduces the resource burden linked with the cold chain and provides flexibility in dosage and administration through different routes. Such a dry powder presentation may be especially useful in the development of a vaccine towards the respiratory infectious disease tuberculosis (TB). This study assesses the immunogenicity and protective efficacy of spray-dried ID93+GLA-SE, a promising TB vaccine candidate, against Mycobacterium tuberculosis (Mtb) in a murine model when administered via different routes. Four administration routes for the spray-dried ID93+GLA-SE were evaluated along with relevant controls—1) reconstitution and intramuscular injection, 2) reconstitution and intranasal delivery, 3) nasal dry powder delivery via inhalation, and 4) pulmonary dry powder delivery via inhalation. Dry powder intranasal and pulmonary delivery was achieved using a custom nose-only inhalation device, and optimization using representative vaccine-free powder demonstrated that approximately 10 and 44% of the maximum possible delivered dose would be delivered for intranasal delivery and pulmonary delivery, respectively. Spray-dried powder was engineered according to the different administration routes including maintaining approximately equivalent delivered doses of ID93 and GLA. Vaccine properties of the different spray-dried lots were assessed for quality control in terms of nanoemulsion droplet diameter, polydispersity index, adjuvant content, and antigen content. Our results using the Mtb mouse challenge model show that both intranasal reconstituted vaccine delivery as well as pulmonary dry powder vaccine delivery resulted in Mtb control in infected mice comparable to traditional intramuscular delivery. Improved protection in these two vaccinated groups over their respective control groups coincided with the presence of cytokine-producing T cell responses. In summary, our results provide novel vaccine formulations and delivery routes that can be harnessed to provide protection against Mtb infection. [ABSTRACT FROM AUTHOR]

In this work, we explore machine learning through a model-agnostic feature representation known as braiding, that employs braid manifolds to interpret multipath ray bundles. We generate training and testing data using the well-known BELLHOP model to simulate shallow water acoustic channels across a wide range of multipath scattering activity. We examine three different machine learning techniques—k-nearest neighbors, random forest tree ensemble, and a fully connected neural network—as well as two machine learning applications. The first application applies known physical parameters and braid information to determine the number of reflections the acoustic signal may undergo through the environment. The second application applies braid path information to determine if a braid is an important representation of the channel (i.e., evolving across bands of higher amplitude activity in the channel). Testing accuracy of the best trained machine learning algorithm in the first application was 86.70% and the testing accuracy of the second application was 99.94%. This work can be potentially beneficial in examining how the reflectors in the environment changeover time while also determining relevant braids for faster channel estimation. [ABSTRACT FROM AUTHOR]

Uncoordinated random access (URA) wireless communication schemes provide an attractive framework to enable the necessary communication backbone for the advancement of dense sensor systems, many sensors deployed in a relatively small area. By itself, URA is unsuitable for moderately dense networks due to the crippling levels of interference that result from within the communication network. Digital beamforming has been proposed to alleviate intra-URA-network interference with a post-reception formation of multiple simultaneous beams that allow a single receiver to “hear” only the transmissions meant for it and to block out all others. A high density network can result in interference originating from the same direction which cannot be mitigated with beamforming. We propose the addition of post-beamformed multiuser detection (MUD) with the use of direct sequence spread spectrum (DSSS) waveforms to help further combat the interference problem. Motivated by practical design choices such as transceiver weight and size as well as operational expectations of variable and/or evolving node densities, we explore trades between the DSSS time-spreading factor, number of antennas per node, and network node density. Our results show throughput improvements with the addition of MUD, while the most improvements are with the addition of MUD paired with an appropriate choice of spreading factor. Insights from these results provide guidelines for the development of future systems not only aided by MUD and beamforming, but also by on-the-fly adaptation of the DSSS signature waveform time-spreading factor to mitigate the level of interference present at any time. [ABSTRACT FROM AUTHOR]

This paper introduces a feature extraction technique that identifies highly informative features from sonar magnitude spectra for automated target classification. The approach involves creating feature representations through convolution of a two-dimensional Gabor wavelet and acoustic color magnitudes to capture elastic waves. This feature representation contains extracted localized features in the form of Gabor stripes, which are representative of unique targets and are invariant of target aspect angle. Further processing removes non-informative features through a threshold-based culling. This paper presents an approach that begins connecting model-based domain knowledge with machine learning techniques to allow interpretation of the extracted features while simultaneously enabling robust target classification. The relative performance of three supervised machine learning classifiers, specifically a support vector machine, random forest, and feed-forward neural network are used to quantitatively demonstrate the representations' informationally rich extracted features. Classifiers are trained and tested with acoustic color spectrograms and features extracted using the algorithm, interpreted as stripes, from two public domain field datasets. An increase in classification performance is generally seen, with the largest being a 47% increase from the random forest tree trained on the 1–31 kHz PondEx10 data, suggesting relatively small datasets can achieve high classification accuracy if model-cognizant feature extraction is utilized. [ABSTRACT FROM AUTHOR]

"Palate Poetry, Kitchen Truths: Coming Home to Cooking" is a long essay comprising non-didactic philosophical reflections on the wisdom of home cooking attained over the first three months spent in Covid- 19 lockdown. I make a case for home cooking and home eating as an experiential strategy that can, mutatis mutandis, alert us to ontologies and knowledge systems that resist the seeming inexorability of neoliberal, millennial urbanised living. I do so without holding forth any normative rejection of technology and other exigencies of modern living; and gesture instead towards an inclusive paradigm where machines can be applied towards a promotion of food making and food sharing that is ethical, cosmopolitan, communityminded, ecologically aware, and yet forward-looking. The auto-ethnographic methodology covers both the analytical prose and the interspersed poems it provides a discursive matrix for. I found myself planting these poems (and accompanying images of food from my kitchen) at strategic moments in the argumentation so as to allow the reader, experimentally, a detour and respite from the critical density of the prose. I suppose I am experimenting with the possibility of treating of the same subject in different mediums and then gathering them back into the fold of the personal, reflective essay. [ABSTRACT FROM AUTHOR]

Estrogen receptor 1 (ESR1, which encodes estrogen receptor-alpha) is a key driver gene for the initiation and progression of hormone receptor-positive breast cancer. Estrogen receptor-alpha (ER) is expressed in up to 70% of cases, and patients are routinely treated with endocrine therapies. However, the development of resistance over time is common and occurs in one-third of ER-positive breast tumors, leading to disease progression and death. X-box binding protein 1 (XBP1), a key component of the unfolded protein response (UPR) and ER signaling pathway, generates a positive feedback regulatory loop that leads to increased expression of XBP1 and ER in luminal breast cancer. In this review, we highlight new insights into the mechanisms of crosstalk between XBP1 and ER signaling and its clinical implications. Next, we describe the key signaling nodes that play an important role in XBP1-mediated endocrine resistance in breast cancer. Further, we discuss XBP1 gene mutations in breast cancer and the role of these mutations in the emergence of endocrine resistance and response to treatment. Finally, we discuss the current state and future directions for targeting XBP1 in combination with standard endocrine therapy to improve clinical outcomes in endocrine-resistant breast cancer patients. [ABSTRACT FROM AUTHOR]

In this article, we propose channel estimation techniques for shallow water acoustic channels that exhibit rapidly fluctuating high-amplitude multipath activity across different regions of the channel support. Specifically, we impose support constraints on the channel impulse response that confine tracking the shallow water acoustic channel to within the most active regions within the channel delay spread. The key idea is to focus on channel estimation performance through the banded nature of the multipath arrivals in the delay versus time channel that we denote as subregions of the channel delay spread. Because we are examining sparse shallow water acoustic channels, we adopt the well-known Lasso metric and related mixed-norm optimization techniques, but in contrast to traditional sparse sensing approaches, we use masked constraints to prioritize the estimation of regions of interest within the channel delay spread. This provides a tradeoff between computational time and estimation performance that we explore in detail over experimental field data from the SPACE08 experiment and over simulated channels emulating diverse oceanic conditions. [ABSTRACT FROM AUTHOR]

Microbiome research has increased dramatically in recent years, driven by advances in technology and significant reductions in the cost of analysis. Such research has unlocked a wealth of data, which has yielded tremendous insight into the nature of the microbial communities, including their interactions and effects, both within a host and in an external environment as part of an ecological community. Understanding the role of microbiota, including their dynamic interactions with their hosts and other microbes, can enable the engineering of new diagnostic techniques and interventional strategies that can be used in a diverse spectrum of fields, spanning from ecology and agriculture to medicine and from forensics to exobiology. From June 19–23 in 2017, the NIH and NSF jointly held an Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome. This review is inspired by some of the topics that arose as priority areas from this unique, interactive workshop. The goal of this review is to summarize the Innovation Lab's findings by introducing the reader to emerging challenges, exciting potential, and current directions in microbiome research. The review is broken into five key topic areas: (1) interactions between microbes and the human body, (2) evolution and ecology of microbes, including the role played by the environment and microbe-microbe interactions, (3) analytical and mathematical methods currently used in microbiome research, (4) leveraging knowledge of microbial composition and interactions to develop engineering solutions, and (5) interventional approaches and engineered microbiota that may be enabled by selectively altering microbial composition. As such, this review seeks to arm the reader with a broad understanding of the priorities and challenges in microbiome research today and provide inspiration for future investigation and multi-disciplinary collaboration. [ABSTRACT FROM AUTHOR]

LiDAR provides highly accurate 3-D point clouds. However, data need to be manually labeled in order to provide subsequent useful information. Manual annotation of such data is time-consuming, tedious, and error prone, and hence, in this article, we present three automatic methods for annotating trees in LiDAR data. The first method requires high-density point clouds and uses certain LiDAR data attributes for the purpose of tree identification, achieving almost 90% accuracy. The second method uses a voxel-based 3-D convolutional neural network on low-density LiDAR data sets and is able to identify most large trees accurately but struggles with smaller ones due to the voxelization process. The third method is a scaled version of the PointNet++ method and works directly on outdoor point clouds and achieves an $F_{\mathrm{ score}}$ of 82.1% on the ISPRS benchmark data set, comparable to the state-of-the-art methods but with increased efficiency. [ABSTRACT FROM AUTHOR]

The lungs are the most vulnerable site for air-borne infections. Immunologic compartmentalization of the lungs into airway lumen and interstitium has paved the way to determine the immune status of the site of pathogen entry, which is crucial for the outcome of any air-borne infections. Vaccination via the nasal route with Mycobacterium indicus pranii (MIP), a prospective candidate vaccine against tuberculosis (TB), has been reported to confer superior protection as compared to the subcutaneous (s.c.) route in small-animal models of TB. However, the immune mechanism remains only partly understood. Here, we showed that intranasal (i.n.) immunization of mice with MIP resulted in a significant recruitment of CD4+ and CD8+ T-cells expressing activation markers in the lung airway lumen. A strong memory T-cell response was observed in the lung airway lumen after i.n. MIP vaccination, compared with s.c. vaccination. The recruitment of these T-cells was regulated primarily by CXCR3–CXCL11 axis in "MIP i.n." group. MIP-primed T-cells in the lung airway lumen effectively transferred protective immunity into naïve mice against Mycobacterium tuberculosis (M.tb) infection and helped reducing the pulmonary bacterial burden. These signatures of protective immune response were virtually absent or very low in unimmunized and subcutaneously immunized mice, respectively, before and after M.tb challenge. Our study provides mechanistic insights for MIP-elicited protective response against M.tb infection. [ABSTRACT FROM AUTHOR]

This paper proposes channel estimation using energy efficient transmission of signal dictionaries for shallow water acoustic communications. Specifically, the multi-columned structure of the channel delay spread is exploited to design partially sampled dictionary in a two-dimensional (2-D) frequency representation of the channel. The key contribution of this work is to achieve considerable energy saving in the transmission of complex exponential signals, designed specifically for real-time shallow water channel estimation at the receiver. This is accomplished by harnessing 2-D frequency localization with compressive transmission and modified-compressive sensing with prior information to exploit the sparse structure of the rapidly fluctuating shallow water acoustic channel in real time. The proposed technique reduces demands on transmitted signal energy by harnessing the reconstruction ability of sparse sensing while retaining key non-sparse channel elements that represent important multipath phenomena. Numerical evidence based on experimental channel estimates demonstrates the efficacy of the proposed work. [ABSTRACT FROM AUTHOR]