Hyper-Spectral Image Analysis with Partially-Latent Regression and Spatial Markov Dependencies

Hyper-spectral data can be analyzed to recover physical properties at large planetary scales. This involves resolving inverse problems which can be addressed within machine learning, with the advantage that, once a relationship between physical parameters and spectra has been established in a data-driven fashion, the learned relationship can be used to estimate physical parameters for new hyper-spectral observations. Within this framework, we propose a spatially-constrained and partially-latent regression method which maps high-dimensional inputs (hyper-spectral images) onto low-dimensional responses (physical parameters such as the local chemical composition of the soil). The proposed regression model comprises two key features. Firstly, it combines a Gaussian mixture of locally-linear mappings (GLLiM) with a partially-latent response model. While the former makes high-dimensional regression tractable, the latter enables to deal with physical parameters that cannot be observed or, more generally, with data contaminated by experimental artifacts that cannot be explained with noise models. Secondly, spatial constraints are introduced in the model through a Markov random field (MRF) prior which provides a spatial structure to the Gaussian-mixture hidden variables. Experiments conducted on a database composed of remotely sensed observations collected from the Mars planet by the Mars Express orbiter demonstrate the effectiveness of the proposed model.Comment: 12 pages, 4 figures, 3 table

Ovarian cancer symptom awareness and anticipated delayed presentation in a population sample

Background: While ovarian cancer is recognised as having identifiable early symptoms, understanding of the key determinants of symptom awareness and early presentation is limited. A population-based survey of ovarian cancer awareness and anticipated delayed presentation with symptoms was conducted as part of the International Cancer Benchmarking Partnership (ICBP). Methods: Women aged over 50 years were recruited using random probability sampling (n = 1043). Computer-assisted telephone interviews were used to administer measures including ovarian cancer symptom recognition, anticipated time to presentation with ovarian symptoms, health beliefs (perceived risk, perceived benefits/barriers to early presentation, confidence in symptom detection, ovarian cancer worry), and demographic variables. Logistic regression analysis was used to identify the contribution of independent variables to anticipated presentation (categorised as < 3 weeks or ≥ 3 weeks). Results: The most well-recognised symptoms of ovarian cancer were post-menopausal bleeding (87.4%), and persistent pelvic (79.0%) and abdominal (85.0%) pain. Symptoms associated with eating difficulties and changes in bladder/bowel habits were recognised by less than half the sample. Lower symptom awareness was significantly associated with older age (p ≤ 0.001), being single (p ≤ 0.001), lower education (p ≤ 0.01), and lack of personal experience of ovarian cancer (p ≤ 0.01). The odds of anticipating a delay in time to presentation of ≥ 3 weeks were significantly increased in women educated to degree level (OR = 2.64, 95% CI 1.61 – 4.33, p ≤ 0.001), women who reported more practical barriers (OR = 1.60, 95% CI 1.34 – 1.91, p ≤ 0.001) and more emotional barriers (OR = 1.21, 95% CI 1.06 – 1.40, p ≤ 0.01), and those less confident in symptom detection (OR = 0.56, 95% CI 0.42 – 0.73, p ≤ 0.001), but not in those who reported lower symptom awareness (OR = 0.99, 95% CI 0.91 – 1.07, p = 0.74). Conclusions: Many symptoms of ovarian cancer are not well-recognised by women in the general population. Evidence-based interventions are needed not only to improve public awareness but also to overcome the barriers to recognising and acting on ovarian symptoms, if delays in presentation are to be minimised

Enumeration of Mycobacterium avium subsp. paratuberculosis by quantitative real-time PCR, culture on solid media and optical densitometry

<p>Abstract</p> <p>Background</p> <p>Different approaches are used for determining the number of <it>Mycobacterium avium </it>subsp. <it>paratuberculosis </it>(MAP) cells in a suspension. The majority of them are based upon culture (determination of CFU) or visual/instrumental direct counting of MAP cells. In this study, we have compared the culture method with a previously published F57 based quantitative real-time PCR (F57qPCR) method, to determine their relative abilities to count the number of three different MAP isolates in suspensions with the same optical densities (OD). McFarland turbidity standards were also compared with F57qPCR and culture, due to its frequent inclusion and use in MAP studies.</p> <p>Findings</p> <p>The numbers of MAP in two-fold serial dilutions of isolates with respective OD measurements were determined by F57qPCR and culture. It was found that culture provided lower MAP CFU counts by approximately two log₁₀, compared to F57qPCR. The McFarland standards (as defined for <it>E. coli</it>) showed an almost perfect fit with the enumeration of MAP performed by F57qPCR.</p> <p>Conclusions</p> <p>It is recommended to use culture and/or qPCR estimations of MAP numbers in experiments where all subsequent counts are performed using the same method. It is certainly not recommended the use of culture as the standard for qPCR experiments and <it>vice versa</it>.</p

The Outcome of Phagocytic Cell Division with Infectious Cargo Depends on Single Phagosome Formation

Given that macrophages can proliferate and that certain microbes survive inside phagocytic cells, the question arises as to the post-mitotic distribution of microbial cargo. Using macrophage-like cells we evaluated the post-mitotic distribution of intracellular Cryptococcus yeasts and polystyrene beads by comparing experimental data to a stochastic model. For beads, the post-mitotic distribution was that expected from chance alone. However, for yeast cells the post-mitotic distribution was unequal, implying preferential sorting to one daughter cell. This mechanism for unequal distribution was phagosomal fusion, which effectively reduced the intracellular particle number. Hence, post-mitotic intracellular particle distribution is stochastic, unless microbial and/or host factors promote unequal distribution into daughter cells. In our system unequal cargo distribution appeared to benefit the microbe by promoting host cell exocytosis. Post-mitotic infectious cargo distribution is a new parameter to consider in the study of intracellular pathogens since it could potentially define the outcome of phagocytic-microbial interactions

Predictors of Bacterial Meningitis in Resource-Limited Contexts: An Angolan Case

BACKGROUND: Despite the great morbidity and mortality that childhood bacterial meningitis (BM) is experiencing in Africa, diagnosis of BM in resource-limited contexts is still a challenge. Several algorithms and clinical predictors have been proposed to help physicians in decision-making but a lot of these markers used variables that are calculable only in well-equipped laboratories. Predictors or algorithm based on parameters that can be easily performed in basic laboratories can help significantly in BM diagnosis, even in resource-limited settings, rural hospitals or health centers. RESULTS: This retrospective study examined 145 cerebral-spinal fluid (CSF) specimens from children from 2 months to 14 years. CSF specimens were divided into two groups, according to the presence or not of a clinical diagnosis of BM. For each specimen, CSF aspect, CSF white blood cells (WBC) count, CSF glucose and protein concentration were analyzed and statistical analysis were performed. CSF WBC count ≥10/µl is no more a valuable predictor of BM. CSF protein concentration ≥50 mg/dl has a better sensitivity for BM diagnosis and when used with CSF glucose concentration ≤40 mg/dl, can help to diagnose correctly almost all the BM cases. An algorithm including CSF protein concentration, glucose concentration and WBC count has been proposed to rule out BM and to correctly diagnose it. CONCLUSIONS: In resource-limited health centers, the availability of a combination of easy-to-obtain parameters can significantly help physicians in BM diagnosis. The prompt identification of a BM case can be rapid treated or transferred to adequate structures and can modify the outcome in the patient

Demographic and microbial characteristics of extrapulmonary tuberculosis cases diagnosed in Malatya, Turkey, 2001-2007

<p>Abstract</p> <p>Background</p> <p>Extrapulmonary tuberculosis (EPTB) has an increasing rate in Turkey. The reason remains largely unknown. A better understanding of the demographic and microbial characteristics of EPTB in the Turkish population would extend the knowledgebase of EPTB and allow us to develop better strategies to control tuberculosis (TB).</p> <p><b>Methods</b></p> <p>We retrospectively evaluated clinical and laboratory data of 397 bacteriologically-confirmed TB cases diagnosed during an eight year-period using by chi-square analysis and multivariate logistic regression model.</p> <p>Results</p> <p>Of the 397 study patients, 103 (25.9%) had EPTB and 294 (74.1%) had pulmonary tuberculosis (PTB). The most commonly seen two types of EPTB were genitourinary TB (27.2%) and meningeal TB (19.4%). TB in bone/joints, pleural cavity, lymph nodes, skin, and peritoneal cavity occurred at a frequency ranging from 9.7% to 10.7%. The age distribution was significantly different (P < 0.01) between PTB and EPTB, with patients older than 45 years tending to have an increased risk of EPTB. Furthermore, the distribution of different types of EPTB differed significantly among age groups (P = 0.03). Meningeal and bone and/or joint TB were more commonly observed among the male patients, while lymphatic, genitourinary, and peritoneal TB cases were more frequently seen among females. Unique strain infection was statistically significantly associated with EPTB (OR: 2.82, 95% CI [1.59, 5.00])</p> <p>Conclusions</p> <p>EPTB accounted for a significant proportion of TB cases in Malatya, Turkey between 2001 and 2007. The current study has provided an insight into the dynamics of EPTB in Malatya, Turkey. However, the risk factors for having EPTB in Malatya, Turkey remain to be assessed in future studies using population-based or randomly selected sample.</p

Patients’ and family caregivers’ experiences with a newly implemented hospital at home program in British Columbia, Canada: Preliminary results

The Hospital at Home (HaH) model of care, which enables the provision of acute-level care in the patient’s own home as an alternative to brick and mortar hospital admission, was introduced in British Columbia, Canada in November 2020, starting with 9 inpatient “beds” in the community. The AT-HOME research group applied a patient-oriented approach to evaluate the patients’ and family caregivers’ (FCGs) experiences with the program as it was implemented and expanded throughout Victoria, BC. In this paper, we discuss the development of the survey instruments, including process and timelines (three phases); and present preliminary findings of the observational research study (six months of patient and FCG feedback data). The preliminary results show that 100% of patients (n=75) and 95% of FCGs (n=57) had an overall positive experience with the program (rated 6-10 on a 10-point scale where 0 meant ‘very poor’ and 10 ‘very good’). 100% of these patients and 96% of these FCGs would recommend the program to their friends and family and 97% of these patients and 96% of these FCGs would choose the program again if faced with the same situation. The preliminary results on metrics pertaining to care quality; information sharing and experiences with the admission and discharge processes; FCG’s roles, medication management, and more are discussed here. The final results of the patient and FCG experiences will be reported at the end of the data collection period. We can conclude that this new HaH program has been positively received by patients and FCGs thus far and they support program expansion Experience Framework This article is associated with the Innovation & Technology lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this len