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CellProfiler is a widely used software for creating reproducible, reusable image analysis workflows without needing to code. In addition to the >90 modules that make up the main CellProfiler program, CellProfiler has a plugins system that allows for the creation of new modules which integrate with other Python tools or tools that are packaged in software containers. The CellProfiler-plugins repository contains a number of these CellProfiler modules, especially modules that are experimental and/or dependency-heavy. Here, we present an upgraded CellProfiler-plugins repository, an example of accessing containerised tools, improved documentation and added citation/reference tools to facilitate the use and contribution of the community., (© 2023 Royal Microscopical Society.)

Background: Planning for place of death is considered troublesome for patients with hematological cancer. Qualitative studies have focused on healthcare professionals and caregivers. To date, no study has been conducted from the patient's perspective of planning for place of death in the last year of life., Objective: To develop an understanding of how patients with hematological cancer experience planning for place of death in their last year of life., Methods: The study used constructivist grounded theory, semistructured interviews, a constant comparison technique, and memoing to collect and analyze data. The 21 participants were attending a cancer center, cancer unit, or hospice in the United Kingdom., Results: This article describes one core category, factors influencing planning for death, within the incurable hematology cancer illness trajectory through the following 2 subcategories: personal factors-driving away, developing a legacy, designing a death plan, and disease determining; and environmental factors-dependent determination, displacement of the home, and discernment of services., Conclusion: This critical study illustrates that planning for place of death is complex and multifaceted in conjunction with an unpredictable incurable illness trajectory., Implications for Practice: Preferences for the place of death will change over time depending on the illness trajectory experienced by patients with hematological cancer and the level of physical and emotional energy and independence afforded to discuss and plan., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Deep learning has greatly accelerated research in biological image analysis yet it often requires programming skills and specialized tool installation. Here we present Piximi, a modern, no-programming image analysis tool leveraging deep learning. Implemented as a web application at Piximi.app, Piximi requires no installation and can be accessed by any modern web browser. Its client-only architecture preserves the security of researcher data by running all computation locally. Piximi offers four core modules: a deep learning classifier, an image annotator, measurement modules, and pre-trained deep learning segmentation modules. Piximi is interoperable with existing tools and workflows by supporting import and export of common data and model formats. The intuitive researcher interface and easy access to Piximi allows biological researchers to obtain insights into images within just a few minutes. Piximi aims to bring deep learning-powered image analysis to a broader community by eliminating barriers to entry.

We herein describe a postdoctoral training program designed to train biologists with microscopy experience in bioimage analysis. We detail the rationale behind the program, the various components of the training program, and outcomes in terms of works produced and the career effects on past participants. We analyze the results of an anonymous survey distributed to past and present participants, indicating overall high value of all 12 rated aspects of the program, but significant heterogeneity in which aspects were most important to each participant. Finally, we propose this model as a template for other programs which may want to train experts in professional skill sets, and discuss the important considerations when running such a program. We believe that such programs can have extremely positive impact for both the trainees themselves and the broader scientific community., Competing Interests: Conflicts of interest: The authors declare no financial conflict of interest.

Background: For hematology cancer patients, the process of dying is described as "troublesome." Qualitative studies have focused on views of healthcare professionals and caregiver stakeholders. To date, there have been no studies from the patient's perspective on facing death while in the last year of life., Objective: The aim of this study was to develop an understanding of the hematology cancer patient's experience of the process of dying in the last year of life., Methods: The study method was constructivist grounded theory using semistructured interviews, a constant comparison technique, and memoing to collection and analysis of data. The 21 participants were attending a UK cancer center, a cancer unit, or a hospice., Results: This article describes 1 core category within the incurable hematology cancer illness trajectory through 4 subcategories: transitional phase, chronic phase, dying phase, and liminal phase., Conclusion: This unique study illustrates that, although life can be prolonged, "facing death" still occurs upon hospitalization and relapse regularly over the illness trajectory., Implications for Practice: It is important that clinical practice acknowledges those participants in an incurable illness trajectory while living are focused on avoiding death rather than the ability to cure the disease. Services need to be responsive to the ambiguity of both living and dying by providing holistic management simultaneously, especially after critical episodes of care, to enhance the process of care in the last year of life, and assessment should incorporate the discussion of experiencing life-threatening events., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Drug resistance is a challenge in anticancer therapy. In many cases, cancers can be resistant to the drug prior to exposure, that is, possess intrinsic drug resistance. However, we lack target-independent methods to anticipate resistance in cancer cell lines or characterize intrinsic drug resistance without a priori knowledge of its cause. We hypothesized that cell morphology could provide an unbiased readout of drug resistance. To test this hypothesis, we used HCT116 cells, a mismatch repair-deficient cancer cell line, to isolate clones that were resistant or sensitive to bortezomib, a well-characterized proteasome inhibitor and anticancer drug to which many cancer cells possess intrinsic resistance. We then expanded these clones and measured high-dimensional single-cell morphology profiles using Cell Painting, a high-content microscopy assay. Our imaging- and computation-based profiling pipeline identified morphological features that differed between resistant and sensitive cells. We used these features to generate a morphological signature of bortezomib resistance. We then employed this morphological signature to analyze a set of HCT116 clones (five resistant and five sensitive) that had not been included in the signature training dataset, and correctly predicted sensitivity to bortezomib in seven cases, in the absence of drug treatment. This signature predicted bortezomib resistance better than resistance to other drugs targeting the ubiquitin-proteasome system, indicating specificity for mechanisms of resistance to bortezomib. Our results establish a proof-of-concept framework for the unbiased analysis of drug resistance using high-content microscopy of cancer cells, in the absence of drug treatment., Competing Interests: MK, AB, DS, BC, YH, SS, AC, TK, GW No competing interests declared, (© 2023, Kelley et al.)

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks., (© 2023. The Author(s).)

A primary obstacle in translating genetic associations with disease into therapeutic strategies is elucidating the cellular programs affected by genetic risk variants and effector genes. Here, we introduce LipocyteProfiler, a cardiometabolic-disease-oriented high-content image-based profiling tool that enables evaluation of thousands of morphological and cellular profiles that can be systematically linked to genes and genetic variants relevant to cardiometabolic disease. We show that LipocyteProfiler allows surveillance of diverse cellular programs by generating rich context- and process-specific cellular profiles across hepatocyte and adipocyte cell-state transitions. We use LipocyteProfiler to identify known and novel cellular mechanisms altered by polygenic risk of metabolic disease, including insulin resistance, fat distribution, and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse deep phenotypic profiling in lipocytes and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease., Competing Interests: J.C.F. has received consulting honoraria from Goldfinch Bio and Astra Zeneca and speaking honoraria from Novo Nordisk, Astra Zeneca, and Merck for research presentations over which he had full control of content. M.C. holds equity in Waypoint Bio, serves as a consultant for Pfizer, and is a member of the Nestle Scientific Advisory Board. The authors have filed a provisional patent application (63/218,656)., (© 2023.)

Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Summary: Image-based experiments can yield many thousands of individual measurements describing each object of interest, such as cells in microscopy screens. CellProfiler Analyst is a free, open-source software package designed for the exploration of quantitative image-derived data and the training of machine learning classifiers with an intuitive user interface. We have now released CellProfiler Analyst 3.0, which in addition to enhanced performance adds support for neural network classifiers, identifying rare object subsets, and direct transfer of objects of interest from visualization tools into the Classifier tool for use as training data. This release also increases interoperability with the recently released CellProfiler 4, making it easier for users to detect and measure particular classes of objects in their analyses., Availability: CellProfiler Analyst binaries for Windows and MacOS are freely available for download at https://cellprofileranalyst.org/. Source code is implemented in Python 3 and is available at https://github.com/CellProfiler/CellProfiler-Analyst/. A sample dataset is available at https://cellprofileranalyst.org/examples, based on images freely available from the Broad Bioimage Benchmark Collection., (© The Author(s) 2021. Published by Oxford University Press.)

Background: Imaging data contains a substantial amount of information which can be difficult to evaluate by eye. With the expansion of high throughput microscopy methodologies producing increasingly large datasets, automated and objective analysis of the resulting images is essential to effectively extract biological information from this data. CellProfiler is a free, open source image analysis program which enables researchers to generate modular pipelines with which to process microscopy images into interpretable measurements., Results: Herein we describe CellProfiler 4, a new version of this software with expanded functionality. Based on user feedback, we have made several user interface refinements to improve the usability of the software. We introduced new modules to expand the capabilities of the software. We also evaluated performance and made targeted optimizations to reduce the time and cost associated with running common large-scale analysis pipelines., Conclusions: CellProfiler 4 provides significantly improved performance in complex workflows compared to previous versions. This release will ensure that researchers will have continued access to CellProfiler's powerful computational tools in the coming years., (© 2021. The Author(s).)

We describe new open source software called QuantiFish for rapid quantitation of fluorescent foci in zebrafish larvae, to support infection research in this animal model. QuantiFish extends the conventional measurements of bacterial load and number of bacterial foci to include measures for dissemination of infection. These are represented by the proportions of bacteria between foci and their spatial distribution. We showcase these measures by comparison of intravenous and hindbrain routes of Mycobacterium marinum infection, which are indistinguishable by measurement of bacterial load and not consistently differentiated by the number of bacterial foci. The intravenous route showed dose dependent dissemination of infection, reflected by increased spatial dispersion of bacteria and lower proportions of bacteria distributed across many foci. In contrast, hindbrain infection resulted in localised disease, limited to a smaller area and higher proportions of bacteria distributed across fewer foci. The application of QuantiFish may extend beyond models of infection, to study other pathologies such as metastatic cancer.

The glucocorticoid receptor (GR) is a major drug target in inflammatory disease. However, chronic glucocorticoid (GC) treatment leads to disordered energy metabolism, including increased weight gain, adiposity, and hepatosteatosis - all programs modulated by the circadian clock. We demonstrated that while antiinflammatory GC actions were maintained irrespective of dosing time, the liver was significantly more GC sensitive during the day. Temporal segregation of GC action was underpinned by a physical interaction of GR with the circadian transcription factor REVERBa and co-binding with liver-specific hepatocyte nuclear transcription factors (HNFs) on chromatin. REVERBa promoted efficient GR recruitment to chromatin during the day, acting in part by maintaining histone acetylation, with REVERBa-dependent GC responses providing segregation of carbohydrate and lipid metabolism. Importantly, deletion of Reverba inverted circadian liver GC sensitivity and protected mice from hepatosteatosis induced by chronic GC administration. Our results reveal a mechanism by which the circadian clock acts through REVERBa in liver on elements bound by HNF4A/HNF6 to direct GR action on energy metabolism.

To determine the effect of two forms of warm-up on postexercise bronchoconstriction in athletes with exercise-induced asthma, 12 moderately trained persons with asthma (age = 26.5 +/- 2.2 yr; height = 169.2 +/- 2.6 cm; weight = 64.3 +/- 2.6kg; VO2max = 52.7 +/- 1.3 ml.kg-1.min-1) were tested under three experimental conditions; continuous warm-up (CW), interval warm-up (IW), and control (C). CW consisted of 15 min of treadmill running at a velocity corresponding to 60% VO2max followed by an exercise challenge test (ET = 6 min at 90% VO2max). IW involved 8 x 30-s runs (1.5 min rest between bouts of exercise), at an intensity equivalent to 100% VO2max, followed by an ET. C consisted of only the ET. FEV1, FVC, and MMEFR were measured prior to the experimental conditions, repeated before the ET, and every 2 min during a 25-min passive recovery period, using a Breon spirometer. Postexercise changes in pulmonary function were recorded as the largest decrese in FEV1, FVC, and MMEFR during the recovery period, and expressed as a percentage of baseline values. Significant differences were detected in %FEV1 (34. 6,16.7,29.7: P = 0.009), %FVC (30.0,10.7,21.0: P = 0.03), and %MMEFR (50.0,30.2,43.4: P = 0.05), in comparing C, CW, and IW, respectively. Scheffe's test detected significance (P < 0.05) between C and CW for all three dependent variables; no statistical significance between C and IW or IW and CW occurred. These data indicate that a continuous warm-up of 15 min at 60% VO2max can significantly decrease postexercise bronchoconstriction in moderately trained athletes.

In 10 nonasthmatic subjects and 11 patients with asthma, we measured pulmonary resistance (RL), functional residual capacity (FRC), and specific conductance (sGaw) before, during, and after submaximal treadmill exercise. Nonasthmatic subjects did not change RL, FRC, or sGaw from base-line resting values during or after exercise. In patients with asthma, RL decreased significantly during exercise, both when exercise was begun from the control resting state and from conditions of elevated RL after a preceding period of exercise. When asthmatic patients inhaled a standardized dose of aerosolized histamine, the increase in RL during exercise was significantly less than the increase in RL when they breathed histamine at rest. When patients hyperventilated at rest with tidal volumes, breathing frequencies, and end-tidal CO2 tensions similar to those during exercise conditions, bronchodilatation also occurred, and the increase in RL following inhaled histamine during isocapnic hyperventilation was also less than at rest. Since bronchodilatation and inhibition of histamine-induced bronchoconstriction occur during both exercise and isocapnic hyperventilation, we suggest that the mechanism of bronchodilatation during exercise may not necessarily be related to metabolic factors associated with exercise.

In order to determine the influence of two artificially induced alkalotic states on the ability to perform maximal exercise, six male subjects (mean age, 22.0 years; mean height, 176.8 cm; mean weight, 69.1 kg; mean VO2 max, 3.83 l min-1) were studied during three experimental trials. The subjects performed six 60-s cycling bouts, at a work rate corresponding to 125% VO2 max, with 60 s recovery between work bouts; these regimens were performed 1 h after the ingestion of a solution containing either; I, placebo; II, NaHCO3 in a dosage of 0.15 g per kg body weight; or III, NaHCO3 0.30 g per kg body weight. The sixth work bout was continued until the pedal velocity dropped below 50 rev min-1. Total work done for the entire work period was calculated. Blood samples were taken from a forearm vein prior to the exercise bouts for analysis of pH and HCO3. The results showed a significant pre-exercise difference in pH and HCO3 for all conditions (P less than 0.01). In conditions where artificial alkalosis had been achieved prior to exercise there was significant increase in the work produced: I, 121.6 kJ; II, 133.1 kJ; III, 133.5 kJ (P less than 0.05). The time to fatigue in the six bout was also significantly increased; I, 74.7 s; II, 111.0 s; III, 106.0 p (P less than 0.05). There were no significant differences between conditions II and III. Thus augmentation of the bicarbonate reserves has a significant positive effect on the energy metabolism in interval-type exercise, leading to an increase in the work done and in the time to fatigue.(ABSTRACT TRUNCATED AT 250 WORDS)

Salbutamol and treadmill performance in non-atopic athletes. Med. Sci. Sports Exerc., Vol. 15, No. 6, pp. 520-522, 1983. Nineteen aerobic, non-atopic, athletes (10 females, 9 males) were studied in a double-blind fashion to determine the effect of a therapeutic dosage of salbutamol on pulmonary function, oxygen consumption (VO2max), heart rate (HR), and anaerobic threshold (AT). A placebo and salbutamol (in aerosol form) were administered in a dosage of two puffs four times per day. Forced vital capacity (FVC), FEV1.0, and mid-maximal expiratory flow were assessed prior to a maximal treadmill run, and at 5, 10, and 15 min of recovery. Resting and maximal HR, VO2max, AT, and VE were determined prior to and immediately after the 1-wk experimental period. Pre-test results showed no evidence of airway obstruction in any athlete. There was no significant change in any pulmonary function variable as a result of salbutamol administration. Maximal oxygen consumption showed a slight, nonsignificant (P greater than 0.05) decrease in both the salbutamol and placebo groups. There was also a similar nonsignificant decrease in pulmonary function in both groups. Resting and maximal HR and AT were unchanged. These results indicate that therapeutic administration of a selective beta-2 agonist does not affect pulmonary function or performance-related variables in non-atopic elite athletes.

In order to determine the effects of an inhaled bronchodilator on the acute effects of ozone exposure on competitive cyclists, three subjects exercised on a stationary cycle ergometer for one hour in 0.34 +/- 0.02 ppm ozone, 29.8 +/- 0.3 degrees C. and 36.5 +/- 0.5% relative humidity under three experimental conditions. The initial test involved no pre-medication and served as a control. Using a double blind protocol the subjects were either given a placebo or salbutamol (200 micrograms via aerosol) prior to the second and third exposures. Pre- and post-exercise pulmonary function tests demonstrated a reduction in forced vital capacity (FVC) and forced expiratory volume in one second (FEV1), however, the magnitude of this reduction was not changed by the administration of salbutamol. These data suggest that pre-treatment with salbutamol is ineffective in reducing or eliminating pulmonary discomfort or respiratory dysfunction.