OBJECTIVE: There is concern that the provision of the clinical high risk for psychosis (CHR) label is stigmatizing. Prior research suggests people have nuanced reactions to feedback involving the CHR label, including a positive experience receiving feedback and improvement in negative emotions (e.g., shame), while also exhibiting concerns about self-perception and perceptions from others related to the label. The current pilot study aimed to evaluate whether individuals at CHR showed changes in emotional and stigma-related experiences following a CHR psychoeducation intervention, BEGIN: Brief Educational Guide for Individuals in Need.
METHODS: Participants at CHR (N = 26) identified via the Structured Interview for Psychosis-Risk Syndromes completed the Mental Health Attitudes Interview measuring symptom-related and CHR label-related stigma at pre- and post-intervention.
RESULTS: Stigma did not increase and participants had greater positive emotions (e.g., feeling hopeful and relieved), post-BEGIN.
CONCLUSIONS: This study suggests that standardized CHR psychoeducation does not increase stigma in individuals at CHR.

UNASSIGNED: There is a lack of consensus in the addiction field as to how to refer to alumni of residential treatment who no longer use substances or who reduce their use. In the literature, this label and broader identity are typically discussed in technical (amount and frequency of use) or social terms (environment and social network changes).
UNASSIGNED: The current paper seeks to simplify the discussion by focusing on personal labels without complex technical or social considerations. Alumni of an inpatient addiction treatment facility were asked how they refer to themselves regarding their sobriety status post-discharge.
UNASSIGNED: Forty-nine patients were contacted 3 months post-discharge from a residential inpatient addiction treatment (men = 67%; Mage = 47.75 years). The patients completed a post-discharge assessment that was conducted by a trained research assistant over a 20-minute video call. The current study focused on a \"sobriety label\" measure in which patients indicated what they want to be called. Patients also explained why they chose their answer in an open-ended question.
UNASSIGNED: Most patients identified as in recovery (n = 29; 59.18%) followed by a sober person (n = 7; 14.29%) and four other responses. No alum selected the in remission option, which is notably a common way to refer to patients who no longer use substances.
UNASSIGNED: The current study adds a critical patient/alumni perspective to the existing body of literature and serves as a call to action for researchers to add a similar \"sobriety label\" measure to future assessments, studies, and batteries in effort to bring consistency to the labels, definitions, and identities that are published. This methodology of understanding how this population identifies will create uniformity in future literature and decrease the stigma surrounding addiction.
There is a history of inconsistent use of labels, definitions, and identities in the addiction treatment field. Few past studies have directly asked patients how they self-label, and it is important to ask those who use substances or who have reduced their use what they preferred to be called. This study asked a simple question to alumni of an inpatient treatment facility what they want to be called. We then asked them to explain why they chose that answer. Most alumni identified as “in recovery” or “a sober person”. This simple tool can be utilized by other facilities and also highlights that many research studies are referring to individuals by terms they do not prefer (eg, “in remission”).

Salt intake reduction is a global concern. In particular, Japanese consume higher amounts of salt than those of other ethnicities. The sodium content is mentioned on the label of industrially prepared dishes with an intention of reducing salt intake. This study aimed to evaluate the difference between the actual sodium content and labeled salt value of industrially prepared Japanese single dishes. Samples labeled \"estimated\" were collected and classified as Japanese, Western, and Chinese cuisines. The sodium content ranged from 180 to 1011 mg/100 g. The sodium content was higher than their reported values in other countries. Specifically, Chinese dishes contained high amounts of sodium, although the chloride content was similar across cuisine styles. Further, the molar ratio (i.e., sodium/chloride) had no significant effect on the difference between the actual content and labeled value. The measured salt contents were 20% higher than the labeled values. The results of decision tree analysis indicated that if the labeled salt value of stir-fried foods is determined by calculation, the actual sodium content is much higher than the labeled salt value. These findings are crucial for customers, dietitian, and researchers as they refer to the labeled salt value to determine the sodium content of industrially prepared foods.

BACKGROUND: Machine learning (ML) models can yield faster and more accurate medical diagnoses; however, developing ML models is limited by a lack of high-quality labeled training data. Crowdsourced labeling is a potential solution but can be constrained by concerns about label quality.
OBJECTIVE: This study aims to examine whether a gamified crowdsourcing platform with continuous performance assessment, user feedback, and performance-based incentives could produce expert-quality labels on medical imaging data.
METHODS: In this diagnostic comparison study, 2384 lung ultrasound clips were retrospectively collected from 203 emergency department patients. A total of 6 lung ultrasound experts classified 393 of these clips as having no B-lines, one or more discrete B-lines, or confluent B-lines to create 2 sets of reference standard data sets (195 training clips and 198 test clips). Sets were respectively used to (1) train users on a gamified crowdsourcing platform and (2) compare the concordance of the resulting crowd labels to the concordance of individual experts to reference standards. Crowd opinions were sourced from DiagnosUs (Centaur Labs) iOS app users over 8 days, filtered based on past performance, aggregated using majority rule, and analyzed for label concordance compared with a hold-out test set of expert-labeled clips. The primary outcome was comparing the labeling concordance of collated crowd opinions to trained experts in classifying B-lines on lung ultrasound clips.
RESULTS: Our clinical data set included patients with a mean age of 60.0 (SD 19.0) years; 105 (51.7%) patients were female and 114 (56.1%) patients were White. Over the 195 training clips, the expert-consensus label distribution was 114 (58%) no B-lines, 56 (29%) discrete B-lines, and 25 (13%) confluent B-lines. Over the 198 test clips, expert-consensus label distribution was 138 (70%) no B-lines, 36 (18%) discrete B-lines, and 24 (12%) confluent B-lines. In total, 99,238 opinions were collected from 426 unique users. On a test set of 198 clips, the mean labeling concordance of individual experts relative to the reference standard was 85.0% (SE 2.0), compared with 87.9% crowdsourced label concordance (P=.15). When individual experts\' opinions were compared with reference standard labels created by majority vote excluding their own opinion, crowd concordance was higher than the mean concordance of individual experts to reference standards (87.4% vs 80.8%, SE 1.6 for expert concordance; P<.001). Clips with discrete B-lines had the most disagreement from both the crowd consensus and individual experts with the expert consensus. Using randomly sampled subsets of crowd opinions, 7 quality-filtered opinions were sufficient to achieve near the maximum crowd concordance.
CONCLUSIONS: Crowdsourced labels for B-line classification on lung ultrasound clips via a gamified approach achieved expert-level accuracy. This suggests a strategic role for gamified crowdsourcing in efficiently generating labeled image data sets for training ML systems.

The claustrum has a unique thin sheet-like structure that makes it hard to identify in typical anatomical MRI scans. Attempts have been made to identify the claustrum in anatomical images with either automatic segmentation techniques or using atlas-based approaches. However, the resulting labels fail to include the ventral claustrum portion, which consists of fragmented grey matter referred to as \"puddles\". The current dataset is a high-resolution label of the whole claustrum manually defined using an ultra-high resolution postmortem MRI image of one individual. Manual labelling was performed by four independent research trainees. Two trainees labelled the left claustrum and another two trainees labelled the right claustrum. For every hemisphere we created a union of the two labels and assessed the label correspondence using dice coefficients. We provide size measurements of the labels in MNI space by calculating the oriented bounding box size. These data are the first manual claustrum segmentation labels that include both the dorsal and ventral claustrum regions at such a high resolution in standard space. The label can be used to approximate the claustrum location in typical in vivo MRI scans of healthy individuals.

Fluorescent labels have strongly contributed to many advancements in bioanalysis, molecular biology, molecular imaging, and medical diagnostics. Despite a large toolbox of molecular and nanoscale fluorophores to choose from, there is still a need for brighter labels, e.g., for flow cytometry and fluorescence microscopy, that are preferably of molecular nature. This requires versatile concepts for fluorophore multimerization, which involves the shielding of dyes from other chromophores and possible quenchers in their neighborhood. In addition, to increase the number of readout parameters for fluorescence microscopy and eventually also flow cytometry, control and tuning of the labels\' fluorescence lifetimes is desired. Searching for bright multi-chromophoric or multimeric labels, we developed PEGylated dyes bearing functional groups for their bioconjugation and explored their spectroscopic properties and photostability in comparison to those of the respective monomeric dyes for two exemplarily chosen fluorophores excitable at 488 nm. Subsequently, these dyes were conjugated with anti-CD4 and anti-CD8 immunoglobulins to obtain fluorescent conjugates suitable for the labeling of cells and beads. Finally, the suitability of these novel labels for fluorescence lifetime imaging and target discrimination based upon lifetime measurements was assessed. Based upon the results of our spectroscopic studies including measurements of fluorescence quantum yields (QY) and fluorescence decay kinetics we could demonstrate the absence of significant dye-dye interactions and self-quenching in these multimeric labels. Moreover, in a first fluorescence lifetime imaging (FLIM) study, we could show the future potential of this multimerization concept for lifetime discrimination and multiplexing.

BACKGROUND: Interest in finding efficient ways to remove penicillin allergy alerts has grown as a result of awareness of the considerable excess of false-negative diagnoses in patients with penicillin allergy labels (90%-95%), the poorer course with non-ß-lactam antibiotics, the increase in bacterial resistance, and the fact that these problems can affect up to 20% of the population in some countries. The strategies proposed have generated many publications in countries where the number of allergists to conduct such studies is low. In many cases where delabeling is performed, the risk of ß-lactam allergy is low, and a single penicillin challenge is sufficient to delabel the alert. However, other less \"ultrarapid\" strategies can be used to administer a ß-lactam during an admission for infection and thus postpone delabeling until traditional drug allergy consultations. However, the definitive withdrawal of ß-lactam alerts is threatened by nonremoval of alerts in electronic health records and by the reactivation or nonsynchronization of alerts between electronic systems at different levels of care. Allergy departments need to reflect on how to implement practices that enable rapid and efficient delabeling of drug allergy alerts, especially in patients with major comorbidities.

Za\'atar mix products are mainly composed of the dried and ground leaves and/or blossoms of wild and cultivated plant species (Origanum, Thymbra, Thymus, and Satureja) with the addition of condiments. The aim of this study was to evaluate the occurrence of aflatoxins, chemical composition (carbohydrates, fibre, fat, protein, moisture, ash, and acid contents), mineral content (Na, Ca, and K), and colour traits (L*a*b*) in relation to food label and food standards compliance. Measured and labelled fat content did not agree for approximately 91% of the samples. There was also no agreement between the measured and labelled fibre contents. The total content of aflatoxins in the tested samples ranged from 2 to 63.7 ng g-1. Eleven (69%) of the 16 analysed products had total aflatoxins higher than the maximum permitted limit of the European Commission. The KAS and LAZ products had significantly lighter colour (the highest L* values), while the ALAQ product had the darkest colour (lowest L* value). The range of sodium content in the tested products was 105.1-1425.3 mg/100 g. In conclusion, za\'atar mix products that are available in local markets do not have accurate nutritional labelling information, and the occurrence of aflatoxins was very high. Further studies are needed to evaluate the reasons for these quality defects.

BACKGROUND: Despite known recommendations regarding standards for print size and the intuitive importance of vision in reading prescription labels, the predictive nature of vision and prescription label readability remains largely undefined. Furthermore, while the importance of vision is recognized, various demographic factors associated with the ability to read prescription labels have not been fully elucidated.
OBJECTIVE: Describe relationships between visual acuity, point size, and readability of prescription labels and provide insight into demographic factors associated with prescription label readability.
METHODS: Cross-sectional examination of prescription label readability by older, community-dwelling adults. Subjects were evaluated as to demographics, visual acuity, and ability to read test instruments consisting of unaltered prescription label features of five medications dispensed by community pharmacies and two drug samples. Descriptive statistics in conjunction with a logit predictive model were employed for data analysis.
RESULTS: Instructions for medication use were most recognizable, identified and correctly read by 95.60% of the study cohort while directions for the use of drug samples were lowest (34.91%). Among prescription label features, auxiliary labels consistently demonstrated poor readability. Level of visual acuity was statistically related to the ability to read prescription labels while identifying prescription label components increased proportionally with point size. Race, gender, and history of a recent eye examination were statistically significant predictors of prescription label reading ability. Visual acuity alone was found to explain approximately 26% of the variablity in ability to read Rx labels.
CONCLUSIONS: Visual acuity is predictive of the ability to access Rx label information and should be considered a modifiable variable for improving prescription label reading ability amenable by appropriate eye care and spectacle correction.

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