The efficient natural transformation of Neisseria meningitidis allows the rapid construction of bacterial mutants in which the genes of interest are interrupted or replaced by antibiotic-resistance cassettes. However, this proved to be a double-edged sword, i.e., although facilitating the genetic characterization of this important human pathogen, it has limited the development of strategies for constructing markerless mutants without antibiotic-resistance markers. In addition, efficient tools for complementation or labeling are also lacking in N. meningitidis. In this study, we significantly expand the meningococcal genetic toolbox by developing new and efficient tools for the construction of markerless mutants (using a dual counterselection strategy), genetic complementation (using integrative vectors), and cell labeling (using a self-labeling protein tag). This expanded toolbox paves the way for more in-depth genetic characterization of N. meningitidis and might also be useful in other Neisseria species.IMPORTANCENeisseria meningitidis and Neisseria gonorrhoeae are two important human pathogens. Research focusing on these bacteria requires genetic engineering, which is facilitated by their natural ability to undergo transformation. However, the ease of mutant engineering has led the Neisseria community to neglect the development of more sophisticated tools for gene editing, particularly for N. meningitidis. In this study, we have significantly expanded the meningococcal genetic toolbox by developing novel and efficient tools for markerless mutant construction, genetic complementation, and cell tagging. This expanded toolbox paves the way for more in-depth genetic characterization of N. meningitidis and might also be useful in other Neisseria species.

The genome contains numerous regulatory elements that may undergo complex interactions and contribute to the establishment, maintenance, and change of cellular identity. Three-dimensional genome organization can be explored with fluorescence in situ hybridization (FISH) at the single-cell level, but the detection of small genomic loci remains challenging. Here, we provide a rapid and simple protocol for the generation of bright FISH probes suited for the detection of small genomic elements. We systematically optimized probe design and synthesis, screened polymerases for their ability to incorporate dye-labeled nucleotides, and streamlined purification conditions to yield nanoscopy-compatible oligonucleotides with dyes in variable arrays (NOVA probes). With these probes, we detect genomic loci ranging from genome-wide repetitive regions down to non-repetitive loci below the kilobase scale. In conclusion, we introduce a simple workflow to generate densely labeled oligonucleotide pools that facilitate detection and nanoscopic measurements of small genomic elements in single cells.

One of the main public health issues that has recently been observed in a greater number of children is being overweight. The cause certainly lies in the decreasing physical activity of children, but mostly in their eating habits. Soft drinks are recognized as the most significant contributor to body overweight due to high sugar content; thus, as a result of numerous campaigns, part of the sugar is replaced by artificial sweeteners (ASs). Despite their advantage due to their low caloric value, WHO recommends that they should not be used to achieve weight control or as prevention for reducing the risk of non-communicable diseases, as there is no evidence of their effectiveness. Apart from beverages, artificial sweetener combinations are also added to a variety of \"low fat\" and \"high protein\" food products, which are highly favored especially among the young population. Therefore, it is necessary to take care of the cumulative intake. The conducted study included a survey of 323 parents of children aged 1-14 years, as well as an analysis of the AS content in the products most often consumed by the respondents. The results of the survey show that a large part of children (40%) aged 3-14 often consume soft drinks. Different products (soft drinks, juices/nectars, syrups) were sampled based on the respondents\' responses, and an analysis showed that 54% of them contained one or more ASs. In addition, the survey indicated parents\' lack of information about the presence of AS in products, as 51% of parents declared that they do not read the declarations of the products they buy. It is necessary to persist in consumer education and changes in dietary preferences and habits, especially among children.

BACKGROUND: National food environment policies can contribute to the reduction of diet-related non-communicable diseases. Yet, their implementation in the Netherlands remains low. It has been hypothesized that the media can play a pivotal role in inducing spikes in policy attention, thereby shaping political action. The aim of this study was to examine the discourse on food policies in Dutch newspaper articles between 2000-2022, by analyzing arguments used by various actors.
METHODS: A systematic search in Nexis Uni was used to identify newspaper articles that covered national-level Dutch food environment policies published in seven Dutch national newspapers between 2000-2022. Covered policies were classified into six domains including food composition, labeling, promotion, prices, provision and retail and into the four stages of the policy cycle; policy formulation, decision-making, implementation, and evaluation. A grey literature search was used to identify food policies implemented during 2000-2022. Descriptive statistics were used to summarize coverage of policies over time, policy type and policy stage. An interpretive content analysis was performed on a random subsample of the newspaper articles to determine the actors, viewpoints and arguments of the food policies.
RESULTS: We identified 896 relevant newspaper articles. The coverage of food policies in newspapers was initially low but peaked in 2018/2021/2022. Through grey literature search we identified 6 food policies which were implemented or adjusted between 2000-2022. The majority of the newspaper articles reported on food pricing policies and were discussed in the policy formulation stage. Academics (mainly supportive) were the most and food industry (mostly opposing) the least cited actors. Supportive arguments highlighted health consequences, health inequalities and collective responsibility, whereas opposing arguments focused on unwanted governmental interference and ineffectiveness of policies.
CONCLUSIONS: Dutch newspaper articles covering food policies represented a variety of actors and arguments, with individual versus collective responsibility for food choices playing a central role in the arguments. These insights may serve as a basis for further research into why certain arguments are used and their effect on policy attention and implementation.

To assess the risk of food allergies in foods processed under the Japanese food labeling system, estimating exposure to hidden allergens is necessary. We assessed exposure to egg protein in foods processed according to the Japanese food labeling system. First, we estimated the concentration distribution of egg protein by Bayesian methods using data from the literature and the measurement of food products with precautional declarations in the labeling margin. We then estimated the food-intake portion-size distribution under two scenarios: soft drink consumption as an example of single, high-intake consumption, and confections, which are frequently consumed by children, as a realistic example of low-intake consumption. Finally, we estimated the distribution of unexpected intake of egg proteins in the form of single consumption. The mean exposure to egg protein under the high-intake scenario was estimated to be 0.0164 mg for 1-15-year-olds, 0.0171 mg for 4-15-year-olds, 0.0181 mg for 7-15-year-olds, and ≥0.0188 mg for 16-year-olds. The mean exposure to egg protein under the low-intake scenario was estimated to be 0.0018 mg for 1-15-year-olds, 0.0019 mg for 4-15-year-olds, 0.0020 mg for 7-15-year-olds, and ≥0.0022 mg for 16-year-olds. Compared to the reference dose of 2.0 mg proposed by the Joint the Food and Agriculture Organization (FAO)/World Health Organization (WHO) Expert Committee, the risk of onset of food allergies due to egg protein contamination from foods without egg labeling is considered to be extremely low under the current Japanese food labeling system.

Prenylation (isopentenylation), a key post-transcriptional modification with a hydrophobic prenyl group onto the biomacromolecules such as RNA and proteins, influences their localization and function. Prenyltransferases mediate this process, while cytokinin oxidases degrade the prenylated adenosine in plants. This review summarizes current progress in detecting prenylation modifications in RNA across species and their effects on protein synthesis. Advanced methods have been developed to label and study these modifications in vitro and in vivo, despite challenges posed by the inert chemical properties of prenyl groups. Continued advancements in bioorthogonal chemistry promise new tools for understanding the precise biological functions of prenylated RNA modifications and other related proteins.

Radiolabeled peptides are valuable tools for diagnosis or therapies; they are often radiofluorinated using an indirect approach based on an F-18 prosthetic group. Herein, we are reporting our results on the F-18 radiolabeling of three peptides using two different methods based on click reactions. The first one used the well-known CuAAC reaction, and the second one is based on our recently reported hetero-Diels-Alder (HDA) using a dithioesters (thia-Diels-Alder) reaction. Both methods have been automated, and the 18F-peptides were obtained in similar yields and synthesis time (37-39% decay corrected yields by both methods in 120-140 min). However, to obtain similar yields, the CuAAC needs a large amount of copper along with many additives, while the HDA is a catalyst and metal-free reaction necessitating only an appropriate ratio of water/ethanol. The HDA can therefore be considered as a minimalist method offering easy access to fluorine-18 labeled peptides and making it a valuable additional tool for the indirect and site-specific labeling of peptides or biomolecules.

Inspired by significant technical advancements, a rapidly growing stream of research explores human lay beliefs and reactions surrounding AI tools, which employ algorithms to mimic elements of human intelligence. This literature predominantly documents negative reactions to these tools or the underlying algorithms, often referred to as algorithm aversion or, alternatively, a preference for humans. This article proposes a third interpretation: people may be averse to their labels, but appreciative of their output. This perspective offers three core insights for how we study people\'s reactions to algorithms. Research would benefit from (1) carefully considering the labeling of AI tools, (2) broadening the scope of study to include interactions with these tools, and (3) accounting for their technical configuration.

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.

Self-reported penicillin allergy is highly prevalent. Different studies estimate that 10% of the population is labeled as such. This label, confirmed or suspected, forces us to take precautions and replace the antibiotic treatment of choice (frequently beta-lactams) with other 2nd or 3rd choice alternatives with worse overall results: side effects, resistance, costs, etc. The penicillin allergy label, once placed, remains in the medical record. It is only confirmed in less than 5% of patients, either because it has been placed inappropriately or because over time the sensitivity decreases and may disappear. Penicillin Allergy Decision Rule -PEN-FAST- is a validated and simple clinical prediction rule that estimates the risk of presenting an allergic reaction. Its use, together with algorithms that involve primary care in the study and delabeling of low-risk patients, can change our clinical practice.