The role of MRI to estimate liver iron concentration (LIC) for identifying patients with iron overload and guiding the titration of chelation therapy is increasingly established for routine clinical practice. However, the existence of multiple MRI-based LIC quantification techniques limits standardization and widespread clinical adoption. In this article, we review the existing and widely accepted MRI-based LIC estimation methods at 1.5 T and 3 T: signal intensity ratio (SIR) and relaxometry (R2 and R2*) and discuss the basic principles, acquisition and analysis protocols, and MRI-LIC calibrations for each technique. Further, we provide an up-to-date information on MRI vendor implementations and available offline commercial and free software for each MRI-based LIC quantification approach. We also briefly review the emerging and advanced MRI techniques for LIC estimation and their current limitations for clinical use. Lastly, we discuss the implications of MRI-based LIC measurements on clinical use and decision-making in the management of patients with iron overload. Some of the key highlights from this review are as follows: 1) Both R2 and R2* can estimate accurate and reproducible LIC, when validated acquisition parameters and analysis protocols are applied, 2) Although the Ferriscan R2 method has been widely used, recent consensus and guidelines endorse R2*-MRI as the most accurate and reproducible method for LIC estimation, 3) Ongoing efforts aim to establish R2*-MRI as the standard approach for quantifying LIC, and 4) Emerging R2*-MRI techniques employ radial sampling strategies and offer improved motion compensation and broader dynamic range for LIC estimation. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

BACKGROUND: The online pharmacy market is growing, with legitimate online pharmacies offering advantages such as convenience and accessibility. However, this increased demand has attracted malicious actors into this space, leading to the proliferation of illegal vendors that use deceptive techniques to rank higher in search results and pose serious public health risks by dispensing substandard or falsified medicines. Search engine providers have started integrating generative artificial intelligence (AI) into search engine interfaces, which could revolutionize search by delivering more personalized results through a user-friendly experience. However, improper integration of these new technologies carries potential risks and could further exacerbate the risks posed by illicit online pharmacies by inadvertently directing users to illegal vendors.
OBJECTIVE: The role of generative AI integration in reshaping search engine results, particularly related to online pharmacies, has not yet been studied. Our objective was to identify, determine the prevalence of, and characterize illegal online pharmacy recommendations within the AI-generated search results and recommendations.
METHODS: We conducted a comparative assessment of AI-generated recommendations from Google\'s Search Generative Experience (SGE) and Microsoft Bing\'s Chat, focusing on popular and well-known medicines representing multiple therapeutic categories including controlled substances. Websites were individually examined to determine legitimacy, and known illegal vendors were identified by cross-referencing with the National Association of Boards of Pharmacy and LegitScript databases.
RESULTS: Of the 262 websites recommended in the AI-generated search results, 47.33% (124/262) belonged to active online pharmacies, with 31.29% (82/262) leading to legitimate ones. However, 19.04% (24/126) of Bing Chat\'s and 13.23% (18/136) of Google SGE\'s recommendations directed users to illegal vendors, including for controlled substances. The proportion of illegal pharmacies varied by drug and search engine. A significant difference was observed in the distribution of illegal websites between search engines. The prevalence of links leading to illegal online pharmacies selling prescription medications was significantly higher (P=.001) in Bing Chat (21/86, 24%) compared to Google SGE (6/92, 6%). Regarding the suggestions for controlled substances, suggestions generated by Google led to a significantly higher number of rogue sellers (12/44, 27%; P=.02) compared to Bing (3/40, 7%).
CONCLUSIONS: While the integration of generative AI into search engines offers promising potential, it also poses significant risks. This is the first study to shed light on the vulnerabilities within these platforms while highlighting the potential public health implications associated with their inadvertent promotion of illegal pharmacies. We found a concerning proportion of AI-generated recommendations that led to illegal online pharmacies, which could not only potentially increase their traffic but also further exacerbate existing public health risks. Rigorous oversight and proper safeguards are urgently needed in generative search to mitigate consumer risks, making sure to actively guide users to verified pharmacies and prioritize legitimate sources while excluding illegal vendors from recommendations.

UNASSIGNED: Consumption of unsafe foods increases morbidity and mortality and is currently an issue, particularly in low- and middle-income countries. Policy actions to ensure food safety are dominated by mitigation of biological and chemical hazards through supply-side risk management, lessening the degree to which consumer perspectives of food safety are considered.
UNASSIGNED: This study aimed to provide an in-depth understanding, from vendor and consumer perspectives, of how food-safety concerns of consumers translate into their subsequent food-choice behaviors in 6 diverse low- and middle-income countries.
UNASSIGNED: Six Drivers of Food Choice projects (2016-2022) provided transcripts from 17 focus group discussions and 343 interviews conducted in Ghana, Guinea, India, Kenya, Tanzania, and Vietnam. Qualitative thematic analysis was used to identify emerging themes important to food safety.
UNASSIGNED: The analysis suggests that consumers constructed meaning about food safety through personal lived experience and social influences. Community and family members contributed knowledge about food safety. Concerns about food safety were influenced by reputations of and relationships with food vendors. Consumers\' mistrust of food vendors was amplified by purposeful adulteration or unsafe selling practices and new methods used to produce food. Moreover, consumers were reassured of food safety by positive relationships with vendors; meals cooked at home; implementation of policies and following regulations; vendor adherence to environmental sanitation and food-hygiene practices; cleanliness of vendors\' appearance; and vendors\' or producers\' agency to use risk mitigation strategies in production, processing, and distribution of food.
UNASSIGNED: Consumers integrated their meanings, knowledge, and concerns about food safety to achieve assurance about the safety of their foods when making food-choice decisions. The success of food-safety policies hinges on consideration of consumers\' food-safety concerns in their design and implementation, alongside actions to reduce risk in food supply.

UNASSIGNED: Food Safety and Standards Authority of India, established under the Food Safety and Standards Act, 2006, is mandated with disseminating evidence-based standards, regulating the manufacture, storage, distribution, sale, and import of street food, for ensuring the availability of safe and wholesome food for human consumption and matters connected in addition to that or incidental to that. Hence, this study was conducted to ascertain the conformance of the design of street food vendor\'s carts to the prescribed standards.
UNASSIGNED: We conducted a cross-sectional study in Chandigarh between July 2017 and March 2018 among 400 street food vendors. The primary dependent variable of the study was conformance. The carts were evaluated for their conformance to the standard recommended design based upon a checklist designed using the guidelines of Food Safety and Standards Regulations, 2011.
UNASSIGNED: Almost half of the respondents had an experience of 6-15 years (48.5%) and were earning between Rs. 500 and 1000/day (56.3%). The majority of them (95%) were migrants from other states. Only 26.3% were using mobile vending sites. On regression analysis, better cart score was predicted by age, education, increasing experience, higher income, when food was prepared at home only, and with assistance in the form of helpers.
UNASSIGNED: This study indicates that although the policy was formulated 8 years back, the standards of street food carts were still below par in Chandigarh. The government should give technical specifications and ensure uniformity at the national level.

Despite being one of the first African countries to prioritize food safety, foodborne diseases are of acute concern in Ethiopia. This review aims to understand food safety-related perspectives and practices among consumers and food vendors in Ethiopia to identify motivations, beliefs, and values that shape and/or drive their practices. A well-defined search and review identified 116 relevant articles. These spanned eight of the ten regional states and two chartered cities, with most work focusing on urban areas and on a sample within one state or chartered city. Ninety-four studies focused on vendors or food handlers; fifteen articles examined both consumers and vendors, but only four assessed interactions between the groups. Meat, dairy products, and ready-to-eat (street) foods were the most studied food groups. Food service establishments were the most examined outlets. Forty-six studies examined generic food safety issues or concerns. Overall, 102 studies assessed food safety practices; 53 studies examined knowledge, and 19 studies assessed attitudes. A gap in vendors\' observed practices versus knowledge and attitudes was noted. Consumer deductions of food safety were based on vendor practices. Both groups used physical attributes based on senses to assess quality and safety of animal-source foods, had their own \'coping\' strategies to address food safety-related concerns, and had similar views on consumer choice motives. Analysis of food and the food handling environment revealed a high level of contamination. An additional study, included after the original search, identified training to be effective in influencing knowledge, attitudes, and practices - though results for attitudes and practices were not sustained in the long term. Future research should address consumers and consumer-vendor interactions and include the full triad of knowledge-attitudes-practices. It is also recommended to focus on nutrient-rich foods as well as on traditional markets and local eateries. Improving the quality of research will be critical to improve food safety in Ethiopia.

BACKGROUND: The COVID-19 pandemic has significantly disrupted the food retail environment. However, its impact on fresh fruit and vegetable vendors remains unclear; these are often smaller, more community centered, and may lack the financial infrastructure to withstand supply and demand changes induced by such crises.
OBJECTIVE: This study documents the methodology used to assess fresh fruit and vegetable vendor closures in New York City (NYC) following the start of the COVID-19 pandemic by using Google Street View, the new Apple Look Around database, and in-person checks.
METHODS: In total, 6 NYC neighborhoods (in Manhattan and Brooklyn) were selected for analysis; these included two socioeconomically advantaged neighborhoods (Upper East Side, Park Slope), two socioeconomically disadvantaged neighborhoods (East Harlem, Brownsville), and two Chinese ethnic neighborhoods (Chinatown, Sunset Park). For each neighborhood, Google Street View was used to virtually walk down each street and identify vendors (stores, storefronts, street vendors, or wholesalers) that were open and active in 2019 (ie, both produce and vendor personnel were present at a location). Past vendor surveillance (when available) was used to guide these virtual walks. Each identified vendor was geotagged as a Google Maps pinpoint that research assistants then physically visited. Using the \"notes\" feature of Google Maps as a data collection tool, notes were made on which of three categories best described each vendor: (1) open, (2) open with a more limited setup (eg, certain sections of the vendor unit that were open and active in 2019 were missing or closed during in-person checks), or (3) closed/absent.
RESULTS: Of the 135 open vendors identified in 2019 imagery data, 35% (n=47) were absent/closed and 10% (n=13) were open with more limited setups following the beginning of the COVID-19 pandemic. When comparing boroughs, 35% (28/80) of vendors in Manhattan were absent/closed, as were 35% (19/55) of vendors in Brooklyn. Although Google Street View was able to provide 2019 street view imagery data for most neighborhoods, Apple Look Around was required for 2019 imagery data for some areas of Park Slope. Past surveillance data helped to identify 3 additional established vendors in Chinatown that had been missed in street view imagery. The Google Maps \"notes\" feature was used by multiple research assistants simultaneously to rapidly collect observational data on mobile devices.
CONCLUSIONS: The methodology employed enabled the identification of closures in the fresh fruit and vegetable retail environment and can be used to assess closures in other contexts. The use of past baseline surveillance data to aid vendor identification was valuable for identifying vendors that may have been absent or visually obstructed in the street view imagery data. Data collection using Google Maps likewise has the potential to enhance the efficiency of fieldwork in future studies.

Despite standardization efforts, vendors still use specific proprietary software algorithms for echocardiographic strain measurements, which result in high inter-vendor variability. Using vendor-independent software could be one solution. Little is known, however, how vendor specific image characteristics can influence tracking results of such software. We therefore investigated the reproducibility, accuracy, and scar detection ability of strain measurements on images from different vendors by using a vendor-independent software. A vendor-independent software (TomTec Image Arena) was used to analyse datasets of 63 patients which were obtained on machines from four different ultrasound machine vendors (GE, Philips, Siemens, Toshiba). We measured the tracking feasibility, inter-vendor bias, the relative test-re-test variability and scar discrimination ability of strain measurements. Cardiac magnetic resonance delayed enhancement images were used as the reference standard of scar definition. Tracking feasibility on vendor datasets were significantly different (p < 0.001). Variability of global longitudinal strain (GLS) measurements was similar among the vendors whereas variability of segmental longitudinal strain (SLS) showed modest difference. Relative test-re-test variability of GLS and SLS showed no relevant differences. No significant difference in scar detection capability was observed. Average GLS and SLS values were similar among vendors. Reproducibility of GLS measurements showed no difference among vendors and was in acceptable range. SLS reproducibility was high but similar for all vendors. No relevant difference was found for identifying regional dysfunction. Tracking feasibility showed a substantial difference among images from different vendors. Our findings demonstrate that tracking results depend mainly on the software used and show little influence from vendor specific image characteristics.

Electronic health record (EHR) log data capture clinical workflows and are a rich source of information to understand variation in practice patterns. Variation in how EHRs are used to document and support care delivery is associated with clinical and operational outcomes, including measures of provider well-being and burnout. Standardized measures that describe EHR use would facilitate generalizability and cross-institution, cross-vendor research. Here, we describe the current state of outpatient EHR use measures offered by various EHR vendors, guided by our prior conceptual work that proposed seven core measures to describe EHR use. We evaluate these measures and other reporting options provided by vendors for maturity and similarity to previously proposed standardized measures. Working toward improved standardization of EHR use measures can enable and accelerate high-impact research on physician burnout and job satisfaction as well as organizational efficiency and patient health.

BACKGROUND: The microbiome has emerged as an important player in the pathophysiology of a whole spectrum of diseases that affect the critically ill. We hypothesized that differences in microbiota composition across vendors can influence murine models of pulmonary lipopolysaccharide (LPS) inflammation and Gram-negative pneumonia.
METHODS: A multi-vendor approach was used with genetically similar mice derived from three different vendors (Janvier, Envigo, Charles River). This model was employed to study the effect on the host response to a pulmonary LPS challenge (1 μg Klebsiella pneumoniae LPS, intranasal), as well as experimental K. pneumoniae infection (ATCC43816, 1 × 104 CFU, intranasal).
RESULTS: Gut microbiota analysis revealed profound intervendor differences in bacterial composition as shown by beta diversity and at various taxonomic levels. Tumor necrosis factor (TNF)-α and interleukin (IL)-6 release in lung and bronchoalveolar lavage fluid (BALF) were determined 6 and 24 h after intranasal treatment with LPS. No differences were found between the groups, with the exception for Envigo, showing a higher level of TNFα in lung and BALF at 6 h compared to Janvier and Charles River. In another set of experiments, mice from different vendors were subjected to a clinically relevant model of Gram-negative pneumonia (K. pneumoniae). At 12 and 36 h post-infection, no intervendor differences were found in bacterial dissemination, or TNFα and IL-6 levels in the lungs. In line, markers for organ failure did not differ between groups.
CONCLUSIONS: Although there was a marked variation in the gut microbiota composition of mice from different vendors, the hypothesized impact on our models of pulmonary inflammation and severe pneumonia was limited. This is of significance for experimental settings, showing that differences in gut microbiota do not have to lead to differences in outcome.

Although Sprague Dawley outbred rats are commonly used in behavioral, physiological, and pharmacological studies, dramatic differences in responses may emerge from rats obtained from different suppliers even when sex, age, and environmental conditions are maintained constant. In the present study, we compared behavioral responses on three tests related to anxiety of Sprague Dawley female and male rats obtained from three different vendors in the United States: Charles River, Envigo, and Taconic. All rats were tested in the open field, light-dark box, and elevated zero maze. We found reduced time spent in the center area of the open field and decreased light compartment duration in the light-dark box test in female and male rats from Taconic compared to Charles River and Envigo rats, suggesting anxiety-like behaviors differ between the three vendors. No vendor differences were found on performance in the elevated zero maze. Furthermore, the contribution of stress hormones to vendor differences was examined by measuring serum corticosterone levels in rats 30 min after exposure to the elevated zero maze. There were no vendor differences in corticosterone levels, suggesting that endogenous levels of stress hormones most likely did not contribute to vendor differences in anxiety-like behaviors. Collectively, these findings highlight the importance of vendor selection of the Sprague Dawley stock for research involving behavioral tests related to anxiety.