Public Response to Federal Electronic Cigarette Regulations Analyzed Using Social Media Data Through Natural Language Processing: Topic Modeling Study.

BACKGROUND: e-Cigarette (electronic cigarette) use has been a public health issue in the United States. On June 23, 2022, the US Food and Drug Administration (FDA) issued marketing denial orders (MDOs) to Juul Labs Inc for all their products currently marketed in the United States. However, one day later, on June 24, 2022, a federal appeals court granted a temporary reprieve to Juul Labs that allowed it to keep its e-cigarettes on the market. As the conversation around Juul continues to evolve, it is crucial to gain insights into the sentiments and opinions expressed by individuals on social media. OBJECTIVE: This study aims to conduct a comprehensive analysis of tweets before and after the ban on Juul, aiming to shed light on public perceptions and sentiments surrounding this contentious topic and to better understand the life cycle of public health-related policy on social media. METHODS: Natural language processing (NLP) techniques were used, including state-of-the-art BERTopic topic modeling and sentiment analysis. A total of 6023 tweets and 22,288 replies or retweets were collected from Twitter (rebranded as X in 2023) between June 2022 and October 2022. The encoded topics were used in time-trend analysis to depict the boom-and-bust cycle. Content analyses of retweets were also performed to better understand public perceptions and sentiments about this contentious topic. RESULTS: The attention surrounding the FDA's ban on Juul lasted no longer than a week on Twitter. Not only the news (ie, tweets with a YouTube link that directs to the news site) related to the announcement itself, but the surrounding discussions (eg, potential consequences of this ban or block and concerns toward kids or youth health) diminished shortly after June 23, 2022, the date when the ban was officially announced. Although a short rebound was observed on July 4, 2022, which was contributed by the suspension on the following day, discussions dried out in 2 days. Out of the top 50 most retweeted tweets, we observed that, except for neutral (23/45, 51%) sentiment that broadcasted the announcement, posters responded more negatively (19/45, 42%) to the FDA's ban. CONCLUSIONS: We observed a short life cycle for this news announcement, with a preponderance of negative sentiment toward the FDA's ban on Juul. Policy makers could use tactics such as issuing ongoing updates and reminders about the ban, highlighting its impact on public health, and actively engaging with influential social media users who can help maintain the conversation.

Broadband, high-resolution spatial heterodyne Raman spectroscopy measurement based on a multi-Littrow-angle multi-grating.

This paper proposes a spatial heterodyne Raman spectrometer (SHRS) based on a multi-Littrow-angle multi-grating (MLAMG). Compared with a conventional multi-grating, the MLAMG not only provides higher spectral resolution and a broader spectral range, but is also easier to produce. A verification breadboard system is built using the MLAMG combined with four sub-gratings with a groove density of 300 gr/mm and Littrow angles of 4.6355°, 4.8536°, 5.0820°, and 5.3253°. This MLAMG-SHRS is used to obtain the Raman spectra of inorganic solids and organic solutions for different integration times, laser powers, suspension contents, and containers. The Raman spectra of mixed targets and minerals are also presented. The experiments demonstrate that the MLAMG-SHRS is suitable for broadband measurements at high spectral resolution in a wide range of potential applications.

E-cigarette use during pregnancy and its association with adverse birth outcomes in the US.

The popularity of e-cigarette use among young adults is a growing concern. However, little is known about factors associated with e-cigarette use in pregnant women and birth outcomes. In this retrospective cohort study, we evaluated the influence of several factors on behavioral changes in e-cigarette use before and during pregnancy, and assessed the association between e-cigarette use and subsequent birth outcomes among pregnant women. The Population Assessment of Tobacco and Health (PATH) study, a government-sponsored national longitudinal study based in the US, Waves 1 through 4 (2013-2018) were used. Multivariate logistic regressions were conducted to estimate behavioral changes in e-cigarette use during pregnancy and subsequent influence on high-risk birth (e.g., preterm birth, low birth weight, birth defects, etc.) and fetal death. Although pregnant women who quit vaping before pregnancy (OR = 1.14, 95% CI 0.54-2.40) or had any use during pregnancy (OR = 1.19, 95% CI 0.38-3.73) showed non-differential risk of having a high-risk birth in comparison to women who did not initiate vaping, we observed that the usage of mint/menthol flavor was correlated with higher risk of fetus death (OR = 3.27, 95% CI 1.17-9.19). Healthcare providers should encourage e-cigarette users to quit prior to and during early pregnancy.

The Association Between Tobacco Retailer Outlet Density and Prevalence of Cigarette Smoking in Virginia.

OBJECTIVE: We examine the association between tobacco retail outlet density and adult smoking prevalence at the county level in Virginia, controlling for spatial autocorrelations. AIMS AND METHODS: Pooling data from 2020 County Health Rankings (compiled data from various sources including, but not limited to, the National Center for Health Statistics-Mortality Files, the Behavioral Risk Factor Surveillance System (BRFSS), and the American Community Survey) and Counter Tools, we conducted regression analyses that accounted for spatial autocorrelation (spatial lag models, LMlag) and adjusted for county-level access to healthcare, demographics, SES, environmental factors, risk conditions or behaviors, and population health measures. RESULTS: Our estimates provide evidence that every increase of one tobacco retail outlet per 1000 persons was associated with 1.16 percentage points (95% CI: 0.80-1.52) higher smoking prevalence at the county level in Virginia after controlling for spatial autocorrelation. The effect of outlet density was largely explained by social determinants of health such as SES, risky conditions or behaviors, and environmental factors. We further noticed that the impact of social determinants of health were closely related and can be explained by indicators of population health (rates of mental distress (ß = 1.49, 95% CI: 1.31-1.67) and physical inactivity (ß = 0.07, 95% CI: 0.04-0.10). CONCLUSIONS: Although higher tobacco outlet density was associated with an increase in county-level smoking prevalence, the impact of outlet density was largely explained by social determinants of health and mental illness. Improving well-being at the community level could be a promising strategy in future tobacco control policies. IMPLICATION: The influence of tobacco outlet density seems to be explained by other social determinants of health and population level of mental or physical health. Thus, efforts to reduce tobacco use and consequent negative health effects should explore the impact of improving regional living standards. However, a sole focus on economic growth may not be sufficient, whereas a focus on such things as promoting work-life balance and improving overall well-being at the community level may be more.

Social Media Data Mining of Antitobacco Campaign Messages: Machine Learning Analysis of Facebook Posts.

BACKGROUND: Social media platforms provide a valuable source of public health information, as one-third of US adults seek specific health information online. Many antitobacco campaigns have recognized such trends among youth and have shifted their advertising time and effort toward digital platforms. Timely evidence is needed to inform the adaptation of antitobacco campaigns to changing social media platforms. OBJECTIVE: In this study, we conducted a content analysis of major antitobacco campaigns on Facebook using machine learning and natural language processing (NLP) methods, as well as a traditional approach, to investigate the factors that may influence effective antismoking information dissemination and user engagement. METHODS: We collected 3515 posts and 28,125 associated comments from 7 large national and local antitobacco campaigns on Facebook between 2018 and 2021, including the Real Cost, Truth, CDC Tobacco Free (formally known as Tips from Former Smokers, where "CDC" refers to the Centers for Disease Control and Prevention), the Tobacco Prevention Toolkit, Behind the Haze VA, the Campaign for Tobacco-Free Kids, and Smoke Free US campaigns. NLP methods were used for content analysis, including parsimonious rule-based models for sentiment analysis and topic modeling. Logistic regression models were fitted to examine the relationship of antismoking message-framing strategies and viewer responses and engagement. RESULTS: We found that large campaigns from government and nonprofit organizations had more user engagements compared to local and smaller campaigns. Facebook users were more likely to engage in negatively framed campaign posts. Negative posts tended to receive more negative comments (odds ratio [OR] 1.40, 95% CI 1.20-1.65). Positively framed posts generated more negative comments (OR 1.41, 95% CI 1.19-1.66) as well as positive comments (OR 1.29, 95% CI 1.13-1.48). Our content analysis and topic modeling uncovered that the most popular campaign posts tended to be informational (ie, providing new information), where the key phrases included talking about harmful chemicals (n=43, 43%) as well as the risk to pets (n=17, 17%). CONCLUSIONS: Facebook users tend to engage more in antitobacco educational campaigns that are framed negatively. The most popular campaign posts are those providing new information, with key phrases and topics discussing harmful chemicals and risks of secondhand smoke for pets. Educational campaign designers can use such insights to increase the reach of antismoking campaigns and promote behavioral changes.

Identification of effective alleles and haplotypes conferring pre-harvest sprouting resistance in winter wheat cultivars.

BACKGROUND: Pre-harvest sprouting (PHS) is a serious limiting factor for wheat (Triticum aestivum L.) grain yield and end-use quality. Identification of reliable molecular markers and PHS-resistant germplasms is vital to improve PHS resistance by molecular marker-assisted selection (MAS), but the effects of allelic variation and haplotypes in genes conferring PHS resistance in winter wheat cultivars are less understood. RESULTS: Resistance to PHS was tested in 326 commercial winter wheat cultivars for three consecutive growing seasons from 2018-2020. The effects of alleles and haplotypes of 10 genes associated with PHS resistance were determined for all cultivars and were validated by introgressing the PHS-resistance allele and haplotype into a susceptible wheat cultivar. High level of phenotypic variation in PHS resistance was observed in this set of cultivars and 8 of them were highly resistant to PHS with stable germination index (GI) of less than 25% in each individual year. Allelic effects of nine genes and TaMFT haplotype analysis demonstrated that the haplotype Hap1 with low-GI alleles at five positions had the best PHS resistance. This haplotype has the priority to use in improving PHS resistance because of its high effectiveness and rare present in the current commercial cultivars. Among 14 main allelic combinations (ACs) identified, the AC1 carrying the haplotype Hap1 and the TaSdr-B1a allele had better PHS resistance than the other classes. The introgression of Hap1 and TaSdr-B1a is able to significantly improve the PHS resistance in the susceptible cultivar Lunxuan 13. CONCLUSIONS: The effectiveness of alleles conferring PHS resistance in winter wheat cultivars was determined and the useful alleles and haplotypes were identified, providing valuable information for parental selection and MAS aiming at improving PHS-resistance in winter wheat. The identification of the PHS-resistant cultivars without known resistance alleles offers an opportunity to explore new PHS-resistant genes.

Ovarian steroid cell tumor causing isosexual pseudoprecocious puberty in a young girl: an instructive case and literature review.

BACKGROUND: Steroid cell tumors (SCTs) are very rare sex cord-stromal tumors and account only for less than 0.1% of ovarian neoplasms. SCTs might comprise diverse steroid-secreting cells; hence, the characteristic clinical features were affected by their propensity to secrete a variety of hormones rather than mass effect resulting in compression symptoms and signs. To date, ovarian SCTs have seldom been reported in children, particularly very young children; and pseudoprecocious puberty (PPP) as its unique principal manifestation should be reiterated. CASE PRESENTATION: We reported a 1-year-8-month-old girl presenting with rapid bilateral breast and pubic hair development within a 2-month period. Undetectable levels of LH and FSH along with excessively high estradiol after stimulation with gonadotropin-releasing hormone (GnRH), as well as a heterogeneous mass inside left ovary shown in pelvic sonography indicate isosexual PPP. Her gonadal hormones returned remarkably to the prepubertal range the day after surgery, and histology of the ovary mass demonstrated SCTs containing abundant luteinized stromal cells. CONCLUSION: The case highlighted that SCTs causing isosexual PPP should be taken into consideration in any young children coexistent with rapidly progressive puberty given a remarkable secretion of sex hormones. This article also reviewed thoroughly relevant reported cases to enrich the clinical experience of SCTs in the pediatric group.

Stress hyperglycemia as first sign of asymptomatic type 1 diabetes: an instructive case.

BACKGROUND: Stress hyperglycemia (SH) is considered a transient manifestation and routine diagnostic evaluation was thought to be unnecessary due to the lack of definite correlation with diabetes mellitus (DM). Although SH was usually benign and long-term treatment was superfluous, it might be the first sign of insulinopenic status such as type 1 DM (T1DM). CASE PRESENTATION: We reported a boy with acute asthma attack presented incidentally with high blood glucose levels exceeding 300 mg/dL and obvious glycemic variability. A prolonged hyperglycemic duration of more than 48 h was also noticed. To elucidate his unique situation, glucagon test and insulin autoantibody survey were done which showed insulinopenia with positive anti-insulin antibody and glutamic acid decarboxylase antibody despite the absence of overt DM symptoms and signs. CONCLUSIONS: This case highlights that SH might be a prodromal presentation in T1DM children, especially when accompanied simultaneously with extreme hyperglycemia, apparent glucose variability, as well as prolonged hyperglycemic duration.

Healthfulness Assessment of Recipes Shared on Pinterest: Natural Language Processing and Content Analysis.

BACKGROUND: Although Pinterest has become a popular platform for distributing influential information that shapes users' behaviors, the role of recipes pinned on Pinterest in these behaviors is not well understood. OBJECTIVE: This study aims to explore the patterns of food ingredients and the nutritional content of recipes posted on Pinterest and to examine the factors associated with recipes that engage more users. METHODS: Data were collected from Pinterest between June 28 and July 12, 2020 (207 recipes and 2818 comments). All samples were collected via 2 new user accounts with no search history. A codebook was developed with a raw agreement rate of 0.97 across all variables. Content analysis and natural language processing sentiment analysis techniques were employed. RESULTS: Recipes using seafood or vegetables as the main ingredient had, on average, fewer calories and less sodium, sugar, and cholesterol than meat- or poultry-based recipes. For recipes using meat as the main ingredient, more than half of the energy was obtained from fat (277/490, 56.6%). Although the most followed pinners tended to post recipes containing more poultry or seafood and less meat, recipes with higher fat content or providing more calories per serving were more popular, having more shared photos or videos and comments. The natural language processing-based sentiment analysis suggested that Pinterest users weighted taste more heavily than complexity (225/2818, 8.0%) and health (84/2828, 2.9%). CONCLUSIONS: Although popular pinners tended to post recipes with more seafood or poultry or vegetables and less meat, recipes with higher fat and sugar content were more user-engaging, with more photo or video shares and comments. Data on Pinterest behaviors can inform the development and implementation of nutrition health interventions to promote healthy recipe sharing on social media platforms.

Proteasome Inhibitors Interrupt the Activation of Non-Canonical NF-κB Signaling Pathway and Induce Cell Apoptosis in Cytarabine-Resistant HL60 Cells.

Over half of older patients with acute myeloid leukemia (AML) do not respond to cytotoxic chemotherapy, and most responders relapse because of drug resistance. Cytarabine is the main drug used for the treatment of AML. Intensive treatment with high-dose cytarabine can increase the overall survival rate and reduce the relapse rate, but it also increases the likelihood of drug-related side effects. To optimize cytarabine treatment, understanding the mechanism underlying cytarabine resistance in leukemia is necessary. In this study, the gene expression profiles of parental HL60 cells and cytarabine-resistant HL60 (R-HL60) cells were compared through gene expression arrays. Then, the differential gene expression between parental HL60 and R-HL60 cells was measured using KEGG software. The expression of numerous genes associated with the nuclear factor κB (NF-κB) signaling pathway changed during the development of cytarabine resistance. Proteasome inhibitors inhibited the activity of non-canonical NF-κB signaling pathway and induced the apoptosis of R-HL60 cells. The study results support the application and possible mechanism of proteasome inhibitors in patients with relapsed or refractory leukemia.

Elevated temperature as the dominant stressor on the harmful algal bloom-causing dinoflagellate Prorocentrum obtusidens in a future ocean scenario.

Marine dinoflagellates are increasingly affected by ongoing global climate changes. While understanding of their physiological and molecular responses to individual stressors anticipated in the future ocean has improved, their responses to multiple concurrent stressors remain poorly understood. Here, we investigated the individual and combined effects of elevated temperature (26 °C relative to 22 °C), increased pCO2 (1000 µatm relative to 400 µatm), and high nitrogen: phosphorus ratio (180:1 relative to 40:1) on a harmful algal bloom-causing dinoflagellate Prorocentrum obtusidens under short-term (28 days) exposure. Elevated temperature was the most dominant stressor affecting P. obtusidens at physiological and transcriptomic levels. It significantly increased cell growth rate and maximum photosynthetic efficiency (Fv/Fm), but reduced chlorophyll a, particulate organic carbon, particulate organic nitrogen, and particulate organic phosphorus. Elevated temperature also interacted with other stressors to produce synergistic positive effects on cell growth and Fv/Fm. Transcriptomic analysis indicated that elevated temperature promoted energy production by enhancing glycolysis, tricarboxylic acid cycle, and nitrogen and carbon assimilation, which supported rapid cell growth but reduced material storage. Increased pCO2 enhanced the expression of genes involved in ionic acid-base regulation and oxidative stress resistance, whereas a high N:P ratio inhibited photosynthesis, compromising cell viability, although the effect was alleviated by elevated temperature. The combined effect of these multiple stressors resulted in increased energy metabolism and up-regulation of material-synthesis pathways compared to the effect caused by elevated temperature alone. Our results underscore ocean warming as the predominant stressor for dinoflagellates and highlight the complex, synergistic effects of multi-stressors on dinoflagellates.

Anxiolytic-like effects of YL-IPA08, a potent ligand for the translocator protein (18 kDa) via regulating the synaptic plasticity in hippocampus.

TSPO, translocator protein (18 kDa) ligands have demonstrated consistent antidepression and anxiolytic effects in several preclinical studies. This study aimed to examine whether YL-IPA08[N-ethyl-N-(2-pyridinylmethyl)-2-(3,4-ichlorophenyl) -7-methylimidazo [1,2-a] pyridine-3-acetamide hydrochloride], a potent and selective TSPO ligand synthesized by our institute, could alleviate anxiety-related behaviors induced by electric shock (ES) and investigate its underlying mechanism. As expected, we showed that chronic treatment with YL-IPA08 significantly reversed anxiety-related behaviors induced by electrical stimulation (0.5 mA, 12 times, duration 1s, interval 10s) exposure. Using the analysis of RNA-sequencing (RNA-seq) technology, it was found that the differential genes associated with the anxiolytic effect of YL-IPA08 were mainly related to synaptic plasticity. Furthermore, YL-IPA08 restored the decreased levels of brain-derived neurotrophic factor (BDNF), synapse-related protein (e.g. synapsin-1 and post-synaptic density95, PSD95), and the number of doublecortin (DCX) + neurons in the hippocampus of post-ES mice. In addition, YL-IPA08 also enhanced the dendritic complexity and dendritic spine density of hippocampal dentate gyrus (DG) granule neurons. Meanwhile, the induction of long-term potentiation (LTP) was significantly enhanced by YL-IPA08. In summary, the findings from the current study showed that YL-IPA08 exerted a clear anxiolytic effect, which might be partially mediated by promoting hippocampal neuroplasticity.

Graphene-Doped Piezoelectric Transducers by Kriging Optimal Model for Detecting Various Types of Laryngeal Movements.

This study fabricated piezoelectric fibers of polyvinylidene fluoride (PVDF) with graphene using near-field electrospinning (NFES) technology. A uniform experimental design table U*774 was applied, considering weight percentage (1-13 wt%), the distance between needle and disk collector (2.1-3.9 mm), and applied voltage (14.5-17.5 kV). We optimized the parameters using electrical property measurements and the Kriging response surface method. Adding 13 wt% graphene significantly improved electrical conductivity, increasing from 17.7 µS/cm for pure PVDF to 187.5 µS/cm. The fiber diameter decreased from 21.4 µm in PVDF/1% graphene to 9.1 µm in PVDF/13% graphene. Adding 5 wt% graphene increased the ß-phase content by 6.9%, reaching 65.4% compared to pure PVDF fibers. Material characteristics were investigated using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), contact angle measurements, and tensile testing. Optimal parameters included 3.47 wt% graphene, yielding 15.82 mV voltage at 5 Hz and 5 N force (2.04 times pure PVDF). Force testing showed a sensitivity (S) of 7.67 log(mV/N). Fibers were attached to electrodes for piezoelectric sensor applications. The results affirmed enhanced electrical conductivity, piezoelectric performance, and mechanical strength. The optimized piezoelectric sensor could be applied to measure physiological signals, such as attaching it to the throat under different conditions to measure the output voltage. The force-to-voltage conversion facilitated subsequent analysis.

CD20highCD138low tumor-infiltrating lymphocytes predominantly related to cytokine‒cytokine receptor interactions are associated with favorable outcomes in neuroblastoma patients.

Recent advances have revealed that the role of the immune system is prominent in the antitumor response. In the present study, it is aimed to provide an expression profile of tumor-infiltrating lymphocytes (TILs), including mature B cells, plasma cells, and their clinical relevance in neuroblastoma. The expression of CD20 and CD138 was analyzed in the Cangelosi786 dataset (n = 769) as a training dataset and in our cohort (n = 120) as a validation cohort. CD20 high expression was positively associated with favorable overall survival (OS) and event-free survival (EFS) (OS: P < 0.001; EFS: P < 0.001) in the training dataset, whereas CD138 high expression was associated with poor OS and EFS (OS: P < 0.001; EFS: P < 0.001) in both the training and validation datasets. Accordingly, a combined pattern of CD20 and CD138 expression was developed, whereby neuroblastoma patients with CD20highCD138low expression had a consistently favorable OS and EFS compared with those with CD20lowCD138high expression in both the training and validation cohorts (P < 0.0001 and P < 0.01, respectively). Examination of potential molecular functions revealed that signaling pathways, including cytokine‒cytokine receptor interactions, chemokine, and the NF-kappa B signaling pathways, were involved. Differentially expressed genes, such as BMP7, IL7R, BIRC3, CCR7, CXCR5, CCL21, and CCL19, predominantly play important roles in predicting the survival of neuroblastoma patients. Our study proposes that a new combination of CD20 and CD138 signatures is associated with neuroblastoma patient survival. The related signaling pathways reflect the close associations among the number of TILs, cytokine abundance and patient outcomes and provide therapeutic insights into neuroblastoma.

Spectrum of PHEX Mutations and FGF23 Profiles in a Taiwanese Cohort With X-Linked Hypophosphatemia Including 102 Patients.

BACKGROUND/AIM: X-linked hypophosphatemia (XLH), the most common form of hereditary rickets, results from loss-of-function mutations in the phosphate-regulating PHEX gene. Elevated fibroblast growth factor 23 (FGF23) contributes to hypophosphatemia in XLH. This study aimed to characterize PHEX variants and serum FGF23 profiles in Taiwanese patients with XLH. PATIENTS AND METHODS: We retrospectively reviewed the records of 102 patients clinically suspected of having hypophosphatemic rickets from 2006 to 2022. Serum intact Fibroblast growth factor-23 (iFGF23) levels were measured on clinic visit days. PHEX mutations were identified using Sanger sequencing, and negative cases were analyzed using whole-exome sequencing. RESULTS: The majority (92.1%) of patients exhibited elevated FGF23 compared with normal individuals. Among 102 patients, 44 distinct PHEX mutations were identified. Several mutations recurred in multiple unrelated Taiwanese families. We discovered a high frequency of novel PHEX mutations and identified variants associated with extreme FGF23 elevation and tumorigenesis. CONCLUSION: Our findings revealed the PHEX genotypic variants and FGF23 levels in Taiwanese patients with XLH. These results are crucial given the recent approval of burosumab, a monoclonal FGF23 antibody, for XLH therapy. This study provides key insights into the clinical management of XLH in Taiwan.

Associations between use of specific social media sites and electronic cigarette use among college students.

OBJECTIVE: To examine dose-response associations between use of specific social media sites and the use of electronic cigarettes (e-cigarettes) and traditional cigarettes. METHODS: This was a cross-sectional study of 298 first-year college students enrolled in the fall 2019 semester at a large state university. Heckman selection and Probit model were used to estimate associations between use of specific social media sites and e-cigarette/traditional cigarette use. RESULTS: Each additional hour per day spent on Snapchat was associated with a 4.61% increase in the probability of lifetime e-cigarette use. In addition, among current e-cigarette users, more time spent on Snapchat was associated with more frequent e-cigarette use (marginal effects: 0.13, p = 0.001). Facebook, Twitter, Snapchat and Instagram were not associated with traditional cigarette smoking. CONCLUSION: Snapchat was the only major social media platform associated with both lifetime and current e-cigarette use.

Cross-cohort analysis identified an immune checkpoint-based signature to predict the clinical outcomes of neuroblastoma.

BACKGROUND: Neuroblastoma (NB) places a substantial health burden on families worldwide. This study aimed to develop an immune checkpoint-based signature (ICS) based on the expression of immune checkpoints to better assess patient survival risk and potentially guide patient selection for immunotherapy of NB. METHODS: Immunohistochemistry integrated with digital pathology was used to determine the expression levels of 9 immune checkpoints in 212 tumor tissues used as the discovery set. The GSE85047 dataset (n=272) was used as a validation set in this study. In the discovery set, the ICS was constructed using a random forest algorithm and confirmed in the validation set to predict overall survival (OS) and event-free survival (EFS). Kaplan-Meier curves with a log-rank test were drawn to compare the survival differences. A receiver operating characteristic (ROC) curve was applied to calculate the area under the curve (AUC). RESULTS: Seven immune checkpoints, including PD-L1, B7-H3, IDO1, VISTA, T-cell immunoglobulin and mucin domain containing-3 (TIM-3), inducible costimulatory molecule (ICOS) and costimulatory molecule 40 (OX40), were identified as abnormally expressed in NB in the discovery set. OX40, B7-H3, ICOS and TIM-3 were eventually selected for the ICS model in the discovery set, and 89 patients with high risk had an inferior OS (HR 15.91, 95% CI 8.87 to 28.55, p<0.001) and EFS (HR 4.30, 95% CI 2.80 to 6.62, p<0.001). Furthermore, the prognostic value of the ICS was confirmed in the validation set (p<0.001). Multivariate Cox regression analysis demonstrated that age and the ICS were independent risk factors for OS in the discovery set (HR 6.17, 95% CI 1.78 to 21.29 and HR 1.18, 95% CI 1.12 to 1.25, respectively). Furthermore, nomogram A combining the ICS and age demonstrated significantly better prognostic value than age alone in predicting the patients' 1-year, 3-year and 5-year OS in the discovery set (1 year: AUC, 0.891 (95% CI 0.797 to 0.985) vs 0.675 (95% CI 0.592 to 0.758); 3 years: 0.875 (95% CI 0.817 to 0.933) vs 0.701 (95% CI 0.645 to 0.758); 5 years: 0.898 (95% CI 0.851 to 0.940) vs 0.724 (95% CI 0.673 to 0.775), respectively), which was confirmed in the validation set. CONCLUSIONS: We propose an ICS that significantly differentiates between low-risk and high-risk patients, which might add prognostic value to age and provide clues for immunotherapy in NB.

Clinical Significance of a CD3/CD8-Based Immunoscore in Neuroblastoma Patients Using Digital Pathology.

Background: Infiltrating immune cells have been reported as prognostic markers in many cancer types. We aimed to evaluate the prognostic role of tumor-infiltrating lymphocytes, namely CD3+ T cells, CD8+ cytotoxic T cells and memory T cells (CD45RO+), in neuroblastoma. Patients and Methods: Immunohistochemistry was used to determine the expression of CD3, CD8 and CD45RO in the tumor samples of 244 neuroblastoma patients. We then used digital pathology to calculate the densities of these markers and derived an immunoscore based on such densities. Results: Densities of CD3+ and CD8+ T cells in tumor were positively associated with the overall survival (OS) and event-free survival (EFS), whereas density of CD45RO+ T cells in tumor was negatively associated with OS but not EFS. An immunoscore with low density of CD3 and CD8 (CD3-CD8-) was indictive of a greater risk of death (hazard ratio 6.39, 95% confidence interval 3.09-13.20) and any event (i.e., relapse at any site, progressive disease, second malignancy, or death) (hazard ratio 4.65, 95% confidence interval 2.73-7.93). Multivariable analysis revealed that the CD3-CD8- immunoscore was an independent prognostic indicator for OS, even after adjusting for other known prognostic indicators. Conclusions: The new immunoscore based on digital pathology evaluated densities of tumor-infiltrating CD3+ and CD8+ T cells contributes to the prediction of prognosis in neuroblastoma patients.

Epidemiological retrospective analysis in major burn patients: single centre medical records from 2009 to 2019.

Burns cause a loss of skin barrier function, rendering it prone to infection. The prevention of infection comprises a focus on the treatment of patients with burns. Therefore, we analysed the results of microbiological tests of patients with severe and extremely severe burns to provide a basis for the prevention and treatment of infection in patients with burns. The results of microbiological tests of patients with severe and extremely severe burns admitted to our burn centre between 2009 and 2019 were retrospectively reviewed. The overall positive rate of microbial detection was 40.67% and did not significantly decline over the 10-year study period. The most common positive sites were wounds, sputum, and urine. The most common bacterial species causing the infections were Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Furthermore, the predictors of a positive detection, overall and at various sites, mainly included the burn area and depth, inhalation injury, and length of the hospital stay. Positive detection was an important predictor of the prognosis. In particular, a positive blood culture and Klebsiella pneumoniae had better predictive strength for mortality than other sites and strains. This study analysed the microbiological testing results at a single burn centre over a period of 10 years. The results provide information regarding the predictors of a positive detection and the influence of a positive detection on prognosis, and can be used as a basis for the development of clinical infection prevention and treatment strategies, as well as the selection of treatment measures.

Clinical actionability of triaging DNA mismatch repair deficient colorectal cancer from biopsy samples using deep learning.

BACKGROUND: We aimed to develop a deep learning (DL) model to predict DNA mismatch repair (MMR) status in colorectal cancers (CRC) based on hematoxylin and eosin-stained whole-slide images (WSIs) and assess its clinical applicability. METHODS: The DL model was developed and validated through three-fold cross validation using 441 WSIs from the Cancer Genome Atlas (TCGA) and externally validated using 78 WSIs from the Pathology AI Platform (PAIP), and 355 WSIs from surgical specimens and 341 WSIs from biopsy specimens of the Sun Yet-sun University Cancer Center (SYSUCC). Domain adaption and multiple instance learning (MIL) techniques were adopted for model development. The performance of the models was evaluated using the area under the receiver operating characteristic curve (AUROC). A dual-threshold strategy was also built from the surgical cohorts and validated in the biopsy cohort. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1-score, and the percentage of patients avoiding IHC testing were evaluated. FINDINGS: The MIL model achieved an AUROC of 0·8888±0·0357 in the TCGA-validation cohort, 0·8806±0·0232 in the PAIP cohort, 0·8457±0·0233 in the SYSUCC-surgical cohort, and 0·7679±0·0342 in the SYSUCC-biopsy cohort. A dual-threshold triage strategy was used to rule-in and rule-out dMMR patients with remaining uncertain patients recommended for further IHC testing, which kept sensitivity higher than 90% and specificity higher than 95% on deficient MMR patient triage from both the surgical and biopsy specimens, result in more than half of patients avoiding IHC based MMR testing. INTERPRETATION: A DL-based method that could directly predict CRC MMR status from WSIs was successfully developed, and a dual-threshold triage strategy was established to minimize the number of patients for further IHC testing. FUNDING: The study was funded by the National Natural Science Foundation of China (82073159, 81871971 and 81700576), the Natural Science Foundation of Guangdong Province (No. 2021A1515011792 and No.2022A1515012403) and Medical Scientific Research Foundation of Guangdong Province of China (No. A2020392).